diff --git a/tensorflow/BUILD b/tensorflow/BUILD
index b98be57ec08..1ab6ee2dc0e 100644
--- a/tensorflow/BUILD
+++ b/tensorflow/BUILD
@@ -308,10 +308,12 @@ filegroup(
         "//tensorflow/tensorboard/components/vz_sorting/test:all_files",
         "//tensorflow/tensorboard/lib:all_files",
         "//tensorflow/tensorboard/plugins:all_files",
-        "//tensorflow/tensorboard/plugins/debugger:all_files",
         "//tensorflow/tensorboard/plugins/projector:all_files",
         "//tensorflow/tensorboard/plugins/text:all_files",
         "//tensorflow/tensorboard/scripts:all_files",
+        "//tensorflow/tools/api/golden:all_files",
+        "//tensorflow/tools/api/lib:all_files",
+        "//tensorflow/tools/api/tests:all_files",
         "//tensorflow/tools/common:all_files",
         "//tensorflow/tools/compatibility:all_files",
         "//tensorflow/tools/dist_test/server:all_files",
@@ -346,6 +348,11 @@ filegroup(
     ),
 )
 
+filegroup(
+    name = "docs_src",
+    data = glob(["docs_src/**/*.md"]),
+)
+
 # -------------------------------------------
 # New rules should be added above this target.
 # -------------------------------------------
diff --git a/tensorflow/compiler/xla/BUILD b/tensorflow/compiler/xla/BUILD
index 35c0efb8f0f..26ad8ac5f8f 100644
--- a/tensorflow/compiler/xla/BUILD
+++ b/tensorflow/compiler/xla/BUILD
@@ -44,6 +44,17 @@ xla_proto_library(
     ],
 )
 
+cc_library(
+    name = "test",
+    testonly = 1,
+    hdrs = ["test.h"],
+    visibility = [":friends"],
+    deps = [
+        "//tensorflow/core:lib_internal",
+        "//tensorflow/core:test",
+    ],
+)
+
 cc_library(
     name = "types",
     hdrs = ["types.h"],
@@ -256,10 +267,9 @@ cc_test(
         ":array4d",
         ":literal_util",
         ":shape_util",
-        ":test_helpers",
+        ":test",
         ":types",
         "//tensorflow/core:lib",
-        "//tensorflow/core:test",
         "//tensorflow/core:test_main",
     ],
 )
diff --git a/tensorflow/compiler/xla/literal_util_test.cc b/tensorflow/compiler/xla/literal_util_test.cc
index e53763376bf..91971c3e24c 100644
--- a/tensorflow/compiler/xla/literal_util_test.cc
+++ b/tensorflow/compiler/xla/literal_util_test.cc
@@ -21,14 +21,16 @@ limitations under the License.
 #include "tensorflow/compiler/xla/array4d.h"
 #include "tensorflow/compiler/xla/layout_util.h"
 #include "tensorflow/compiler/xla/shape_util.h"
-#include "tensorflow/compiler/xla/test_helpers.h"
+#include "tensorflow/compiler/xla/test.h"
 #include "tensorflow/compiler/xla/types.h"
-#include "tensorflow/core/platform/test.h"
 #include "tensorflow/core/platform/types.h"
 
 namespace xla {
 namespace {
 
+using ::testing::ElementsAre;
+using ::testing::ElementsAreArray;
+
 class LiteralUtilTest : public ::testing::Test {
  protected:
   LiteralUtilTest() {
@@ -159,9 +161,7 @@ TEST_F(LiteralUtilTest, CreateR3FromArray3d) {
   // clang-format on
 
   auto literal = LiteralUtil::CreateR3FromArray3D(array_3d);
-  EXPECT_MATCH(testing::PBToVec<tensorflow::protobuf_int64>(
-                   literal->shape().dimensions()),
-               testing::VectorMatcher<tensorflow::protobuf_int64>({2, 3, 2}));
+  EXPECT_THAT(literal->shape().dimensions(), ElementsAre(2, 3, 2));
   string result = LiteralUtil::ToString(*literal);
   const string expected = R"(f32[2,3,2] {
 { { 1, 2 },
@@ -182,9 +182,7 @@ TEST_F(LiteralUtilTest, LiteralR4F32ProjectedStringifies) {
     {2001, 2002},
   }, /*projection_p=*/1, /*projection_z=*/2);
   // clang-format on
-  EXPECT_MATCH(
-      testing::PBToVec(literal->shape().dimensions()),
-      testing::VectorMatcher<tensorflow::protobuf_int64>({1, 2, 3, 2}));
+  EXPECT_THAT(literal->shape().dimensions(), ElementsAre(1, 2, 3, 2));
   string result = LiteralUtil::ToString(*literal);
   const string expected = R"(f32[1,2,3,2] {
   {  // i0=0
@@ -204,10 +202,8 @@ TEST_F(LiteralUtilTest, LiteralR4F32ProjectedStringifies) {
 }
 
 TEST_F(LiteralUtilTest, LiteralR4F32Stringifies) {
-  EXPECT_MATCH(
-      testing::PBToVec<tensorflow::protobuf_int64>(
-          literal_r4_2x2x3x3_dim0major_->shape().dimensions()),
-      testing::VectorMatcher<tensorflow::protobuf_int64>({2, 2, 3, 3}));
+  EXPECT_THAT(literal_r4_2x2x3x3_dim0major_->shape().dimensions(),
+              ElementsAre(2, 2, 3, 3));
   string result = LiteralUtil::ToString(*literal_r4_2x2x3x3_dim0major_);
   const string expected = R"(f32[2,2,3,3] {
   {  // i0=0
@@ -516,27 +512,23 @@ TEST_F(LiteralUtilTest, TestR2LinearLayout) {
   auto mat_dim0minor = LiteralUtil::CreateR2WithLayout<int>(
       {{1, 2, 3}, {4, 5, 6}}, layout_r2_dim0minor_);
   EXPECT_EQ(mat_dim0minor->s32s_size(), 6);
-  EXPECT_MATCH(testing::PBToVec<int32>(mat_dim0minor->s32s()),
-               testing::VectorMatcher<int32>({1, 4, 2, 5, 3, 6}));
+  EXPECT_THAT(mat_dim0minor->s32s(), ElementsAre(1, 4, 2, 5, 3, 6));
 
   // Test expected memory layout when using Relayout to row major.
   auto relaid_mat_to_dim0major =
       LiteralUtil::Relayout(*mat_dim0minor, layout_r2_dim0major_);
-  EXPECT_MATCH(testing::PBToVec<int32>(relaid_mat_to_dim0major->s32s()),
-               testing::VectorMatcher<int32>({1, 2, 3, 4, 5, 6}));
+  EXPECT_THAT(relaid_mat_to_dim0major->s32s(), ElementsAre(1, 2, 3, 4, 5, 6));
 
   // Test expected memory layout of R2 created with dim0-major (row-major).
   auto mat_dim0major = LiteralUtil::CreateR2WithLayout<int>(
       {{1, 2, 3}, {4, 5, 6}}, layout_r2_dim0major_);
   EXPECT_EQ(mat_dim0major->s32s_size(), 6);
-  EXPECT_MATCH(testing::PBToVec<int32>(mat_dim0major->s32s()),
-               testing::VectorMatcher<int32>({1, 2, 3, 4, 5, 6}));
+  EXPECT_THAT(mat_dim0major->s32s(), ElementsAre(1, 2, 3, 4, 5, 6));
 
   // Test expected memory layout when using Relayout to column major.
   auto relaid_mat_to_dim0minor =
       LiteralUtil::Relayout(*mat_dim0major, layout_r2_dim0minor_);
-  EXPECT_MATCH(testing::PBToVec<int32>(relaid_mat_to_dim0minor->s32s()),
-               testing::VectorMatcher<int32>({1, 4, 2, 5, 3, 6}));
+  EXPECT_THAT(relaid_mat_to_dim0minor->s32s(), ElementsAre(1, 4, 2, 5, 3, 6));
 }
 
 TEST_F(LiteralUtilTest, TestR3LinearLayout) {
@@ -558,28 +550,28 @@ TEST_F(LiteralUtilTest, TestR3LinearLayout) {
 
   EXPECT_EQ(lit_dim0minor->s32s_size(), 12);
   std::vector<int> expected_dim0minor{1, 7, 4, 10, 2, 8, 5, 11, 3, 9, 6, 12};
-  EXPECT_MATCH(testing::PBToVec<int32>(lit_dim0minor->s32s()),
-               testing::VectorMatcher<int32>(expected_dim0minor));
+  EXPECT_THAT(lit_dim0minor->s32s(),
+              testing::ElementsAreArray(expected_dim0minor));
 
   // Test expected memory layout when using Relayout to row major.
   auto relaid_lit_to_dim0major =
       LiteralUtil::Relayout(*lit_dim0minor, layout_r3_dim0major_);
   std::vector<int> expected_dim0major{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
-  EXPECT_MATCH(testing::PBToVec<int32>(relaid_lit_to_dim0major->s32s()),
-               testing::VectorMatcher<int32>(expected_dim0major));
+  EXPECT_THAT(relaid_lit_to_dim0major->s32s(),
+              testing::ElementsAreArray(expected_dim0major));
 
   // Test expected memory layout of R3 created with dim0-major (row-major).
   auto lit_dim0major = LiteralUtil::CreateR3FromArray3DWithLayout<int>(
       arr3d, layout_r3_dim0major_);
   EXPECT_EQ(lit_dim0major->s32s_size(), 12);
-  EXPECT_MATCH(testing::PBToVec<int32>(lit_dim0major->s32s()),
-               testing::VectorMatcher<int32>(expected_dim0major));
+  EXPECT_THAT(lit_dim0major->s32s(),
+              testing::ElementsAreArray(expected_dim0major));
 
   // Test expected memory layout when using Relayout to column major.
   auto relaid_lit_to_dim0minor =
       LiteralUtil::Relayout(*lit_dim0major, layout_r3_dim0minor_);
-  EXPECT_MATCH(testing::PBToVec<int32>(relaid_lit_to_dim0minor->s32s()),
-               testing::VectorMatcher<int32>(expected_dim0minor));
+  EXPECT_THAT(relaid_lit_to_dim0minor->s32s(),
+              testing::ElementsAreArray(expected_dim0minor));
 }
 
 TEST_F(LiteralUtilTest, SliceR0S32) {
diff --git a/tensorflow/compiler/xla/service/BUILD b/tensorflow/compiler/xla/service/BUILD
index 695e4e7f079..fc69d8eb3a6 100644
--- a/tensorflow/compiler/xla/service/BUILD
+++ b/tensorflow/compiler/xla/service/BUILD
@@ -1431,7 +1431,9 @@ cc_library(
     deps = [
         ":hlo",
         ":hlo_pass",
+        "//tensorflow/compiler/xla:shape_util",
         "//tensorflow/compiler/xla:status_macros",
+        "//tensorflow/compiler/xla:util",
         "//tensorflow/compiler/xla/service/gpu:ir_emission_utils",
         "//tensorflow/core:lib",
     ],
@@ -1442,11 +1444,13 @@ cc_test(
     srcs = ["transpose_folding_test.cc"],
     deps = [
         ":hlo",
+        ":shape_inference",
         ":transpose_folding",
         "//tensorflow/compiler/xla:literal_util",
         "//tensorflow/compiler/xla:shape_util",
         "//tensorflow/compiler/xla:test_helpers",
         "//tensorflow/compiler/xla:xla_data_proto",
+        "//tensorflow/compiler/xla/client:computation_builder",
         "//tensorflow/compiler/xla/service/gpu:ir_emission_utils",
         "//tensorflow/core:lib",
         "//tensorflow/core:test_main",
diff --git a/tensorflow/compiler/xla/service/cpu/cpu_compiler.cc b/tensorflow/compiler/xla/service/cpu/cpu_compiler.cc
index c5433d4b89d..4fbdb15e70e 100644
--- a/tensorflow/compiler/xla/service/cpu/cpu_compiler.cc
+++ b/tensorflow/compiler/xla/service/cpu/cpu_compiler.cc
@@ -232,7 +232,14 @@ Status CpuCompiler::RunHloPasses(HloModule* hlo_module,
     pass.AddPass<ReshapeMover>();
     pass.AddPass<HloConstantFolding>();
   }
-  pipeline.AddPass<TransposeFolding>(PotentiallyImplementedAsEigenDot);
+  pipeline.AddPass<TransposeFolding>(
+      [](const HloInstruction& dot,
+         const TransposeFolding::OperandIndices& candidate_operands) {
+        return PotentiallyImplementedAsEigenDot(dot)
+                   ? candidate_operands
+                   : TransposeFolding::OperandIndices{};
+      },
+      TransposeFolding::NeverFoldTranspose);
   pipeline.AddPass<HloSubcomputationUnification>();
   pipeline.AddPass<HloCSE>(/*is_layout_sensitive=*/false);
   pipeline.AddPass<CpuInstructionFusion>();
diff --git a/tensorflow/compiler/xla/service/gpu/gpu_compiler.cc b/tensorflow/compiler/xla/service/gpu/gpu_compiler.cc
index f692f28bd98..1d2111c427c 100644
--- a/tensorflow/compiler/xla/service/gpu/gpu_compiler.cc
+++ b/tensorflow/compiler/xla/service/gpu/gpu_compiler.cc
@@ -133,7 +133,13 @@ tensorflow::Status OptimizeHloModule(HloModule* hlo_module,
       pass.AddPass<HloConstantFolding>();
     }
     pipeline.AddPass<ConvolutionFolding>();
-    pipeline.AddPass<TransposeFolding>(ImplementedAsGemm);
+    pipeline.AddPass<TransposeFolding>(
+        [](const HloInstruction& dot,
+           const TransposeFolding::OperandIndices& candidate_operands) {
+          return ImplementedAsGemm(dot) ? candidate_operands
+                                        : TransposeFolding::OperandIndices{};
+        },
+        TransposeFolding::NeverFoldTranspose);
     pipeline.AddPass<HloSubcomputationUnification>();
     pipeline.AddPass<HloCSE>(/*is_layout_sensitive=*/false);
     pipeline.AddPass<HloDCE>();
diff --git a/tensorflow/compiler/xla/service/gpu/ir_emission_utils.h b/tensorflow/compiler/xla/service/gpu/ir_emission_utils.h
index 4d3e9b10b2e..e8c68a6ef72 100644
--- a/tensorflow/compiler/xla/service/gpu/ir_emission_utils.h
+++ b/tensorflow/compiler/xla/service/gpu/ir_emission_utils.h
@@ -25,16 +25,7 @@ limitations under the License.
 namespace xla {
 namespace gpu {
 
-const int64 kWarpSize = 32;
-
-// Precondition: "hlo" is an operand of a Dot instruction.
-//
-// Returns whether "hlo" is foldable to its user.
-bool IsOperandFoldableToDot(const HloInstruction& hlo);
-
-// Returns true if GpuCompiler can fold any operands of "dot" into "dot" for
-// better performance.
-bool CanFoldOperandsIntoDot(const HloInstruction& dot);
+constexpr int64 kWarpSize = 32;
 
 // Returns true if `hlo` will be implemented as a call to BLAS gemm.
 bool ImplementedAsGemm(const HloInstruction& hlo);
diff --git a/tensorflow/compiler/xla/service/transpose_folding.cc b/tensorflow/compiler/xla/service/transpose_folding.cc
index 07e0ce89f6a..cfb90e6e1d4 100644
--- a/tensorflow/compiler/xla/service/transpose_folding.cc
+++ b/tensorflow/compiler/xla/service/transpose_folding.cc
@@ -21,7 +21,9 @@ limitations under the License.
 #include "tensorflow/compiler/xla/service/gpu/ir_emission_utils.h"
 #include "tensorflow/compiler/xla/service/hlo_computation.h"
 #include "tensorflow/compiler/xla/service/hlo_instruction.h"
+#include "tensorflow/compiler/xla/shape_util.h"
 #include "tensorflow/compiler/xla/status_macros.h"
+#include "tensorflow/compiler/xla/util.h"
 #include "tensorflow/core/lib/core/errors.h"
 #include "tensorflow/core/lib/core/status.h"
 #include "tensorflow/core/platform/logging.h"
@@ -30,43 +32,56 @@ namespace xla {
 
 namespace {
 
-bool IsOperandFoldableToDot(const HloInstruction& hlo) {
-  return hlo.IsRank2Transpose() &&
-         hlo.user_count() == 1;  // The dot is its only user.
-}
-
-bool CanFoldOperandsIntoDot(
+TransposeFolding::OperandIndices CanFoldOperandsIntoDot(
     const HloInstruction& dot,
-    const TransposeFolding::IsTransposableGemmFn& is_transposable_gemm) {
+    const TransposeFolding::TransposableGemmOperandsFn&
+        transposable_gemm_operands) {
   if (HloOpcode::kDot != dot.opcode()) {
-    return false;
+    return {};
   }
 
-  if (!is_transposable_gemm(dot)) {
-    return false;
+  TransposeFolding::OperandIndices operand_set;
+  for (int64 i = 0; i < dot.operand_count(); ++i) {
+    auto& operand = *dot.operand(i);
+    if (operand.IsRank2Transpose() && operand.user_count() == 1) {
+      operand_set.push_back(i);
+    }
   }
 
-  const HloInstruction* lhs = dot.operand(0);
-  const HloInstruction* rhs = dot.operand(1);
-  bool lhs_foldable = IsOperandFoldableToDot(*lhs);
-  bool rhs_foldable = IsOperandFoldableToDot(*rhs);
-  if (!lhs_foldable && !rhs_foldable) {
-    return false;
-  }
-  return true;
+  return transposable_gemm_operands(dot, operand_set);
 }
 
+TransposeFolding::OperandIndices CanFoldOperandsIntoConvolution(
+    const HloInstruction& convolution,
+    const TransposeFolding::TransposableConvOperandsFn&
+        transposable_conv_operands) {
+  if (HloOpcode::kConvolution != convolution.opcode()) {
+    return {};
+  }
+
+  // We only support folding the RHS.
+  const int64 kRhsOperandIndex = 1;
+  auto& operand = *convolution.operand(kRhsOperandIndex);
+  if (operand.opcode() == HloOpcode::kTranspose && operand.user_count() == 1) {
+    return transposable_conv_operands(convolution, {kRhsOperandIndex});
+  }
+
+  return {};
+}
+
+using InstructionOperandsPair =
+    std::pair<HloInstruction*, TransposeFolding::OperandIndices>;
+
 // Folds the operands of `dot` that are foldable transposes. `computation` is
-// the parent HLO computation of `dot`. `module` is the parent HloModule of
-// `computation`.
+// the parent HLO computation of `dot`.
 //
 // Returns whether the module is changed.
-bool FoldTransposeIntoDot(HloInstruction* dot, HloComputation* computation) {
+bool FoldTransposeIntoDot(InstructionOperandsPair pair,
+                          HloComputation* computation) {
+  auto* dot = pair.first;
   std::vector<HloInstruction*> instructions_to_fuse(1, dot);
-  for (HloInstruction* operand : dot->operands()) {
-    if (IsOperandFoldableToDot(*operand)) {
-      instructions_to_fuse.push_back(operand);
-    }
+  for (const int64 operand_index : pair.second) {
+    instructions_to_fuse.push_back(dot->mutable_operand(operand_index));
   }
 
   // Early-exit if no operands are foldable.
@@ -79,28 +94,95 @@ bool FoldTransposeIntoDot(HloInstruction* dot, HloComputation* computation) {
   return true;
 }
 
+// Folds the operands of `convolution` that are foldable transposes.
+// `computation` is the parent HLO computation of `convolution`.
+//
+// Returns whether the module is changed.
+bool FoldTransposeIntoConvolution(InstructionOperandsPair pair,
+                                  HloComputation* computation) {
+  auto& convolution = *pair.first;
+
+  // We only support fusing the RHS transpose into convolution.
+  //
+  // ConvolutionDimensionNumbers doesn't make enough of a distinction between
+  // the output and the activations.
+  //
+  // TODO(b/37125184): Support transposing the LHS too.
+  if (pair.second.size() != 1 || pair.second.front() != 1) {
+    return false;
+  }
+
+  const ConvolutionDimensionNumbers& dnums =
+      convolution.convolution_dimension_numbers();
+  HloInstruction& transpose = *convolution.mutable_operand(1);
+  CHECK_EQ(transpose.opcode(), HloOpcode::kTranspose);
+  const auto& transpose_dimensions = transpose.dimensions();
+  HloInstruction& transpose_operand = *transpose.mutable_operand(0);
+
+  // Everything remains the same except for the kernel dimension numbers. We
+  // need to apply the transpose permutation to the original shape to figure out
+  // what the new logical dimensions are.
+  ConvolutionDimensionNumbers new_dnums = dnums;
+  new_dnums.set_kernel_input_feature_dimension(
+      transpose_dimensions[dnums.kernel_input_feature_dimension()]);
+  new_dnums.set_kernel_output_feature_dimension(
+      transpose_dimensions[dnums.kernel_output_feature_dimension()]);
+  for (auto& kernel_spatial_dimension :
+       *new_dnums.mutable_kernel_spatial_dimensions()) {
+    kernel_spatial_dimension = transpose_dimensions[kernel_spatial_dimension];
+  }
+
+  auto new_conv = HloInstruction::CreateConvolve(
+      convolution.shape(), convolution.mutable_operand(0), &transpose_operand,
+      convolution.window(), new_dnums);
+  TF_CHECK_OK(computation->ReplaceWithNewInstruction(&convolution,
+                                                     std::move(new_conv)));
+
+  return true;
+}
+
 }  // namespace
 
-TransposeFolding::TransposeFolding(IsTransposableGemmFn is_transposable_gemm)
-    : is_transposable_gemm_(std::move(is_transposable_gemm)) {}
+TransposeFolding::TransposeFolding(
+    TransposableGemmOperandsFn transposable_gemm_operands,
+    TransposableConvOperandsFn transposable_conv_operands)
+    : transposable_gemm_operands_(std::move(transposable_gemm_operands)),
+      transposable_conv_operands_(std::move(transposable_conv_operands)) {}
 
 StatusOr<bool> TransposeFolding::Run(HloModule* module) {
   // Modifying the graph while traversing is dangerous, so we find all folding
   // opportunities before actually folding them.
   HloComputation* entry_computation = module->entry_computation();
 
-  std::vector<HloInstruction*> foldable_dots;
-  auto visit_fn = [this, &foldable_dots](HloInstruction* instruction) {
-    if (CanFoldOperandsIntoDot(*instruction, is_transposable_gemm_)) {
-      foldable_dots.emplace_back(instruction);
+  std::vector<std::pair<HloInstruction*, OperandIndices>> foldable_dots;
+  std::vector<std::pair<HloInstruction*, OperandIndices>> foldable_convolutions;
+  auto visit_fn = [this, &foldable_dots,
+                   &foldable_convolutions](HloInstruction* instruction) {
+    {
+      OperandIndices operand_indices =
+          CanFoldOperandsIntoDot(*instruction, transposable_gemm_operands_);
+      if (!operand_indices.empty()) {
+        foldable_dots.emplace_back(instruction, operand_indices);
+      }
+    }
+    {
+      OperandIndices operand_indices = CanFoldOperandsIntoConvolution(
+          *instruction, transposable_conv_operands_);
+      if (!operand_indices.empty()) {
+        foldable_convolutions.emplace_back(
+            std::make_pair(instruction, operand_indices));
+      }
     }
     return tensorflow::Status::OK();
   };
   TF_RETURN_IF_ERROR(entry_computation->root_instruction()->Accept(visit_fn));
 
   bool changed = false;
-  for (HloInstruction* dot : foldable_dots) {
-    changed |= FoldTransposeIntoDot(dot, entry_computation);
+  for (InstructionOperandsPair& pair : foldable_dots) {
+    changed |= FoldTransposeIntoDot(pair, entry_computation);
+  }
+  for (InstructionOperandsPair& pair : foldable_convolutions) {
+    changed |= FoldTransposeIntoConvolution(pair, entry_computation);
   }
   return changed;
 }
diff --git a/tensorflow/compiler/xla/service/transpose_folding.h b/tensorflow/compiler/xla/service/transpose_folding.h
index d857c04ed8d..71e8446452f 100644
--- a/tensorflow/compiler/xla/service/transpose_folding.h
+++ b/tensorflow/compiler/xla/service/transpose_folding.h
@@ -25,16 +25,37 @@ namespace xla {
 // operator is implemented by a GEMM kernel that can transpose its inputs.
 class TransposeFolding : public HloPassInterface {
  public:
-  // IsTransposableGemmFn should return true iff the instruction argument is
-  // implemented as a GEMM kernel that supports transposing its arguments.
-  typedef std::function<bool(const HloInstruction&)> IsTransposableGemmFn;
-  explicit TransposeFolding(IsTransposableGemmFn is_transposable_gemm);
+  using OperandIndices = std::vector<int64>;
+
+  // Returns the set of foldable operands for a given HLO and some candidate
+  // operands.
+  using FoldableOperands = std::function<OperandIndices(const HloInstruction&,
+                                                        const OperandIndices&)>;
+  using TransposableGemmOperandsFn = FoldableOperands;
+  using TransposableConvOperandsFn = FoldableOperands;
+
+  // Helper function to explicitly not fold transposes.
+  static OperandIndices NeverFoldTranspose(const HloInstruction&,
+                                           const OperandIndices&) {
+    return {};
+  }
+  // transposable_gemm_operands returns the set of operands it wants to fold if
+  // the instruction argument is implemented as a GEMM kernel that supports
+  // transposing its arguments.
+  //
+  // transposable_conv_operands returns the set of operands it wants to fold if
+  // the instruction argument is implemented as a convolution that supports
+  // transposing its arguments.
+  explicit TransposeFolding(
+      TransposableGemmOperandsFn transposable_gemm_operands,
+      TransposableConvOperandsFn transposable_conv_operands);
   tensorflow::StringPiece name() const override { return "transpose-folding"; }
 
   StatusOr<bool> Run(HloModule* module) override;
 
  private:
-  IsTransposableGemmFn is_transposable_gemm_;
+  TransposableGemmOperandsFn transposable_gemm_operands_;
+  TransposableConvOperandsFn transposable_conv_operands_;
 };
 
 }  // namespace xla
diff --git a/tensorflow/compiler/xla/service/transpose_folding_test.cc b/tensorflow/compiler/xla/service/transpose_folding_test.cc
index 09f932e29e6..ea5ab2b9171 100644
--- a/tensorflow/compiler/xla/service/transpose_folding_test.cc
+++ b/tensorflow/compiler/xla/service/transpose_folding_test.cc
@@ -16,15 +16,17 @@ limitations under the License.
 #include "tensorflow/compiler/xla/service/transpose_folding.h"
 
 #include <memory>
-#include <set>
+#include <unordered_set>
 #include <vector>
 
+#include "tensorflow/compiler/xla/client/computation_builder.h"
 #include "tensorflow/compiler/xla/literal_util.h"
 #include "tensorflow/compiler/xla/service/gpu/ir_emission_utils.h"
 #include "tensorflow/compiler/xla/service/hlo_computation.h"
 #include "tensorflow/compiler/xla/service/hlo_instruction.h"
 #include "tensorflow/compiler/xla/service/hlo_module.h"
 #include "tensorflow/compiler/xla/service/hlo_opcode.h"
+#include "tensorflow/compiler/xla/service/shape_inference.h"
 #include "tensorflow/compiler/xla/shape_util.h"
 #include "tensorflow/compiler/xla/test_helpers.h"
 #include "tensorflow/compiler/xla/xla_data.pb.h"
@@ -35,12 +37,22 @@ namespace xla {
 class TransposeFoldingTest : public ::testing::Test {
  protected:
   void FoldTranspose(HloModule* module) {
-    TransposeFolding transpose_folding(gpu::ImplementedAsGemm);
+    TransposeFolding transpose_folding(
+        [](const HloInstruction& dot,
+           const TransposeFolding::OperandIndices& candidate_operands) {
+          return gpu::ImplementedAsGemm(dot)
+                     ? candidate_operands
+                     : TransposeFolding::OperandIndices{};
+        },
+        [](const HloInstruction& convolution,
+           const TransposeFolding::OperandIndices& candidate_operands) {
+          return candidate_operands;
+        });
     EXPECT_IS_OK(transpose_folding.Run(module).status());
   }
 };
 
-TEST_F(TransposeFoldingTest, FoldTranspose) {
+TEST_F(TransposeFoldingTest, FoldDotTranspose) {
   auto builder = HloComputation::Builder("entry_computation");
   HloInstruction* x = builder.AddInstruction(HloInstruction::CreateParameter(
       /*parameter_number=*/0, ShapeUtil::MakeShape(F32, {2, 3}),
@@ -61,7 +73,7 @@ TEST_F(TransposeFoldingTest, FoldTranspose) {
   FoldTranspose(&module);
 
   // Instructions after folding: x, y, and the fusion.
-  std::set<HloInstruction*> instruction_set;
+  std::unordered_set<HloInstruction*> instruction_set;
   for (auto& instruction : entry_computation->instructions()) {
     instruction_set.insert(instruction.get());
   }
@@ -77,7 +89,7 @@ TEST_F(TransposeFoldingTest, FoldTranspose) {
   EXPECT_EQ(4, fusion->fused_instructions().size());
 }
 
-TEST_F(TransposeFoldingTest, FoldTransposeConstant) {
+TEST_F(TransposeFoldingTest, FoldDotTransposeConstant) {
   auto builder = HloComputation::Builder("entry_computation");
   // 2x1
   HloInstruction* const0 = builder.AddInstruction(
@@ -115,7 +127,7 @@ TEST_F(TransposeFoldingTest, FoldTransposeConstant) {
             entry_computation->root_instruction()->fused_instructions().size());
 }
 
-TEST_F(TransposeFoldingTest, FuseWithConstantOperands) {
+TEST_F(TransposeFoldingTest, FuseDotWithConstantOperands) {
   auto builder = HloComputation::Builder("entry");
   // (1.0 + 2.0) * (2.0 - 3.0)
   HloInstruction* const1 = builder.AddInstruction(
@@ -146,4 +158,168 @@ TEST_F(TransposeFoldingTest, FuseWithConstantOperands) {
   EXPECT_EQ(6, callee_computation->instructions().size());
 }
 
+// Test that a two dimension swap of the kernel gets folded into convolution.
+TEST_F(TransposeFoldingTest, FoldConvDimSwapTransposeRhs) {
+  auto builder = HloComputation::Builder("entry_computation");
+  HloInstruction* x = builder.AddInstruction(HloInstruction::CreateParameter(
+      /*parameter_number=*/0, ShapeUtil::MakeShape(F32, {2, 3, 1, 1}),
+      /*name=*/"x"));
+  HloInstruction* y = builder.AddInstruction(HloInstruction::CreateParameter(
+      /*parameter_number=*/1, ShapeUtil::MakeShape(F32, {3, 2, 1, 1}),
+      /*name=*/"y"));
+  HloInstruction* transpose_y =
+      builder.AddInstruction(HloInstruction::CreateTranspose(
+          ShapeUtil::MakeShape(F32, {2, 3, 1, 1}), y, {1, 0, 2, 3}));
+  auto dnums = ComputationBuilder::CreateDefaultConvDimensionNumbers();
+  Window window;
+  for (int i = 0; i < 2; ++i) {
+    WindowDimension* dim = window.add_dimensions();
+    dim->set_padding_low(0);
+    dim->set_padding_high(0);
+    dim->set_base_dilation(1);
+    dim->set_window_dilation(1);
+    dim->set_stride(1);
+    dim->set_size(
+        transpose_y->shape().dimensions(dnums.kernel_spatial_dimensions(i)));
+  }
+  StatusOr<Shape> conv_shape = ShapeInference::InferConvolveShape(
+      x->shape(), transpose_y->shape(), window, dnums);
+  EXPECT_IS_OK(conv_shape);
+  HloInstruction* conv = builder.AddInstruction(HloInstruction::CreateConvolve(
+      conv_shape.ValueOrDie(), x, transpose_y, window, dnums));
+
+  HloModule module("test_module");
+  HloComputation* entry_computation =
+      module.AddEntryComputation(builder.Build(conv));
+  FoldTranspose(&module);
+
+  // Instructions after folding: x, y, and the convolution.
+  std::unordered_set<HloInstruction*> instruction_set;
+  for (auto& instruction : entry_computation->instructions()) {
+    instruction_set.insert(instruction.get());
+  }
+  CHECK_EQ(1, instruction_set.erase(x)) << "x is not in entry_computation.";
+  CHECK_EQ(1, instruction_set.erase(y)) << "y is not in entry_computation.";
+  CHECK_EQ(1, instruction_set.size())
+      << "entry_computation should contain exactly 3 instructions.";
+  HloInstruction* new_conv = *instruction_set.begin();
+  EXPECT_EQ(HloOpcode::kConvolution, new_conv->opcode());
+  EXPECT_EQ(dnums.kernel_input_feature_dimension(),
+            new_conv->convolution_dimension_numbers()
+                .kernel_output_feature_dimension());
+  EXPECT_EQ(dnums.kernel_output_feature_dimension(),
+            new_conv->convolution_dimension_numbers()
+                .kernel_input_feature_dimension());
+}
+
+// Test that a complex transpose of the kernel gets folded into convolution.
+TEST_F(TransposeFoldingTest, FoldConvComplexTransposeRhs) {
+  auto builder = HloComputation::Builder("entry_computation");
+  HloInstruction* x = builder.AddInstruction(HloInstruction::CreateParameter(
+      /*parameter_number=*/0, ShapeUtil::MakeShape(F32, {2, 3, 1, 1}),
+      /*name=*/"x"));
+  HloInstruction* y = builder.AddInstruction(HloInstruction::CreateParameter(
+      /*parameter_number=*/1, ShapeUtil::MakeShape(F32, {1, 2, 1, 3}),
+      /*name=*/"y"));
+  HloInstruction* transpose_y =
+      builder.AddInstruction(HloInstruction::CreateTranspose(
+          ShapeUtil::MakeShape(F32, {2, 3, 1, 1}), y, {1, 3, 0, 2}));
+  auto dnums = ComputationBuilder::CreateDefaultConvDimensionNumbers();
+  Window window;
+  for (int i = 0; i < 2; ++i) {
+    WindowDimension* dim = window.add_dimensions();
+    dim->set_padding_low(0);
+    dim->set_padding_high(0);
+    dim->set_base_dilation(1);
+    dim->set_window_dilation(1);
+    dim->set_stride(1);
+    dim->set_size(
+        transpose_y->shape().dimensions(dnums.kernel_spatial_dimensions(i)));
+  }
+  StatusOr<Shape> conv_shape = ShapeInference::InferConvolveShape(
+      x->shape(), transpose_y->shape(), window, dnums);
+  EXPECT_IS_OK(conv_shape);
+  HloInstruction* conv = builder.AddInstruction(HloInstruction::CreateConvolve(
+      conv_shape.ValueOrDie(), x, transpose_y, window, dnums));
+
+  HloModule module("test_module");
+  HloComputation* entry_computation =
+      module.AddEntryComputation(builder.Build(conv));
+  FoldTranspose(&module);
+
+  // Instructions after folding: x, y, and the convolution.
+  std::unordered_set<HloInstruction*> instruction_set;
+  for (auto& instruction : entry_computation->instructions()) {
+    instruction_set.insert(instruction.get());
+  }
+  CHECK_EQ(1, instruction_set.erase(x)) << "x is not in entry_computation.";
+  CHECK_EQ(1, instruction_set.erase(y)) << "y is not in entry_computation.";
+  CHECK_EQ(1, instruction_set.size())
+      << "entry_computation should contain exactly 3 instructions.";
+  HloInstruction* new_conv = *instruction_set.begin();
+  EXPECT_EQ(HloOpcode::kConvolution, new_conv->opcode());
+  EXPECT_EQ(dnums.kernel_input_feature_dimension(),
+            new_conv->convolution_dimension_numbers()
+                .kernel_output_feature_dimension());
+  EXPECT_EQ(dnums.kernel_spatial_dimensions(1),
+            new_conv->convolution_dimension_numbers()
+                .kernel_input_feature_dimension());
+  EXPECT_EQ(
+      dnums.kernel_output_feature_dimension(),
+      new_conv->convolution_dimension_numbers().kernel_spatial_dimensions(0));
+  EXPECT_EQ(
+      dnums.kernel_spatial_dimensions(0),
+      new_conv->convolution_dimension_numbers().kernel_spatial_dimensions(1));
+}
+
+// Test that a transpose of the activations does not get folded into
+// convolution.
+TEST_F(TransposeFoldingTest, FoldConvTransposeLhs) {
+  auto builder = HloComputation::Builder("entry_computation");
+  HloInstruction* x = builder.AddInstruction(HloInstruction::CreateParameter(
+      /*parameter_number=*/0, ShapeUtil::MakeShape(F32, {3, 2, 1, 1}),
+      /*name=*/"x"));
+  HloInstruction* y = builder.AddInstruction(HloInstruction::CreateParameter(
+      /*parameter_number=*/1, ShapeUtil::MakeShape(F32, {2, 3, 1, 1}),
+      /*name=*/"y"));
+  HloInstruction* transpose_x =
+      builder.AddInstruction(HloInstruction::CreateTranspose(
+          ShapeUtil::MakeShape(F32, {2, 3, 1, 1}), x, {1, 0, 2, 3}));
+  auto dnums = ComputationBuilder::CreateDefaultConvDimensionNumbers();
+  Window window;
+  for (int i = 0; i < 2; ++i) {
+    WindowDimension* dim = window.add_dimensions();
+    dim->set_padding_low(0);
+    dim->set_padding_high(0);
+    dim->set_base_dilation(1);
+    dim->set_window_dilation(1);
+    dim->set_stride(1);
+    dim->set_size(y->shape().dimensions(dnums.kernel_spatial_dimensions(i)));
+  }
+  StatusOr<Shape> conv_shape = ShapeInference::InferConvolveShape(
+      transpose_x->shape(), y->shape(), window, dnums);
+  EXPECT_IS_OK(conv_shape);
+  HloInstruction* conv = builder.AddInstruction(HloInstruction::CreateConvolve(
+      conv_shape.ValueOrDie(), transpose_x, y, window, dnums));
+
+  HloModule module("test_module");
+  HloComputation* entry_computation =
+      module.AddEntryComputation(builder.Build(conv));
+  FoldTranspose(&module);
+
+  // Instructions after folding: transpose_x, y, and the convolution.
+  std::unordered_set<HloInstruction*> instruction_set;
+  for (auto& instruction : entry_computation->instructions()) {
+    instruction_set.insert(instruction.get());
+  }
+  CHECK_EQ(1, instruction_set.erase(x)) << "x is not in entry_computation.";
+  CHECK_EQ(1, instruction_set.erase(y)) << "y is not in entry_computation.";
+  CHECK_EQ(1, instruction_set.erase(transpose_x))
+      << "transpose_x is not in entry_computation.";
+  CHECK_EQ(1, instruction_set.erase(conv))
+      << "transpose_x is not in entry_computation.";
+  CHECK_EQ(0, instruction_set.size())
+      << "entry_computation should contain exactly 4 instructions.";
+}
+
 }  // namespace xla
diff --git a/tensorflow/compiler/xla/test.h b/tensorflow/compiler/xla/test.h
new file mode 100644
index 00000000000..87a8c5f3a52
--- /dev/null
+++ b/tensorflow/compiler/xla/test.h
@@ -0,0 +1,48 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_COMPLIER_XLA_TEST_H_
+#define TENSORFLOW_COMPLIER_XLA_TEST_H_
+
+// This header includes gmock.h and enables the use of gmock matchers in tests
+// in third_party/tensorflow/compiler/xla.
+//
+// Test including this header can use the macros EXPECT_THAT(...) and
+// ASSERT_THAT(...) in combination with gmock matchers.
+// Example:
+//  std::vector<int> vec = Foo();
+//  EXPECT_THAT(vec, ::testing::ElementsAre(1,2,3));
+//
+// For more details on gmock matchers see:
+// https://github.com/google/googletest/blob/master/googlemock/docs/CheatSheet.md#matchers
+//
+// The advantages of using gmock matchers instead of self defined matchers are
+// better error messages, more maintainable tests and more test coverage.
+//
+// Note that while the use of gmock matchers is allowed in the xla project, the
+// use of mocks is disallowed in the whole tensorflow project!
+
+#include "tensorflow/core/platform/platform.h"
+
+#if defined(PLATFORM_GOOGLE) || defined(PLATFORM_GOOGLE_ANDROID)
+#include "testing/base/public/gmock.h"
+#else
+#include <gmock/gmock-generated-matchers.h>
+#include <gmock/gmock-matchers.h>
+#endif
+
+#include "tensorflow/core/platform/test.h"
+
+#endif  // TENSORFLOW_COMPLIER_XLA_TEST_H_
diff --git a/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_buffer.h b/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_buffer.h
index 22ec5349f86..5e316538cef 100644
--- a/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_buffer.h
+++ b/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_buffer.h
@@ -55,7 +55,7 @@ class WeightedQuantilesBuffer {
       : max_size_(std::min(block_size << 1, max_elements)) {
     QCHECK(max_size_ > 0) << "Invalid buffer specification: (" << block_size
                           << ", " << max_elements << ")";
-    map_.reserve(max_size_);
+    vec_.reserve(max_size_);
   }
 
   // Disallow copying as it's semantically non-sensical in the Squawd algorithm
@@ -77,42 +77,48 @@ class WeightedQuantilesBuffer {
       return;
     }
 
-    // Insert entry to map if not already present else
-    // accumulate the new weight.
-    auto result = map_.insert(BufferMapEntry(value, weight));
-    if (!result.second) {
-      result.first->second += weight;
-    }
+    // Push back the entry to the buffer.
+    vec_.push_back(BufferEntry(value, weight));
   }
 
-  // Returns a sorted vector view of the base buffer. Callers should
-  // minimize how often this is called, ideally only right after the buffer
-  // becomes full.
-  std::vector<BufferEntry> GenerateEntryList() const {
+  // Returns a sorted vector view of the base buffer and clears the buffer.
+  // Callers should minimize how often this is called, ideally only right after
+  // the buffer becomes full.
+  std::vector<BufferEntry> GenerateEntryList() {
     std::vector<BufferEntry> ret;
-    ret.reserve(map_.size());
-    std::transform(map_.begin(), map_.end(), std::back_inserter(ret),
-                   [](const BufferMapEntry& map_entry) {
-                     return BufferEntry(map_entry.first, map_entry.second);
-                   });
+    if (vec_.size() == 0) {
+      return ret;
+    }
+    ret.swap(vec_);
+    vec_.reserve(max_size_);
     std::sort(ret.begin(), ret.end());
+    size_t num_entries = 0;
+    for (size_t i = 1; i < ret.size(); ++i) {
+      if (ret[i].value != ret[i - 1].value) {
+        BufferEntry tmp = ret[i];
+        ++num_entries;
+        ret[num_entries] = tmp;
+      } else {
+        ret[num_entries].weight += ret[i].weight;
+      }
+    }
+    ret.resize(num_entries + 1);
     return ret;
   }
 
-  int64 Size() const { return map_.size(); }
-  bool IsFull() const { return map_.size() >= max_size_; }
-  void Clear() { map_.clear(); }
+  int64 Size() const { return vec_.size(); }
+  bool IsFull() const { return vec_.size() >= max_size_; }
+  void Clear() { vec_.clear(); }
 
  private:
-  using BufferMap = typename std::unordered_map<ValueType, WeightType>;
-  using BufferMapEntry = typename BufferMap::value_type;
+  using BufferVector = typename std::vector<BufferEntry>;
 
   // Comparison function.
   static constexpr decltype(CompareFn()) kCompFn = CompareFn();
 
   // Base buffer.
   size_t max_size_;
-  BufferMap map_;
+  BufferVector vec_;
 };
 
 template <typename ValueType, typename WeightType, typename CompareFn>
diff --git a/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_buffer_test.cc b/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_buffer_test.cc
index 02696fb4f18..8e403186651 100644
--- a/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_buffer_test.cc
+++ b/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_buffer_test.cc
@@ -69,47 +69,32 @@ TEST_F(WeightedQuantilesBufferTest, PushEntryFull) {
   expected.emplace_back(2, 4);
   expected.emplace_back(5, 9);
 
-  // At this point, we have a compaction and duplicate entry 2 is merged.
-  EXPECT_FALSE(buffer.IsFull());
-  EXPECT_EQ(buffer.GenerateEntryList(), expected);
-
-  // Push another unique entry.
-  buffer.PushEntry(3, 2);
+  // At this point, we have pushed 4 entries and we expect the buffer to be
+  // full.
   EXPECT_TRUE(buffer.IsFull());
+  EXPECT_EQ(buffer.GenerateEntryList(), expected);
+  EXPECT_FALSE(buffer.IsFull());
+}
 
+TEST_F(WeightedQuantilesBufferTest, PushEntryFullDeath) {
+  // buffer capacity is 4.
+  Buffer buffer(2, 100);
+  buffer.PushEntry(5, 9);
+  buffer.PushEntry(2, 3);
+  buffer.PushEntry(-1, 7);
+  buffer.PushEntry(2, 1);
+
+  std::vector<BufferEntry> expected;
+  expected.emplace_back(-1, 7);
+  expected.emplace_back(2, 4);
+  expected.emplace_back(5, 9);
+
+  // At this point, we have pushed 4 entries and we expect the buffer to be
+  // full.
+  EXPECT_TRUE(buffer.IsFull());
   // Can't push any more entries before clearing.
   EXPECT_DEATH(({ buffer.PushEntry(6, 6); }), "Buffer already full");
 }
 
-TEST_F(WeightedQuantilesBufferTest, RandomizedPush) {
-  // buffer capacity is 6.
-  Buffer buffer(3, 100);
-  std::array<double, 5> elements = {{1.1, 2.3, 5.1, 8.0, 12.6}};
-  std::array<double, elements.size()> counts;
-  counts.fill(0.0);
-
-  random::PhiloxRandom philox(13);
-  random::SimplePhilox rand(&philox);
-
-  for (int iters = 10000; iters-- > 0; --iters) {
-    // Add entry.
-    int32 picked_idx = rand.Uniform(elements.size());
-    buffer.PushEntry(elements[picked_idx], 1.0);
-    ++counts[picked_idx];
-
-    // We can't fill buffer with a number of unique elements < capacity.
-    EXPECT_FALSE(buffer.IsFull());
-  }
-
-  // Ensure we didn't lose any information.
-  std::vector<BufferEntry> expected;
-  for (int i = 0; i < elements.size(); ++i) {
-    if (counts[i] > 0) {
-      expected.emplace_back(elements[i], counts[i]);
-    }
-  }
-  EXPECT_EQ(buffer.GenerateEntryList(), expected);
-}
-
 }  // namespace
 }  // namespace tensorflow
diff --git a/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_stream.h b/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_stream.h
index ad2358e4c43..daf0e480003 100644
--- a/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_stream.h
+++ b/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_stream.h
@@ -91,12 +91,11 @@ class WeightedQuantilesStream {
     // and push weighted quantile summary up the level chain.
     if (buffer_.IsFull()) {
       PushBuffer(buffer_);
-      buffer_.Clear();
     }
   }
 
   // Pushes full buffer while maintaining approximation error invariants.
-  void PushBuffer(const Buffer& buffer) {
+  void PushBuffer(Buffer& buffer) {
     // Validate state.
     QCHECK(!finalized_) << "Finalize() already called.";
 
@@ -124,7 +123,6 @@ class WeightedQuantilesStream {
 
     // Flush any remaining buffer elements.
     PushBuffer(buffer_);
-    buffer_.Clear();
 
     // Create final merged summary.
     local_summary_.Clear();
diff --git a/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_summary_test.cc b/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_summary_test.cc
index e6d10bf08b6..0bdfb406641 100644
--- a/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_summary_test.cc
+++ b/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_summary_test.cc
@@ -91,9 +91,10 @@ TEST_F(WeightedQuantilesSummaryTest, BuildFromBuffer) {
 }
 
 TEST_F(WeightedQuantilesSummaryTest, CompressSeparately) {
+  const auto entry_list = buffer1_->GenerateEntryList();
   for (int new_size = 9; new_size >= 2; --new_size) {
     Summary summary;
-    summary.BuildFromBufferEntries(buffer1_->GenerateEntryList());
+    summary.BuildFromBufferEntries(entry_list);
     summary.Compress(new_size);
 
     // Expect a max approximation error of 1 / n
@@ -161,10 +162,12 @@ TEST_F(WeightedQuantilesSummaryTest, CompressRandomized) {
 
 TEST_F(WeightedQuantilesSummaryTest, MergeSymmetry) {
   // Create two separate summaries and merge.
+  const auto list_1 = buffer1_->GenerateEntryList();
+  const auto list_2 = buffer2_->GenerateEntryList();
   Summary summary1;
-  summary1.BuildFromBufferEntries(buffer1_->GenerateEntryList());
+  summary1.BuildFromBufferEntries(list_1);
   Summary summary2;
-  summary2.BuildFromBufferEntries(buffer2_->GenerateEntryList());
+  summary2.BuildFromBufferEntries(list_2);
 
   // Merge summary 2 into 1 and verify.
   summary1.Merge(summary2);
@@ -178,7 +181,7 @@ TEST_F(WeightedQuantilesSummaryTest, MergeSymmetry) {
   EXPECT_EQ(summary1.Size(), 14);  // 14 unique values.
 
   // Merge summary 1 into 2 and verify same result.
-  summary1.BuildFromBufferEntries(buffer1_->GenerateEntryList());
+  summary1.BuildFromBufferEntries(list_1);
   summary2.Merge(summary1);
   EXPECT_EQ(summary2.ApproximationError(), 0.0);
   EXPECT_EQ(summary2.MinValue(),
diff --git a/tensorflow/contrib/cmake/tf_python.cmake b/tensorflow/contrib/cmake/tf_python.cmake
index 39fbf603f0e..178e03c222e 100755
--- a/tensorflow/contrib/cmake/tf_python.cmake
+++ b/tensorflow/contrib/cmake/tf_python.cmake
@@ -212,7 +212,6 @@ add_python_module("tensorflow/tensorboard")
 add_python_module("tensorflow/tensorboard/backend")
 add_python_module("tensorflow/tensorboard/backend/event_processing")
 add_python_module("tensorflow/tensorboard/plugins")
-add_python_module("tensorflow/tensorboard/plugins/debugger")
 add_python_module("tensorflow/tensorboard/plugins/projector")
 add_python_module("tensorflow/tensorboard/plugins/text")
 add_python_module("tensorflow/tensorboard/scripts")
diff --git a/tensorflow/contrib/factorization/BUILD b/tensorflow/contrib/factorization/BUILD
index 7f359bea51c..8dc78da6ba3 100644
--- a/tensorflow/contrib/factorization/BUILD
+++ b/tensorflow/contrib/factorization/BUILD
@@ -202,6 +202,7 @@ tf_py_test(
     additional_deps = [
         ":factorization_py",
         ":factorization_py_CYCLIC_DEPENDENCIES_THAT_NEED_TO_GO",
+        ":factorization_ops_test_utils_py",
         "//third_party/py/numpy",
         "//tensorflow/python:array_ops",
         "//tensorflow/python:client_testlib",
diff --git a/tensorflow/contrib/factorization/python/ops/factorization_ops.py b/tensorflow/contrib/factorization/python/ops/factorization_ops.py
index b853652629c..8fb33dad6fd 100644
--- a/tensorflow/contrib/factorization/python/ops/factorization_ops.py
+++ b/tensorflow/contrib/factorization/python/ops/factorization_ops.py
@@ -190,7 +190,8 @@ class WALSModel(object):
                num_col_shards=1,
                row_weights=1,
                col_weights=1,
-               use_factors_weights_cache=True):
+               use_factors_weights_cache=True,
+               use_gramian_cache=True):
     """Creates model for WALS matrix factorization.
 
     Args:
@@ -224,6 +225,8 @@ class WALSModel(object):
       col_weights: See row_weights.
       use_factors_weights_cache: When True, the factors and weights will be
         cached on the workers before the updates start. Defaults to True.
+      use_gramian_cache: When True, the Gramians will be cached on the workers
+        before the updates start. Defaults to True.
     """
     self._input_rows = input_rows
     self._input_cols = input_cols
@@ -243,6 +246,7 @@ class WALSModel(object):
                                                   self._num_col_shards,
                                                   "col_weights")
     self._use_factors_weights_cache = use_factors_weights_cache
+    self._use_gramian_cache = use_gramian_cache
     self._row_factors = self._create_factors(self._input_rows,
                                              self._n_components,
                                              self._num_row_shards, row_init,
@@ -495,10 +499,13 @@ class WALSModel(object):
     """Creates local cache of factors, weights and gramian for rows and columns.
 
     Note that currently the caching strategy is as follows:
-    When initiating a row(column) update, the column(row) gramian is computed
-    and cached while the row gramian is reset; optionally, column(row) factors
-    and weights are cached and row(column) factors and weights are reset when
-    use_factors_weights_cache is True.
+    When initiating a row (resp. column) update:
+      - The column (resp. row) gramian is computed.
+      - Optionally, if use_gramian_cache is True, the column (resp. row) Gramian
+        is cached, while the row (resp. column) gramian is reset.
+      - Optionally, if use_factors_weights_cache is True, the column (resp. row)
+        factors and weights are cached, while the row (resp. column) factors and
+        weights are reset.
     """
 
     (self._row_factors_cache, row_factors_cache_init,
@@ -515,18 +522,20 @@ class WALSModel(object):
         self._row_weights,
         "row_wt_cache",
         pass_through=not self._use_factors_weights_cache)
-
     (self._col_wt_cache, col_wt_cache_init, _) = self._cached_copy(
         self._col_weights,
         "col_wt_cache",
         pass_through=not self._use_factors_weights_cache)
-
     (self._row_gramian_cache, row_gramian_cache_init,
      row_gramian_cache_reset) = self._cached_copy(
-         self._row_gramian, "row_gramian_cache", pass_through=False)
+         self._row_gramian,
+         "row_gramian_cache",
+         pass_through=not self._use_gramian_cache)
     (self._col_gramian_cache, col_gramian_cache_init,
      col_gramian_cache_reset) = self._cached_copy(
-         self._col_gramian, "col_gramian_cache", pass_through=False)
+         self._col_gramian,
+         "col_gramian_cache",
+         pass_through=not self._use_gramian_cache)
 
     self._row_updates_init = control_flow_ops.group(col_factors_cache_init,
                                                     row_factors_cache_reset,
diff --git a/tensorflow/contrib/factorization/python/ops/wals.py b/tensorflow/contrib/factorization/python/ops/wals.py
index 3fd2cbbec2b..41211859f18 100644
--- a/tensorflow/contrib/factorization/python/ops/wals.py
+++ b/tensorflow/contrib/factorization/python/ops/wals.py
@@ -18,7 +18,10 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.contrib.factorization.python.ops import factorization_ops
 from tensorflow.contrib.framework.python.ops import variables as framework_variables
+from tensorflow.contrib.learn.python.learn.estimators import estimator
+from tensorflow.contrib.learn.python.learn.estimators import model_fn
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
 from tensorflow.python.ops import array_ops
@@ -221,3 +224,321 @@ class _SweepHook(session_run_hook.SessionRunHook):
     self._is_sweep_done = run_values.results[0]
     logging.info("Partial fit done.")
 
+
+def _wals_factorization_model_function(features, labels, mode, params):
+  """Model function for the WALSFactorization estimator.
+
+  Args:
+    features: Dictionary of features. See WALSMatrixFactorization.
+    labels: Must be None.
+    mode: A model_fn.ModeKeys object.
+    params: Dictionary of parameters containing arguments passed to the
+      WALSMatrixFactorization constructor.
+
+  Returns:
+    A ModelFnOps object.
+  """
+  assert labels is None
+  use_factors_weights_cache = (
+      params["use_factors_weights_cache_for_training"]
+      and mode == model_fn.ModeKeys.TRAIN)
+  use_gramian_cache = (
+      params["use_gramian_cache_for_training"]
+      and mode == model_fn.ModeKeys.TRAIN)
+  model = factorization_ops.WALSModel(
+      params["num_rows"],
+      params["num_cols"],
+      params["embedding_dimension"],
+      unobserved_weight=params["unobserved_weight"],
+      regularization=params["regularization_coeff"],
+      row_init=params["row_init"],
+      col_init=params["col_init"],
+      num_row_shards=params["num_row_shards"],
+      num_col_shards=params["num_col_shards"],
+      row_weights=params["row_weights"],
+      col_weights=params["col_weights"],
+      use_factors_weights_cache=use_factors_weights_cache,
+      use_gramian_cache=use_gramian_cache)
+
+  # Get input rows and cols. We either update rows or columns depending on
+  # the value of row_sweep, which is maintained using a session hook
+  input_rows = features[WALSMatrixFactorization.INPUT_ROWS]
+  input_cols = features[WALSMatrixFactorization.INPUT_COLS]
+  input_row_indices, _ = array_ops.unique(input_rows.indices[:, 0])
+  input_col_indices, _ = array_ops.unique(input_cols.indices[:, 0])
+
+  # Train ops, controlled using the SweepHook
+  # We need to run the following ops:
+  # Before a row sweep:
+  #   row_update_prep_gramian_op
+  #   initialize_row_update_op
+  # During a row sweep:
+  #   update_row_factors_op
+  # Before a col sweep:
+  #   col_update_prep_gramian_op
+  #   initialize_col_update_op
+  # During a col sweep:
+  #   update_col_factors_op
+
+  is_row_sweep_var = variables.Variable(
+      True, "is_row_sweep",
+      collections=[ops.GraphKeys.GLOBAL_VARIABLES])
+  # The row sweep is determined by is_row_sweep_var (controlled by the
+  # sweep_hook) in TRAIN mode, and manually in EVAL mode.
+  is_row_sweep = (features[WALSMatrixFactorization.PROJECT_ROW]
+                  if mode == model_fn.ModeKeys.EVAL else is_row_sweep_var)
+
+  def update_row_factors():
+    return model.update_row_factors(sp_input=input_rows, transpose_input=False)
+  def update_col_factors():
+    return model.update_col_factors(sp_input=input_cols, transpose_input=True)
+  _, train_op, loss = control_flow_ops.cond(
+      is_row_sweep, update_row_factors, update_col_factors)
+
+  row_prep_ops = [model.row_update_prep_gramian_op,
+                  model.initialize_row_update_op]
+  col_prep_ops = [model.col_update_prep_gramian_op,
+                  model.initialize_col_update_op]
+  cache_init_ops = [model.worker_init]
+
+  sweep_hook = _SweepHook(
+      is_row_sweep_var,
+      train_op,
+      params["num_rows"],
+      params["num_cols"],
+      input_row_indices,
+      input_col_indices,
+      row_prep_ops,
+      col_prep_ops,
+      cache_init_ops,
+  )
+
+  # Prediction ops (only return predictions in INFER mode)
+  predictions = {}
+  if mode == model_fn.ModeKeys.INFER:
+    project_row = features[WALSMatrixFactorization.PROJECT_ROW]
+    projection_weights = features.get(
+        WALSMatrixFactorization.PROJECTION_WEIGHTS)
+    def get_row_projection():
+      return model.project_row_factors(
+          sp_input=input_rows,
+          projection_weights=projection_weights,
+          transpose_input=False)
+    def get_col_projection():
+      return model.project_col_factors(
+          sp_input=input_cols,
+          projection_weights=projection_weights,
+          transpose_input=True)
+
+    predictions[WALSMatrixFactorization.PROJECTION_RESULT] = (
+        control_flow_ops.cond(
+            project_row, get_row_projection, get_col_projection))
+
+  return model_fn.ModelFnOps(
+      mode=mode,
+      predictions=predictions,
+      loss=loss,
+      eval_metric_ops={},
+      train_op=train_op,
+      training_hooks=[sweep_hook])
+
+
+class WALSMatrixFactorization(estimator.Estimator):
+  """An Estimator for Weighted Matrix Factorization, using the WALS method.
+
+  WALS (Weighted Alternating Least Squares) is an algorithm for weighted matrix
+  factorization. It computes a low-rank approximation of a given sparse (n x m)
+  matrix A, by a product of two matrices, U * V^T, where U is a (n x k) matrix
+  and V is a (m x k) matrix. Here k is the rank of the approximation, also
+  called the embedding dimension. We refer to U as the row factors, and V as the
+  column factors.
+  See tensorflow/contrib/factorization/g3doc/wals.md for the precise problem
+  formulation.
+
+  The training proceeds in sweeps: during a row_sweep, we fix V and solve for U.
+  During a column sweep, we fix U and solve for V. Each one of these problems is
+  an unconstrained quadratic minimization problem and can be solved exactly (it
+  can also be solved in mini-batches, since the solution decouples nicely).
+  The alternating between sweeps is achieved by using a hook during training,
+  which is responsible for keeping track of the sweeps and running preparation
+  ops at the beginning of each sweep. It also updates the global_step variable,
+  which keeps track of the number of batches processed since the beginning of
+  training.
+  The current implementation assumes that the training is run on a single
+  machine, and will fail if config.num_worker_replicas is not equal to one.
+  Training is done by calling self.fit(input_fn=input_fn), where input_fn
+  provides two queues: one for rows of the input matrix, and one for rows of the
+  transposed input matrix (i.e. columns of the original matrix). Note that
+  during a row sweep, only row batches are processed (ignoring column batches)
+  and vice-versa.
+
+  For prediction, given a new set of input rows A' (e.g. new rows of the A
+  matrix), we compute a corresponding set of row factors U', such that U' * V^T
+  is a good approximation of A'. We call this operation a row projection. A
+  similar operation is defined for columns.
+  Projection is done by calling self.get_projections(input_fn=input_fn), where
+  input_fn satisfies the constraints given below.
+
+  The input functions must satisfy the following constraints: Calling input_fn
+  must return a tuple (features, labels) where labels is None, and features is
+  a dict containing the following keys:
+  TRAIN:
+    - WALSMatrixFactorization.INPUT_ROWS: float32 SparseTensor (matrix).
+      Rows of the input matrix to process (or to project).
+    - WALSMatrixFactorization.INPUT_COLS: float32 SparseTensor (matrix).
+      Columns of the input matrix to process (or to project), transposed.
+  INFER:
+    - WALSMatrixFactorization.INPUT_ROWS: float32 SparseTensor (matrix).
+      Rows to project.
+    - WALSMatrixFactorization.INPUT_COLS: float32 SparseTensor (matrix).
+      Columns to project.
+    - WALSMatrixFactorization.PROJECT_ROW: Boolean Tensor. Whether to project
+      the rows or columns.
+    - WALSMatrixFactorization.PROJECTION_WEIGHTS (Optional): float32 Tensor
+      (vector). The weights to use in the projection.
+  EVAL:
+    - WALSMatrixFactorization.INPUT_ROWS: float32 SparseTensor (matrix).
+      Rows to project.
+    - WALSMatrixFactorization.INPUT_COLS: float32 SparseTensor (matrix).
+      Columns to project.
+    - WALSMatrixFactorization.PROJECT_ROW: Boolean Tensor. Whether to project
+      the rows or columns.
+  """
+  # Keys to be used in model_fn
+  # Features keys
+  INPUT_ROWS = "input_rows"
+  INPUT_COLS = "input_cols"
+  PROJECT_ROW = "project_row"
+  PROJECTION_WEIGHTS = "projection_weights"
+  # Predictions key
+  PROJECTION_RESULT = "projection"
+
+  def __init__(self,
+               num_rows,
+               num_cols,
+               embedding_dimension,
+               unobserved_weight=0.1,
+               regularization_coeff=None,
+               row_init="random",
+               col_init="random",
+               num_row_shards=1,
+               num_col_shards=1,
+               row_weights=1,
+               col_weights=1,
+               use_factors_weights_cache_for_training=True,
+               use_gramian_cache_for_training=True,
+               model_dir=None,
+               config=None):
+    """Creates a model for matrix factorization using the WALS method.
+
+    Args:
+      num_rows: Total number of rows for input matrix.
+      num_cols: Total number of cols for input matrix.
+      embedding_dimension: Dimension to use for the factors.
+      unobserved_weight: Weight of the unobserved entries of matrix.
+      regularization_coeff: Weight of the L2 regularization term. Defaults to
+        None, in which case the problem is not regularized.
+      row_init: Initializer for row factor. Must be either:
+        - A tensor: The row factor matrix is initialized to this tensor,
+        - A numpy constant,
+        - "random": The rows are initialized using a normal distribution.
+      col_init: Initializer for column factor. See row_init.
+      num_row_shards: Number of shards to use for the row factors.
+      num_col_shards: Number of shards to use for the column factors.
+      row_weights: Must be in one of the following three formats:
+        - None: In this case, the weight of every entry is the unobserved_weight
+          and the problem simplifies to ALS. Note that, in this case,
+          col_weights must also be set to "None".
+        - List of lists of non-negative scalars, of the form
+          [[w_0, w_1, ...], [w_k, ... ], [...]],
+          where the number of inner lists equal to the number of row factor
+          shards and the elements in each inner list are the weights for the
+          rows of that shard. In this case,
+          w_ij = unonbserved_weight + row_weights[i] * col_weights[j].
+        - A non-negative scalar: This value is used for all row weights.
+          Note that it is allowed to have row_weights as a list and col_weights
+          as a scalar, or vice-versa.
+      col_weights: See row_weights.
+      use_factors_weights_cache_for_training: Boolean, whether the factors and
+        weights will be cached on the workers before the updates start, during
+        training. Defaults to True.
+        Note that caching is disabled during prediction.
+      use_gramian_cache_for_training: Boolean, whether the Gramians will be
+        cached on the workers before the updates start, during training.
+        Defaults to True. Note that caching is disabled during prediction.
+      model_dir: The directory to save the model results and log files.
+      config: A Configuration object. See Estimator.
+
+    Raises:
+      ValueError: If config.num_worker_replicas is strictly greater than one.
+        The current implementation only supports running on a single worker.
+    """
+    # TODO(walidk): Support distributed training.
+    # TODO(walidk): Support power-law based weight computation.
+    # TODO(walidk): Add factor lookup by indices, with caching.
+    # TODO(walidk): Support caching during prediction.
+
+    params = {
+        "num_rows": num_rows,
+        "num_cols": num_cols,
+        "embedding_dimension": embedding_dimension,
+        "unobserved_weight": unobserved_weight,
+        "regularization_coeff": regularization_coeff,
+        "row_init": row_init,
+        "col_init": col_init,
+        "num_row_shards": num_row_shards,
+        "num_col_shards": num_col_shards,
+        "row_weights": row_weights,
+        "col_weights": col_weights,
+        "use_factors_weights_cache_for_training":
+            use_factors_weights_cache_for_training,
+        "use_gramian_cache_for_training": use_gramian_cache_for_training
+    }
+    self._row_factors_names = ["row_factors_shard_%d" % i
+                               for i in range(num_row_shards)]
+    self._col_factors_names = ["col_factors_shard_%d" % i
+                               for i in range(num_col_shards)]
+
+    super(WALSMatrixFactorization, self).__init__(
+        model_fn=_wals_factorization_model_function,
+        params=params,
+        model_dir=model_dir,
+        config=config)
+
+    if self._config is not None and self._config.num_worker_replicas > 1:
+      raise ValueError("WALSMatrixFactorization must be run on a single worker "
+                       "replica.")
+
+  def get_row_factors(self):
+    """Returns the row factors of the model, loading them from checkpoint.
+
+    Should only be run after training.
+
+    Returns:
+      A list of the row factors of the model.
+    """
+    return [self.get_variable_value(name) for name in self._row_factors_names]
+
+  def get_col_factors(self):
+    """Returns the column factors of the model, loading them from checkpoint.
+
+    Should only be run after training.
+
+    Returns:
+      A list of the column factors of the model.
+    """
+    return [self.get_variable_value(name) for name in self._col_factors_names]
+
+  def get_projections(self, input_fn):
+    """Computes the projections of the rows or columns given in input_fn.
+
+    Runs predict() with the given input_fn, and returns the results. Should only
+    be run after training.
+
+    Args:
+      input_fn: Input function which specifies the rows or columns to project.
+    Returns:
+      A generator of the projected factors.
+    """
+    return (result[WALSMatrixFactorization.PROJECTION_RESULT]
+            for result in self.predict(input_fn=input_fn))
diff --git a/tensorflow/contrib/factorization/python/ops/wals_test.py b/tensorflow/contrib/factorization/python/ops/wals_test.py
index 2ae2d3ab058..3f5787ea871 100644
--- a/tensorflow/contrib/factorization/python/ops/wals_test.py
+++ b/tensorflow/contrib/factorization/python/ops/wals_test.py
@@ -18,16 +18,311 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import itertools
+import json
+import numpy as np
+
+from tensorflow.contrib.factorization.python.ops import factorization_ops_test_utils
 from tensorflow.contrib.factorization.python.ops import wals as wals_lib
+from tensorflow.contrib.learn.python.learn import run_config
+from tensorflow.contrib.learn.python.learn.estimators import run_config as run_config_lib
+from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import sparse_tensor
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import control_flow_ops
+from tensorflow.python.ops import embedding_ops
+from tensorflow.python.ops import math_ops
+from tensorflow.python.ops import sparse_ops
 from tensorflow.python.ops import state_ops
 from tensorflow.python.ops import variables
 from tensorflow.python.platform import test
+from tensorflow.python.training import input as input_lib
 from tensorflow.python.training import session_run_hook
 
 
+class WALSMatrixFactorizationTest(test.TestCase):
+  INPUT_MATRIX = factorization_ops_test_utils.INPUT_MATRIX
+
+  def np_array_to_sparse(self, np_array):
+    """Transforms an np.array to a tf.SparseTensor."""
+    return factorization_ops_test_utils.np_matrix_to_tf_sparse(np_array)
+
+  def calculate_loss(self):
+    """Calculates the loss of the current (trained) model."""
+    current_rows = embedding_ops.embedding_lookup(
+        self._model.get_row_factors(), math_ops.range(self._num_rows),
+        partition_strategy='div')
+    current_cols = embedding_ops.embedding_lookup(
+        self._model.get_col_factors(), math_ops.range(self._num_cols),
+        partition_strategy='div')
+    row_wts = embedding_ops.embedding_lookup(
+        self._row_weights, math_ops.range(self._num_rows),
+        partition_strategy='div')
+    col_wts = embedding_ops.embedding_lookup(
+        self._col_weights, math_ops.range(self._num_cols),
+        partition_strategy='div')
+    sp_inputs = self.np_array_to_sparse(self.INPUT_MATRIX)
+    return factorization_ops_test_utils.calculate_loss(
+        sp_inputs, current_rows, current_cols, self._regularization_coeff,
+        self._unobserved_weight, row_wts, col_wts)
+
+  # TODO(walidk): Replace with input_reader_utils functions once open sourced.
+  def remap_sparse_tensor_rows(self, sp_x, row_ids, shape):
+    """Remaps the row ids of a tf.SparseTensor."""
+    old_row_ids, old_col_ids = array_ops.split(
+        value=sp_x.indices, num_or_size_splits=2, axis=1)
+    new_row_ids = array_ops.gather(row_ids, old_row_ids)
+    new_indices = array_ops.concat([new_row_ids, old_col_ids], 1)
+    return sparse_tensor.SparseTensor(
+        indices=new_indices, values=sp_x.values, dense_shape=shape)
+
+  # TODO(walidk): Add an option to randomize inputs.
+  def input_fn(self, np_matrix, batch_size, project_row=None,
+               projection_weights=None, col_ids=None):
+    """Returns an input_fn that selects row and col batches from np_matrix."""
+    def extract_features(row_batch, col_batch, shape):
+      row_ids = row_batch[0]
+      col_ids = col_batch[0]
+      rows = self.remap_sparse_tensor_rows(row_batch[1], row_ids, shape)
+      cols = self.remap_sparse_tensor_rows(col_batch[1], col_ids, shape)
+      features = {
+          wals_lib.WALSMatrixFactorization.INPUT_ROWS: rows,
+          wals_lib.WALSMatrixFactorization.INPUT_COLS: cols,
+      }
+      return features
+
+    def _fn():
+      num_rows = np.shape(np_matrix)[0]
+      num_cols = np.shape(np_matrix)[1]
+      row_ids = math_ops.range(num_rows, dtype=dtypes.int64)
+      col_ids = math_ops.range(num_cols, dtype=dtypes.int64)
+      sp_mat = self.np_array_to_sparse(np_matrix)
+      sp_mat_t = sparse_ops.sparse_transpose(sp_mat)
+      row_batch = input_lib.batch(
+          [row_ids, sp_mat],
+          batch_size=min(batch_size, num_rows),
+          capacity=10,
+          enqueue_many=True)
+      col_batch = input_lib.batch(
+          [col_ids, sp_mat_t],
+          batch_size=min(batch_size, num_cols),
+          capacity=10,
+          enqueue_many=True)
+
+      features = extract_features(row_batch, col_batch, sp_mat.dense_shape)
+      if projection_weights is not None:
+        weights_batch = input_lib.batch(
+            projection_weights,
+            batch_size=batch_size,
+            capacity=10,
+            enqueue_many=True)
+        features[wals_lib.WALSMatrixFactorization.PROJECTION_WEIGHTS] = (
+            weights_batch)
+      if project_row is not None:
+        features[wals_lib.WALSMatrixFactorization.PROJECT_ROW] = (
+            constant_op.constant(project_row))
+
+      labels = None
+      return features, labels
+
+    return _fn
+
+  @property
+  def row_steps(self):
+    return np.ceil(self._num_rows / self.batch_size)
+
+  @property
+  def col_steps(self):
+    return np.ceil(self._num_cols / self.batch_size)
+
+  @property
+  def batch_size(self):
+    return 2
+
+  @property
+  def use_cache(self):
+    return False
+
+  def setUp(self):
+    self._num_rows = 5
+    self._num_cols = 7
+    self._embedding_dimension = 3
+    self._unobserved_weight = 0.1
+    self._num_row_shards = 2
+    self._num_col_shards = 3
+    self._regularization_coeff = 0.01
+    self._col_init = [
+        # Shard 0.
+        [[-0.36444709, -0.39077035, -0.32528427],
+         [1.19056475, 0.07231052, 2.11834812],
+         [0.93468881, -0.71099287, 1.91826844]],
+        # Shard 1.
+        [[1.18160152, 1.52490723, -0.50015002],
+         [1.82574749, -0.57515913, -1.32810032]],
+        # Shard 2.
+        [[-0.15515432, -0.84675711, 0.13097958],
+         [-0.9246484, 0.69117504, 1.2036494]],
+    ]
+    self._row_weights = [[0.1, 0.2, 0.3], [0.4, 0.5]]
+    self._col_weights = [[0.1, 0.2, 0.3], [0.4, 0.5], [0.6, 0.7]]
+
+    # Values of row and column factors after running one iteration or factor
+    # updates.
+    self._row_factors_0 = [[0.097689, -0.219293, -0.020780],
+                           [0.50842, 0.64626, 0.22364],
+                           [0.401159, -0.046558, -0.192854]]
+    self._row_factors_1 = [[1.20597, -0.48025, 0.35582],
+                           [1.5564, 1.2528, 1.0528]]
+    self._col_factors_0 = [[2.4725, -1.2950, -1.9980],
+                           [0.44625, 1.50771, 1.27118],
+                           [1.39801, -2.10134, 0.73572]]
+    self._col_factors_1 = [[3.36509, -0.66595, -3.51208],
+                           [0.57191, 1.59407, 1.33020]]
+    self._col_factors_2 = [[3.3459, -1.3341, -3.3008],
+                           [0.57366, 1.83729, 1.26798]]
+    self._model = wals_lib.WALSMatrixFactorization(
+        self._num_rows,
+        self._num_cols,
+        self._embedding_dimension,
+        self._unobserved_weight,
+        col_init=self._col_init,
+        regularization_coeff=self._regularization_coeff,
+        num_row_shards=self._num_row_shards,
+        num_col_shards=self._num_col_shards,
+        row_weights=self._row_weights,
+        col_weights=self._col_weights,
+        use_factors_weights_cache_for_training=self.use_cache,
+        use_gramian_cache_for_training=self.use_cache)
+
+  def test_fit(self):
+    # Row sweep.
+    input_fn = self.input_fn(np_matrix=self.INPUT_MATRIX,
+                             batch_size=self.batch_size)
+    self._model.fit(input_fn=input_fn, steps=self.row_steps)
+    row_factors = self._model.get_row_factors()
+    self.assertAllClose(row_factors[0], self._row_factors_0, atol=1e-3)
+    self.assertAllClose(row_factors[1], self._row_factors_1, atol=1e-3)
+
+    # Col sweep.
+    # Running fit a second time will resume training from the checkpoint.
+    input_fn = self.input_fn(np_matrix=self.INPUT_MATRIX,
+                             batch_size=self.batch_size)
+    self._model.fit(input_fn=input_fn, steps=self.col_steps)
+    col_factors = self._model.get_col_factors()
+    self.assertAllClose(col_factors[0], self._col_factors_0, atol=1e-3)
+    self.assertAllClose(col_factors[1], self._col_factors_1, atol=1e-3)
+    self.assertAllClose(col_factors[2], self._col_factors_2, atol=1e-3)
+
+  def test_predict(self):
+    input_fn = self.input_fn(np_matrix=self.INPUT_MATRIX,
+                             batch_size=self.batch_size)
+    # Project rows 1 and 4 from the input matrix.
+    proj_input_fn = self.input_fn(
+        np_matrix=self.INPUT_MATRIX[[1, 4], :],
+        batch_size=2,
+        project_row=True,
+        projection_weights=[[0.2, 0.5]])
+
+    self._model.fit(input_fn=input_fn, steps=self.row_steps)
+    projections = self._model.get_projections(proj_input_fn)
+    projected_rows = list(itertools.islice(projections, 2))
+
+    self.assertAllClose(
+        projected_rows,
+        [self._row_factors_0[1], self._row_factors_1[1]],
+        atol=1e-3)
+
+    # Project columns 5, 3, 1 from the input matrix.
+    proj_input_fn = self.input_fn(
+        np_matrix=self.INPUT_MATRIX[:, [5, 3, 1]],
+        batch_size=3,
+        project_row=False,
+        projection_weights=[[0.6, 0.4, 0.2]])
+
+    self._model.fit(input_fn=input_fn, steps=self.col_steps)
+    projections = self._model.get_projections(proj_input_fn)
+    projected_cols = list(itertools.islice(projections, 3))
+    self.assertAllClose(
+        projected_cols,
+        [self._col_factors_2[0], self._col_factors_1[0],
+         self._col_factors_0[1]],
+        atol=1e-3)
+
+  def test_eval(self):
+    # Do a row sweep then evaluate the model on row inputs.
+    # The evaluate function returns the loss of the projected rows, but since
+    # projection is idempotent, the eval loss must match the model loss.
+    input_fn = self.input_fn(np_matrix=self.INPUT_MATRIX,
+                             batch_size=self.batch_size)
+    self._model.fit(input_fn=input_fn, steps=self.row_steps)
+    eval_input_fn_row = self.input_fn(np_matrix=self.INPUT_MATRIX, batch_size=1,
+                                      project_row=True)
+    loss = self._model.evaluate(
+        input_fn=eval_input_fn_row, steps=self._num_rows)['loss']
+
+    with self.test_session():
+      true_loss = self.calculate_loss()
+
+    self.assertNear(
+        loss, true_loss, err=.001,
+        msg="""After row update, eval loss = {}, does not match the true
+        loss = {}.""".format(loss, true_loss))
+
+    # Do a col sweep then evaluate the model on col inputs.
+    self._model.fit(input_fn=input_fn, steps=self.col_steps)
+    eval_input_fn_col = self.input_fn(np_matrix=self.INPUT_MATRIX, batch_size=1,
+                                      project_row=False)
+    loss = self._model.evaluate(
+        input_fn=eval_input_fn_col, steps=self._num_cols)['loss']
+
+    with self.test_session():
+      true_loss = self.calculate_loss()
+
+    self.assertNear(
+        loss, true_loss, err=.001,
+        msg="""After row update, eval loss = {}, does not match the true
+        loss = {}.""".format(loss, true_loss))
+
+
+class WALSMatrixFactorizationTestCached(WALSMatrixFactorizationTest):
+
+  @property
+  def use_cache(self):
+    return True
+
+
+class WALSMatrixFactorizationTestFullBatch(WALSMatrixFactorizationTest):
+
+  @property
+  def batch_size(self):
+    return 100
+
+
+class WALSMatrixFactorizationUnsupportedTest(test.TestCase):
+
+  def setUp(self):
+    pass
+
+  def testDistributedWALSUnsupported(self):
+    tf_config = {
+        'cluster': {
+            run_config_lib.TaskType.PS: ['host1:1', 'host2:2'],
+            run_config_lib.TaskType.WORKER: ['host3:3', 'host4:4']
+        },
+        'task': {
+            'type': run_config_lib.TaskType.WORKER,
+            'index': 1
+        }
+    }
+    with test.mock.patch.dict('os.environ',
+                              {'TF_CONFIG': json.dumps(tf_config)}):
+      config = run_config.RunConfig()
+    self.assertEqual(config.num_worker_replicas, 2)
+    with self.assertRaises(ValueError):
+      self._model = wals_lib.WALSMatrixFactorization(1, 1, 1, config=config)
+
+
 class SweepHookTest(test.TestCase):
 
   def setUp(self):
@@ -45,7 +340,7 @@ class SweepHookTest(test.TestCase):
 
   def run_hook_with_indices(self, sweep_hook, row_indices, col_indices):
     with self.test_session() as sess:
-      # Before run
+      # Before run.
       run_context = session_run_hook.SessionRunContext(
           original_args=None, session=sess)
       sess_run_args = sweep_hook.before_run(run_context)
@@ -53,11 +348,11 @@ class SweepHookTest(test.TestCase):
           self._input_row_indices_ph: row_indices,
           self._input_col_indices_ph: col_indices
       }
-      # Run
+      # Run.
       run_results = sess.run(sess_run_args.fetches, feed_dict=feed_dict)
       run_values = session_run_hook.SessionRunValues(
           results=run_results, options=None, run_metadata=None)
-      # After run
+      # After run.
       sweep_hook.after_run(run_context, run_values)
 
   def test_row_sweep(self):
@@ -74,9 +369,9 @@ class SweepHookTest(test.TestCase):
           self._col_prep_ops,
           self._init_ops)
 
-      # Initialize variables
+      # Initialize variables.
       sess.run([variables.global_variables_initializer()])
-      # Row sweep
+      # Row sweep.
       self.run_hook_with_indices(sweep_hook, [], [])
       self.assertTrue(sess.run(self._init_done),
                       msg='init ops not run by the sweep_hook')
diff --git a/tensorflow/contrib/layers/python/layers/embedding_ops.py b/tensorflow/contrib/layers/python/layers/embedding_ops.py
index b1a7f7ee59a..f231ee38597 100644
--- a/tensorflow/contrib/layers/python/layers/embedding_ops.py
+++ b/tensorflow/contrib/layers/python/layers/embedding_ops.py
@@ -351,7 +351,7 @@ def _sampled_scattered_embedding_lookup(
     # No need to validate the indices since we have checked the params
     # dimensions and we know the largest id.
     result = embedding_ops.embedding_lookup(
-        params, ids, partition_strategy="div", validate_indices=False)
+        params, ids, partition_strategy="div")
 
     return array_ops.reshape(result,
                              array_ops.concat([values_shape, [dimension]], 0))
@@ -681,19 +681,17 @@ def embedding_lookup_sparse_with_distributed_aggregation(
     return embeddings
 
 
-def _do_gather(params, ids, validate_indices=True, name=None):
+def _do_gather(params, ids, name=None):
   """Deals with doing gather differently for resource variables."""
   if isinstance(params, resource_variable_ops.ResourceVariable):
     return params.sparse_read(ids, name=name)
-  return array_ops.gather(
-      params, ids, name=name, validate_indices=validate_indices)
+  return array_ops.gather(params, ids, name=name)
 
 
 def _embedding_lookup_with_distributed_aggregation(params,
                                                    ids,
                                                    partition_strategy="mod",
                                                    name=None,
-                                                   validate_indices=True,
                                                    max_norm=None,
                                                    weights=None,
                                                    idx=None,
@@ -724,8 +722,7 @@ def _embedding_lookup_with_distributed_aggregation(params,
       params = ops.convert_n_to_tensor_or_indexed_slices(params, name="params")
     if np == 1:
       with ops.colocate_with(params[0]):
-        ret = maybe_normalize(
-            _do_gather(params[0], ids, validate_indices=validate_indices))
+        ret = maybe_normalize(_do_gather(params[0], ids))
         ignore_weights = weights is None
         if not ignore_weights:
           if weights.dtype != ret.dtype:
@@ -803,9 +800,7 @@ def _embedding_lookup_with_distributed_aggregation(params,
       partitioned_result = []
       for p in xrange(np):
         with ops.colocate_with(params[p]):
-          partitioned_result.append(
-              _do_gather(
-                  params[p], gather_ids[p], validate_indices=validate_indices))
+          partitioned_result.append(_do_gather(params[p], gather_ids[p]))
 
       ignore_weights = weights is None
       if not ignore_weights:
diff --git a/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_test.py b/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_test.py
index 8b419700db0..c5bfc6e1fd5 100644
--- a/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_test.py
+++ b/tensorflow/contrib/linalg/python/kernel_tests/linear_operator_test.py
@@ -78,8 +78,9 @@ class LinearOperatorApplyOnly(linalg.LinearOperator):
   def _shape_tensor(self):
     return array_ops.shape(self._matrix)
 
-  def _apply(self, x, adjoint=False):
-    return math_ops.matmul(self._matrix, x, adjoint_a=adjoint)
+  def _apply(self, x, adjoint=False, adjoint_arg=False):
+    return math_ops.matmul(
+        self._matrix, x, adjoint_a=adjoint, adjoint_b=adjoint_arg)
 
 
 class LinearOperatorTest(test.TestCase):
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator.py b/tensorflow/contrib/linalg/python/ops/linear_operator.py
index 5052a0b15cf..454411d93cf 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator.py
@@ -30,7 +30,6 @@ __all__ = ["LinearOperator"]
 
 
 # TODO(langmore) Use matrix_solve_ls for singular or non-square matrices.
-# TODO(langmore) Add adjoint_x arg to apply, solve.
 class LinearOperator(object):
   """Base class defining a [batch of] linear operator[s].
 
@@ -490,16 +489,18 @@ class LinearOperator(object):
           "Expected argument to have dtype %s.  Found: %s in tensor %s"
           % (self.dtype, arg.dtype, arg))
 
-  def _apply(self, x, adjoint=False):
+  def _apply(self, x, adjoint=False, adjoint_arg=False):
     raise NotImplementedError("_apply is not implemented.")
 
-  def apply(self, x, adjoint=False, name="apply"):
+  def apply(self, x, adjoint=False, adjoint_arg=False, name="apply"):
     """Transform `x` with left multiplication:  `x --> Ax`.
 
     Args:
       x: `Tensor` with compatible shape and same `dtype` as `self`.
         See class docstring for definition of compatibility.
-      adjoint: Python `bool`.  If `True`, left multiply by the adjoint.
+      adjoint: Python `bool`.  If `True`, left multiply by the adjoint: `A^H x`.
+      adjoint_arg:  Python `bool`.  If `True`, compute `A x^H` where `x^H` is
+        the hermitian transpose (transposition and complex conjugation).
       name:  A name for this `Op.
 
     Returns:
@@ -508,11 +509,12 @@ class LinearOperator(object):
     with self._name_scope(name, values=[x]):
       x = ops.convert_to_tensor(x, name="x")
       self._check_input_dtype(x)
-      if adjoint:
-        self.shape[-2].assert_is_compatible_with(x.get_shape()[-2])
-      else:
-        self.shape[-1].assert_is_compatible_with(x.get_shape()[-2])
-      return self._apply(x, adjoint=adjoint)
+
+      self_dim = -2 if adjoint else -1
+      arg_dim = -1 if adjoint_arg else -2
+      self.shape[self_dim].assert_is_compatible_with(x.get_shape()[arg_dim])
+
+      return self._apply(x, adjoint=adjoint, adjoint_arg=adjoint_arg)
 
   def _determinant(self):
     raise NotImplementedError("_det is not implemented.")
@@ -558,13 +560,13 @@ class LinearOperator(object):
     with self._name_scope(name):
       return self._log_abs_determinant()
 
-  def _solve(self, rhs, adjoint=False):
+  def _solve(self, rhs, adjoint=False, adjoint_arg=False):
     # Since this is an exact solve method for all rhs, this will only be
     # available for non-singular (batch) operators, in particular the operator
     # must be square.
     raise NotImplementedError("_solve is not implemented.")
 
-  def solve(self, rhs, adjoint=False, name="solve"):
+  def solve(self, rhs, adjoint=False, adjoint_arg=False, name="solve"):
     """Solve `R` (batch) systems of equations exactly: `A X = rhs`.
 
     Examples:
@@ -588,7 +590,9 @@ class LinearOperator(object):
       rhs: `Tensor` with same `dtype` as this operator and compatible shape.
         See class docstring for definition of compatibility.
       adjoint: Python `bool`.  If `True`, solve the system involving the adjoint
-        of this `LinearOperator`.
+        of this `LinearOperator`:  `A^H X = rhs`.
+      adjoint_arg:  Python `bool`.  If `True`, solve `A X = rhs^H` where `rhs^H`
+        is the hermitian transpose (transposition and complex conjugation).
       name:  A name scope to use for ops added by this method.
 
     Returns:
@@ -608,11 +612,12 @@ class LinearOperator(object):
     with self._name_scope(name, values=[rhs]):
       rhs = ops.convert_to_tensor(rhs, name="rhs")
       self._check_input_dtype(rhs)
-      if adjoint:
-        self.shape[-1].assert_is_compatible_with(rhs.get_shape()[-2])
-      else:
-        self.shape[-2].assert_is_compatible_with(rhs.get_shape()[-2])
-      return self._solve(rhs, adjoint=adjoint)
+
+      self_dim = -1 if adjoint else -2
+      arg_dim = -1 if adjoint_arg else -2
+      self.shape[self_dim].assert_is_compatible_with(rhs.get_shape()[arg_dim])
+
+      return self._solve(rhs, adjoint=adjoint, adjoint_arg=adjoint_arg)
 
   def _to_dense(self):
     """Generic and often inefficient implementation.  Override often."""
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_composition.py b/tensorflow/contrib/linalg/python/ops/linear_operator_composition.py
index 9f3a4d230f7..b1557769b22 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator_composition.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator_composition.py
@@ -225,7 +225,7 @@ class LinearOperatorComposition(linear_operator.LinearOperator):
 
     return array_ops.concat((batch_shape, matrix_shape), 0)
 
-  def _apply(self, x, adjoint=False):
+  def _apply(self, x, adjoint=False, adjoint_arg=False):
     # If self.operators = [A, B], and not adjoint, then
     # apply_order_list = [B, A].
     # As a result, we return A.apply(B.apply(x))
@@ -234,8 +234,9 @@ class LinearOperatorComposition(linear_operator.LinearOperator):
     else:
       apply_order_list = list(reversed(self.operators))
 
-    result = x
-    for operator in apply_order_list:
+    result = apply_order_list[0].apply(
+        x, adjoint=adjoint, adjoint_arg=adjoint_arg)
+    for operator in apply_order_list[1:]:
       result = operator.apply(result, adjoint=adjoint)
     return result
 
@@ -251,7 +252,7 @@ class LinearOperatorComposition(linear_operator.LinearOperator):
       result += operator.log_abs_determinant()
     return result
 
-  def _solve(self, rhs, adjoint=False):
+  def _solve(self, rhs, adjoint=False, adjoint_arg=False):
     # TODO(langmore) Implement solve using solve_ls if some intermediate
     # operator maps to a high dimensional space.
     # In that case, an exact solve may still be possible.
@@ -264,8 +265,9 @@ class LinearOperatorComposition(linear_operator.LinearOperator):
     else:
       solve_order_list = self.operators
 
-    solution = rhs
-    for operator in solve_order_list:
+    solution = solve_order_list[0].solve(
+        rhs, adjoint=adjoint, adjoint_arg=adjoint_arg)
+    for operator in solve_order_list[1:]:
       solution = operator.solve(solution, adjoint=adjoint)
     return solution
 
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_diag.py b/tensorflow/contrib/linalg/python/ops/linear_operator_diag.py
index 0cd7e72a8b6..97e52d08a43 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator_diag.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator_diag.py
@@ -206,8 +206,9 @@ class LinearOperatorDiag(linear_operator.LinearOperator):
             "This diagonal operator contained non-zero imaginary values.  "
             " Thus it was not self-adjoint."))
 
-  def _apply(self, x, adjoint=False):
+  def _apply(self, x, adjoint=False, adjoint_arg=False):
     diag_term = math_ops.conj(self._diag) if adjoint else self._diag
+    x = linear_operator_util.matrix_adjoint(x) if adjoint_arg else x
     diag_mat = array_ops.expand_dims(diag_term, -1)
     return diag_mat * x
 
@@ -218,8 +219,9 @@ class LinearOperatorDiag(linear_operator.LinearOperator):
     return math_ops.reduce_sum(
         math_ops.log(math_ops.abs(self._diag)), reduction_indices=[-1])
 
-  def _solve(self, rhs, adjoint=False):
+  def _solve(self, rhs, adjoint=False, adjoint_arg=False):
     diag_term = math_ops.conj(self._diag) if adjoint else self._diag
+    rhs = linear_operator_util.matrix_adjoint(rhs) if adjoint_arg else rhs
     inv_diag_mat = array_ops.expand_dims(1. / diag_term, -1)
     return rhs * inv_diag_mat
 
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_full_matrix.py b/tensorflow/contrib/linalg/python/ops/linear_operator_full_matrix.py
index f9349682215..64ab5614577 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator_full_matrix.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator_full_matrix.py
@@ -19,6 +19,7 @@ from __future__ import division
 from __future__ import print_function
 
 from tensorflow.contrib.linalg.python.ops import linear_operator
+from tensorflow.contrib.linalg.python.ops import linear_operator_util
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
 from tensorflow.python.ops import array_ops
@@ -172,8 +173,9 @@ class LinearOperatorFullMatrix(linear_operator.LinearOperator):
   def _shape_tensor(self):
     return array_ops.shape(self._matrix)
 
-  def _apply(self, x, adjoint=False):
-    return math_ops.matmul(self._matrix, x, adjoint_a=adjoint)
+  def _apply(self, x, adjoint=False, adjoint_arg=False):
+    return math_ops.matmul(
+        self._matrix, x, adjoint_a=adjoint, adjoint_b=adjoint_arg)
 
   def _determinant(self):
     if self._is_spd:
@@ -187,7 +189,8 @@ class LinearOperatorFullMatrix(linear_operator.LinearOperator):
     abs_det = math_ops.abs(self.determinant())
     return math_ops.log(abs_det)
 
-  def _solve(self, rhs, adjoint=False):
+  def _solve(self, rhs, adjoint=False, adjoint_arg=False):
+    rhs = linear_operator_util.matrix_adjoint(rhs) if adjoint_arg else rhs
     if self._is_spd:
       return linalg_ops.cholesky_solve(self._chol, rhs)
     return linalg_ops.matrix_solve(self._matrix, rhs, adjoint=adjoint)
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_identity.py b/tensorflow/contrib/linalg/python/ops/linear_operator_identity.py
index 60d8b2cdc03..845bf25192e 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator_identity.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator_identity.py
@@ -329,8 +329,9 @@ class LinearOperatorIdentity(BaseLinearOperatorIdentity):
     zeros = array_ops.zeros(shape=special_shape, dtype=self.dtype)
     return x + zeros
 
-  def _apply(self, x, adjoint=False):
+  def _apply(self, x, adjoint=False, adjoint_arg=False):
     # Note that adjoint has no effect since this matrix is self-adjoint.
+    x = linear_operator_util.matrix_adjoint(x) if adjoint_arg else x
     if self._assert_proper_shapes:
       aps = linear_operator_util.assert_compatible_matrix_dimensions(
           self, x)
@@ -343,8 +344,8 @@ class LinearOperatorIdentity(BaseLinearOperatorIdentity):
   def _log_abs_determinant(self):
     return array_ops.zeros(shape=self.batch_shape_tensor(), dtype=self.dtype)
 
-  def _solve(self, rhs, adjoint=False):
-    return self._apply(rhs)
+  def _solve(self, rhs, adjoint=False, adjoint_arg=False):
+    return self._apply(rhs, adjoint_arg=adjoint_arg)
 
   def _diag_part(self):
     return self._ones_diag()
@@ -616,7 +617,8 @@ class LinearOperatorScaledIdentity(BaseLinearOperatorIdentity):
         imag_multiplier,
         message="LinearOperator was not self-adjoint")
 
-  def _apply(self, x, adjoint=False):
+  def _apply(self, x, adjoint=False, adjoint_arg=False):
+    x = linear_operator_util.matrix_adjoint(x) if adjoint_arg else x
     if adjoint:
       matrix = self._multiplier_matrix_conj
     else:
@@ -634,7 +636,8 @@ class LinearOperatorScaledIdentity(BaseLinearOperatorIdentity):
     return self._num_rows_cast_to_real_dtype * math_ops.log(
         self._abs_multiplier)
 
-  def _solve(self, rhs, adjoint=False):
+  def _solve(self, rhs, adjoint=False, adjoint_arg=False):
+    rhs = linear_operator_util.matrix_adjoint(rhs) if adjoint_arg else rhs
     if adjoint:
       matrix = self._multiplier_matrix_conj
     else:
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_test_util.py b/tensorflow/contrib/linalg/python/ops/linear_operator_test_util.py
index 0b7fc3da396..c8bc62eeef9 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator_test_util.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator_test_util.py
@@ -23,6 +23,7 @@ import numpy as np
 import six
 
 from tensorflow.contrib.framework.python.framework import tensor_util as contrib_tensor_util
+from tensorflow.contrib.linalg.python.ops import linear_operator_util
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import random_seed
@@ -213,18 +214,26 @@ class LinearOperatorDerivedClassTest(test.TestCase):
       for shape in self._shapes_to_test:
         for dtype in self._dtypes_to_test:
           for adjoint in False, True:
-            with self.test_session(graph=ops.Graph()) as sess:
-              sess.graph.seed = random_seed.DEFAULT_GRAPH_SEED
-              operator, mat, feed_dict = self._operator_and_mat_and_feed_dict(
-                  shape, dtype, use_placeholder=use_placeholder)
-              x = self._make_x(operator, adjoint=adjoint)
-              op_apply = operator.apply(x, adjoint=adjoint)
-              mat_apply = math_ops.matmul(mat, x, adjoint_a=adjoint)
-              if not use_placeholder:
-                self.assertAllEqual(op_apply.get_shape(), mat_apply.get_shape())
-              op_apply_v, mat_apply_v = sess.run([op_apply, mat_apply],
-                                                 feed_dict=feed_dict)
-              self.assertAC(op_apply_v, mat_apply_v)
+            for adjoint_arg in False, True:
+              with self.test_session(graph=ops.Graph()) as sess:
+                sess.graph.seed = random_seed.DEFAULT_GRAPH_SEED
+                operator, mat, feed_dict = self._operator_and_mat_and_feed_dict(
+                    shape, dtype, use_placeholder=use_placeholder)
+                x = self._make_x(operator, adjoint=adjoint)
+                # If adjoint_arg, compute A X^H^H = A X.
+                if adjoint_arg:
+                  op_apply = operator.apply(
+                      linear_operator_util.matrix_adjoint(x),
+                      adjoint=adjoint, adjoint_arg=adjoint_arg)
+                else:
+                  op_apply = operator.apply(x, adjoint=adjoint)
+                mat_apply = math_ops.matmul(mat, x, adjoint_a=adjoint)
+                if not use_placeholder:
+                  self.assertAllEqual(
+                      op_apply.get_shape(), mat_apply.get_shape())
+                op_apply_v, mat_apply_v = sess.run([op_apply, mat_apply],
+                                                   feed_dict=feed_dict)
+                self.assertAC(op_apply_v, mat_apply_v)
 
   def test_solve(self):
     self._skip_if_tests_to_skip_contains("solve")
@@ -232,18 +241,27 @@ class LinearOperatorDerivedClassTest(test.TestCase):
       for shape in self._shapes_to_test:
         for dtype in self._dtypes_to_test:
           for adjoint in False, True:
-            with self.test_session(graph=ops.Graph()) as sess:
-              sess.graph.seed = random_seed.DEFAULT_GRAPH_SEED
-              operator, mat, feed_dict = self._operator_and_mat_and_feed_dict(
-                  shape, dtype, use_placeholder=use_placeholder)
-              rhs = self._make_rhs(operator, adjoint=adjoint)
-              op_solve = operator.solve(rhs, adjoint=adjoint)
-              mat_solve = linalg_ops.matrix_solve(mat, rhs, adjoint=adjoint)
-              if not use_placeholder:
-                self.assertAllEqual(op_solve.get_shape(), mat_solve.get_shape())
-              op_solve_v, mat_solve_v = sess.run([op_solve, mat_solve],
-                                                 feed_dict=feed_dict)
-              self.assertAC(op_solve_v, mat_solve_v)
+            for adjoint_arg in False, True:
+              with self.test_session(graph=ops.Graph()) as sess:
+                sess.graph.seed = random_seed.DEFAULT_GRAPH_SEED
+                operator, mat, feed_dict = self._operator_and_mat_and_feed_dict(
+                    shape, dtype, use_placeholder=use_placeholder)
+                rhs = self._make_rhs(operator, adjoint=adjoint)
+                # If adjoint_arg, solve A X = (rhs^H)^H = rhs.
+                if adjoint_arg:
+                  op_solve = operator.solve(
+                      linear_operator_util.matrix_adjoint(rhs),
+                      adjoint=adjoint, adjoint_arg=adjoint_arg)
+                else:
+                  op_solve = operator.solve(
+                      rhs, adjoint=adjoint, adjoint_arg=adjoint_arg)
+                mat_solve = linalg_ops.matrix_solve(mat, rhs, adjoint=adjoint)
+                if not use_placeholder:
+                  self.assertAllEqual(
+                      op_solve.get_shape(), mat_solve.get_shape())
+                op_solve_v, mat_solve_v = sess.run([op_solve, mat_solve],
+                                                   feed_dict=feed_dict)
+                self.assertAC(op_solve_v, mat_solve_v)
 
   def test_add_to_tensor(self):
     self._skip_if_tests_to_skip_contains("add_to_tensor")
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_tril.py b/tensorflow/contrib/linalg/python/ops/linear_operator_tril.py
index 38461ce8a22..756e26cc130 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator_tril.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator_tril.py
@@ -173,8 +173,9 @@ class LinearOperatorTriL(linear_operator.LinearOperator):
         self._diag,
         message="Singular operator:  Diagonal contained zero values.")
 
-  def _apply(self, x, adjoint=False):
-    return math_ops.matmul(self._tril, x, adjoint_a=adjoint)
+  def _apply(self, x, adjoint=False, adjoint_arg=False):
+    return math_ops.matmul(
+        self._tril, x, adjoint_a=adjoint, adjoint_b=adjoint_arg)
 
   def _determinant(self):
     return math_ops.reduce_prod(self._diag, reduction_indices=[-1])
@@ -183,7 +184,8 @@ class LinearOperatorTriL(linear_operator.LinearOperator):
     return math_ops.reduce_sum(
         math_ops.log(math_ops.abs(self._diag)), reduction_indices=[-1])
 
-  def _solve(self, rhs, adjoint=False):
+  def _solve(self, rhs, adjoint=False, adjoint_arg=False):
+    rhs = linear_operator_util.matrix_adjoint(rhs) if adjoint_arg else rhs
     return linalg_ops.matrix_triangular_solve(
         self._tril, rhs, lower=True, adjoint=adjoint)
 
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_udvh_update.py b/tensorflow/contrib/linalg/python/ops/linear_operator_udvh_update.py
index 89b5c1ab1b9..4ca77ab1471 100644
--- a/tensorflow/contrib/linalg/python/ops/linear_operator_udvh_update.py
+++ b/tensorflow/contrib/linalg/python/ops/linear_operator_udvh_update.py
@@ -348,21 +348,21 @@ class LinearOperatorUDVHUpdate(linear_operator.LinearOperator):
     return array_ops.concat(
         [batch_shape, self.base_operator.shape_tensor()[-2:]], axis=0)
 
-  def _apply(self, x, adjoint=False):
+  def _apply(self, x, adjoint=False, adjoint_arg=False):
     u = self.u
     v = self.v
     l = self.base_operator
     d = self.diag_operator
 
-    leading_term = l.apply(x, adjoint=adjoint)
+    leading_term = l.apply(x, adjoint=adjoint, adjoint_arg=adjoint_arg)
 
     if adjoint:
-      uh_x = math_ops.matmul(u, x, adjoint_a=True)
+      uh_x = math_ops.matmul(u, x, adjoint_a=True, adjoint_b=adjoint_arg)
       d_uh_x = d.apply(uh_x, adjoint=adjoint)
       v_d_uh_x = math_ops.matmul(v, d_uh_x)
       return leading_term + v_d_uh_x
     else:
-      vh_x = math_ops.matmul(v, x, adjoint_a=True)
+      vh_x = math_ops.matmul(v, x, adjoint_a=True, adjoint_b=adjoint_arg)
       d_vh_x = d.apply(vh_x, adjoint=adjoint)
       u_d_vh_x = math_ops.matmul(u, d_vh_x)
       return leading_term + u_d_vh_x
@@ -398,7 +398,7 @@ class LinearOperatorUDVHUpdate(linear_operator.LinearOperator):
 
     return log_abs_det_c + log_abs_det_d + log_abs_det_l
 
-  def _solve(self, rhs, adjoint=False):
+  def _solve(self, rhs, adjoint=False, adjoint_arg=False):
     if self.base_operator.is_non_singular is False:
       raise ValueError(
           "Solve not implemented unless this is a perturbation of a "
@@ -421,7 +421,7 @@ class LinearOperatorUDVHUpdate(linear_operator.LinearOperator):
       u = self.u
 
     # L^{-1} rhs
-    linv_rhs = l.solve(rhs, adjoint=adjoint)
+    linv_rhs = l.solve(rhs, adjoint=adjoint, adjoint_arg=adjoint_arg)
     # V^H L^{-1} rhs
     vh_linv_rhs = math_ops.matmul(v, linv_rhs, adjoint_a=True)
     # C^{-1} V^H L^{-1} rhs
diff --git a/tensorflow/contrib/training/BUILD b/tensorflow/contrib/training/BUILD
index a781f0cbfc8..a8d8bda060d 100644
--- a/tensorflow/contrib/training/BUILD
+++ b/tensorflow/contrib/training/BUILD
@@ -24,6 +24,7 @@ py_library(
         "python/training/failure_tolerator.py",
         "python/training/feeder.py",
         "python/training/hparam.py",
+        "python/training/python_input.py",
         "python/training/resample.py",
         "python/training/sampling_ops.py",
         "python/training/sequence_queueing_state_saver.py",
@@ -46,8 +47,10 @@ py_library(
         "//tensorflow/python:logging_ops",
         "//tensorflow/python:math_ops",
         "//tensorflow/python:ops",
+        "//tensorflow/python:parsing_ops",
         "//tensorflow/python:platform",
         "//tensorflow/python:random_ops",
+        "//tensorflow/python:script_ops",
         "//tensorflow/python:state_ops",
         "//tensorflow/python:string_ops",
         "//tensorflow/python:summary",
@@ -243,6 +246,26 @@ py_test(
     ],
 )
 
+py_test(
+    name = "python_input_test",
+    size = "medium",
+    srcs = ["python/training/python_input_test.py"],
+    srcs_version = "PY2AND3",
+    tags = ["manual"],
+    deps = [
+        ":training_py",
+        "//tensorflow/python:array_ops",
+        "//tensorflow/python:client_testlib",
+        "//tensorflow/python:data_flow_ops",
+        "//tensorflow/python:framework_for_generated_wrappers",
+        "//tensorflow/python:framework_test_lib",
+        "//tensorflow/python:math_ops",
+        "//tensorflow/python:parsing_ops",
+        "//tensorflow/python:training",
+        "//third_party/py/numpy",
+    ],
+)
+
 py_test(
     name = "evaluation_test",
     size = "small",
diff --git a/tensorflow/contrib/training/__init__.py b/tensorflow/contrib/training/__init__.py
index be097fd9fca..b8d4629ac47 100644
--- a/tensorflow/contrib/training/__init__.py
+++ b/tensorflow/contrib/training/__init__.py
@@ -35,6 +35,7 @@ See @{$python/contrib.training} guide.
 @@HParams
 @@HParamDef
 @@parse_values
+@@python_input
 """
 
 from __future__ import absolute_import
@@ -54,6 +55,7 @@ from tensorflow.contrib.training.python.training.evaluation import wait_for_new_
 from tensorflow.contrib.training.python.training.failure_tolerator import *
 from tensorflow.contrib.training.python.training.feeder import *
 from tensorflow.contrib.training.python.training.hparam import *
+from tensorflow.contrib.training.python.training.python_input import python_input
 from tensorflow.contrib.training.python.training.resample import *
 from tensorflow.contrib.training.python.training.sampling_ops import *
 from tensorflow.contrib.training.python.training.sequence_queueing_state_saver import *
diff --git a/tensorflow/contrib/training/python/training/bucket_ops.py b/tensorflow/contrib/training/python/training/bucket_ops.py
index 7c50f43b792..7e293da5511 100644
--- a/tensorflow/contrib/training/python/training/bucket_ops.py
+++ b/tensorflow/contrib/training/python/training/bucket_ops.py
@@ -251,10 +251,16 @@ def bucket(tensors,
     else:
       which_dequeue = lambda q: q.dequeue_many
 
+    def make_list(t):
+      if isinstance(t, (list, tuple)):
+        return t
+      else:
+        return [t]
+
     enqueues_to_top = [
         top_queue.enqueue(
-            [constant_op.constant(i)] + which_dequeue(q)(
-                bs, name="read_bucket_%d" % i),
+            [constant_op.constant(i)] + make_list(which_dequeue(q)(
+                bs, name="read_bucket_%d" % i)),
             name="enqueue_from_bucket_%d" % i)
         for i, (q, bs) in enumerate(zip(bucket_queues, batch_size))
     ]
@@ -282,6 +288,8 @@ def bucket(tensors,
     dequeued = top_queue.dequeue(name="dequeue_top")
     which_bucket_dequeued = dequeued[0]
     dequeued = dequeued[1:]
+    if len(dequeued) == 1:
+      dequeued = dequeued[0]
     dequeued = _restore_sparse_tensors(dequeued, sparse_info)
     return (which_bucket_dequeued, _as_original_type(tensors, dequeued))
 
diff --git a/tensorflow/contrib/training/python/training/python_input.py b/tensorflow/contrib/training/python/training/python_input.py
new file mode 100644
index 00000000000..7f5420a98a1
--- /dev/null
+++ b/tensorflow/contrib/training/python/training/python_input.py
@@ -0,0 +1,178 @@
+# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Operations for asynchronously reading data from python into queues.
+"""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import threading
+
+import numpy as np
+
+from tensorflow.python.framework import ops
+from tensorflow.python.framework import tensor_shape
+from tensorflow.python.ops import parsing_ops
+from tensorflow.python.ops import script_ops
+
+
+def _process_yielded_dict(feature_values, keys, features, dtypes, shapes):
+  """Read feature_values from the generator and emit a proper output dict."""
+  if not isinstance(feature_values, dict):
+    raise TypeError("generator must return dict, saw: %s" % feature_values)
+
+  processed_values = {}
+  for pk in keys:
+    if feature_values.get(pk, None) is not None:
+      processed_values[pk] = np.asarray(
+          feature_values[pk], dtype=dtypes[pk].as_numpy_dtype)
+      check_shape = tensor_shape.TensorShape(processed_values[pk].shape)
+      if not shapes[pk].is_compatible_with(check_shape):
+        raise ValueError(
+            "Feature '%s' has shape %s that is incompatible with declared "
+            "shape: %s" % (pk, shapes[pk], check_shape))
+      continue
+    if isinstance(features[pk], parsing_ops.FixedLenFeature):
+      if features[pk].default_value is not None:
+        processed_values[pk] = np.asarray(
+            features[pk].default_value, dtype=dtypes[pk].as_numpy_dtype)
+    elif isinstance(features[pk], parsing_ops.FixedLenSequenceFeature):
+      processed_values[pk] = np.empty(
+          [0] + features[pk].shape.aslist(), dtype=dtypes[pk].as_numpy_dtype)
+    else:
+      raise ValueError(
+          "Expected generator to return key '%s' with non-empty value" % pk)
+
+  return processed_values
+
+
+def python_input(generator, features, name=None):
+  """Easily feed data from a python generator into TensorFlow queues.
+
+  Example usage:
+
+  ```python
+  def generator():
+    for i in range(3):
+      yield {"value": i}
+
+  features = {
+    "value": tf.FixedLenFeature(shape=[], dtype=dtypes.int32)
+  }
+
+  tensor_dict = tf.contrib.training.python_input(generator, features)
+  batched_dict = tf.train.batch(
+    tensor_dict, batch_size=2, allow_smaller_final_batch=True)
+
+  s = tf.Session()
+  tf.train.start_queue_runners()
+
+  batch1 = s.run(batched_dict)  # returns {"value": np.array([0, 1])}
+  batch2 = s.run(batched_dict)  # returns {"value": np.array([2])}
+  s.run(batched_dict)  # error: Queue is closed (generator finished at i==3)
+  ```
+
+  Args:
+    generator: A python generator that takes no arguments, and yields dicts
+      containing a single minibatch entry one at a time.
+    features: A python `dict` mapping keys expected from the generator to
+      instances of `tf.FixedLenFeature`, or `tf.FixedLenSequenceFeature`.
+    name: (Optional) A name for the operations.
+
+  Returns:
+    A dict mapping keys of the `features` dict to `Tensor` objects.
+    These `Tensor` objects are outputs of a queue that is fed by `generator`.
+
+  Raises:
+    TypeError: If generator is not callable or features is not a dict.
+    TypeError: If any of features' values are not a Feature object.
+    NotImplementedError: If any of features' values are instances of
+      `SparseFeature` or `VarLenFeature`  (these are not currently supported).
+    ValueError: If any FixedLenSequenceFeatures contain a default value
+      (this field is not supported).
+    ValueError: if any FixedLenSequenceFeatures have allow_missing=False
+      (this field is not supported).
+  """
+  if not callable(generator):
+    raise TypeError("generator must be callable, saw: %s" % generator)
+  if not isinstance(features, dict):
+    raise TypeError("features must be a dict, saw: %s"
+                    % type(features).__name__)
+
+  with ops.name_scope(name, "python_input"):
+    shapes = {}
+    dtypes = {}
+    for k, v in features.items():
+      if isinstance(v, parsing_ops.FixedLenFeature):
+        if v.default_value is not None:
+          value = ops.convert_to_tensor(v.default_value, dtype=v.dtype, name=k)
+          shapes[k] = value.shape
+          dtypes[k] = value.dtype
+        else:
+          tensor_shape.TensorShape(v.shape).assert_is_fully_defined()
+          shapes[k] = tensor_shape.TensorShape(v.shape)
+          dtypes[k] = v.dtype
+      elif isinstance(v, parsing_ops.VarLenFeature):
+        raise NotImplementedError("VarLenFeature not supported")
+      elif isinstance(v, parsing_ops.SparseFeature):
+        raise NotImplementedError("SparseFeature not supported")
+      elif isinstance(v, parsing_ops.FixedLenSequenceFeature):
+        if v.default_value is not None:
+          raise ValueError("FixedLenSequenceFeature with default value not "
+                           "supported")
+        if not v.allow_missing:
+          raise ValueError("FixedLenSequenceFeature with allow_missing=False "
+                           "not supported")
+        tensor_shape.TensorShape(v.shape).assert_is_fully_defined()
+        shapes[k] = tensor_shape.TensorShape([None]).concatenate(v.shape)
+        dtypes[k] = v.dtype
+      else:
+        raise TypeError(
+            "Expected value for features key '%s' to be one of "
+            "FixedLenFeature, VarLenFeature, SparseFeature, or "
+            "FixedLenSequenceFeature.  Got: %s" % (k, v))
+
+    keys = list(shapes.keys())
+    dtypes_list = [dtypes[pk] for pk in keys]
+
+    counter = [0]
+    lock = threading.Lock()
+    iterator = iter(generator())
+
+    def generator_iter():
+      """Iterate through generator output and return np.arrays to py_func."""
+      with lock:
+        try:
+          feature_values = next(iterator)
+          counter[0] += 1
+        except StopIteration as e:
+          raise StopIteration("Iteration finished.  Processed %d entries (%s)"
+                              % (counter[0], e))
+
+      processed_dict = _process_yielded_dict(
+          feature_values, keys, features, dtypes, shapes)
+      return [processed_dict[pk] for pk in keys]
+
+    generator_pyfunc_values = script_ops.py_func(
+        generator_iter, inp=[], Tout=dtypes_list, stateful=True)
+
+    pyfunc_input = {k: v for (k, v) in zip(keys, generator_pyfunc_values)}
+    for k, v in shapes.items():
+      pyfunc_input[k].set_shape(v)
+
+  return pyfunc_input
+
+
+__all__ = ["python_input"]
diff --git a/tensorflow/contrib/training/python/training/python_input_test.py b/tensorflow/contrib/training/python/training/python_input_test.py
new file mode 100644
index 00000000000..afd0f38c2cd
--- /dev/null
+++ b/tensorflow/contrib/training/python/training/python_input_test.py
@@ -0,0 +1,191 @@
+# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for tf.contrib.training.python_input."""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import numpy as np
+from tensorflow.contrib.training.python.training import bucket_ops
+from tensorflow.contrib.training.python.training import python_input
+from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import errors
+from tensorflow.python.ops import parsing_ops
+from tensorflow.python.platform import test
+from tensorflow.python.training import coordinator
+from tensorflow.python.training import input as core_input
+from tensorflow.python.training import queue_runner_impl
+
+
+class PythonInputTest(test.TestCase):
+
+  def testGenerator(self):
+    def simple_generator():
+      for i in range(2):
+        yield {"value": i, "ignored": 3}
+
+    simple_features = {
+        "value": parsing_ops.FixedLenFeature(shape=[], dtype=dtypes.int32)
+    }
+    tensors = python_input.python_input(simple_generator, simple_features)
+    self.assertEqual(["value"], tensors.keys())
+    self.assertEqual(dtypes.int32, tensors["value"].dtype)
+    self.assertEqual((), tensors["value"].shape)
+
+    with self.test_session() as sess:
+      self.assertEqual({"value": 0}, sess.run(tensors))
+      self.assertEqual({"value": 1}, sess.run(tensors))
+      with self.assertRaisesOpError("Iteration finished"):
+        sess.run(tensors)
+
+  def testInvalidGenerator(self):
+    generator1 = lambda: iter([{"value": "a"}])
+    int_features = {
+        "value": parsing_ops.FixedLenFeature(shape=[], dtype=dtypes.int32)
+    }
+    tensors1 = python_input.python_input(generator1, int_features)
+
+    with self.test_session() as sess:
+      with self.assertRaisesOpError("invalid literal"):
+        # Can't convert a string to an integer
+        sess.run(tensors1)
+
+    generator2 = lambda: iter([None])
+    tensors2 = python_input.python_input(generator2, int_features)
+
+    with self.test_session() as sess:
+      with self.assertRaisesOpError("generator must return dict"):
+        sess.run(tensors2)
+
+    generator3 = lambda: iter([{"value": [1, 2]}])
+    tensors3 = python_input.python_input(generator3, int_features)
+
+    with self.test_session() as sess:
+      with self.assertRaisesOpError("incompatible with declared shape"):
+        sess.run(tensors3)
+
+  def testGeneratorWorksWithBatching(self):
+    def simple_generator():
+      for i in range(5):
+        yield {"value": i, "ignored": 3}
+
+    simple_features = {
+        "value": parsing_ops.FixedLenFeature(shape=[], dtype=dtypes.int32)
+    }
+    tensors = python_input.python_input(simple_generator, simple_features)
+
+    # Request batches of size 4 at a time, the final batch may be smaller.
+    batched_tensors = core_input.batch(tensors, batch_size=4,
+                                       allow_smaller_final_batch=True)
+
+    self.assertEqual(["value"], batched_tensors.keys())
+    self.assertEqual(dtypes.int32, batched_tensors["value"].dtype)
+    self.assertEqual([None], batched_tensors["value"].shape.as_list())
+
+    with self.test_session() as sess:
+      # The generator emits 5 items total.  The first 4 are returned in
+      # the first session run; the final one is returned in the
+      # second.  This works because allow_smaller_final_batch=True.
+      coord = coordinator.Coordinator()
+      threads = queue_runner_impl.start_queue_runners(sess=sess, coord=coord)
+      r1 = sess.run(batched_tensors)
+      r2 = sess.run(batched_tensors)
+      self.assertAllEqual([0, 1, 2, 3], r1["value"])
+      self.assertEqual([4], r2["value"])
+      with self.assertRaisesOpError("Iteration finished"):
+        sess.run(tensors)
+      coord.request_stop()
+      for thread in threads:
+        thread.join()
+
+  def testGeneratorWorksWithManyBatchingThreads(self):
+    def simple_generator():
+      for i in range(5000):
+        yield {"value": i, "ignored": 3}
+
+    simple_features = {
+        "value": parsing_ops.FixedLenFeature(shape=[], dtype=dtypes.int32)
+    }
+    tensors = python_input.python_input(simple_generator, simple_features)
+
+    # Request batches of size 20 at a time, the final batch may be smaller.
+    _, batched_tensors = bucket_ops.bucket(
+        tensors, which_bucket=tensors["value"] % 5,
+        batch_size=20, num_buckets=5, num_threads=7, capacity=17,
+        allow_smaller_final_batch=True)
+
+    self.assertEqual(["value"], batched_tensors.keys())
+    self.assertEqual(dtypes.int32, batched_tensors["value"].dtype)
+    self.assertEqual([None], batched_tensors["value"].shape.as_list())
+
+    with self.test_session() as sess:
+      # The generator emits 5 items total.  The first 4 are returned in
+      # the first session run; the final one is returned in the
+      # second.  This works because allow_smaller_final_batch=True.
+      coord = coordinator.Coordinator()
+      threads = queue_runner_impl.start_queue_runners(sess=sess, coord=coord)
+      results = []
+      while True:
+        try:
+          r = sess.run(batched_tensors)
+          results.extend(r["value"].tolist())
+        except errors.OutOfRangeError:
+          break
+      coord.request_stop()
+      for thread in threads:
+        thread.join()
+    self.assertEqual(sorted(results),
+                     list(range(5000)))
+
+  def testVaryingFieldsInGenerator(self):
+    def simple_generator():
+      for i in range(2):
+        yield {"value": i,
+               "seqlen_value": np.ones((i, 1))}
+
+    simple_features = {
+        "value": parsing_ops.FixedLenFeature(shape=[], dtype=dtypes.int32),
+        "seqlen_value": parsing_ops.FixedLenSequenceFeature(
+            shape=[1], dtype=dtypes.float32, allow_missing=True),
+        "empty_value": parsing_ops.FixedLenFeature(
+            default_value=[-1, -2], dtype=dtypes.int32, shape=[2])
+    }
+    tensors = python_input.python_input(simple_generator, simple_features)
+    self.assertEqual(
+        set(["value", "seqlen_value", "empty_value"]), set(tensors.keys()))
+    self.assertEqual(dtypes.int32, tensors["value"].dtype)
+    self.assertEqual((), tensors["value"].shape)
+    self.assertEqual(dtypes.float32, tensors["seqlen_value"].dtype)
+    self.assertEqual([None, 1], tensors["seqlen_value"].shape.as_list())
+    self.assertEqual(dtypes.int32, tensors["empty_value"].dtype)
+    self.assertEqual([2], tensors["empty_value"].shape)
+
+    with self.test_session() as sess:
+      r1 = sess.run(tensors)
+      self.assertAllEqual(0, r1["value"])
+      self.assertAllEqual(np.ones((0, 1)), r1["seqlen_value"])
+      self.assertAllEqual([-1, -2], r1["empty_value"])
+
+      r2 = sess.run(tensors)
+      self.assertAllEqual(1, r2["value"])
+      self.assertAllEqual([[1]], r2["seqlen_value"])
+      self.assertAllEqual([-1, -2], r2["empty_value"])
+
+      with self.assertRaisesOpError("Iteration finished"):
+        sess.run(tensors)
+
+
+if __name__ == "__main__":
+  test.main()
diff --git a/tensorflow/core/grappler/BUILD b/tensorflow/core/grappler/BUILD
index 5d74d3d3b17..476a9ac52a4 100644
--- a/tensorflow/core/grappler/BUILD
+++ b/tensorflow/core/grappler/BUILD
@@ -19,6 +19,7 @@ filegroup(
     srcs = [
         "devices.cc",
         "devices.h",
+        "grappler_item.cc",
         "grappler_item.h",
         "utils.cc",
         "utils.h",
diff --git a/tensorflow/core/grappler/optimizers/BUILD b/tensorflow/core/grappler/optimizers/BUILD
index 2ea150ce188..64d5815bf78 100644
--- a/tensorflow/core/grappler/optimizers/BUILD
+++ b/tensorflow/core/grappler/optimizers/BUILD
@@ -17,6 +17,7 @@ filegroup(
     srcs = glob(
         [
             "*_optimizer.*",
+            "auto_parallel.*",
             "constant_folding.*",
             "model_pruner.*",
             "graph_rewriter.*",
@@ -210,6 +211,7 @@ cc_library(
     ],
     visibility = ["//visibility:public"],
     deps = [
+        ":auto_parallel",
         ":constant_folding",
         ":graph_optimizer",
         ":layout_optimizer",
diff --git a/tensorflow/core/grappler/optimizers/auto_parallel.h b/tensorflow/core/grappler/optimizers/auto_parallel.h
index cac0db2c236..ad90bbe0289 100644
--- a/tensorflow/core/grappler/optimizers/auto_parallel.h
+++ b/tensorflow/core/grappler/optimizers/auto_parallel.h
@@ -25,7 +25,9 @@ namespace grappler {
 // Automatically parallelize a graph by splitting in the batch dimension.
 class AutoParallel : public GraphOptimizer {
  public:
-  AutoParallel(int num_replicas) : num_replicas_(num_replicas) {}
+  AutoParallel(int num_replicas) : num_replicas_(num_replicas) {
+    CHECK(num_replicas_ >= 2);
+  }
   ~AutoParallel() override {}
 
   string name() const override { return "autoparallel"; };
diff --git a/tensorflow/core/grappler/optimizers/meta_optimizer.cc b/tensorflow/core/grappler/optimizers/meta_optimizer.cc
index 0fe9359b753..2ea5adffebc 100644
--- a/tensorflow/core/grappler/optimizers/meta_optimizer.cc
+++ b/tensorflow/core/grappler/optimizers/meta_optimizer.cc
@@ -15,6 +15,7 @@ limitations under the License.
 
 #include "tensorflow/core/grappler/optimizers/meta_optimizer.h"
 #include "tensorflow/core/framework/versions.pb.h"
+#include "tensorflow/core/grappler/optimizers/auto_parallel.h"
 #include "tensorflow/core/grappler/optimizers/constant_folding.h"
 #include "tensorflow/core/grappler/optimizers/graph_optimizer.h"
 #include "tensorflow/core/grappler/optimizers/layout_optimizer.h"
@@ -41,6 +42,10 @@ std::unique_ptr<GraphOptimizer> MetaOptimizer::NewOptimizer(
   if (optimizer == "memory") {
     graph_optimizer.reset(new MemoryOptimizer());
   }
+  if (optimizer == "autoparallel") {
+    graph_optimizer.reset(
+        new AutoParallel(cfg_.auto_parallel().num_replicas()));
+  }
   return graph_optimizer;
 }
 
@@ -63,11 +68,15 @@ Status MetaOptimizer::Optimize(Cluster* cluster, const GrapplerItem& item,
       optimizers.push_back(
           std::unique_ptr<GraphOptimizer>(new MemoryOptimizer()));
     }
+    if (cfg_.auto_parallel().enable()) {
+      optimizers.push_back(std::unique_ptr<GraphOptimizer>(
+          new AutoParallel(cfg_.auto_parallel().num_replicas())));
+    }
   } else {
-    std::set<string> avaliable_optimizers = {"pruning", "constfold", "layout",
-                                             "memory"};
+    std::set<string> available_optimizers = {"pruning", "constfold", "layout",
+                                             "memory", "autoparallel"};
     for (const auto& optimizer : cfg_.optimizers()) {
-      if (avaliable_optimizers.find(optimizer) != avaliable_optimizers.end()) {
+      if (available_optimizers.find(optimizer) != available_optimizers.end()) {
         optimizers.push_back(NewOptimizer(optimizer));
       }
     }
@@ -102,7 +111,8 @@ void MetaOptimizer::Feedback(Cluster* cluster, const GrapplerItem& item,
 }
 
 bool MetaOptimizerEnabled(const RewriterConfig& cfg) {
-  return cfg.optimize_tensor_layout();
+  return cfg.optimize_tensor_layout() || cfg.constant_folding() ||
+         cfg.auto_parallel().enable() || !cfg.optimizers().empty();
 }
 
 Status RunMetaOptimizer(const GrapplerItem& item, const RewriterConfig& cfg,
diff --git a/tensorflow/core/kernels/aggregate_ops.cc b/tensorflow/core/kernels/aggregate_ops.cc
index cbc0537b454..0aa65729de2 100644
--- a/tensorflow/core/kernels/aggregate_ops.cc
+++ b/tensorflow/core/kernels/aggregate_ops.cc
@@ -161,9 +161,11 @@ TF_CALL_NUMBER_TYPES(REGISTER_ADDN_CPU);
 #undef REGISTER_ADDN_CPU
 
 #if GOOGLE_CUDA
-REGISTER_ADDN(Eigen::half, GPU);
-REGISTER_ADDN(float, GPU);
-REGISTER_ADDN(double, GPU);
+#define REGISTER_ADDN_GPU(type) REGISTER_ADDN(type, GPU)
+TF_CALL_GPU_NUMBER_TYPES(REGISTER_ADDN_GPU);
+TF_CALL_complex64(REGISTER_ADDN_GPU);
+TF_CALL_complex128(REGISTER_ADDN_GPU);
+#undef REGISTER_ADDN_GPU
 
 // A special GPU kernel for int32.
 // TODO(b/25387198): Also enable int32 in device memory. This kernel
diff --git a/tensorflow/core/kernels/aggregate_ops_gpu.cu.cc b/tensorflow/core/kernels/aggregate_ops_gpu.cu.cc
index 51393787acb..3f449be7544 100644
--- a/tensorflow/core/kernels/aggregate_ops_gpu.cu.cc
+++ b/tensorflow/core/kernels/aggregate_ops_gpu.cu.cc
@@ -154,6 +154,8 @@ struct Add9Functor<GPUDevice, T> {
   template struct functor::Add9Functor<GPUDevice, type>;
 
 TF_CALL_GPU_NUMBER_TYPES(REGISTER_FUNCTORS);
+TF_CALL_complex64(REGISTER_FUNCTORS);
+TF_CALL_complex128(REGISTER_FUNCTORS);
 
 #undef REGISTER_FUNCTORS
 
diff --git a/tensorflow/core/kernels/quantization_utils_test.cc b/tensorflow/core/kernels/quantization_utils_test.cc
index 84566047405..c7dbc0e5d11 100644
--- a/tensorflow/core/kernels/quantization_utils_test.cc
+++ b/tensorflow/core/kernels/quantization_utils_test.cc
@@ -355,6 +355,24 @@ TEST_F(QuantizationUtilsTest, AvoidBias) {
     const int back_to_int = FloatToQuantized<quint8>(as_float, 0.0f, 2.0f);
     EXPECT_EQ(i, back_to_int);
   }
+
+  // All perfectly representable floats should survive quantization, even
+  // if we pick a range where min is not itself perfectly representable.
+  const float min = -0.1375f;
+  const float max = 1.1385f;
+  const float step_size = (max - min) / 255.0f;
+  const float tolerance = step_size / 1000.0f;
+  // This is the smallest perfectly representable float in the range.
+  float first_float = ceil(min / step_size) * step_size;
+  // TODO(ahentz): The current version always incur a small error, which we
+  // need to account for. We should fix QuantizedToFloat<> to remove this bias.
+  const float expected_error = first_float - min;
+  ASSERT_GT(expected_error, tolerance);
+  for (float f = first_float; f <= max; f += step_size) {
+    const int as_int = FloatToQuantized<quint8>(f, min, max);
+    const float back_to_float = QuantizedToFloat<quint8>(as_int, min, max);
+    EXPECT_NEAR(f, back_to_float + expected_error, tolerance);
+  }
 }
 
 TEST_F(QuantizationUtilsTest, RequantizeInNewRange) {
diff --git a/tensorflow/core/ops/array_ops.cc b/tensorflow/core/ops/array_ops.cc
index e2e07a4bf19..8761c400b11 100644
--- a/tensorflow/core/ops/array_ops.cc
+++ b/tensorflow/core/ops/array_ops.cc
@@ -488,7 +488,7 @@ REGISTER_OP("SplitV")
       ShapeHandle output_shape;
       const Tensor* size_splits = c->input_tensor(1);
       if (rank == InferenceContext::kUnknownRank) {
-        // If the rank of input tensor is unknown, then return unkown shapes.
+        // If the rank of input tensor is unknown, then return unknown shapes.
         output_shape = c->UnknownShape();
         for (int i = 0; i < num_outputs; ++i) {
           c->set_output(i, output_shape);
@@ -497,7 +497,7 @@ REGISTER_OP("SplitV")
         // Throw error if input is a scalar.
         return errors::InvalidArgument("Can't split scalars");
       } else if (size_splits == nullptr || !c->ValueKnown(split_dimension)) {
-        // If split dimension or tensor containing the split sizes is unkown,
+        // If split dimension or tensor containing the split sizes is unknown,
         // then return unknown shapes of same rank as input.
         output_shape = c->UnknownShapeOfRank(rank);
         for (int i = 0; i < num_outputs; ++i) {
@@ -1328,8 +1328,8 @@ this operation will permute `params` accordingly.
 
 `validate_indices`: DEPRECATED. If this operation is assigned to CPU, values in
 `indices` are always validated to be within range. If assigned to GPU,
-out-of-bound indices result in unspecified behavior (currently the result is
-`0`, but this may become an error in the future).
+out-of-bound indices result in safe but unspecified behavior, which may include
+raising an error.
 
 <div style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;">
 <img style="width:100%" src="../../images/Gather.png" alt>
diff --git a/tensorflow/core/protobuf/rewriter_config.proto b/tensorflow/core/protobuf/rewriter_config.proto
index 63821cb55ef..753edba4b84 100644
--- a/tensorflow/core/protobuf/rewriter_config.proto
+++ b/tensorflow/core/protobuf/rewriter_config.proto
@@ -6,6 +6,11 @@ option java_outer_classname = "RewriterConfigProtos";
 option java_multiple_files = true;
 option java_package = "org.tensorflow.framework";
 
+message AutoParallelOptions {
+  bool enable = 1;
+  int32 num_replicas = 2;
+}
+
 message RewriterConfig {
   bool optimize_tensor_layout = 1;
   bool disable_model_pruning = 2;
@@ -19,6 +24,8 @@ message RewriterConfig {
   }
   MemOptType memory_optimization = 4;
 
+  AutoParallelOptions auto_parallel = 5;
+
   // If non-empty, will use this as an alternative way to specify a list of
   // optimizations to turn on and the order of the optimizations.
   repeated string optimizers = 100;
diff --git a/tensorflow/docs_src/tutorials/using_gpu.md b/tensorflow/docs_src/tutorials/using_gpu.md
index d64cdafdefb..dcec62d2749 100644
--- a/tensorflow/docs_src/tutorials/using_gpu.md
+++ b/tensorflow/docs_src/tutorials/using_gpu.md
@@ -57,14 +57,17 @@ have the same device assignment.
 with tf.device('/cpu:0'):
   a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
   b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
-  c = tf.matmul(a, b)
+c = tf.matmul(a, b)
 # Creates a session with log_device_placement set to True.
 sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
 # Runs the op.
 print(sess.run(c))
 ```
 
-You will see that now `a` and `b` are assigned to `cpu:0`.
+You will see that now `a` and `b` are assigned to `cpu:0`. Since a device was
+not explicitly specified for the `MatMul` operation, the TensorFlow runtime will
+choose one based on the operation and available devices (`gpu:0` in this
+example) and automatically copy tensors between devices if required.
 
 ```
 Device mapping:
diff --git a/tensorflow/python/__init__.py b/tensorflow/python/__init__.py
index 3663d8af7ae..5f598364273 100644
--- a/tensorflow/python/__init__.py
+++ b/tensorflow/python/__init__.py
@@ -132,6 +132,7 @@ from tensorflow.python.ops import tensor_array_ops
 # documentation, or remove.
 _allowed_symbols = [
     'AttrValue',
+    'AutoParallelOptions',
     'ConfigProto',
     'DeviceSpec',
     'Event',
diff --git a/tensorflow/python/debug/cli/curses_ui.py b/tensorflow/python/debug/cli/curses_ui.py
index b7549b406b6..d665627a93a 100644
--- a/tensorflow/python/debug/cli/curses_ui.py
+++ b/tensorflow/python/debug/cli/curses_ui.py
@@ -124,7 +124,7 @@ class ScrollBar(object):
       raise ValueError("Insufficient height for ScrollBar (%d)" %
                        (self._max_y - self._min_y + 1))
 
-  def _block_y(self):
+  def _block_y(self, screen_coord_sys=False):
     """Get the 0-based y coordinate of the scroll block.
 
     This y coordinate takes into account the presence of the UP and DN buttons
@@ -132,9 +132,13 @@ class ScrollBar(object):
     location, the return value will be 1; at the bottom location, the return
     value will be self._scroll_bar_height - 2.
 
+    Args:
+      screen_coord_sys: (`bool`) whether the return value will be in the
+        screen coordinate system.
+
     Returns:
       (int) 0-based y coordinate of the scroll block, in the ScrollBar
-        coordinate system, i.e., not the screen coordinate system. For example,
+        coordinate system by default. For example,
         when scroll position is at the top, this return value will be 1 (not 0,
         because of the presence of the UP button). When scroll position is at
         the bottom, this return value will be self._scroll_bar_height - 2
@@ -142,8 +146,10 @@ class ScrollBar(object):
         button).
     """
 
-    return int(float(self._scroll_position) / (self._output_num_rows - 1) *
-               (self._scroll_bar_height - 3)) + 1
+    rel_block_y = int(
+        float(self._scroll_position) / (self._output_num_rows - 1) *
+        (self._scroll_bar_height - 3)) + 1
+    return rel_block_y + self._min_y if screen_coord_sys else rel_block_y
 
   def layout(self):
     """Get the RichTextLines layout of the scroll bar.
@@ -192,9 +198,11 @@ class ScrollBar(object):
       return _SCROLL_UP_A_LINE
     elif mouse_y == self._max_y:
       return _SCROLL_DOWN_A_LINE
-    elif mouse_y > self._block_y() and mouse_y < self._max_y:
+    elif (mouse_y > self._block_y(screen_coord_sys=True) and
+          mouse_y < self._max_y):
       return _SCROLL_DOWN
-    elif mouse_y < self._block_y() and mouse_y > self._min_y:
+    elif (mouse_y < self._block_y(screen_coord_sys=True) and
+          mouse_y > self._min_y):
       return _SCROLL_UP
     else:
       return None
@@ -505,7 +513,7 @@ class CursesUI(base_ui.BaseUI):
   def get_help(self):
     return self._command_handler_registry.get_help()
 
-  def _screen_create_command_textbox(self, existing_command):
+  def _screen_create_command_textbox(self, existing_command=None):
     """Create command textbox on screen.
 
     Args:
@@ -839,6 +847,7 @@ class CursesUI(base_ui.BaseUI):
         else:
           command = self._fetch_hyperlink_command(mouse_x, mouse_y)
           if command:
+            self._screen_create_command_textbox()
             exit_token = self._dispatch_command(command)
             if exit_token is not None:
               raise debugger_cli_common.CommandLineExit(exit_token=exit_token)
@@ -898,13 +907,14 @@ class CursesUI(base_ui.BaseUI):
     """Automatically key in a command to the command Textbox.
 
     Args:
-      command: The command, as a string.
+      command: The command, as a string or None.
       erase_existing: (bool) whether existing text (if any) is to be erased
           first.
     """
     if erase_existing:
       self._erase_existing_command()
 
+    command = command or ""
     for c in command:
       self._command_textbox.do_command(ord(c))
 
@@ -1227,9 +1237,9 @@ class CursesUI(base_ui.BaseUI):
 
     self._scroll_bar = ScrollBar(
         self._max_x - 2,
-        2,
+        3,
         self._max_x - 1,
-        self._output_num_rows,
+        self._output_num_rows + 1,
         self._output_pad_row,
         self._output_pad_height - self._output_pad_screen_height)
 
diff --git a/tensorflow/python/debug/cli/curses_ui_test.py b/tensorflow/python/debug/cli/curses_ui_test.py
index 8219f47ef3a..15e1356d292 100644
--- a/tensorflow/python/debug/cli/curses_ui_test.py
+++ b/tensorflow/python/debug/cli/curses_ui_test.py
@@ -113,7 +113,7 @@ class MockCursesUI(curses_ui.CursesUI):
   def _screen_create_command_window(self):
     pass
 
-  def _screen_create_command_textbox(self, existing_command):
+  def _screen_create_command_textbox(self, existing_command=None):
     """Override to insert observer of existing commands.
 
     Used in testing of history navigation and tab completion.
@@ -1646,6 +1646,25 @@ class ScrollBarTest(test_util.TensorFlowTestCase):
                      scroll_bar.get_click_command(7))
     self.assertIsNone(scroll_bar.get_click_command(8))
 
+  def testClickCommandsAreCorrectForScrollBarNotAtZeroMinY(self):
+    scroll_bar = curses_ui.ScrollBar(0, 5, 1, 12, 10, 20)
+    self.assertIsNone(scroll_bar.get_click_command(0))
+    self.assertIsNone(scroll_bar.get_click_command(4))
+    self.assertEqual(curses_ui._SCROLL_UP_A_LINE,
+                     scroll_bar.get_click_command(5))
+    self.assertEqual(curses_ui._SCROLL_UP,
+                     scroll_bar.get_click_command(6))
+    self.assertEqual(curses_ui._SCROLL_UP,
+                     scroll_bar.get_click_command(7))
+    self.assertIsNone(scroll_bar.get_click_command(8))
+    self.assertEqual(curses_ui._SCROLL_DOWN,
+                     scroll_bar.get_click_command(10))
+    self.assertEqual(curses_ui._SCROLL_DOWN,
+                     scroll_bar.get_click_command(11))
+    self.assertEqual(curses_ui._SCROLL_DOWN_A_LINE,
+                     scroll_bar.get_click_command(12))
+    self.assertIsNone(scroll_bar.get_click_command(13))
+
 
 if __name__ == "__main__":
   googletest.main()
diff --git a/tensorflow/python/estimator/model_fn.py b/tensorflow/python/estimator/model_fn.py
index ee5999c78bc..a9d044fcfec 100644
--- a/tensorflow/python/estimator/model_fn.py
+++ b/tensorflow/python/estimator/model_fn.py
@@ -51,6 +51,7 @@ class ModeKeys(object):
 class MetricKeys(object):
   """Metric key strings."""
   LOSS = 'loss'
+  AVERAGE_LOSS = 'average_loss'
 
 
 class EstimatorSpec(
diff --git a/tensorflow/python/kernel_tests/BUILD b/tensorflow/python/kernel_tests/BUILD
index f21402652fa..ad455babbcd 100644
--- a/tensorflow/python/kernel_tests/BUILD
+++ b/tensorflow/python/kernel_tests/BUILD
@@ -941,6 +941,19 @@ tf_py_test(
     ],
 )
 
+cuda_py_test(
+    name = "aggregate_ops_test",
+    size = "small",
+    srcs = ["aggregate_ops_test.py"],
+    additional_deps = [
+        "//third_party/py/numpy",
+        "//tensorflow/python:array_ops",
+        "//tensorflow/python:client_testlib",
+        "//tensorflow/python:framework_for_generated_wrappers",
+        "//tensorflow/python:math_ops",
+    ],
+)
+
 cuda_py_test(
     name = "argmax_op_test",
     size = "small",
diff --git a/tensorflow/python/kernel_tests/aggregate_ops_test.py b/tensorflow/python/kernel_tests/aggregate_ops_test.py
new file mode 100644
index 00000000000..f56917f7e9b
--- /dev/null
+++ b/tensorflow/python/kernel_tests/aggregate_ops_test.py
@@ -0,0 +1,79 @@
+# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for aggregate_ops."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import numpy as np
+
+from tensorflow.python.framework import dtypes
+from tensorflow.python.ops import array_ops
+from tensorflow.python.ops import math_ops
+from tensorflow.python.platform import test
+
+
+class AddNTest(test.TestCase):
+  # AddN special-cases adding the first M inputs to make (N - M) divisible by 8,
+  # after which it adds the remaining (N - M) tensors 8 at a time in a loop.
+  # Test N in [1, 10] so we check each special-case from 1 to 9 and one
+  # iteration of the loop.
+  _MAX_N = 10
+
+  def _supported_types(self):
+    if test.is_gpu_available():
+      return [dtypes.float16, dtypes.float32, dtypes.float64, dtypes.complex64,
+              dtypes.complex128]
+    return [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
+            dtypes.float16, dtypes.float32, dtypes.float64, dtypes.complex64,
+            dtypes.complex128]
+
+  def _buildData(self, shape, dtype):
+    data = np.random.randn(*shape).astype(dtype.as_numpy_dtype)
+    # For complex types, add an index-dependent imaginary component so we can
+    # tell we got the right value.
+    if dtype.is_complex:
+      return data + 10j * data
+    return data
+
+  def testAddN(self):
+    np.random.seed(12345)
+    with self.test_session(use_gpu=True) as sess:
+      for dtype in self._supported_types():
+        for count in range(1, self._MAX_N + 1):
+          data = [self._buildData((2, 2), dtype) for _ in range(count)]
+          actual = sess.run(math_ops.add_n(data))
+          expected = np.sum(np.vstack(
+              [np.expand_dims(d, 0) for d in data]), axis=0)
+          tol = 5e-3 if dtype == dtypes.float16 else 5e-7
+          self.assertAllClose(expected, actual, rtol=tol, atol=tol)
+
+  def testUnknownShapes(self):
+    np.random.seed(12345)
+    with self.test_session(use_gpu=True) as sess:
+      for dtype in self._supported_types():
+        data = self._buildData((2, 2), dtype)
+        for count in range(1, self._MAX_N + 1):
+          data_ph = array_ops.placeholder(dtype=dtype)
+          actual = sess.run(math_ops.add_n([data_ph] * count), {data_ph: data})
+          expected = np.sum(np.vstack([np.expand_dims(data, 0)] * count),
+                            axis=0)
+          tol = 5e-3 if dtype == dtypes.float16 else 5e-7
+          self.assertAllClose(expected, actual, rtol=tol, atol=tol)
+
+
+if __name__ == "__main__":
+  test.main()
diff --git a/tensorflow/python/ops/control_flow_ops.py b/tensorflow/python/ops/control_flow_ops.py
index c4a27009c3c..dea2180069a 100644
--- a/tensorflow/python/ops/control_flow_ops.py
+++ b/tensorflow/python/ops/control_flow_ops.py
@@ -50,8 +50,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 import six
 from six.moves import xrange  # pylint: disable=redefined-builtin
 
@@ -426,10 +424,11 @@ def merge(inputs, name=None):
 # pylint: enable=protected-access
 
 
-def _convert_tensorarrays_to_flows(tensors_or_tensor_arrays):
-  return [ta.flow if isinstance(ta, tensor_array_ops.TensorArray)
-          else ta
-          for ta in tensors_or_tensor_arrays]
+def _convert_tensorarray_to_flow(tensor_or_tensor_array):
+  if isinstance(tensor_or_tensor_array, tensor_array_ops.TensorArray):
+    return tensor_or_tensor_array.flow
+  else:
+    return tensor_or_tensor_array
 
 
 def _make_tensor_array(ta, t_or_flow):
@@ -1637,63 +1636,77 @@ class CondContext(ControlFlowContext):
         real_val = external_val
     return real_val
 
+  def _BuildCondTensor(self, v):
+    if isinstance(v, ops.Operation):
+      # Use pivot as the proxy for this op.
+      return with_dependencies([v], self._pivot)
+    elif isinstance(v, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
+      values = self._ProcessOutputTensor(v.values)
+      indices = self._ProcessOutputTensor(v.indices)
+      if isinstance(v, ops.IndexedSlices):
+        dense_shape = v.dense_shape
+        if dense_shape is not None:
+          dense_shape = self._ProcessOutputTensor(dense_shape)
+        return ops.IndexedSlices(values, indices, dense_shape)
+      else:
+        dense_shape = self._ProcessOutputTensor(v.dense_shape)
+        return sparse_tensor.SparseTensor(indices, values, dense_shape)
+    else:
+      v = nest.map_structure(_convert_tensorarray_to_flow, v)
+      return self._ProcessOutputTensor(ops.convert_to_tensor(v))
+
   def BuildCondBranch(self, fn):
     """Add the subgraph defined by fn() to the graph."""
-    r = fn()
-    original_r = r
-    result = []
-    if r is not None:
-      if not isinstance(r, list) and not isinstance(r, _basetuple):
-        r = [r]
-        original_r = [original_r]
-      r = _convert_tensorarrays_to_flows(r)
-      for v in r:
-        real_v = v
-        if isinstance(v, ops.Operation):
-          # Use pivot as the proxy for this op.
-          real_v = with_dependencies([v], self._pivot)
-        else:
-          if isinstance(v, (ops.IndexedSlices, sparse_tensor.SparseTensor)):
-            values = self._ProcessOutputTensor(v.values)
-            indices = self._ProcessOutputTensor(v.indices)
-            if isinstance(v, ops.IndexedSlices):
-              dense_shape = v.dense_shape
-              if dense_shape is not None:
-                dense_shape = self._ProcessOutputTensor(dense_shape)
-              real_v = ops.IndexedSlices(values, indices, dense_shape)
-            else:
-              dense_shape = self._ProcessOutputTensor(v.dense_shape)
-              real_v = sparse_tensor.SparseTensor(indices, values, dense_shape)
-          else:
-            real_v = self._ProcessOutputTensor(v)
-        result.append(real_v)
-    return original_r, result
+    original_result = fn()
+    if original_result is None:
+      return None, None
+
+    result = nest.map_structure(self._BuildCondTensor, original_result)
+    if not isinstance(result, (list, _basetuple)):
+      result = [result]
+    return original_result, result
 
 
-def cond(pred, fn1, fn2, name=None):
-  """Return either fn1() or fn2() based on the boolean predicate `pred`.
+def _UnpackIfSingleton(res):
+  if isinstance(res, (list, _basetuple)) and len(res) == 1:
+    return res[0]
+  else:
+    return res
+
+
+def cond(pred, fn1, fn2, strict=False, name=None):
+  """Return either `fn1()` or `fn2()` based on the boolean predicate `pred`.
 
   `fn1` and `fn2` both return lists of output tensors. `fn1` and `fn2` must have
   the same non-zero number and type of outputs.
 
   Note that the conditional execution applies only to the operations defined in
-  fn1 and fn2. Consider the following simple program:
+  `fn1` and `fn2`. Consider the following simple program:
 
   ```python
   z = tf.multiply(a, b)
   result = tf.cond(x < y, lambda: tf.add(x, z), lambda: tf.square(y))
   ```
 
-  If x < y, the `tf.add` operation will be executed and `tf.square`
-  operation will not be executed. Since z is needed for at least one
-  branch of the cond, the `tf.multiply` operation is always executed, unconditionally.
+  If `x < y`, the `tf.add` operation will be executed and `tf.square`
+  operation will not be executed. Since `z` is needed for at least one
+  branch of the `cond`, the `tf.multiply` operation is always executed,
+  unconditionally.
   Although this behavior is consistent with the dataflow model of TensorFlow,
   it has occasionally surprised some users who expected a lazier semantics.
 
+  `tf.cond` supports nested structures as implemented in
+  `tensorflow.python.util.nest`. Both `fn1` and `fn2` must return the same
+  (possibly nested) value structure of lists, tuples, and/or named tuples.
+  Singleton lists and tuples form the only exceptions to this: when returned by
+  `fn1` and/or `fn2`, they are implicitly unpacked to single values. This
+  behavior is disabled by passing `strict=True`.
+
   Args:
     pred: A scalar determining whether to return the result of `fn1` or `fn2`.
     fn1: The callable to be performed if pred is true.
     fn2: The callable to be performed if pred is false.
+    strict: A boolean that enables/disables 'strict' mode; see above.
     name: Optional name prefix for the returned tensors.
 
   Returns:
@@ -1738,23 +1751,43 @@ def cond(pred, fn1, fn2, name=None):
     # Build the graph for the true branch in a new context.
     context_t = CondContext(pred, pivot_1, branch=1)
     context_t.Enter()
-    orig_res, res_t = context_t.BuildCondBranch(fn1)
+    orig_res_t, res_t = context_t.BuildCondBranch(fn1)
+    if orig_res_t is None:
+      raise ValueError("fn1 must have a return value.")
     context_t.ExitResult(res_t)
     context_t.Exit()
 
     # Build the graph for the false branch in a new context.
     context_f = CondContext(pred, pivot_2, branch=0)
     context_f.Enter()
-    _, res_f = context_f.BuildCondBranch(fn2)
+    orig_res_f, res_f = context_f.BuildCondBranch(fn2)
+    if orig_res_f is None:
+      raise ValueError("fn2 must have a return value.")
     context_f.ExitResult(res_f)
     context_f.Exit()
 
+    if not strict:
+      orig_res_t = _UnpackIfSingleton(orig_res_t)
+      orig_res_f = _UnpackIfSingleton(orig_res_f)
+
+    # Check that the return values of the two branches have the same structure.
+    try:
+      nest.assert_same_structure(orig_res_t, orig_res_f)
+    except TypeError as e:
+      raise TypeError(
+          "Incompatible return types of fn1 and fn2: {}".format(e))
+    except ValueError as e:
+      raise ValueError(
+          "Incompatible return values of fn1 and fn2: {}".format(e))
+
     # Add the final merge to the graph.
-    if len(res_t) != len(res_f):
-      raise ValueError("fn1 and fn2 must return the same number of results.")
     if not res_t:
       raise ValueError("fn1 and fn2 must return at least one result.")
-    for x, y in zip(res_t, res_f):
+
+    res_t_flat = nest.flatten(res_t)
+    res_f_flat = nest.flatten(res_f)
+
+    for x, y in zip(res_t_flat, res_f_flat):
       assert ((isinstance(x, ops.IndexedSlices) and
                isinstance(y, ops.IndexedSlices)) or
               (isinstance(x, sparse_tensor.SparseTensor) and
@@ -1765,14 +1798,20 @@ def cond(pred, fn1, fn2, name=None):
       if val_x.dtype.base_dtype != val_y.dtype.base_dtype:
         raise ValueError("Outputs of fn1 and fn2 must have the same type: "
                          "%s, %s" % (val_x.dtype.name, val_y.dtype.name))
-    merges = [merge([x[0], x[1]])[0] for x in zip(res_f, res_t)]
-    merges = _convert_flows_to_tensorarrays(orig_res, merges)
+
+    merges = [merge(pair)[0] for pair in zip(res_f_flat, res_t_flat)]
+    merges = _convert_flows_to_tensorarrays(nest.flatten(orig_res_t), merges)
 
     # Add to collections
     ops.add_to_collection(ops.GraphKeys.COND_CONTEXT, context_t)
     ops.add_to_collection(ops.GraphKeys.COND_CONTEXT, context_f)
 
-    return merges[0] if len(merges) == 1 else merges
+    merges = nest.pack_sequence_as(structure=orig_res_t, flat_sequence=merges)
+
+    # Singleton lists and tuples are automatically unpacked if strict == False.
+    if not strict:
+      merges = _UnpackIfSingleton(merges)
+    return merges
 
 
 def _resource_safe_shape(t):
@@ -2415,8 +2454,8 @@ class WhileContext(ControlFlowContext):
     # Store body_result to keep track of TensorArrays returned by body
     original_body_result = body_result
     # Convert TensorArrays returned by body into their flow variables
-    flat_result = nest.flatten(body_result)
-    result = _convert_tensorarrays_to_flows(flat_result)
+    result = nest.map_structure(_convert_tensorarray_to_flow,
+                                nest.flatten(body_result))
     result = ops.convert_n_to_tensor_or_indexed_slices(result)
 
     # Add NextIteration and the back edges to complete the loop.
@@ -2446,9 +2485,9 @@ class WhileContext(ControlFlowContext):
 
     # Keep original_loop_vars to identify which are TensorArrays
     original_loop_vars = loop_vars
-    flat_loop_vars = nest.flatten(loop_vars)
     # Convert TensorArrays to their flow variables
-    loop_vars = _convert_tensorarrays_to_flows(flat_loop_vars)
+    loop_vars = nest.map_structure(_convert_tensorarray_to_flow,
+                                   nest.flatten(loop_vars))
     loop_vars = ops.convert_n_to_tensor_or_indexed_slices(loop_vars)
     try:
       self.Enter()
@@ -2820,7 +2859,7 @@ def tuple(tensors, name=None, control_inputs=None):
     return tpl
 
 
-def case(pred_fn_pairs, default, exclusive=False, name="case"):
+def case(pred_fn_pairs, default, exclusive=False, strict=False, name="case"):
   """Create a case operation.
 
   The `pred_fn_pairs` parameter is a dict or list of pairs of size N.
@@ -2837,6 +2876,13 @@ def case(pred_fn_pairs, default, exclusive=False, name="case"):
   are returned immediately. If none of the predicates evaluate to True, this
   operation returns the tensors generated by `default`.
 
+  `tf.case` supports nested structures as implemented in
+  `tensorflow.python.util.nest`. Both `fn1` and `fn2` must return the same
+  (possibly nested) value structure of lists, tuples, and/or named tuples.
+  Singleton lists and tuples form the only exceptions to this: when returned by
+  `fn1` and/or `fn2`, they are implicitly unpacked to single values. This
+  behavior is disabled by passing `strict=True`.
+
   Example 1:
     Pseudocode:
     ```
@@ -2877,6 +2923,7 @@ def case(pred_fn_pairs, default, exclusive=False, name="case"):
                    callable which returns a list of tensors.
     default: A callable that returns a list of tensors.
     exclusive: True iff at most one predicate is allowed to evaluate to `True`.
+    strict: A boolean that enables/disables 'strict' mode; see above.
     name: A name for this operation (optional).
 
   Returns:
@@ -2941,20 +2988,31 @@ def case(pred_fn_pairs, default, exclusive=False, name="case"):
 
     # Create an empty tensor, or list, with the right type and shape
     with ops.name_scope("case_create_empty"):
-      dummy_value = default()
+      def _create_empty_constant(dtype, shape):
+        value = ("" if dtype == dtypes.string else dtype.as_numpy_dtype())
+        if shape.ndims is None:
+          return array_ops.constant(value, dtype=dtype)
+        else:
+          temp_shape = [1 if x.value is None else x.value for x in shape]
+          result = array_ops.constant(value, shape=temp_shape, dtype=dtype)
+          result._shape = shape  # pylint: disable=protected-access
+          return result
+
       def _correct_empty(v):
         if isinstance(v, ops.Operation):
           return no_op()
-        elif v.dtype == dtypes.string:
-          return array_ops.constant("")
+        elif isinstance(v, tensor_array_ops.TensorArray):
+          return v
+        elif not hasattr(v, "dtype"):
+          return ops.convert_to_tensor(v)
+        elif isinstance(v, sparse_tensor.SparseTensor):
+          return sparse_tensor.SparseTensor(indices=[[0] * len(v.get_shape())],
+                                            values=[v.dtype.as_numpy_dtype()],
+                                            dense_shape=v.get_shape())
         else:
-          return array_ops.constant(v.dtype.as_numpy_dtype())
+          return _create_empty_constant(v.dtype, v.get_shape())
 
-      if isinstance(dummy_value, collections.Sequence):
-        dummy_type = type(dummy_value)
-        empty = lambda: dummy_type(_correct_empty(v) for v in dummy_value)
-      else:
-        empty = lambda: _correct_empty(dummy_value)
+      empty = lambda: nest.map_structure(_correct_empty, default())
 
     # case_sequence = [
     #   cond(~p3 & ~p2 & ~p1, default, empty),
@@ -2972,7 +3030,7 @@ def case(pred_fn_pairs, default, exclusive=False, name="case"):
         prev_case = cond(
             cp, fn,
             empty if i == 0 else lambda: prev_case,
-            name="If_%d" % i)
+            strict=strict, name="If_%d" % i)
       return prev_case
 
     if exclusive:
@@ -2994,6 +3052,8 @@ def case(pred_fn_pairs, default, exclusive=False, name="case"):
     else:
       case_seq = _build_case()
 
+    if not strict:
+      case_seq = _UnpackIfSingleton(case_seq)
     return case_seq
 
 
diff --git a/tensorflow/python/ops/control_flow_ops_test.py b/tensorflow/python/ops/control_flow_ops_test.py
index 9037dd042dd..a88143224f8 100644
--- a/tensorflow/python/ops/control_flow_ops_test.py
+++ b/tensorflow/python/ops/control_flow_ops_test.py
@@ -18,11 +18,16 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import collections
+import numpy as np
+
 from tensorflow.core.framework import graph_pb2
 from tensorflow.core.framework import node_def_pb2
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
+from tensorflow.python.framework import sparse_tensor
+from tensorflow.python.framework import tensor_shape
 from tensorflow.python.framework.test_util import TensorFlowTestCase
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import control_flow_ops
@@ -37,9 +42,14 @@ from tensorflow.python.ops import variables
 import tensorflow.python.ops.tensor_array_grad  # pylint: disable=unused-import
 from tensorflow.python.platform import googletest
 from tensorflow.python.training import momentum
+from tensorflow.python.util import nest
 from tensorflow.python.util.protobuf import compare
 
 
+TestTuple = collections.namedtuple("TestTuple", "a b")
+SingletonTestTuple = collections.namedtuple("SingletonTestTuple", "a")
+
+
 class GroupTestCase(TensorFlowTestCase):
 
   def _StripNode(self, nd):
@@ -334,5 +344,340 @@ class ContextTest(TensorFlowTestCase):
               control_flow_ops.WhileContext.from_proto(c.to_proto()).to_proto())
 
 
+def _GetNestedShape(nested):
+  def _GetShape(tensor):
+    if isinstance(tensor, tensor_array_ops.TensorArray):
+      return tensor_array_ops.TensorArray
+    elif isinstance(tensor, ops.IndexedSlices):
+      return tensor.dense_shape
+    else:
+      return tensor.get_shape()
+
+  return nest.map_structure(_GetShape, nested)
+
+
+def _CreateTensorArray(size, shape):
+  ta = tensor_array_ops.TensorArray(dtype=dtypes.float32, size=size,
+                                    clear_after_read=False)
+  for i in range(size):
+    ta = ta.write(i, array_ops.zeros(shape))
+  return ta
+
+
+def _RawNestedShape(nested_shape):
+  def _RawShape(shape):
+    if isinstance(shape, tensor_shape.TensorShape) and shape.ndims is not None:
+      return [x.value for x in shape]
+    else:
+      return None
+  return nest.map_structure(_RawShape, nested_shape)
+
+
+# TODO(yori): Add tests for indexed slices.
+class DataTypesTest(TensorFlowTestCase):
+
+  def assertAllEqualNested(self, a, b):
+    if isinstance(a, (list, tuple)):
+      for entry_a, entry_b in zip(a, b):
+        self.assertAllEqualNested(entry_a, entry_b)
+    else:
+      self.assertAllEqual(a, b)
+
+  def _testShape(self, fn_true, fn_false, expected_shape,
+                 strict=False):
+    condition = array_ops.placeholder(dtypes.bool)
+    output_cond = control_flow_ops.cond(condition, fn_true, fn_false,
+                                        strict=strict)
+    self.assertEqual(_RawNestedShape(_GetNestedShape(output_cond)),
+                     _RawNestedShape(expected_shape))
+
+    output_case = control_flow_ops.case([(condition, fn_true)], fn_false,
+                                        strict=strict)
+    self.assertEqual(_RawNestedShape(_GetNestedShape(output_case)),
+                     _RawNestedShape(expected_shape))
+
+  def _testReturnValues(self, fn_true, fn_false, expected_value_true,
+                        expected_value_false, strict=False,
+                        check_cond=True):
+    condition = array_ops.placeholder(dtypes.bool)
+    output_cond = control_flow_ops.cond(condition, fn_true, fn_false,
+                                        strict=strict)
+    output_case = control_flow_ops.case([(condition, fn_true)], fn_false,
+                                        strict=strict)
+
+    with self.test_session() as sess:
+      variables.global_variables_initializer().run()
+      result_cond, result_case = sess.run([output_cond, output_case],
+                                          feed_dict={condition: True})
+      self.assertAllEqualNested(result_cond, expected_value_true)
+      if check_cond:
+        self.assertAllEqualNested(result_case, expected_value_true)
+      result_cond, result_case = sess.run([output_cond, output_case],
+                                          feed_dict={condition: False})
+      self.assertAllEqualNested(result_cond, expected_value_false)
+      if check_cond:
+        self.assertAllEqualNested(result_case, expected_value_false)
+
+  def test_int(self):
+    shape = tensor_shape.TensorShape([])
+    fn_true = lambda: 1
+    fn_false = lambda: 2
+    self._testShape(fn_true, fn_false, shape)
+    self._testReturnValues(fn_true, fn_false, 1, 2)
+    self._testShape(fn_true, fn_false, shape, strict=True)
+    self._testReturnValues(fn_true, fn_false, 1, 2, strict=True)
+
+  def test_float(self):
+    shape = tensor_shape.TensorShape([])
+    fn_true = lambda: 1.0
+    fn_false = lambda: 2.0
+    self._testShape(fn_true, fn_false, shape)
+    self._testReturnValues(fn_true, fn_false, 1.0, 2.0)
+
+  def test_noop(self):
+    shape = tensor_shape.TensorShape(None)
+    self._testShape(control_flow_ops.no_op, control_flow_ops.no_op, shape)
+    self._testReturnValues(control_flow_ops.no_op, control_flow_ops.no_op,
+                           True, False, check_cond=False)
+
+  def test_string(self):
+    shape = tensor_shape.TensorShape([])
+    fn_true = lambda: "abc"
+    fn_false = lambda: "xyz"
+    self._testShape(fn_true, fn_false, shape)
+    self._testReturnValues(fn_true, fn_false, b"abc", b"xyz")
+
+  def test_variable(self):
+    shape = tensor_shape.TensorShape([])
+    fn_true = lambda: variables.Variable(3.0)
+    fn_false = lambda: variables.Variable(4.0)
+    self._testShape(fn_true, fn_false, shape)
+    self._testReturnValues(fn_true, fn_false, 3.0, 4.0)
+
+  def test_none(self):
+    fn_none = lambda: None
+    fn_tensor = lambda: constant_op.constant(1)
+
+    with self.assertRaises(ValueError):
+      control_flow_ops.cond(constant_op.constant(True), fn_none, fn_tensor)
+
+    with self.assertRaises(ValueError):
+      control_flow_ops.cond(constant_op.constant(True), fn_tensor, fn_none)
+
+  def test_tensors(self):
+    def _BuildTrueBranch(dtype):
+      def _Build():
+        return (array_ops.zeros([2, 2], dtype=dtype),
+                array_ops.ones([3, 3], dtype=dtype))
+      return _Build
+
+    def _BuildFalseBranch(dtype):
+      def _Build():
+        return (array_ops.ones([2, 2], dtype=dtype),
+                array_ops.zeros([3, 3], dtype=dtype))
+      return _Build
+
+    for dtype in (dtypes.float16, dtypes.int8, dtypes.int32, dtypes.uint8):
+      shape = (tensor_shape.TensorShape([2, 2]),
+               tensor_shape.TensorShape([3, 3]))
+      fn_true = _BuildTrueBranch(dtype)
+      fn_false = _BuildFalseBranch(dtype)
+      self._testShape(fn_true, fn_false, shape)
+      self._testReturnValues(fn_true, fn_false,
+                             (np.zeros([2, 2]), np.ones([3, 3])),
+                             (np.ones([2, 2]), np.zeros([3, 3])))
+
+  def test_tensors_unknown_shape(self):
+    def _BuildTrueBranch(dtype):
+      def _Build():
+        tensor = array_ops.zeros([2, 2], dtype=dtype)
+        tensor._shape = tensor_shape.TensorShape(None)
+        return tensor
+      return _Build
+
+    def _BuildFalseBranch(dtype):
+      def _Build():
+        tensor = array_ops.ones([2, 2], dtype=dtype)
+        tensor._shape = tensor_shape.TensorShape(None)
+        return tensor
+      return _Build
+
+    for dtype in (dtypes.float16, dtypes.int8, dtypes.int32, dtypes.uint8):
+      shape = tensor_shape.TensorShape(None)
+      fn_true = _BuildTrueBranch(dtype)
+      fn_false = _BuildFalseBranch(dtype)
+      self._testShape(fn_true, fn_false, shape)
+      self._testReturnValues(fn_true, fn_false,
+                             np.zeros([2, 2]), np.ones([2, 2]))
+
+  def test_sparse_tensors(self):
+    shape = tensor_shape.TensorShape([None, None])
+
+    def FnTrue():
+      return [sparse_tensor.SparseTensor(indices=[[0, 0], [1, 2]],
+                                         values=[1, 2], dense_shape=[3, 4])]
+
+    def FnFalse():
+      return [sparse_tensor.SparseTensor(indices=[[0, 0], [2, 1]],
+                                         values=[3, 4], dense_shape=[3, 4])]
+
+    value1 = sparse_tensor.SparseTensorValue(indices=[[0, 0], [1, 2]],
+                                             values=[1, 2], dense_shape=[3, 4])
+    value2 = sparse_tensor.SparseTensorValue(indices=[[0, 0], [2, 1]],
+                                             values=[3, 4], dense_shape=[3, 4])
+    self._testShape(FnTrue, FnFalse, shape)
+    self._testReturnValues(FnTrue, FnFalse, value1, value2)
+    self._testShape(FnTrue, FnFalse, [shape], strict=True)
+    self._testReturnValues(FnTrue, FnFalse, [value1], [value2], strict=True)
+
+  def test_tensors_with_partially_specified_shapes(self):
+    def _BuildBranch(dtype, shape):
+      def _Build():
+        a = array_ops.zeros([2, 2], dtype=dtype)
+        b = array_ops.zeros([5], dtype=dtype)
+        c = array_ops.ones([3, 3], dtype=dtype)
+        a._shape = tensor_shape.TensorShape(shape[0])
+        b._shape = tensor_shape.TensorShape(shape[1])
+        c._shape = tensor_shape.TensorShape(shape[2])
+        return a, b, c
+      return _Build
+
+    for dtype in (dtypes.float16, dtypes.int8, dtypes.int32, dtypes.uint8):
+      shape = (tensor_shape.TensorShape([None, 2]),
+               tensor_shape.TensorShape([None]),
+               tensor_shape.TensorShape([3, None]))
+      fn_true = _BuildBranch(dtype, shape)
+      fn_false = _BuildBranch(dtype, shape)
+      self._testShape(fn_true, fn_false, shape)
+      self._testReturnValues(fn_true, fn_false,
+                             (np.zeros([2, 2]), np.zeros(5), np.ones([3, 3])),
+                             (np.zeros([2, 2]), np.zeros(5), np.ones([3, 3])))
+
+  def test_tensor_arrays(self):
+    element_shape = tensor_shape.TensorShape([2])
+    ta1 = _CreateTensorArray(4, element_shape)
+    ta2 = _CreateTensorArray(4, element_shape)
+    shape = tensor_array_ops.TensorArray
+    fn_true = lambda: ta1
+    fn_false = lambda: ta2
+    self._testShape(fn_true, fn_false, shape)
+
+  def test_tensor_array_reads(self):
+    shape = tensor_shape.TensorShape([2])
+    ta = _CreateTensorArray(4, shape)
+    fn_true = lambda: ta.read(0)
+    fn_false = lambda: ta.read(1)
+    self._testShape(fn_true, fn_false, shape)
+
+  def test_list(self):
+    shape = [tensor_shape.TensorShape([]), tensor_shape.TensorShape([]),
+             tensor_shape.TensorShape([])]
+    fn_true = lambda: [constant_op.constant(1), 2, variables.Variable(3.0)]
+    fn_false = lambda: [constant_op.constant(3), 4, variables.Variable(5.0)]
+    self._testShape(fn_true, fn_false, shape)
+    self._testReturnValues(fn_true, fn_false, [1, 2, 3.0], [3, 4, 5.0])
+
+  def test_non_strict(self):
+    shape = tensor_shape.TensorShape([])
+    fn_tensor = lambda: constant_op.constant(1)
+    fn_list = lambda: [constant_op.constant(2)]
+    fn_tuple = lambda: (constant_op.constant(3),)
+    self._testShape(fn_tensor, fn_list, shape)
+    self._testShape(fn_tensor, fn_tuple, shape)
+    self._testShape(fn_list, fn_tuple, shape)
+    self._testReturnValues(fn_tensor, fn_list, 1, 2)
+    self._testReturnValues(fn_tensor, fn_tuple, 1, 3)
+    self._testReturnValues(fn_list, fn_tuple, 2, 3)
+
+  def test_singleton_strict(self):
+    fn_tensor = lambda: constant_op.constant(1)
+    fn_list = lambda: [constant_op.constant(2)]
+    fn_tuple = lambda: (constant_op.constant(3),)
+
+    with self.assertRaises(ValueError):
+      control_flow_ops.cond(constant_op.constant(True), fn_tensor, fn_list,
+                            strict=True)
+
+    with self.assertRaises(TypeError):
+      control_flow_ops.cond(constant_op.constant(True), fn_list, fn_tuple,
+                            strict=True)
+
+    with self.assertRaises(ValueError):
+      control_flow_ops.case([(constant_op.constant(True), fn_tensor)], fn_list,
+                            strict=True)
+
+    with self.assertRaises(TypeError):
+      control_flow_ops.case([(constant_op.constant(True), fn_list)], fn_tuple,
+                            strict=True)
+
+  def test_singleton_list(self):
+    shape = tensor_shape.TensorShape([])
+    fn_true = lambda: [constant_op.constant(1)]
+    fn_false = lambda: [constant_op.constant(3)]
+    self._testShape(fn_true, fn_false, shape)
+    self._testReturnValues(fn_true, fn_false, 1, 3)
+    self._testShape(fn_true, fn_false, [shape], strict=True)
+    self._testReturnValues(fn_true, fn_false, [1], [3], strict=True)
+
+  def test_singleton_tuple(self):
+    shape = tensor_shape.TensorShape([])
+    fn_true = lambda: (constant_op.constant(1),)
+    fn_false = lambda: (constant_op.constant(3),)
+    self._testShape(fn_true, fn_false, shape)
+    self._testReturnValues(fn_true, fn_false, 1, 3)
+    self._testShape(fn_true, fn_false, (shape,), strict=True)
+    self._testReturnValues(fn_true, fn_false, (1,), (3,),
+                           strict=True)
+
+  def test_singleton_namedtuple(self):
+    shape = tensor_shape.TensorShape([])
+    fn_true = lambda: SingletonTestTuple(constant_op.constant(1))
+    fn_false = lambda: SingletonTestTuple(constant_op.constant(3))
+    self._testShape(fn_true, fn_false, shape)
+    self._testReturnValues(fn_true, fn_false, 1, 3)
+    self._testShape(fn_true, fn_false, SingletonTestTuple(shape),
+                    strict=True)
+    self._testReturnValues(fn_true, fn_false, SingletonTestTuple(1),
+                           SingletonTestTuple(3), strict=True)
+
+  def test_tuple(self):
+    shape = (tensor_shape.TensorShape([]), tensor_shape.TensorShape([]))
+    fn_true = lambda: (constant_op.constant(1), 2)
+    fn_false = lambda: (constant_op.constant(3), 4)
+    self._testShape(fn_true, fn_false, shape)
+    self._testReturnValues(fn_true, fn_false, (1, 2), (3, 4))
+
+  def test_namedtuple(self):
+    shape = TestTuple(tensor_shape.TensorShape([]),
+                      tensor_shape.TensorShape([]))
+    fn_true = lambda: TestTuple(constant_op.constant(1), 2)
+    fn_false = lambda: TestTuple(constant_op.constant(3), 4)
+    self._testShape(fn_true, fn_false, shape)
+    self._testReturnValues(fn_true, fn_false, TestTuple(1, 2), TestTuple(3, 4))
+
+  def test_nested(self):
+    shape = [tensor_shape.TensorShape([]),
+             TestTuple(tensor_shape.TensorShape([]),
+                       [tensor_shape.TensorShape([]),
+                        tensor_shape.TensorShape([])]),
+             tensor_shape.TensorShape([5, 5]),
+             tensor_shape.TensorShape([])]
+
+    def FnTrue():
+      return [constant_op.constant(1),
+              TestTuple(constant_op.constant(2), [3, 4]),
+              array_ops.zeros([5, 5]), 6]
+
+    def FnFalse():
+      return [constant_op.constant(11),
+              TestTuple(constant_op.constant(12), [13, 14]),
+              array_ops.ones([5, 5]), 16]
+
+    self._testShape(FnTrue, FnFalse, shape)
+    self._testReturnValues(FnTrue, FnFalse,
+                           [1, TestTuple(2, [3, 4]), np.zeros([5, 5]), 6],
+                           [11, TestTuple(12, [13, 14]), np.ones([5, 5]), 16])
+
+
 if __name__ == "__main__":
   googletest.main()
diff --git a/tensorflow/python/ops/embedding_ops.py b/tensorflow/python/ops/embedding_ops.py
index 2aeb9ce14d3..168ca7fefcc 100644
--- a/tensorflow/python/ops/embedding_ops.py
+++ b/tensorflow/python/ops/embedding_ops.py
@@ -33,16 +33,16 @@ from tensorflow.python.ops import variables
 from tensorflow.python.platform import tf_logging as logging
 
 
-def _do_gather(params, ids, validate_indices=True, name=None):
+def _do_gather(params, ids, name=None):
   """Deals with doing gather differently for resource variables."""
   if isinstance(params, resource_variable_ops.ResourceVariable):
     return params.sparse_read(ids, name=name)
-  return array_ops.gather(
-      params, ids, name=name, validate_indices=validate_indices)
+  return array_ops.gather(params, ids, name=name)
 
 
 def embedding_lookup(params, ids, partition_strategy="mod", name=None,
-                     validate_indices=True, max_norm=None):
+                     validate_indices=True,  # pylint: disable=unused-argument
+                     max_norm=None):
   """Looks up `ids` in a list of embedding tensors.
 
   This function is used to perform parallel lookups on the list of
@@ -82,7 +82,10 @@ def embedding_lookup(params, ids, partition_strategy="mod", name=None,
       if `len(params) > 1`. Currently `"div"` and `"mod"` are supported. Default
       is `"mod"`.
     name: A name for the operation (optional).
-    validate_indices: Whether or not to validate gather indices.
+    validate_indices: DEPRECATED. If this operation is assigned to CPU, values
+      in `indices` are always validated to be within range.  If assigned to GPU,
+      out-of-bound indices result in safe but unspecified behavior, which may
+      include raising an error.
     max_norm: If not None, embedding values are l2-normalized to the value of
      max_norm.
 
@@ -92,7 +95,7 @@ def embedding_lookup(params, ids, partition_strategy="mod", name=None,
   Raises:
     ValueError: If `params` is empty.
   """
-  if params is None or params == []:  # pylint: disable=g-explicit-bool-comparison
+  if params in (None, (), []):
     raise ValueError("Need at least one param")
   if isinstance(params, variables.PartitionedVariable):
     params = list(params)  # Iterate to get the underlying Variables.
@@ -114,9 +117,7 @@ def embedding_lookup(params, ids, partition_strategy="mod", name=None,
       params = ops.convert_n_to_tensor_or_indexed_slices(params, name="params")
     if np == 1:
       with ops.colocate_with(params[0]):
-        return maybe_normalize(
-            _do_gather(
-                params[0], ids, validate_indices=validate_indices, name=name))
+        return maybe_normalize(_do_gather(params[0], ids, name=name))
     else:
       ids = ops.convert_to_tensor(ids, name="ids")
       flat_ids = array_ops.reshape(ids, [-1])
@@ -176,9 +177,7 @@ def embedding_lookup(params, ids, partition_strategy="mod", name=None,
       partitioned_result = []
       for p in xrange(np):
         with ops.colocate_with(params[p]):
-          partitioned_result.append(
-              _do_gather(params[p], gather_ids[p],
-                         validate_indices=validate_indices))
+          partitioned_result.append(_do_gather(params[p], gather_ids[p]))
       # Stitch these back together
       ret = data_flow_ops.dynamic_stitch(pindices, partitioned_result,
                                          name=name)
diff --git a/tensorflow/python/tools/inspect_checkpoint.py b/tensorflow/python/tools/inspect_checkpoint.py
index 6faf570de72..9942a5d9086 100644
--- a/tensorflow/python/tools/inspect_checkpoint.py
+++ b/tensorflow/python/tools/inspect_checkpoint.py
@@ -95,7 +95,7 @@ def parse_numpy_printoption(kv_str):
         "Setting '%s' from the command line is not supported." % k)
   try:
     v = (v_type(v_str) if v_type is not bool
-         else flags.BooleanParser().Parse(v_str))
+         else flags.BooleanParser().parse(v_str))
   except ValueError as e:
     raise argparse.ArgumentTypeError(e.message)
   np.set_printoptions(**{k: v})
diff --git a/tensorflow/python/training/coordinator.py b/tensorflow/python/training/coordinator.py
index 2863afb21e2..fea2f8240ee 100644
--- a/tensorflow/python/training/coordinator.py
+++ b/tensorflow/python/training/coordinator.py
@@ -106,7 +106,7 @@ class Coordinator(object):
   After a thread has called `coord.request_stop()` the other threads have a
   fixed time to stop, this is called the 'stop grace period' and defaults to 2
   minutes.  If any of the threads is still alive after the grace period expires
-  `coord.join()` raises a RuntimeException reporting the laggards.
+  `coord.join()` raises a RuntimeError reporting the laggards.
 
   ```python
   try:
@@ -117,7 +117,7 @@ class Coordinator(object):
     ...start thread N...(coord, ...)
     # Wait for all the threads to terminate, give them 10s grace period
     coord.join(threads, stop_grace_period_secs=10)
-  except RuntimeException:
+  except RuntimeError:
     ...one of the threads took more than 10s to stop after request_stop()
     ...was called.
   except Exception:
diff --git a/tensorflow/python/training/training.py b/tensorflow/python/training/training.py
index 28c0668d24e..f2bcc561753 100644
--- a/tensorflow/python/training/training.py
+++ b/tensorflow/python/training/training.py
@@ -68,6 +68,7 @@ See the @{$python/train} guide.
 @@LoggingTensorHook
 @@StopAtStepHook
 @@CheckpointSaverHook
+@@CheckpointSaverListener
 @@NewCheckpointReader
 @@StepCounterHook
 @@NanLossDuringTrainingError
@@ -128,6 +129,7 @@ from tensorflow.python.training.basic_session_run_hooks import SecondOrStepTimer
 from tensorflow.python.training.basic_session_run_hooks import LoggingTensorHook
 from tensorflow.python.training.basic_session_run_hooks import StopAtStepHook
 from tensorflow.python.training.basic_session_run_hooks import CheckpointSaverHook
+from tensorflow.python.training.basic_session_run_hooks import CheckpointSaverListener
 from tensorflow.python.training.basic_session_run_hooks import StepCounterHook
 from tensorflow.python.training.basic_session_run_hooks import NanLossDuringTrainingError
 from tensorflow.python.training.basic_session_run_hooks import NanTensorHook
diff --git a/tensorflow/tensorboard/BUILD b/tensorflow/tensorboard/BUILD
index ea409a93124..9772538524e 100644
--- a/tensorflow/tensorboard/BUILD
+++ b/tensorflow/tensorboard/BUILD
@@ -39,6 +39,8 @@ py_binary(
         "//tensorflow/python:platform",
         "//tensorflow/tensorboard/backend:application",
         "//tensorflow/tensorboard/backend/event_processing:event_file_inspector",
+        "//tensorflow/tensorboard/plugins/projector:projector_plugin",
+        "//tensorflow/tensorboard/plugins/text:text_plugin",
         "@org_pocoo_werkzeug//:werkzeug",
     ],
 )
diff --git a/tensorflow/tensorboard/backend/BUILD b/tensorflow/tensorboard/backend/BUILD
index 4e1db853744..d27a22a82b3 100644
--- a/tensorflow/tensorboard/backend/BUILD
+++ b/tensorflow/tensorboard/backend/BUILD
@@ -65,9 +65,6 @@ py_library(
         "//tensorflow/python:platform",
         "//tensorflow/tensorboard/backend/event_processing:event_accumulator",
         "//tensorflow/tensorboard/backend/event_processing:event_multiplexer",
-        "//tensorflow/tensorboard/plugins/debugger:debugger_plugin",
-        "//tensorflow/tensorboard/plugins/projector:projector_plugin",
-        "//tensorflow/tensorboard/plugins/text:text_plugin",
         "@org_pocoo_werkzeug//:werkzeug",
         "@six_archive//:six",
     ],
diff --git a/tensorflow/tensorboard/backend/application.py b/tensorflow/tensorboard/backend/application.py
index 974762822fc..3c8963e302f 100644
--- a/tensorflow/tensorboard/backend/application.py
+++ b/tensorflow/tensorboard/backend/application.py
@@ -43,9 +43,6 @@ from tensorflow.tensorboard.backend import http_util
 from tensorflow.tensorboard.backend import process_graph
 from tensorflow.tensorboard.backend.event_processing import event_accumulator
 from tensorflow.tensorboard.backend.event_processing import event_multiplexer
-from tensorflow.tensorboard.plugins.debugger import debugger_plugin
-from tensorflow.tensorboard.plugins.projector import projector_plugin
-from tensorflow.tensorboard.plugins.text import text_plugin
 
 
 DEFAULT_SIZE_GUIDANCE = {
@@ -97,18 +94,27 @@ class _OutputFormat(object):
   CSV = 'csv'
 
 
-def standard_tensorboard_wsgi(logdir, purge_orphaned_data, reload_interval):
-  """Construct a TensorBoardWSGIApp with standard plugins and multiplexer."""
+def standard_tensorboard_wsgi(
+    logdir,
+    purge_orphaned_data,
+    reload_interval,
+    plugins):
+  """Construct a TensorBoardWSGIApp with standard plugins and multiplexer.
+
+  Args:
+    logdir: The path to the directory containing events files.
+    purge_orphaned_data: Whether to purge orphaned data.
+    reload_interval: The interval at which the backend reloads more data in
+        seconds.
+    plugins: A list of plugins for TensorBoard to initialize.
+
+  Returns:
+    The new TensorBoard WSGI application.
+  """
   multiplexer = event_multiplexer.EventMultiplexer(
       size_guidance=DEFAULT_SIZE_GUIDANCE,
       purge_orphaned_data=purge_orphaned_data)
 
-  plugins = [
-      debugger_plugin.DebuggerPlugin(),
-      projector_plugin.ProjectorPlugin(),
-      text_plugin.TextPlugin(),
-  ]
-
   return TensorBoardWSGIApp(logdir, plugins, multiplexer, reload_interval)
 
 
diff --git a/tensorflow/tensorboard/backend/application_test.py b/tensorflow/tensorboard/backend/application_test.py
index 002709cd5b0..a5181401fa2 100644
--- a/tensorflow/tensorboard/backend/application_test.py
+++ b/tensorflow/tensorboard/backend/application_test.py
@@ -54,15 +54,18 @@ from tensorflow.tensorboard.plugins import base_plugin
 class FakePlugin(base_plugin.TBPlugin):
   """A plugin with no functionality."""
 
-  def __init__(self, plugin_name, is_active_value):
+  def __init__(self, plugin_name, is_active_value, routes_mapping):
     """Constructs a fake plugin.
 
     Args:
       plugin_name: The name of this plugin.
       is_active_value: Whether the plugin is active.
+      routes_mapping: A dictionary mapping from route (string URL path) to the
+        method called when a user issues a request to that route.
     """
     self.plugin_name = plugin_name
     self._is_active_value = is_active_value
+    self._routes_mapping = routes_mapping
 
   def get_plugin_apps(self, multiplexer, logdir):
     """Returns a mapping from routes to handlers offered by this plugin.
@@ -72,9 +75,9 @@ class FakePlugin(base_plugin.TBPlugin):
       logdir: The path to the directory containing logs.
 
     Returns:
-      An empty dict. This plugin offers no routes.
+      A dictionary mapping from routes to handlers offered by this plugin.
     """
-    return {}
+    return self._routes_mapping
 
   def is_active(self):
     """Returns whether this plugin is active.
@@ -97,8 +100,8 @@ class TensorboardServerTest(test.TestCase):
         size_guidance=application.DEFAULT_SIZE_GUIDANCE,
         purge_orphaned_data=True)
     plugins = [
-        FakePlugin(plugin_name='foo', is_active_value=True),
-        FakePlugin(plugin_name='bar', is_active_value=False)
+        FakePlugin(plugin_name='foo', is_active_value=True, routes_mapping={}),
+        FakePlugin(plugin_name='bar', is_active_value=False, routes_mapping={})
     ]
     app = application.TensorBoardWSGIApp(
         self.temp_dir, plugins, multiplexer, reload_interval=0)
@@ -476,10 +479,41 @@ class TensorBoardAssetsTest(test.TestCase):
   def testTagFound(self):
     tag = application.get_tensorboard_tag()
     self.assertTrue(tag)
-    app = application.standard_tensorboard_wsgi('', True, 60)
+    app = application.standard_tensorboard_wsgi('', True, 60, [])
     self.assertEqual(app.tag, tag)
 
 
+class TensorBoardPluginsTest(test.TestCase):
+
+  def testPluginsAdded(self):
+
+    def foo_handler():
+      pass
+
+    def bar_handler():
+      pass
+
+    plugins = [
+        FakePlugin(
+            plugin_name='foo',
+            is_active_value=True,
+            routes_mapping={'/foo_route': foo_handler}),
+        FakePlugin(
+            plugin_name='bar',
+            is_active_value=True,
+            routes_mapping={'/bar_route': bar_handler}),
+    ]
+
+    # The application should have added routes for both plugins.
+    app = application.standard_tensorboard_wsgi('', True, 60, plugins)
+
+    # The routes are prefixed with /data/plugin/[plugin name].
+    self.assertDictContainsSubset({
+        '/data/plugin/foo/foo_route': foo_handler,
+        '/data/plugin/bar/bar_route': bar_handler,
+    }, app.data_applications)
+
+
 class TensorboardSimpleServerConstructionTest(test.TestCase):
   """Tests that the default HTTP server is constructed without error.
 
@@ -533,14 +567,18 @@ class TensorBoardApplcationConstructionTest(test.TestCase):
     # Fails if there is an unnamed plugin
     with self.assertRaises(ValueError):
       # This plugin lacks a name.
-      plugins = [FakePlugin(plugin_name=None, is_active_value=True)]
+      plugins = [
+          FakePlugin(plugin_name=None, is_active_value=True, routes_mapping={})
+      ]
       application.TensorBoardWSGIApp(logdir, plugins, multiplexer, 0)
 
     # Fails if there are two plugins with same name
     with self.assertRaises(ValueError):
       plugins = [
-          FakePlugin(plugin_name='foo', is_active_value=True),
-          FakePlugin(plugin_name='foo', is_active_value=True),
+          FakePlugin(
+              plugin_name='foo', is_active_value=True, routes_mapping={}),
+          FakePlugin(
+              plugin_name='foo', is_active_value=True, routes_mapping={}),
       ]
       application.TensorBoardWSGIApp(logdir, plugins, multiplexer, 0)
 
diff --git a/tensorflow/tensorboard/components/tf_audio_dashboard/tf-audio-dashboard.html b/tensorflow/tensorboard/components/tf_audio_dashboard/tf-audio-dashboard.html
index ad879210d6f..2088cde2787 100644
--- a/tensorflow/tensorboard/components/tf_audio_dashboard/tf-audio-dashboard.html
+++ b/tensorflow/tensorboard/components/tf_audio_dashboard/tf-audio-dashboard.html
@@ -59,12 +59,16 @@ tf-audio-dashboard displays a dashboard that loads audio from a TensorFlow run.
     </style>
   </template>
   <script>
-    Polymer({
+    TF.Dashboard.TfAudioDashboard = Polymer({
       is: "tf-audio-dashboard",
+      factoryImpl: function(backend) {
+        this.backend = backend;
+      },
       properties: {
         dataType: {value: "audio"},
       },
       behaviors: [
+        TF.Dashboard.DashboardBehavior("audio"),
         TF.Dashboard.ReloadBehavior("tf-audio-loader"),
         TF.Backend.Behavior
       ],
diff --git a/tensorflow/tensorboard/components/tf_dashboard_common/BUILD b/tensorflow/tensorboard/components/tf_dashboard_common/BUILD
index 0fb9f70eb97..fd43970fc06 100644
--- a/tensorflow/tensorboard/components/tf_dashboard_common/BUILD
+++ b/tensorflow/tensorboard/components/tf_dashboard_common/BUILD
@@ -41,6 +41,7 @@ tensorboard_typescript_genrule(
     name = "ts",
     srcs = [
         "categorizer.ts",
+        "dashboard-behavior.ts",
         "reload-behavior.ts",
     ],
     typings = [
@@ -89,6 +90,7 @@ tensorboard_ts_library(
     name = "legacy_ts",
     srcs = [
         "categorizer.ts",
+        "dashboard-behavior.ts",
         "reload-behavior.ts",
     ],
     deps = [
diff --git a/tensorflow/tensorboard/components/tf_dashboard_common/dashboard-behavior.ts b/tensorflow/tensorboard/components/tf_dashboard_common/dashboard-behavior.ts
new file mode 100644
index 00000000000..269a62ccf97
--- /dev/null
+++ b/tensorflow/tensorboard/components/tf_dashboard_common/dashboard-behavior.ts
@@ -0,0 +1,40 @@
+/* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+module TF.Dashboard {
+  /**
+   * A behavior that TensorBoard dashboards must implement. This behavior serves
+   * the purpose of an interface.
+   */
+  export function DashboardBehavior(dashboardName) {
+    return {
+      properties: {
+        name: {
+          type: String,
+          value: dashboardName,
+          readOnly: true,
+        },
+      },
+      // This method is called when the dashboard reloads, either when the
+      // dashboard is first visited, periodically reloaded, or manually reloaded
+      // via the user clicking the button. Note that dashboard custom elements
+      // that use TF.Dashboard.ReloadBehavior already implement a reload method.
+      reload() {
+        throw Error(
+            'The ' + dashboardName + ' dashboard does not implement reload.');
+      },
+    };
+  }
+}
diff --git a/tensorflow/tensorboard/components/tf_dashboard_common/tf-dashboard.html b/tensorflow/tensorboard/components/tf_dashboard_common/tf-dashboard.html
index 4c7c91d1713..9e2f6b9589b 100644
--- a/tensorflow/tensorboard/components/tf_dashboard_common/tf-dashboard.html
+++ b/tensorflow/tensorboard/components/tf_dashboard_common/tf-dashboard.html
@@ -22,4 +22,5 @@ limitations under the License.
 <link rel="import" href="tf-downloader.html">
 <link rel="import" href="tf-no-data-warning.html">
 
+<script src="dashboard-behavior.js"></script>
 <script src="reload-behavior.js"></script>
diff --git a/tensorflow/tensorboard/components/tf_dashboard_common/tf-run-selector.html b/tensorflow/tensorboard/components/tf_dashboard_common/tf-run-selector.html
index 8f2ea402e89..81a72793b96 100644
--- a/tensorflow/tensorboard/components/tf_dashboard_common/tf-run-selector.html
+++ b/tensorflow/tensorboard/components/tf_dashboard_common/tf-run-selector.html
@@ -139,17 +139,9 @@ Properties out:
       },
     },
     observers: [
+      "_onBackendUpdate(backend)",
       "_logdirSet(logdir)",
     ],
-    ready: function() {
-      // Populate the logdir.
-      this.backend.logdir().then(logdirObject => {
-        this.set('logdir', logdirObject.logdir);
-      }).catch(e => {
-        // Fetching the logdir failed. Prevent the exception from logging to
-        // console. The console already logs a 404 network event.
-      });
-    },
     _toggleAll: function() {
       this.$.multiCheckbox.toggleAll();
     },
@@ -157,8 +149,21 @@ Properties out:
     _breakString: function(originalString) {
       return originalString.replace(/([\/=\-_,])/g, "$1<wbr>");
     },
+    _onBackendUpdate: function(backend) {
+      if (backend === undefined) {
+        return;
+      }
+
+      // When the backend is set, the selector can request the logdir.
+      backend.logdir().then(logdirObject => {
+        this.set('logdir', logdirObject.logdir);
+      }).catch(e => {
+        // Fetching the logdir failed. Prevent the exception from logging to
+        // console. The console already logs a 404 network event.
+      });
+    },
     _logdirSet: function(logdir) {
-      if (!logdir) {
+      if (logdir === undefined) {
         // The logdir has not been set yet.
         return;
       }
diff --git a/tensorflow/tensorboard/components/tf_distribution_dashboard/tf-distribution-dashboard.html b/tensorflow/tensorboard/components/tf_distribution_dashboard/tf-distribution-dashboard.html
index 2da848bd99e..58ae396cb45 100644
--- a/tensorflow/tensorboard/components/tf_distribution_dashboard/tf-distribution-dashboard.html
+++ b/tensorflow/tensorboard/components/tf_distribution_dashboard/tf-distribution-dashboard.html
@@ -101,9 +101,13 @@ contains vz-distribution-charts embedded inside tf-panes-helper's.
   </template>
 
   <script>
-    Polymer({
+    TF.Dashboard.TfDistributionDashboard = Polymer({
       is: "tf-distribution-dashboard",
+      factoryImpl: function(backend) {
+        this.backend = backend;
+      },
       behaviors: [
+        TF.Dashboard.DashboardBehavior("distributions"),
         TF.Dashboard.ReloadBehavior("tf-chart-scaffold"),
         TF.Backend.Behavior,
       ],
diff --git a/tensorflow/tensorboard/components/tf_graph/tf-graph-scene.html b/tensorflow/tensorboard/components/tf_graph/tf-graph-scene.html
index 09513699c30..9dc2a361e25 100644
--- a/tensorflow/tensorboard/components/tf_graph/tf-graph-scene.html
+++ b/tensorflow/tensorboard/components/tf_graph/tf-graph-scene.html
@@ -619,6 +619,18 @@ Polymer({
     renderHierarchy: Object,
     name: String,
     colorBy: String,
+
+    // For each render hierarchy, we only fit it to the viewport once (when the scene is attached to
+    // the DOM). We do not fit the hierarchy again (unless the user clicks the reset button). For
+    // instance, if the user enters a certain view in the graph, switches to another dashboard, and
+    // returns to the graph dashboard, the user expects the previous view. These properties enable
+    // that behavior.
+
+    /** Whether the scene has fit the current render hierarchy (to the viewport) at least once. */
+    _hasRenderHierarchyBeenFitOnce: Boolean,
+    /** Whether this scene element is currently attached to a parent element. */
+    _isAttached: Boolean,
+
     /** @type {d3_zoom} d3 zoom object */
     _zoom: Object,
     highlightedNode: {
@@ -723,7 +735,10 @@ Polymer({
   },
   observers: [
     '_colorByChanged(colorBy)',
-    '_buildAndFit(renderHierarchy)',
+    '_renderHierarchyChanged(renderHierarchy)',
+    // Animation and fitting must come after the observer for the hierarchy changing because we must
+    // first build the render hierarchy.
+    '_animateAndFit(_isAttached, renderHierarchy)',
     '_updateHealthPills(nodeNamesToHealthPills, healthPillStepIndex)',
   ],
   getNode: function(nodeName) {
@@ -826,9 +841,24 @@ Polymer({
         tf.graph.layout.PARAMS.minimap.size,
         tf.graph.layout.PARAMS.subscene.meta.labelHeight);
   },
-  _buildAndFit: function(renderHierarchy) {
+  attached: function() {
+    this.set('_isAttached', true);
+  },
+  detached: function() {
+    this.set('_isAttached', false);
+  },
+  _renderHierarchyChanged: function(renderHierarchy) {
+    this._hasRenderHierarchyBeenFitOnce = false;
     this._resetState();
     this._build(renderHierarchy);
+  },
+  _animateAndFit: function(isAttached, renderHierarchy) {
+    if (this._hasRenderHierarchyBeenFitOnce || !isAttached) {
+      // Do not animate and fit if the scene has already fitted this render hierarchy once. Or if
+      // the graph dashboard is not attached (in which case the scene lacks DOM info for fitting).
+      return;
+    }
+
     // Fit to screen after the graph is done animating.
     setTimeout(this.fit.bind(this), tf.graph.layout.PARAMS.animation.duration);
   },
@@ -881,6 +911,7 @@ Polymer({
     }
   },
   fit: function() {
+    this._hasRenderHierarchyBeenFitOnce = true;
     tf.graph.scene.fit(this.$.svg, this.$.root, this._zoom, function() {
       this._zoomed = false;
     }.bind(this));
diff --git a/tensorflow/tensorboard/components/tf_graph_dashboard/tf-graph-dashboard.html b/tensorflow/tensorboard/components/tf_graph_dashboard/tf-graph-dashboard.html
index d62e4ccedc2..12f3d948d23 100644
--- a/tensorflow/tensorboard/components/tf_graph_dashboard/tf-graph-dashboard.html
+++ b/tensorflow/tensorboard/components/tf_graph_dashboard/tf-graph-dashboard.html
@@ -104,9 +104,14 @@ out-hierarchy-params="{{_hierarchyParams}}"
 
 <script>
 (function() {
-Polymer({
+TF.Dashboard.TfGraphDashboard = Polymer({
   is: 'tf-graph-dashboard',
+  factoryImpl: function(backend, debuggerDataEnabled) {
+    this.backend = backend;
+    this.debuggerDataEnabled = debuggerDataEnabled;
+  },
   behaviors: [
+    TF.Dashboard.DashboardBehavior("graphs"),
     TF.Dashboard.ReloadBehavior("tf-graph-dashboard"),
     TF.Backend.Behavior,
   ],
diff --git a/tensorflow/tensorboard/components/tf_histogram_dashboard/tf-histogram-dashboard.html b/tensorflow/tensorboard/components/tf_histogram_dashboard/tf-histogram-dashboard.html
index f8c9cc4537f..dd433982d1f 100644
--- a/tensorflow/tensorboard/components/tf_histogram_dashboard/tf-histogram-dashboard.html
+++ b/tensorflow/tensorboard/components/tf_histogram_dashboard/tf-histogram-dashboard.html
@@ -121,9 +121,13 @@ contains vz-histogram-timeseries embedded inside tf-panes-helper's.
   </template>
 
   <script>
-    Polymer({
+    TF.Dashboard.TfHistogramDashboard = Polymer({
       is: "tf-histogram-dashboard",
+      factoryImpl: function(backend) {
+        this.backend = backend;
+      },
       behaviors: [
+        TF.Dashboard.DashboardBehavior("histograms"),
         TF.Dashboard.ReloadBehavior("tf-chart-scaffold"),
         TF.Backend.Behavior,
       ],
diff --git a/tensorflow/tensorboard/components/tf_image_dashboard/tf-image-dashboard.html b/tensorflow/tensorboard/components/tf_image_dashboard/tf-image-dashboard.html
index 19c272a4683..0200b65030c 100644
--- a/tensorflow/tensorboard/components/tf_image_dashboard/tf-image-dashboard.html
+++ b/tensorflow/tensorboard/components/tf_image_dashboard/tf-image-dashboard.html
@@ -106,8 +106,11 @@ tf-image-dashboard displays a dashboard that loads images from a TensorFlow run.
     </style>
   </template>
   <script>
-    Polymer({
+    TF.Dashboard.TfImageDashboard = Polymer({
       is: "tf-image-dashboard",
+      factoryImpl: function(backend) {
+        this.backend = backend;
+      },
       properties: {
         backend: Object,
         dataType: {
@@ -116,8 +119,9 @@ tf-image-dashboard displays a dashboard that loads images from a TensorFlow run.
         },
       },
       behaviors: [
-          TF.Dashboard.ReloadBehavior("tf-chart-scaffold"),
-          TF.Backend.Behavior,
+        TF.Dashboard.DashboardBehavior("images"),
+        TF.Dashboard.ReloadBehavior("tf-chart-scaffold"),
+        TF.Backend.Behavior,
       ],
       attached: function() {
         this.async(function() {
diff --git a/tensorflow/tensorboard/components/tf_scalar_dashboard/tf-scalar-dashboard.html b/tensorflow/tensorboard/components/tf_scalar_dashboard/tf-scalar-dashboard.html
index 641573366a6..723a01d0e6a 100644
--- a/tensorflow/tensorboard/components/tf_scalar_dashboard/tf-scalar-dashboard.html
+++ b/tensorflow/tensorboard/components/tf_scalar_dashboard/tf-scalar-dashboard.html
@@ -190,9 +190,14 @@ contains vz-line-charts embedded inside tf-panes-helper's.
   </template>
 
   <script>
-    Polymer({
+    TF.Dashboard.TfScalarDashboard = Polymer({
       is: "tf-scalar-dashboard",
+      factoryImpl: function(backend, router) {
+        this.backend = backend;
+        this.router = router;
+      },
       behaviors: [
+        TF.Dashboard.DashboardBehavior("scalars"),
         TF.Dashboard.ReloadBehavior("tf-chart-scaffold"),
         TF.Backend.Behavior,
       ],
diff --git a/tensorflow/tensorboard/components/tf_tensorboard/tf-tensorboard.html b/tensorflow/tensorboard/components/tf_tensorboard/tf-tensorboard.html
index b5b2e2d5a86..a1925c1f6b1 100644
--- a/tensorflow/tensorboard/components/tf_tensorboard/tf-tensorboard.html
+++ b/tensorflow/tensorboard/components/tf_tensorboard/tf-tensorboard.html
@@ -57,9 +57,9 @@ allows the user to toggle between various dashboards.
         <div id="toolbar-content">
           <div class="toolbar-title">TensorBoard</div>
           <paper-tabs selected="{{modeIndex}}" noink class="tabs" id="tabs">
-            <template is="dom-repeat" items="[[tabs]]">
-              <template is="dom-if" if="[[_isTabEnabled(item)]]">
-                <paper-tab data-mode="[[item]]">[[item]]</paper-tab>
+            <template is="dom-repeat" items="[[_dashboards]]">
+              <template is="dom-if" if="[[_isTabEnabled(item.name)]]">
+                <paper-tab data-mode="[[item.name]]">[[item.name]]</paper-tab>
               </template>
             </template>
           </paper-tabs>
@@ -82,67 +82,7 @@ allows the user to toggle between various dashboards.
         </div>
       </paper-toolbar>
 
-      <div id="content" class="fit">
-        <content id="injected-overview"></content>
-
-        <template is="dom-if" if="[[_modeIsScalars(mode)]]">
-          <tf-scalar-dashboard
-            id="scalars"
-            backend="[[_backend]]"
-            router="[[router]]"
-          ></tf-scalar-dashboard>
-        </template>
-
-        <template is="dom-if" if="[[_modeIsImages(mode)]]">
-          <tf-image-dashboard
-            id="images"
-            backend="[[_backend]]"
-          ></tf-image-dashboard>
-        </template>
-
-        <template is="dom-if" if="[[_modeIsAudio(mode)]]">
-          <tf-audio-dashboard
-            id="audio"
-            backend="[[_backend]]"
-          ></tf-audio-dashboard>
-        </template>
-
-        <template is="dom-if" if="[[_modeIsGraphs(mode)]]">
-          <tf-graph-dashboard
-            id="graphs"
-            backend="[[_backend]]"
-            debugger-data-enabled="[[_debuggerDataEnabled]]"
-          ></tf-graph-dashboard>
-        </template>
-
-        <template is="dom-if" if="[[_modeIsDistributions(mode)]]">
-          <tf-distribution-dashboard
-            id="distributions"
-            backend="[[_backend]]"
-          ></tf-distribution-dashboard>
-        </template>
-
-        <template is="dom-if" if="[[_modeIsHistograms(mode)]]">
-          <tf-histogram-dashboard
-            id="histograms"
-            backend="[[_backend]]"
-          ></tf-histogram-dashboard>
-        </template>
-
-        <template is="dom-if" if="[[_modeIsEmbeddings(mode)]]">
-          <vz-projector-dashboard
-            id="projector"
-            route-prefix="/data/plugin/projector">
-          </vz-projector-dashboard>
-        </template>
-
-        <template is="dom-if" if="[[_modeIsText(mode)]]">
-          <tf-text-dashboard
-            id="text"
-            backend="[[_backend]]">
-          </tf-text-dashboard>
-        </template>
-      </div>
+      <div id="content" class="fit"></div>
     </paper-header-panel>
 
     <style>
@@ -233,16 +173,21 @@ allows the user to toggle between various dashboards.
             return match && match.length == 1;
           },
         },
+        _dashboards: {
+          type: Array,
+          computed: "_makeDashboardList(_backend, router, _debuggerDataEnabled)",
+        },
+        // Maps dashboard name to dashboard object.
+        _dashboardMapping: {
+          type: Object,
+          computed: "_makeDashboardMapping(_dashboards)",
+        },
         // Which tab is selected (scalars, graph, images etc).
         mode: {
           type: String,
           computed: '_getModeFromIndex(modeIndex)',
           notify: true,
-        },
-        tabs: {
-          type: Array,
-          readOnly: true,
-          value: TF.Globals.TABS,
+          observer: '_modeChanged',
         },
         // If this is set to a string, TensorBoard will switch to "demo mode"
         // and attempt to load serialized json data from that directory. You can
@@ -267,7 +212,7 @@ allows the user to toggle between various dashboards.
         return true;
       },
       _getModeFromIndex: function(modeIndex) {
-        var mode = this.tabs[modeIndex];
+        var mode = this._dashboards[modeIndex].name;
         TF.URIStorage.setString(TF.URIStorage.TAB, mode);
         return mode;
       },
@@ -279,34 +224,10 @@ allows the user to toggle between various dashboards.
         return new TF.Backend.Backend(router);
       },
       _isReloadDisabled: function(mode) {
-        return !this._debuggerDataEnabled && this._modeIsGraphs(mode);
-      },
-      _modeIsScalars: function(mode) {
-        return mode === "scalars";
-      },
-      _modeIsImages: function(mode) {
-        return mode === "images";
-      },
-      _modeIsAudio: function(mode) {
-        return mode === "audio";
-      },
-      _modeIsGraphs: function(mode) {
-        return mode === "graphs";
-      },
-      _modeIsEmbeddings: function(mode) {
-        return mode === "embeddings";
-      },
-      _modeIsDistributions: function(mode) {
-        return mode === "distributions";
-      },
-      _modeIsHistograms: function(mode) {
-        return mode === "histograms";
-      },
-      _modeIsText: function(mode) {
-        return mode === "text";
+        return !this._debuggerDataEnabled && mode == 'graphs';
       },
       selectedDashboard: function() {
-        var dashboard = this.$$("#" + this.mode);
+        var dashboard = this._dashboardMapping[this.mode];
         if (dashboard == null) {
           throw new Error(`Unable to find dashboard for mode: ${this.mode}`);
         }
@@ -320,24 +241,67 @@ allows the user to toggle between various dashboards.
           this._getModeFromHash();
         }.bind(this));
       },
+      _makeDashboardList: function(backend, router, debuggerDataEnabled) {
+        if (!backend || !router) {
+          // The dashboards require these entities. We are not ready to construct dashboards.
+          return null;
+        }
+
+        return [
+          new TF.Dashboard.TfScalarDashboard(backend, router),
+          new TF.Dashboard.TfImageDashboard(backend),
+          new TF.Dashboard.TfAudioDashboard(backend),
+          new TF.Dashboard.TfGraphDashboard(backend, debuggerDataEnabled),
+          new TF.Dashboard.TfDistributionDashboard(backend),
+          new TF.Dashboard.TfHistogramDashboard(backend),
+          new TF.Dashboard.VzProjectorDashboard('/data/plugin/projector'),
+          new TF.Dashboard.TfTextDashboard(backend),
+        ];
+      },
+      _makeDashboardMapping: function(dashboards) {
+        if (!dashboards) {
+          return null;
+        }
+
+        let mapping = {};
+        dashboards.forEach(function(dashboard) {
+          mapping[dashboard.name] = dashboard;
+        });
+        return mapping;
+      },
       _getModeFromHash: function() {
         var tabName = TF.URIStorage.getString(TF.URIStorage.TAB);
-        var modeIndex = this.tabs.indexOf(tabName);
-        if (modeIndex == -1 && this.modeIndex == null) {
+        var modeIndex;
+        for (var i = 0; i < this._dashboards.length; i++) {
+          if (this._dashboards[i].name == tabName) {
+            modeIndex = i;
+            break;
+          }
+        }
+
+        if (modeIndex === undefined && this.modeIndex == null) {
           // Select the first tab as default.
           this.set('modeIndex', 0);
         }
-        if (modeIndex != -1 && modeIndex != this.modeIndex) {
+        if (modeIndex !== undefined && modeIndex != this.modeIndex) {
           this.set('modeIndex', modeIndex);
         }
       },
+      _modeChanged: function(mode) {
+        let currentDashboard = this.$.content.firstChild;
+        if (currentDashboard) {
+          this.$.content.removeChild(currentDashboard);
+        }
+
+        if (!mode || !this._dashboardMapping) {
+          return;
+        }
+
+        // Append the new dashboard.
+        const newDashboard = this.selectedDashboard();
+        this.$.content.appendChild(newDashboard);
+      },
       reload: function() {
-        if (this._modeIsEmbeddings(this.mode)) {
-          return;
-        }
-        if (!this._debuggerDataEnabled && this._modeIsGraphs(this.mode)) {
-          return;
-        }
         this.selectedDashboard().reload();
       },
       openSettings: function() {
diff --git a/tensorflow/tensorboard/components/tf_text_dashboard/tf-text-dashboard.html b/tensorflow/tensorboard/components/tf_text_dashboard/tf-text-dashboard.html
index d39c890a7ae..d771c9821ca 100644
--- a/tensorflow/tensorboard/components/tf_text_dashboard/tf-text-dashboard.html
+++ b/tensorflow/tensorboard/components/tf_text_dashboard/tf-text-dashboard.html
@@ -82,8 +82,11 @@ tf-text-dashboard displays a dashboard that loads texts from a TensorFlow run.
     </style>
   </template>
   <script>
-    Polymer({
+    TF.Dashboard.TfTextDashboard = Polymer({
       is: "tf-text-dashboard",
+      factoryImpl: function(backend) {
+        this.backend = backend;
+      },
       properties: {
         backend: Object,
         dataType: {
@@ -92,15 +95,15 @@ tf-text-dashboard displays a dashboard that loads texts from a TensorFlow run.
         },
       },
       behaviors: [
-          TF.Dashboard.ReloadBehavior("tf-chart-scaffold"),
-          TF.Backend.Behavior,
+        TF.Dashboard.DashboardBehavior("text"),
+        TF.Dashboard.ReloadBehavior("tf-chart-scaffold"),
+        TF.Backend.Behavior,
       ],
       attached: function() {
         this.async(function() {
           this.fire("rendered");
         });
       },
-
     });
   </script>
 </dom-module>
diff --git a/tensorflow/tensorboard/components/vz_projector/vz-projector-dashboard.html b/tensorflow/tensorboard/components/vz_projector/vz-projector-dashboard.html
index b641bb0f293..a641a54e418 100644
--- a/tensorflow/tensorboard/components/vz_projector/vz-projector-dashboard.html
+++ b/tensorflow/tensorboard/components/vz_projector/vz-projector-dashboard.html
@@ -16,6 +16,7 @@ limitations under the License.
 -->
 
 <link rel="import" href="../polymer/polymer.html">
+<link rel="import" href="../tf-dashboard-common/tf-dashboard.html">
 <link rel="import" href="../tf-dashboard-common/tf-no-data-warning.html">
 <link rel="import" href="vz-projector.html">
 
@@ -37,18 +38,33 @@ limitations under the License.
 </template>
 <script>
 (function() {
-Polymer({
+TF.Dashboard.VzProjectorDashboard = Polymer({
   is: 'vz-projector-dashboard',
+  factoryImpl: function(routePrefix) {
+    this.routePrefix = routePrefix;
+  },
   properties: {
     dataNotFound: Boolean,
     routePrefix: String
   },
-  ready() {
-    var self = this;
-    d3.json(this.routePrefix + '/runs', function(err, runs) {
-      self.dataNotFound = (runs.length === 0);
+  behaviors: [
+    TF.Dashboard.DashboardBehavior("embeddings"),
+  ],
+  observers: [
+    "_routePrefixSet(routePrefix)",
+  ],
+  reload: function() {
+    // Do not reload the embedding projector. Reloading could take a long time.
+  },
+  _routePrefixSet: function(routePrefix) {
+    if (routePrefix === undefined) {
+      // The route prefix has not been set yet.
+      return;
+    }
+    d3.json(routePrefix + '/runs', (err, runs) => {
+      this.set('dataNotFound', runs.length === 0);
     });
-  }
+  },
 });
 })();
 </script>
diff --git a/tensorflow/tensorboard/plugins/debugger/BUILD b/tensorflow/tensorboard/plugins/debugger/BUILD
deleted file mode 100644
index 38aa719b9b9..00000000000
--- a/tensorflow/tensorboard/plugins/debugger/BUILD
+++ /dev/null
@@ -1,55 +0,0 @@
-# Description:
-# TensorBoard plugin for interacting with tfdbg, the TensorFlow debugger
-
-package(default_visibility = ["//tensorflow:internal"])
-
-licenses(["notice"])  # Apache 2.0
-
-exports_files(["LICENSE"])
-
-load("//tensorflow:tensorflow.bzl", "py_test")
-
-## TensorFlow Debugger Plugiin ##
-py_library(
-    name = "debugger_plugin",
-    srcs = ["debugger_plugin.py"],
-    srcs_version = "PY2AND3",
-    deps = [
-        "//tensorflow/python:framework",
-        "//tensorflow/python:platform",
-        "//tensorflow/tensorboard/backend:http_util",
-        "//tensorflow/tensorboard/backend/event_processing:event_accumulator",
-        "//tensorflow/tensorboard/backend/event_processing:event_file_loader",
-        "//tensorflow/tensorboard/plugins:base_plugin",
-    ],
-)
-
-py_test(
-    name = "debugger_plugin_test",
-    size = "small",
-    srcs = ["debugger_plugin_test.py"],
-    main = "debugger_plugin_test.py",
-    srcs_version = "PY2AND3",
-    tags = ["no_pip"],
-    deps = [
-        ":debugger_plugin",
-        "//tensorflow/core:protos_all_py",
-        "//tensorflow/python:client_testlib",
-        "//tensorflow/python:pywrap_tensorflow",
-        "//tensorflow/python:util",
-        "//tensorflow/tensorboard/backend:application",
-        "//tensorflow/tensorboard/backend/event_processing:event_multiplexer",
-        "//third_party/py/numpy",
-        "@org_pocoo_werkzeug//:werkzeug",
-    ],
-)
-
-filegroup(
-    name = "all_files",
-    srcs = glob(
-        [
-            "*",
-        ],
-    ),
-    visibility = ["//tensorflow:__subpackages__"],
-)
diff --git a/tensorflow/tensorboard/plugins/debugger/debugger_plugin.py b/tensorflow/tensorboard/plugins/debugger/debugger_plugin.py
deleted file mode 100644
index 5d34bb91dbd..00000000000
--- a/tensorflow/tensorboard/plugins/debugger/debugger_plugin.py
+++ /dev/null
@@ -1,355 +0,0 @@
-# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-"""The plugin for serving data from a TensorFlow debugger."""
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import collections
-import glob
-import json
-import os
-import re
-
-from werkzeug import wrappers
-
-from tensorflow.python.framework import tensor_util
-from tensorflow.python.platform import tf_logging as logging
-from tensorflow.tensorboard.backend import http_util
-from tensorflow.tensorboard.backend.event_processing import event_accumulator
-from tensorflow.tensorboard.backend.event_processing import event_file_loader
-from tensorflow.tensorboard.plugins import base_plugin
-
-# The prefix of routes provided by this plugin.
-_PLUGIN_PREFIX_ROUTE = 'debugger'
-
-# HTTP routes.
-_HEALTH_PILLS_ROUTE = '/health_pills'
-
-# The POST key of HEALTH_PILLS_ROUTE for a JSON list of node names.
-_NODE_NAMES_POST_KEY = 'node_names'
-
-# The POST key of HEALTH_PILLS_ROUTE for the run to retrieve health pills for.
-_RUN_POST_KEY = 'run'
-
-# The default run to retrieve health pills for.
-_DEFAULT_RUN = '.'
-
-# The POST key of HEALTH_PILLS_ROUTE for the specific step to retrieve health
-# pills for.
-_STEP_POST_KEY = 'step'
-
-# A glob pattern for files containing debugger-related events.
-_DEBUGGER_EVENTS_GLOB_PATTERN = 'events.debugger*'
-
-
-class DebuggerPlugin(base_plugin.TBPlugin):
-  """TensorFlow Debugger plugin. Receives requests for debugger-related data.
-
-  That data could include health pills, which unveil the status of tensor
-  values.
-  """
-
-  plugin_name = _PLUGIN_PREFIX_ROUTE
-
-  def get_plugin_apps(self, multiplexer, logdir):
-    """Obtains a mapping between routes and handlers. Stores the logdir.
-
-    Args:
-      multiplexer: The EventMultiplexer that provides TB data.
-      logdir: The logdir string - the directory of events files.
-
-    Returns:
-      A mapping between routes and handlers (functions that respond to
-      requests).
-    """
-    self._event_multiplexer = multiplexer
-    self._logdir = logdir
-    return {
-        _HEALTH_PILLS_ROUTE: self._serve_health_pills_handler,
-    }
-
-  def is_active(self):
-    """Determines whether this plugin is active.
-
-    This plugin is active if any health pills information is present for any
-    run. This method must be called only after get_plugin_apps has been called.
-
-    Returns:
-      A boolean. Whether this plugin is active.
-    """
-    for run_name in self._event_multiplexer.Runs():
-      if self._event_multiplexer.GetOpsWithHealthPills(run_name):
-        return True
-
-    return False
-
-  @wrappers.Request.application
-  def _serve_health_pills_handler(self, request):
-    """A (wrapped) werkzeug handler for serving health pills.
-
-    Accepts POST requests and responds with health pills. The request accepts
-    several POST parameters:
-
-      node_names: (required string) A JSON-ified list of node names for which
-          the client would like to request health pills.
-      run: (optional string) The run to retrieve health pills for. Defaults to
-          '.'. This data is sent via POST (not GET) since URL length is limited.
-      step: (optional integer): The session run step for which to
-          retrieve health pills. If provided, the handler reads the health pills
-          of that step from disk (which is slow) and produces a response with
-          only health pills at that step. If not provided, the handler returns a
-          response with health pills at all steps sampled by the event
-          multiplexer (the fast path). The motivation here is that, sometimes,
-          one desires to examine health pills at a specific step (to say find
-          the first step that causes a model to blow up with NaNs).
-          get_plugin_apps must be called before this slower feature is used
-          because that method passes the logdir (directory path) to this plugin.
-
-    This handler responds with a JSON-ified object mapping from node names to a
-    list (of size 1) of health pill event objects, each of which has these
-    properties.
-
-    {
-        'wall_time': float,
-        'step': int,
-        'node_name': string,
-        'output_slot': int,
-        # A list of 12 floats that summarizes the elements of the tensor.
-        'value': float[],
-    }
-
-    Node names for which there are no health pills to be found are excluded from
-    the mapping.
-
-    Args:
-      request: The request issued by the client for health pills.
-
-    Returns:
-      A werkzeug BaseResponse object.
-    """
-    if request.method != 'POST':
-      logging.error(
-          '%s requests are forbidden by the debugger plugin.', request.method)
-      return wrappers.Response(status=405)
-
-    if _NODE_NAMES_POST_KEY not in request.form:
-      logging.error(
-          'The %r POST key was not found in the request for health pills.',
-          _NODE_NAMES_POST_KEY)
-      return wrappers.Response(status=400)
-
-    jsonified_node_names = request.form[_NODE_NAMES_POST_KEY]
-    try:
-      node_names = json.loads(jsonified_node_names)
-    except Exception as e:  # pylint: disable=broad-except
-      # Different JSON libs raise different exceptions, so we just do a
-      # catch-all here. This problem is complicated by how Tensorboard might be
-      # run in many different environments, as it is open-source.
-      logging.error('Could not decode node name JSON string %r: %s',
-                    jsonified_node_names, e)
-      return wrappers.Response(status=400)
-
-    if not isinstance(node_names, list):
-      logging.error('%r is not a JSON list of node names:',
-                    jsonified_node_names)
-      return wrappers.Response(status=400)
-
-    run = request.form.get(_RUN_POST_KEY, _DEFAULT_RUN)
-    step_string = request.form.get(_STEP_POST_KEY, None)
-    if step_string is None:
-      # Use all steps sampled by the event multiplexer (Relatively fast).
-      mapping = self._obtain_sampled_health_pills(run, node_names)
-    else:
-      # Read disk to obtain the health pills for that step (Relatively slow).
-      # Make sure that the directory for the run exists.
-      # Determine the directory of events file to read.
-      events_directory = self._logdir
-      if run != _DEFAULT_RUN:
-        # Use the directory for the specific run.
-        events_directory = os.path.join(events_directory, run)
-
-      step = int(step_string)
-      try:
-        mapping = self._obtain_health_pills_at_step(
-            events_directory, node_names, step)
-      except IOError as error:
-        logging.error(
-            'Error retrieving health pills for step %d: %s', step, error)
-        return wrappers.Response(status=404)
-
-    # Convert event_accumulator.HealthPillEvents to JSON-able dicts.
-    jsonable_mapping = {}
-    for node_name, events in mapping.items():
-      jsonable_mapping[node_name] = [e._asdict() for e in events]
-    return http_util.Respond(request, jsonable_mapping, 'application/json')
-
-  def _obtain_sampled_health_pills(self, run, node_names):
-    """Obtains the health pills for a run sampled by the event multiplexer.
-
-    This is much faster than the alternative path of reading health pills from
-    disk.
-
-    Args:
-      run: The run to fetch health pills for.
-      node_names: A list of node names for which to retrieve health pills.
-
-    Returns:
-      A dictionary mapping from node name to a list of
-      event_accumulator.HealthPillEvents.
-    """
-    mapping = {}
-    for node_name in node_names:
-      try:
-        mapping[node_name] = self._event_multiplexer.HealthPills(run, node_name)
-      except KeyError:
-        logging.info('No health pills found for node %r.', node_name)
-        continue
-
-    return mapping
-
-  def _obtain_health_pills_at_step(self, events_directory, node_names, step):
-    """Reads disk to obtain the health pills for a run at a specific step.
-
-    This could be much slower than the alternative path of just returning all
-    health pills sampled by the event multiplexer. It could take tens of minutes
-    to complete this call for large graphs for big step values (in the
-    thousands).
-
-    Args:
-      events_directory: The directory containing events for the desired run.
-      node_names: A list of node names for which to retrieve health pills.
-      step: The step to obtain health pills for.
-
-    Returns:
-      A dictionary mapping from node name to a list of health pill objects (see
-      docs for _serve_health_pills_handler for properties of those objects).
-
-    Raises:
-      IOError: If no files with health pill events could be found.
-    """
-    # Obtain all files with debugger-related events.
-    pattern = os.path.join(events_directory, _DEBUGGER_EVENTS_GLOB_PATTERN)
-    file_paths = glob.glob(pattern)
-
-    if not file_paths:
-      raise IOError(
-          'No events files found that matches the pattern %r.', pattern)
-
-    # Sort by name (and thus by timestamp).
-    file_paths.sort()
-
-    mapping = collections.defaultdict(list)
-    node_name_set = frozenset(node_names)
-
-    for file_path in file_paths:
-      should_stop = self._process_health_pill_event(
-          node_name_set, mapping, step, file_path)
-      if should_stop:
-        break
-
-    return mapping
-
-  def _process_health_pill_event(self, node_name_set, mapping, target_step,
-                                 file_path):
-    """Creates health pills out of data in an event.
-
-    Creates health pills out of the event and adds them to the mapping.
-
-    Args:
-      node_name_set: A set of node names that are relevant.
-      mapping: The mapping from node name to event_accumulator.HealthPillEvents.
-          This object may be destructively modified.
-      target_step: The target step at which to obtain health pills.
-      file_path: The path to the file with health pill events.
-
-    Returns:
-      Whether we should stop reading events because future events are no longer
-      relevant.
-    """
-    events_loader = event_file_loader.EventFileLoader(file_path)
-    for event in events_loader.Load():
-      if not event.HasField('summary'):
-        logging.warning('An event in a debugger events file lacks a summary.')
-        continue
-
-      if event.step < target_step:
-        # This event is not of the relevant step. We perform this check
-        # first because the majority of events will be eliminated from
-        # consideration by this check.
-        continue
-
-      if event.step > target_step:
-        # We have passed the relevant step. No need to read more events.
-        return True
-
-      for value in event.summary.value:
-        # Since we seek health pills for a specific step, this function
-        # returns 1 health pill per node per step. The wall time is the
-        # seconds since the epoch.
-        health_pill = self._process_health_pill_value(
-            node_name_set, event.wall_time, event.step, value)
-        if not health_pill:
-          continue
-        mapping[health_pill.node_name].append(health_pill)
-
-    # Keep reading events.
-    return False
-
-  def _process_health_pill_value(self, node_name_set, wall_time, step, value):
-    """Creates a dict containing various properties of a health pill.
-
-    Args:
-      node_name_set: A set of node names that are relevant.
-      wall_time: The wall time in seconds.
-      step: The session run step of the event.
-      value: The health pill value.
-
-    Returns:
-      An event_accumulator.HealthPillEvent. Or None if one could not be created.
-    """
-    if not value.HasField('tensor'):
-      logging.warning(
-          'An event in a debugger events file lacks a tensor value.')
-      return None
-
-    if value.tag != event_accumulator.HEALTH_PILL_EVENT_TAG:
-      logging.warning(
-          ('A debugger-related event lacks the %r tag. It instead has '
-           'the %r tag.'), event_accumulator.HEALTH_PILL_EVENT_TAG, value.tag)
-      return None
-
-    match = re.match(r'^(.*):(\d+):DebugNumericSummary$', value.node_name)
-    if not match:
-      logging.warning(
-          ('A event with a health pill has an invalid watch, (i.e., an '
-           'unexpected debug op): %r'), value.node_name)
-      return None
-
-    node_name = match.group(1)
-    if node_name not in node_name_set:
-      # This event is not relevant.
-      return None
-
-    # Since we seek health pills for a specific step, this function
-    # returns 1 health pill per node per step. The wall time is the
-    # seconds since the epoch.
-    return event_accumulator.HealthPillEvent(
-        wall_time=wall_time,
-        step=step,
-        node_name=node_name,
-        output_slot=int(match.group(2)),
-        value=list(tensor_util.MakeNdarray(value.tensor)))
diff --git a/tensorflow/tensorboard/plugins/debugger/debugger_plugin_test.py b/tensorflow/tensorboard/plugins/debugger/debugger_plugin_test.py
deleted file mode 100644
index f1cc2e06da2..00000000000
--- a/tensorflow/tensorboard/plugins/debugger/debugger_plugin_test.py
+++ /dev/null
@@ -1,300 +0,0 @@
-# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-"""Tests the Tensorboard debugger data plugin."""
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import collections
-import json
-import os
-import shutil
-
-import numpy as np
-from werkzeug import test as werkzeug_test
-from werkzeug import wrappers
-
-from tensorflow.core.framework import types_pb2
-from tensorflow.core.util import event_pb2
-from tensorflow.python import pywrap_tensorflow
-from tensorflow.python.platform import test
-from tensorflow.python.util import compat
-from tensorflow.tensorboard.backend import application
-from tensorflow.tensorboard.backend.event_processing import event_multiplexer
-from tensorflow.tensorboard.plugins.debugger import debugger_plugin
-
-
-class DebuggerPluginTest(test.TestCase):
-
-  def setUp(self):
-    # Populate the log directory with debugger event for run '.'.
-    self.log_dir = self.get_temp_dir()
-    file_prefix = compat.as_bytes(os.path.join(self.log_dir, 'events.debugger'))
-    writer = pywrap_tensorflow.EventsWriter(file_prefix)
-    writer.WriteEvent(
-        self._CreateEventWithDebugNumericSummary(
-            op_name='layers/Matmul',
-            output_slot=0,
-            wall_time=42,
-            step=2,
-            list_of_values=[1, 2, 3]))
-    writer.WriteEvent(
-        self._CreateEventWithDebugNumericSummary(
-            op_name='layers/Matmul',
-            output_slot=1,
-            wall_time=43,
-            step=7,
-            list_of_values=[4, 5, 6]))
-    writer.WriteEvent(
-        self._CreateEventWithDebugNumericSummary(
-            op_name='logits/Add',
-            output_slot=0,
-            wall_time=1337,
-            step=7,
-            list_of_values=[7, 8, 9]))
-    writer.WriteEvent(
-        self._CreateEventWithDebugNumericSummary(
-            op_name='logits/Add',
-            output_slot=0,
-            wall_time=1338,
-            step=8,
-            list_of_values=[10, 11, 12]))
-    writer.Close()
-
-    # Populate the log directory with debugger event for run 'run_foo'.
-    run_foo_directory = os.path.join(self.log_dir, 'run_foo')
-    os.mkdir(run_foo_directory)
-    file_prefix = compat.as_bytes(
-        os.path.join(run_foo_directory, 'events.debugger'))
-    writer = pywrap_tensorflow.EventsWriter(file_prefix)
-    writer.WriteEvent(
-        self._CreateEventWithDebugNumericSummary(
-            op_name='layers/Variable',
-            output_slot=0,
-            wall_time=4242,
-            step=42,
-            list_of_values=[13, 14, 15]))
-    writer.Close()
-
-    # Start a server that will receive requests and respond with health pills.
-    self.multiplexer = event_multiplexer.EventMultiplexer({
-        '.': self.log_dir,
-        'run_foo': run_foo_directory,
-    })
-    self.plugin = debugger_plugin.DebuggerPlugin()
-    wsgi_app = application.TensorBoardWSGIApp(
-        self.log_dir, [self.plugin],
-        self.multiplexer,
-        reload_interval=0)
-    self.server = werkzeug_test.Client(wsgi_app, wrappers.BaseResponse)
-
-  def tearDown(self):
-    # Remove the directory with debugger-related events files.
-    shutil.rmtree(self.log_dir, ignore_errors=True)
-
-  def _CreateEventWithDebugNumericSummary(
-      self, op_name, output_slot, wall_time, step, list_of_values):
-    """Creates event with a health pill summary.
-
-    Args:
-      op_name: The name of the op to which a DebugNumericSummary was attached.
-      output_slot: The numeric output slot for the tensor.
-      wall_time: The numeric wall time of the event.
-      step: The step of the event.
-      list_of_values: A python list of values within the tensor.
-
-    Returns:
-      A event_pb2.Event with a health pill summary.
-    """
-    event = event_pb2.Event(step=step, wall_time=wall_time)
-    value = event.summary.value.add(
-        tag='__health_pill__',
-        node_name='%s:%d:DebugNumericSummary' % (op_name, output_slot))
-    value.tensor.tensor_shape.dim.add(size=len(list_of_values))
-    value.tensor.dtype = types_pb2.DT_DOUBLE
-    value.tensor.tensor_content = np.array(
-        list_of_values, dtype=np.float64).tobytes()
-    return event
-
-  def _DeserializeResponse(self, byte_content):
-    """Deserializes byte content that is a JSON encoding.
-
-    Args:
-      byte_content: The byte content of a JSON response.
-
-    Returns:
-      The deserialized python object decoded from JSON.
-    """
-    return json.loads(byte_content.decode('utf-8'))
-
-  def testHealthPillsRouteProvided(self):
-    """Tests that the plugin offers the route for requesting health pills."""
-    apps = self.plugin.get_plugin_apps(self.multiplexer, self.log_dir)
-    self.assertIn('/health_pills', apps)
-    self.assertIsInstance(apps['/health_pills'], collections.Callable)
-
-  def testHealthPillsPluginIsActive(self):
-    self.plugin.get_plugin_apps(self.multiplexer, self.log_dir)
-
-    # The multiplexer has sampled health pills.
-    self.assertTrue(self.plugin.is_active())
-
-  def testHealthPillsPluginIsInactive(self):
-    self.plugin.get_plugin_apps(
-        event_multiplexer.EventMultiplexer({}), self.log_dir)
-
-    # The multiplexer lacks sampled health pills.
-    self.assertFalse(self.plugin.is_active())
-
-  def testRequestHealthPillsForRunFoo(self):
-    """Tests that the plugin produces health pills for a specified run."""
-    response = self.server.post(
-        '/data/plugin/debugger/health_pills',
-        data={
-            'node_names': json.dumps(['layers/Variable', 'unavailable_node']),
-            'run': 'run_foo',
-        })
-    self.assertEqual(200, response.status_code)
-    self.assertDictEqual({
-        'layers/Variable': [{
-            'wall_time': 4242,
-            'step': 42,
-            'node_name': 'layers/Variable',
-            'output_slot': 0,
-            'value': [13, 14, 15],
-        }],
-    }, self._DeserializeResponse(response.get_data()))
-
-  def testRequestHealthPillsForDefaultRun(self):
-    """Tests that the plugin produces health pills for the default '.' run."""
-    # Do not provide a 'run' parameter in POST data.
-    response = self.server.post(
-        '/data/plugin/debugger/health_pills',
-        data={
-            'node_names': json.dumps(['logits/Add', 'unavailable_node']),
-        })
-    self.assertEqual(200, response.status_code)
-    # The health pills for 'layers/Matmul' should not be included since the
-    # request excluded that node name.
-    self.assertDictEqual({
-        'logits/Add': [
-            {
-                'wall_time': 1337,
-                'step': 7,
-                'node_name': 'logits/Add',
-                'output_slot': 0,
-                'value': [7, 8, 9],
-            },
-            {
-                'wall_time': 1338,
-                'step': 8,
-                'node_name': 'logits/Add',
-                'output_slot': 0,
-                'value': [10, 11, 12],
-            },
-        ],
-    }, self._DeserializeResponse(response.get_data()))
-
-  def testGetRequestsUnsupported(self):
-    """Tests that GET requests are unsupported."""
-    response = self.server.get('/data/plugin/debugger/health_pills')
-    self.assertEqual(405, response.status_code)
-
-  def testRequestsWithoutProperPostKeyUnsupported(self):
-    """Tests that requests lacking the node_names POST key are unsupported."""
-    response = self.server.post('/data/plugin/debugger/health_pills')
-    self.assertEqual(400, response.status_code)
-
-  def testRequestsWithBadJsonUnsupported(self):
-    """Tests that requests with undecodable JSON are unsupported."""
-    response = self.server.post(
-        '/data/plugin/debugger/health_pills',
-        data={
-            'node_names': 'some obviously non JSON text',
-        })
-    self.assertEqual(400, response.status_code)
-
-  def testRequestsWithNonListPostDataUnsupported(self):
-    """Tests that requests with loads lacking lists of ops are unsupported."""
-    response = self.server.post(
-        '/data/plugin/debugger/health_pills',
-        data={
-            'node_names': json.dumps({
-                'this is a dict': 'and not a list.'
-            }),
-        })
-    self.assertEqual(400, response.status_code)
-
-  def testFetchHealthPillsForSpecificStep(self):
-    """Tests that requesting health pills at a specific steps works.
-
-    This path may be slow in real life because it reads from disk.
-    """
-    # Request health pills for these nodes at step 7 specifically.
-    response = self.server.post(
-        '/data/plugin/debugger/health_pills',
-        data={
-            'node_names': json.dumps(['logits/Add', 'layers/Matmul']),
-            'step': 7
-        })
-    self.assertEqual(200, response.status_code)
-    # The response should only include health pills at step 7.
-    self.assertDictEqual({
-        'logits/Add': [
-            {
-                'wall_time': 1337,
-                'step': 7,
-                'node_name': 'logits/Add',
-                'output_slot': 0,
-                'value': [7, 8, 9],
-            },
-        ],
-        'layers/Matmul': [
-            {
-                'wall_time': 43,
-                'step': 7,
-                'node_name': 'layers/Matmul',
-                'output_slot': 1,
-                'value': [4, 5, 6],
-            },
-        ],
-    }, self._DeserializeResponse(response.get_data()))
-
-  def testNoHealthPillsForSpecificStep(self):
-    """Tests that an empty mapping is returned for no health pills at a step."""
-    response = self.server.post(
-        '/data/plugin/debugger/health_pills',
-        data={
-            'node_names': json.dumps(['some/clearly/non-existent/op']),
-            'step': 7
-        })
-    self.assertEqual(200, response.status_code)
-    self.assertDictEqual({}, self._DeserializeResponse(response.get_data()))
-
-  def testNoHealthPillsForOutOfRangeStep(self):
-    """Tests that an empty mapping is returned for an out of range step."""
-    response = self.server.post(
-        '/data/plugin/debugger/health_pills',
-        data={
-            'node_names': json.dumps(['logits/Add', 'layers/Matmul']),
-            # This step higher than that of any event written to disk.
-            'step': 42424242
-        })
-    self.assertEqual(200, response.status_code)
-    self.assertDictEqual({}, self._DeserializeResponse(response.get_data()))
-
-if __name__ == '__main__':
-  test.main()
diff --git a/tensorflow/tensorboard/tensorboard.py b/tensorflow/tensorboard/tensorboard.py
index f3900d1e5df..f371a01f35b 100644
--- a/tensorflow/tensorboard/tensorboard.py
+++ b/tensorflow/tensorboard/tensorboard.py
@@ -32,7 +32,8 @@ from tensorflow.python.platform import flags
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.tensorboard.backend import application
 from tensorflow.tensorboard.backend.event_processing import event_file_inspector as efi
-
+from tensorflow.tensorboard.plugins.projector import projector_plugin
+from tensorflow.tensorboard.plugins.text import text_plugin
 
 # TensorBoard flags
 
@@ -88,8 +89,18 @@ flags.DEFINE_string(
 FLAGS = flags.FLAGS
 
 
-def create_tb_app():
-  """Read the flags, and create a TensorBoard WSGI application."""
+def create_tb_app(plugins):
+  """Read the flags, and create a TensorBoard WSGI application.
+
+  Args:
+    plugins: A list of plugins for TensorBoard to initialize.
+
+  Raises:
+    ValueError: if a logdir is not specified.
+
+  Returns:
+    A new TensorBoard WSGI application.
+  """
   if not FLAGS.logdir:
     raise ValueError('A logdir must be specified. Run `tensorboard --help` for '
                      'details and examples.')
@@ -98,7 +109,8 @@ def create_tb_app():
   return application.standard_tensorboard_wsgi(
       logdir=logdir,
       purge_orphaned_data=FLAGS.purge_orphaned_data,
-      reload_interval=FLAGS.reload_interval)
+      reload_interval=FLAGS.reload_interval,
+      plugins=plugins)
 
 
 def make_simple_server(tb_app, host, port):
@@ -184,7 +196,11 @@ def main(unused_argv=None):
     efi.inspect(FLAGS.logdir, event_file, FLAGS.tag)
     return 0
   else:
-    tb = create_tb_app()
+    plugins = [
+        projector_plugin.ProjectorPlugin(),
+        text_plugin.TextPlugin(),
+    ]
+    tb = create_tb_app(plugins)
     run_simple_server(tb)
 
 if __name__ == '__main__':
diff --git a/tensorflow/tools/api/golden/BUILD b/tensorflow/tools/api/golden/BUILD
new file mode 100644
index 00000000000..08436396a6c
--- /dev/null
+++ b/tensorflow/tools/api/golden/BUILD
@@ -0,0 +1,24 @@
+# TensorFlow API backwards compatibility test goldens.
+
+package(
+    default_visibility = ["//tensorflow/tools/api:__subpackages__"],
+)
+
+licenses(["notice"])  # Apache 2.0
+
+filegroup(
+    name = "api_golden",
+    srcs = glob(["*.pbtxt"]),
+)
+
+filegroup(
+    name = "all_files",
+    srcs = glob(
+        ["**/*"],
+        exclude = [
+            "**/METADATA",
+            "**/OWNERS",
+        ],
+    ),
+    visibility = ["//tensorflow:__subpackages__"],
+)
diff --git a/tensorflow/tools/api/golden/tensorflow.-aggregation-method.pbtxt b/tensorflow/tools/api/golden/tensorflow.-aggregation-method.pbtxt
new file mode 100644
index 00000000000..f79029d3fe0
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-aggregation-method.pbtxt
@@ -0,0 +1,24 @@
+path: "tensorflow.AggregationMethod"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.gradients_impl.AggregationMethod\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "ADD_N"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DEFAULT"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "EXPERIMENTAL_ACCUMULATE_N"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "EXPERIMENTAL_TREE"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-attr-value.-list-value.pbtxt b/tensorflow/tools/api/golden/tensorflow.-attr-value.-list-value.pbtxt
new file mode 100644
index 00000000000..0fb1aaba283
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-attr-value.-list-value.pbtxt
@@ -0,0 +1,108 @@
+path: "tensorflow.AttrValue.ListValue"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.attr_value_pb2.ListValue\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "B_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FUNC_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "F_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "I_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SHAPE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "S_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TENSOR_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TYPE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-attr-value.pbtxt b/tensorflow/tools/api/golden/tensorflow.-attr-value.pbtxt
new file mode 100644
index 00000000000..e7a3a1f02fa
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-attr-value.pbtxt
@@ -0,0 +1,120 @@
+path: "tensorflow.AttrValue"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.attr_value_pb2.AttrValue\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "B_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FUNC_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "F_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "I_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "LIST_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "ListValue"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "PLACEHOLDER_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SHAPE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "S_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TENSOR_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TYPE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-auto-parallel-options.pbtxt b/tensorflow/tools/api/golden/tensorflow.-auto-parallel-options.pbtxt
new file mode 100644
index 00000000000..c8f3e8fb154
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-auto-parallel-options.pbtxt
@@ -0,0 +1,84 @@
+path: "tensorflow.AutoParallelOptions"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.rewriter_config_pb2.AutoParallelOptions\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "ENABLE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "NUM_REPLICAS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-conditional-accumulator-base.pbtxt b/tensorflow/tools/api/golden/tensorflow.-conditional-accumulator-base.pbtxt
new file mode 100644
index 00000000000..c9a32c16b34
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-conditional-accumulator-base.pbtxt
@@ -0,0 +1,29 @@
+path: "tensorflow.ConditionalAccumulatorBase"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.ConditionalAccumulatorBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "accumulator_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'dtype\', \'shape\', \'accumulator_ref\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "num_accumulated"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "set_global_step"
+    argspec: "args=[\'self\', \'new_global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-conditional-accumulator.pbtxt b/tensorflow/tools/api/golden/tensorflow.-conditional-accumulator.pbtxt
new file mode 100644
index 00000000000..d23b3bd0cae
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-conditional-accumulator.pbtxt
@@ -0,0 +1,38 @@
+path: "tensorflow.ConditionalAccumulator"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.ConditionalAccumulator\'>"
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.ConditionalAccumulatorBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "accumulator_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'dtype\', \'shape\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'conditional_accumulator\'], "
+  }
+  member_method {
+    name: "apply_grad"
+    argspec: "args=[\'self\', \'grad\', \'local_step\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'None\'], "
+  }
+  member_method {
+    name: "num_accumulated"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "set_global_step"
+    argspec: "args=[\'self\', \'new_global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "take_grad"
+    argspec: "args=[\'self\', \'num_required\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-config-proto.-device-count-entry.pbtxt b/tensorflow/tools/api/golden/tensorflow.-config-proto.-device-count-entry.pbtxt
new file mode 100644
index 00000000000..29bb3be35cb
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-config-proto.-device-count-entry.pbtxt
@@ -0,0 +1,84 @@
+path: "tensorflow.ConfigProto.DeviceCountEntry"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.config_pb2.DeviceCountEntry\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "KEY_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-config-proto.pbtxt b/tensorflow/tools/api/golden/tensorflow.-config-proto.pbtxt
new file mode 100644
index 00000000000..805a9bdd4f1
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-config-proto.pbtxt
@@ -0,0 +1,132 @@
+path: "tensorflow.ConfigProto"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.config_pb2.ConfigProto\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "ALLOW_SOFT_PLACEMENT_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "DEVICE_COUNT_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DEVICE_FILTERS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DeviceCountEntry"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "GPU_OPTIONS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GRAPH_OPTIONS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "INTER_OP_PARALLELISM_THREADS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "INTRA_OP_PARALLELISM_THREADS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "LOG_DEVICE_PLACEMENT_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "OPERATION_TIMEOUT_IN_MS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "PLACEMENT_PERIOD_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "RPC_OPTIONS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SESSION_INTER_OP_THREAD_POOL_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "USE_PER_SESSION_THREADS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-d-type.pbtxt b/tensorflow/tools/api/golden/tensorflow.-d-type.pbtxt
new file mode 100644
index 00000000000..0b5b88bba80
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-d-type.pbtxt
@@ -0,0 +1,77 @@
+path: "tensorflow.DType"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.dtypes.DType\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "as_datatype_enum"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "as_numpy_dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "base_dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "is_bool"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "is_complex"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "is_floating"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "is_integer"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "is_numpy_compatible"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "is_quantized"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "is_unsigned"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "limits"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "max"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "min"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "real_dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "size"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'type_enum\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "is_compatible_with"
+    argspec: "args=[\'self\', \'other\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-device-spec.pbtxt b/tensorflow/tools/api/golden/tensorflow.-device-spec.pbtxt
new file mode 100644
index 00000000000..92e535c3414
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-device-spec.pbtxt
@@ -0,0 +1,37 @@
+path: "tensorflow.DeviceSpec"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.device.DeviceSpec\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "job"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "replica"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "task"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'job\', \'replica\', \'task\', \'device_type\', \'device_index\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "from_string"
+    argspec: "args=[\'spec\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "merge_from"
+    argspec: "args=[\'self\', \'dev\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "parse_from_string"
+    argspec: "args=[\'self\', \'spec\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "to_string"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-dimension.pbtxt b/tensorflow/tools/api/golden/tensorflow.-dimension.pbtxt
new file mode 100644
index 00000000000..a9ab27719b4
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-dimension.pbtxt
@@ -0,0 +1,25 @@
+path: "tensorflow.Dimension"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.tensor_shape.Dimension\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "value"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "assert_is_compatible_with"
+    argspec: "args=[\'self\', \'other\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "is_compatible_with"
+    argspec: "args=[\'self\', \'other\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "merge_with"
+    argspec: "args=[\'self\', \'other\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-event.pbtxt b/tensorflow/tools/api/golden/tensorflow.-event.pbtxt
new file mode 100644
index 00000000000..9bf8c124288
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-event.pbtxt
@@ -0,0 +1,112 @@
+path: "tensorflow.Event"
+tf_class {
+  is_instance: "<class \'tensorflow.core.util.event_pb2.Event\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FILE_VERSION_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GRAPH_DEF_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "LOG_MESSAGE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "META_GRAPH_DEF_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SESSION_LOG_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "STEP_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SUMMARY_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TAGGED_RUN_METADATA_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "WALL_TIME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-f-i-f-o-queue.pbtxt b/tensorflow/tools/api/golden/tensorflow.-f-i-f-o-queue.pbtxt
new file mode 100644
index 00000000000..72cc5324476
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-f-i-f-o-queue.pbtxt
@@ -0,0 +1,62 @@
+path: "tensorflow.FIFOQueue"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.FIFOQueue\'>"
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.QueueBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "dtypes"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "names"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "queue_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "shapes"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'capacity\', \'dtypes\', \'shapes\', \'names\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'fifo_queue\'], "
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\', \'cancel_pending_enqueues\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
+  member_method {
+    name: "dequeue"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "dequeue_many"
+    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "dequeue_up_to"
+    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "enqueue"
+    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "enqueue_many"
+    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_list"
+    argspec: "args=[\'index\', \'queues\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "size"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-fixed-len-feature.pbtxt b/tensorflow/tools/api/golden/tensorflow.-fixed-len-feature.pbtxt
new file mode 100644
index 00000000000..6933814a7b6
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-fixed-len-feature.pbtxt
@@ -0,0 +1,27 @@
+path: "tensorflow.FixedLenFeature"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.parsing_ops.FixedLenFeature\'>"
+  is_instance: "<class \'tensorflow.python.ops.parsing_ops.FixedLenFeature\'>"
+  is_instance: "<type \'tuple\'>"
+  member {
+    name: "default_value"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "shape"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "count"
+  }
+  member_method {
+    name: "index"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-fixed-len-sequence-feature.pbtxt b/tensorflow/tools/api/golden/tensorflow.-fixed-len-sequence-feature.pbtxt
new file mode 100644
index 00000000000..c5387879519
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-fixed-len-sequence-feature.pbtxt
@@ -0,0 +1,31 @@
+path: "tensorflow.FixedLenSequenceFeature"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.parsing_ops.FixedLenSequenceFeature\'>"
+  is_instance: "<class \'tensorflow.python.ops.parsing_ops.FixedLenSequenceFeature\'>"
+  is_instance: "<type \'tuple\'>"
+  member {
+    name: "allow_missing"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "default_value"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "shape"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "count"
+  }
+  member_method {
+    name: "index"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-fixed-length-record-reader.pbtxt b/tensorflow/tools/api/golden/tensorflow.-fixed-length-record-reader.pbtxt
new file mode 100644
index 00000000000..e7e36e2bb35
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-fixed-length-record-reader.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.FixedLengthRecordReader"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.io_ops.FixedLengthRecordReader\'>"
+  is_instance: "<class \'tensorflow.python.ops.io_ops.ReaderBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "reader_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "supports_serialize"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'record_bytes\', \'header_bytes\', \'footer_bytes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "num_records_produced"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "num_work_units_completed"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read"
+    argspec: "args=[\'self\', \'queue\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read_up_to"
+    argspec: "args=[\'self\', \'queue\', \'num_records\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "reset"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "restore_state"
+    argspec: "args=[\'self\', \'state\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "serialize_state"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-g-p-u-options.pbtxt b/tensorflow/tools/api/golden/tensorflow.-g-p-u-options.pbtxt
new file mode 100644
index 00000000000..48cda623f7c
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-g-p-u-options.pbtxt
@@ -0,0 +1,104 @@
+path: "tensorflow.GPUOptions"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.config_pb2.GPUOptions\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "ALLOCATOR_TYPE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "ALLOW_GROWTH_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DEFERRED_DELETION_BYTES_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "PER_PROCESS_GPU_MEMORY_FRACTION_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "POLLING_ACTIVE_DELAY_USECS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "POLLING_INACTIVE_DELAY_MSECS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "VISIBLE_DEVICE_LIST_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-graph-def.pbtxt b/tensorflow/tools/api/golden/tensorflow.-graph-def.pbtxt
new file mode 100644
index 00000000000..1495e847cb0
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-graph-def.pbtxt
@@ -0,0 +1,92 @@
+path: "tensorflow.GraphDef"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.graph_pb2.GraphDef\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "LIBRARY_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "NODE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "VERSIONS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "VERSION_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-graph-keys.pbtxt b/tensorflow/tools/api/golden/tensorflow.-graph-keys.pbtxt
new file mode 100644
index 00000000000..ef2cfe3787e
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-graph-keys.pbtxt
@@ -0,0 +1,136 @@
+path: "tensorflow.GraphKeys"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.ops.GraphKeys\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "ACTIVATIONS"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "ASSET_FILEPATHS"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "BIASES"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "CONCATENATED_VARIABLES"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "COND_CONTEXT"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "EVAL_STEP"
+    mtype: "<type \'str\'>"
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+    mtype: "<type \'str\'>"
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+    mtype: "<type \'str\'>"
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+  member {
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+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "TRAINABLE_RESOURCE_VARIABLES"
+    mtype: "<type \'str\'>"
+  }
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+    mtype: "<type \'str\'>"
+  }
+  member {
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+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "UPDATE_OPS"
+    mtype: "<type \'str\'>"
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+  member {
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+    mtype: "<type \'str\'>"
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+  member {
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+    mtype: "<type \'str\'>"
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+  member {
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+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-graph-options.pbtxt b/tensorflow/tools/api/golden/tensorflow.-graph-options.pbtxt
new file mode 100644
index 00000000000..0844f891cad
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-graph-options.pbtxt
@@ -0,0 +1,112 @@
+path: "tensorflow.GraphOptions"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.config_pb2.GraphOptions\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "BUILD_COST_MODEL_AFTER_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "BUILD_COST_MODEL_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "ENABLE_BFLOAT16_SENDRECV_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "ENABLE_RECV_SCHEDULING_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "INFER_SHAPES_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "OPTIMIZER_OPTIONS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "PLACE_PRUNED_GRAPH_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "REWRITE_OPTIONS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TIMELINE_STEP_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
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+  }
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+  member_method {
+    name: "ClearField"
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+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-graph.pbtxt b/tensorflow/tools/api/golden/tensorflow.-graph.pbtxt
new file mode 100644
index 00000000000..566456a255d
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-graph.pbtxt
@@ -0,0 +1,129 @@
+path: "tensorflow.Graph"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.ops.Graph\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "building_function"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "finalized"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "graph_def_versions"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "seed"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "version"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
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+    name: "add_to_collection"
+    argspec: "args=[\'self\', \'name\', \'value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "add_to_collections"
+    argspec: "args=[\'self\', \'names\', \'value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "as_default"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "as_graph_def"
+    argspec: "args=[\'self\', \'from_version\', \'add_shapes\'], varargs=None, keywords=None, defaults=[\'None\', \'False\'], "
+  }
+  member_method {
+    name: "as_graph_element"
+    argspec: "args=[\'self\', \'obj\', \'allow_tensor\', \'allow_operation\'], varargs=None, keywords=None, defaults=[\'True\', \'True\'], "
+  }
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+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=None"
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+    argspec: "args=[], varargs=args, keywords=kwds, defaults=None"
+  }
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+    argspec: "args=[], varargs=args, keywords=kwds, defaults=None"
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+    argspec: "args=[\'self\', \'control_inputs\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "create_op"
+    argspec: "args=[\'self\', \'op_type\', \'inputs\', \'dtypes\', \'input_types\', \'name\', \'attrs\', \'op_def\', \'compute_shapes\', \'compute_device\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'True\', \'True\'], "
+  }
+  member_method {
+    name: "device"
+    argspec: "args=[], varargs=args, keywords=kwds, defaults=None"
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+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
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+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
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+    argspec: "args=[\'self\', \'name\', \'scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
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+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
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+    name: "gradient_override_map"
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+    argspec: "args=[\'self\', \'tensor\'], varargs=None, keywords=None, defaults=None"
+  }
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+    argspec: "args=[\'self\', \'tensor_or_op\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "name_scope"
+    argspec: "args=[], varargs=args, keywords=kwds, defaults=None"
+  }
+  member_method {
+    name: "prevent_feeding"
+    argspec: "args=[\'self\', \'tensor\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "prevent_fetching"
+    argspec: "args=[\'self\', \'op\'], varargs=None, keywords=None, defaults=None"
+  }
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+    name: "unique_name"
+    argspec: "args=[\'self\', \'name\', \'mark_as_used\'], varargs=None, keywords=None, defaults=[\'True\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-histogram-proto.pbtxt b/tensorflow/tools/api/golden/tensorflow.-histogram-proto.pbtxt
new file mode 100644
index 00000000000..2567d2fe602
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-histogram-proto.pbtxt
@@ -0,0 +1,104 @@
+path: "tensorflow.HistogramProto"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.summary_pb2.HistogramProto\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "BUCKET_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
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+    name: "BUCKET_LIMIT_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "MAX_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
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+    name: "MIN_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "NUM_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SUM_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
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+    name: "ByteSize"
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+    name: "ClearExtension"
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+    name: "ClearField"
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+    name: "DiscardUnknownFields"
+  }
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+  }
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+    name: "HasField"
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+    name: "IsInitialized"
+  }
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+    name: "ListFields"
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+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
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+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-identity-reader.pbtxt b/tensorflow/tools/api/golden/tensorflow.-identity-reader.pbtxt
new file mode 100644
index 00000000000..2eda320d636
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-identity-reader.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.IdentityReader"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.io_ops.IdentityReader\'>"
+  is_instance: "<class \'tensorflow.python.ops.io_ops.ReaderBase\'>"
+  is_instance: "<type \'object\'>"
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+    mtype: "<type \'property\'>"
+  }
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+    mtype: "<type \'property\'>"
+  }
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+    name: "__init__"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
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+    name: "num_records_produced"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
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+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read"
+    argspec: "args=[\'self\', \'queue\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
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+    name: "read_up_to"
+    argspec: "args=[\'self\', \'queue\', \'num_records\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
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+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "restore_state"
+    argspec: "args=[\'self\', \'state\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "serialize_state"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-indexed-slices.pbtxt b/tensorflow/tools/api/golden/tensorflow.-indexed-slices.pbtxt
new file mode 100644
index 00000000000..fee84d85307
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-indexed-slices.pbtxt
@@ -0,0 +1,42 @@
+path: "tensorflow.IndexedSlices"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.ops.IndexedSlices\'>"
+  is_instance: "<class \'tensorflow.python.framework.ops._TensorLike\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "dense_shape"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "device"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "graph"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "indices"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "values"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'values\', \'indices\', \'dense_shape\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-interactive-session.pbtxt b/tensorflow/tools/api/golden/tensorflow.-interactive-session.pbtxt
new file mode 100644
index 00000000000..623f4b1a273
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-interactive-session.pbtxt
@@ -0,0 +1,43 @@
+path: "tensorflow.InteractiveSession"
+tf_class {
+  is_instance: "<class \'tensorflow.python.client.session.InteractiveSession\'>"
+  is_instance: "<class \'tensorflow.python.client.session.BaseSession\'>"
+  is_instance: "<class \'tensorflow.python.client.session.SessionInterface\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "graph"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "graph_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "sess_str"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'target\', \'graph\', \'config\'], varargs=None, keywords=None, defaults=[\'\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "as_default"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
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+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
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+    argspec: "args=[\'self\', \'handle\', \'fetches\', \'feed_dict\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "partial_run_setup"
+    argspec: "args=[\'self\', \'fetches\', \'feeds\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "run"
+    argspec: "args=[\'self\', \'fetches\', \'feed_dict\', \'options\', \'run_metadata\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-log-message.pbtxt b/tensorflow/tools/api/golden/tensorflow.-log-message.pbtxt
new file mode 100644
index 00000000000..a43c5eb7e30
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-log-message.pbtxt
@@ -0,0 +1,112 @@
+path: "tensorflow.LogMessage"
+tf_class {
+  is_instance: "<class \'tensorflow.core.util.event_pb2.LogMessage\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DEBUGGING"
+    mtype: "<type \'int\'>"
+  }
+  member {
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+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "ERROR"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
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+    mtype: "<type \'int\'>"
+  }
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+    mtype: "<type \'int\'>"
+  }
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+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Level"
+    mtype: "<class \'google.protobuf.internal.enum_type_wrapper.EnumTypeWrapper\'>"
+  }
+  member {
+    name: "MESSAGE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
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+    mtype: "<type \'int\'>"
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+  member_method {
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+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-name-attr-list.-attr-entry.pbtxt b/tensorflow/tools/api/golden/tensorflow.-name-attr-list.-attr-entry.pbtxt
new file mode 100644
index 00000000000..2750bd780ca
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-name-attr-list.-attr-entry.pbtxt
@@ -0,0 +1,84 @@
+path: "tensorflow.NameAttrList.AttrEntry"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.attr_value_pb2.AttrEntry\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
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+    mtype: "<type \'int\'>"
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+  member_method {
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+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
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+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
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+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-name-attr-list.pbtxt b/tensorflow/tools/api/golden/tensorflow.-name-attr-list.pbtxt
new file mode 100644
index 00000000000..d10faf67d02
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-name-attr-list.pbtxt
@@ -0,0 +1,88 @@
+path: "tensorflow.NameAttrList"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.attr_value_pb2.NameAttrList\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "ATTR_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "AttrEntry"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "NAME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
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+    name: "ByteSize"
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+  member_method {
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+  }
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+  member_method {
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+  member_method {
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+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
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+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-node-def.-attr-entry.pbtxt b/tensorflow/tools/api/golden/tensorflow.-node-def.-attr-entry.pbtxt
new file mode 100644
index 00000000000..b1b62d60f1e
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-node-def.-attr-entry.pbtxt
@@ -0,0 +1,84 @@
+path: "tensorflow.NodeDef.AttrEntry"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.node_def_pb2.AttrEntry\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "KEY_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
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+  member_method {
+    name: "ByteSize"
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+  member_method {
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+  member_method {
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+  }
+  member_method {
+    name: "ClearField"
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+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-node-def.pbtxt b/tensorflow/tools/api/golden/tensorflow.-node-def.pbtxt
new file mode 100644
index 00000000000..b812b4df2b3
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-node-def.pbtxt
@@ -0,0 +1,100 @@
+path: "tensorflow.NodeDef"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.node_def_pb2.NodeDef\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "ATTR_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "AttrEntry"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "DEVICE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "INPUT_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "NAME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "OP_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
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+  member_method {
+    name: "ClearExtension"
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+  member_method {
+    name: "ClearField"
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+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
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+  member_method {
+    name: "FindInitializationErrors"
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+  member_method {
+    name: "FromString"
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+  member_method {
+    name: "HasExtension"
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+  member_method {
+    name: "HasField"
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+  member_method {
+    name: "ListFields"
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+  member_method {
+    name: "MergeFrom"
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+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-op-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.-op-error.pbtxt
new file mode 100644
index 00000000000..7e59615534f
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-op-error.pbtxt
@@ -0,0 +1,29 @@
+path: "tensorflow.OpError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\', \'error_code\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-operation.pbtxt b/tensorflow/tools/api/golden/tensorflow.-operation.pbtxt
new file mode 100644
index 00000000000..0f43a49ee96
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-operation.pbtxt
@@ -0,0 +1,65 @@
+path: "tensorflow.Operation"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.ops.Operation\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "control_inputs"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "device"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "graph"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "inputs"
+    mtype: "<type \'property\'>"
+  }
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+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "outputs"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "traceback"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "type"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'g\', \'inputs\', \'output_types\', \'control_inputs\', \'input_types\', \'original_op\', \'op_def\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "colocation_groups"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_attr"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "run"
+    argspec: "args=[\'self\', \'feed_dict\', \'session\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "values"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-optimizer-options.pbtxt b/tensorflow/tools/api/golden/tensorflow.-optimizer-options.pbtxt
new file mode 100644
index 00000000000..5dd1ee47c96
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-optimizer-options.pbtxt
@@ -0,0 +1,128 @@
+path: "tensorflow.OptimizerOptions"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.config_pb2.OptimizerOptions\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DEFAULT"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "DO_COMMON_SUBEXPRESSION_ELIMINATION_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DO_CONSTANT_FOLDING_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DO_FUNCTION_INLINING_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "GLOBAL_JIT_LEVEL_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GlobalJitLevel"
+    mtype: "<class \'google.protobuf.internal.enum_type_wrapper.EnumTypeWrapper\'>"
+  }
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+    mtype: "<type \'int\'>"
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+    mtype: "<class \'google.protobuf.internal.enum_type_wrapper.EnumTypeWrapper\'>"
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+    name: "FromString"
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+  member_method {
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+    name: "HasField"
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+    name: "IsInitialized"
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+  member_method {
+    name: "ListFields"
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+    name: "MergeFrom"
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+    name: "MergeFromString"
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+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
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+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-padding-f-i-f-o-queue.pbtxt b/tensorflow/tools/api/golden/tensorflow.-padding-f-i-f-o-queue.pbtxt
new file mode 100644
index 00000000000..1bfe723ce75
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-padding-f-i-f-o-queue.pbtxt
@@ -0,0 +1,62 @@
+path: "tensorflow.PaddingFIFOQueue"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.PaddingFIFOQueue\'>"
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.QueueBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "dtypes"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "names"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "queue_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "shapes"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'capacity\', \'dtypes\', \'shapes\', \'names\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'padding_fifo_queue\'], "
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\', \'cancel_pending_enqueues\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
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+    name: "dequeue"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
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+    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "dequeue_up_to"
+    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "enqueue"
+    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "enqueue_many"
+    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_list"
+    argspec: "args=[\'index\', \'queues\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "size"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-priority-queue.pbtxt b/tensorflow/tools/api/golden/tensorflow.-priority-queue.pbtxt
new file mode 100644
index 00000000000..dbe25f3a5b9
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-priority-queue.pbtxt
@@ -0,0 +1,62 @@
+path: "tensorflow.PriorityQueue"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.PriorityQueue\'>"
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.QueueBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "dtypes"
+    mtype: "<type \'property\'>"
+  }
+  member {
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+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "names"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "queue_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "shapes"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
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+    argspec: "args=[\'self\', \'capacity\', \'types\', \'shapes\', \'names\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'priority_queue\'], "
+  }
+  member_method {
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+    argspec: "args=[\'self\', \'cancel_pending_enqueues\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
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+    name: "dequeue"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
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+    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "dequeue_up_to"
+    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "enqueue"
+    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "enqueue_many"
+    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_list"
+    argspec: "args=[\'index\', \'queues\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "size"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-queue-base.pbtxt b/tensorflow/tools/api/golden/tensorflow.-queue-base.pbtxt
new file mode 100644
index 00000000000..9263d73a511
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-queue-base.pbtxt
@@ -0,0 +1,61 @@
+path: "tensorflow.QueueBase"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.QueueBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "dtypes"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "names"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "queue_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "shapes"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'dtypes\', \'shapes\', \'names\', \'queue_ref\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\', \'cancel_pending_enqueues\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
+  member_method {
+    name: "dequeue"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "dequeue_many"
+    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "dequeue_up_to"
+    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "enqueue"
+    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "enqueue_many"
+    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_list"
+    argspec: "args=[\'index\', \'queues\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "size"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-random-shuffle-queue.pbtxt b/tensorflow/tools/api/golden/tensorflow.-random-shuffle-queue.pbtxt
new file mode 100644
index 00000000000..ec783ffe5a0
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-random-shuffle-queue.pbtxt
@@ -0,0 +1,62 @@
+path: "tensorflow.RandomShuffleQueue"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.RandomShuffleQueue\'>"
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.QueueBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "dtypes"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "names"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "queue_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "shapes"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'capacity\', \'min_after_dequeue\', \'dtypes\', \'shapes\', \'names\', \'seed\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'random_shuffle_queue\'], "
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\', \'cancel_pending_enqueues\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
+  member_method {
+    name: "dequeue"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "dequeue_many"
+    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "dequeue_up_to"
+    argspec: "args=[\'self\', \'n\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "enqueue"
+    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "enqueue_many"
+    argspec: "args=[\'self\', \'vals\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_list"
+    argspec: "args=[\'index\', \'queues\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "size"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-reader-base.pbtxt b/tensorflow/tools/api/golden/tensorflow.-reader-base.pbtxt
new file mode 100644
index 00000000000..f6a3ce76a15
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-reader-base.pbtxt
@@ -0,0 +1,45 @@
+path: "tensorflow.ReaderBase"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.io_ops.ReaderBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "reader_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "supports_serialize"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'reader_ref\', \'supports_serialize\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
+  member_method {
+    name: "num_records_produced"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "num_work_units_completed"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read"
+    argspec: "args=[\'self\', \'queue\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read_up_to"
+    argspec: "args=[\'self\', \'queue\', \'num_records\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "reset"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "restore_state"
+    argspec: "args=[\'self\', \'state\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "serialize_state"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-register-gradient.pbtxt b/tensorflow/tools/api/golden/tensorflow.-register-gradient.pbtxt
new file mode 100644
index 00000000000..4d6e4137d12
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-register-gradient.pbtxt
@@ -0,0 +1,9 @@
+path: "tensorflow.RegisterGradient"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.ops.RegisterGradient\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'op_type\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-rewriter-config.pbtxt b/tensorflow/tools/api/golden/tensorflow.-rewriter-config.pbtxt
new file mode 100644
index 00000000000..34d2e176128
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-rewriter-config.pbtxt
@@ -0,0 +1,112 @@
+path: "tensorflow.RewriterConfig"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.rewriter_config_pb2.RewriterConfig\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "AUTO_PARALLEL_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "CONSTANT_FOLDING_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "DISABLE_MODEL_PRUNING_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "MANUAL"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "MEMORY_OPTIMIZATION_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "MemOptType"
+    mtype: "<class \'google.protobuf.internal.enum_type_wrapper.EnumTypeWrapper\'>"
+  }
+  member {
+    name: "NO_MEM_OPT"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "OPTIMIZERS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "OPTIMIZE_TENSOR_LAYOUT_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-run-metadata.pbtxt b/tensorflow/tools/api/golden/tensorflow.-run-metadata.pbtxt
new file mode 100644
index 00000000000..808fa0fa217
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-run-metadata.pbtxt
@@ -0,0 +1,88 @@
+path: "tensorflow.RunMetadata"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.config_pb2.RunMetadata\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "COST_GRAPH_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "PARTITION_GRAPHS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "STEP_STATS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-run-options.pbtxt b/tensorflow/tools/api/golden/tensorflow.-run-options.pbtxt
new file mode 100644
index 00000000000..5ad6804a78c
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-run-options.pbtxt
@@ -0,0 +1,116 @@
+path: "tensorflow.RunOptions"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.config_pb2.RunOptions\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DEBUG_OPTIONS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FULL_TRACE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "HARDWARE_TRACE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "INTER_OP_THREAD_POOL_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "NO_TRACE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "OUTPUT_PARTITION_GRAPHS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SOFTWARE_TRACE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TIMEOUT_IN_MS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TRACE_LEVEL_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TraceLevel"
+    mtype: "<class \'google.protobuf.internal.enum_type_wrapper.EnumTypeWrapper\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-session-log.pbtxt b/tensorflow/tools/api/golden/tensorflow.-session-log.pbtxt
new file mode 100644
index 00000000000..ec66d7f3354
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-session-log.pbtxt
@@ -0,0 +1,108 @@
+path: "tensorflow.SessionLog"
+tf_class {
+  is_instance: "<class \'tensorflow.core.util.event_pb2.SessionLog\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "CHECKPOINT"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "CHECKPOINT_PATH_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "MSG_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "START"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "STATUS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "STATUS_UNSPECIFIED"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "STOP"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SessionStatus"
+    mtype: "<class \'google.protobuf.internal.enum_type_wrapper.EnumTypeWrapper\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-session.pbtxt b/tensorflow/tools/api/golden/tensorflow.-session.pbtxt
new file mode 100644
index 00000000000..f5c597548f4
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-session.pbtxt
@@ -0,0 +1,47 @@
+path: "tensorflow.Session"
+tf_class {
+  is_instance: "<class \'tensorflow.python.client.session.Session\'>"
+  is_instance: "<class \'tensorflow.python.client.session.BaseSession\'>"
+  is_instance: "<class \'tensorflow.python.client.session.SessionInterface\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "graph"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "graph_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "sess_str"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'target\', \'graph\', \'config\'], varargs=None, keywords=None, defaults=[\'\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "as_default"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "partial_run"
+    argspec: "args=[\'self\', \'handle\', \'fetches\', \'feed_dict\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "partial_run_setup"
+    argspec: "args=[\'self\', \'fetches\', \'feeds\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "reset"
+    argspec: "args=[\'target\', \'containers\', \'config\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "run"
+    argspec: "args=[\'self\', \'fetches\', \'feed_dict\', \'options\', \'run_metadata\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-sparse-conditional-accumulator.pbtxt b/tensorflow/tools/api/golden/tensorflow.-sparse-conditional-accumulator.pbtxt
new file mode 100644
index 00000000000..2260279ad2b
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-sparse-conditional-accumulator.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.SparseConditionalAccumulator"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.SparseConditionalAccumulator\'>"
+  is_instance: "<class \'tensorflow.python.ops.data_flow_ops.ConditionalAccumulatorBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "accumulator_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'dtype\', \'shape\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'sparse_conditional_accumulator\'], "
+  }
+  member_method {
+    name: "apply_grad"
+    argspec: "args=[\'self\', \'grad_indices\', \'grad_values\', \'grad_shape\', \'local_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'None\'], "
+  }
+  member_method {
+    name: "apply_indexed_slices_grad"
+    argspec: "args=[\'self\', \'grad\', \'local_step\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'None\'], "
+  }
+  member_method {
+    name: "num_accumulated"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "set_global_step"
+    argspec: "args=[\'self\', \'new_global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "take_grad"
+    argspec: "args=[\'self\', \'num_required\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "take_indexed_slices_grad"
+    argspec: "args=[\'self\', \'num_required\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-sparse-feature.pbtxt b/tensorflow/tools/api/golden/tensorflow.-sparse-feature.pbtxt
new file mode 100644
index 00000000000..d875394fb5d
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-sparse-feature.pbtxt
@@ -0,0 +1,35 @@
+path: "tensorflow.SparseFeature"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.parsing_ops.SparseFeature\'>"
+  is_instance: "<class \'tensorflow.python.ops.parsing_ops.SparseFeature\'>"
+  is_instance: "<type \'tuple\'>"
+  member {
+    name: "already_sorted"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "index_key"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "size"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "value_key"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "count"
+  }
+  member_method {
+    name: "index"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-sparse-tensor-value.pbtxt b/tensorflow/tools/api/golden/tensorflow.-sparse-tensor-value.pbtxt
new file mode 100644
index 00000000000..d33fd4d5d7b
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-sparse-tensor-value.pbtxt
@@ -0,0 +1,26 @@
+path: "tensorflow.SparseTensorValue"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.sparse_tensor.SparseTensorValue\'>"
+  is_instance: "<type \'tuple\'>"
+  member {
+    name: "dense_shape"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "indices"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "values"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "count"
+  }
+  member_method {
+    name: "index"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-sparse-tensor.pbtxt b/tensorflow/tools/api/golden/tensorflow.-sparse-tensor.pbtxt
new file mode 100644
index 00000000000..eac236d4982
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-sparse-tensor.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.SparseTensor"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.sparse_tensor.SparseTensor\'>"
+  is_instance: "<class \'tensorflow.python.framework.ops._TensorLike\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "dense_shape"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "graph"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "indices"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "values"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'indices\', \'values\', \'dense_shape\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "eval"
+    argspec: "args=[\'self\', \'feed_dict\', \'session\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "from_value"
+    argspec: "args=[\'cls\', \'sparse_tensor_value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_shape"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-summary.-audio.pbtxt b/tensorflow/tools/api/golden/tensorflow.-summary.-audio.pbtxt
new file mode 100644
index 00000000000..781010d75e2
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-summary.-audio.pbtxt
@@ -0,0 +1,96 @@
+path: "tensorflow.Summary.Audio"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.summary_pb2.Audio\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "CONTENT_TYPE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "ENCODED_AUDIO_STRING_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "LENGTH_FRAMES_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "NUM_CHANNELS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SAMPLE_RATE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-summary.-image.pbtxt b/tensorflow/tools/api/golden/tensorflow.-summary.-image.pbtxt
new file mode 100644
index 00000000000..feb9c7ee927
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-summary.-image.pbtxt
@@ -0,0 +1,92 @@
+path: "tensorflow.Summary.Image"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.summary_pb2.Image\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "COLORSPACE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "ENCODED_IMAGE_STRING_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "HEIGHT_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "WIDTH_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-summary.-value.pbtxt b/tensorflow/tools/api/golden/tensorflow.-summary.-value.pbtxt
new file mode 100644
index 00000000000..d02fb9ecd48
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-summary.-value.pbtxt
@@ -0,0 +1,108 @@
+path: "tensorflow.Summary.Value"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.summary_pb2.Value\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "AUDIO_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "HISTO_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "IMAGE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "NODE_NAME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "OBSOLETE_OLD_STYLE_HISTOGRAM_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SIMPLE_VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TAG_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TENSOR_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
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+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-summary.pbtxt b/tensorflow/tools/api/golden/tensorflow.-summary.pbtxt
new file mode 100644
index 00000000000..38de17fa9e5
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-summary.pbtxt
@@ -0,0 +1,92 @@
+path: "tensorflow.Summary"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.summary_pb2.Summary\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "Audio"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "Image"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Value"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
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+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
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+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-t-f-record-reader.pbtxt b/tensorflow/tools/api/golden/tensorflow.-t-f-record-reader.pbtxt
new file mode 100644
index 00000000000..cdf79373919
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-t-f-record-reader.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.TFRecordReader"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.io_ops.TFRecordReader\'>"
+  is_instance: "<class \'tensorflow.python.ops.io_ops.ReaderBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "reader_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "supports_serialize"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'name\', \'options\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
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+    name: "num_records_produced"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "num_work_units_completed"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read"
+    argspec: "args=[\'self\', \'queue\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read_up_to"
+    argspec: "args=[\'self\', \'queue\', \'num_records\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "reset"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "restore_state"
+    argspec: "args=[\'self\', \'state\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "serialize_state"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-tensor-array.pbtxt b/tensorflow/tools/api/golden/tensorflow.-tensor-array.pbtxt
new file mode 100644
index 00000000000..a0fad4df524
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-tensor-array.pbtxt
@@ -0,0 +1,69 @@
+path: "tensorflow.TensorArray"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.tensor_array_ops.TensorArray\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "flow"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "handle"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'dtype\', \'size\', \'dynamic_size\', \'clear_after_read\', \'tensor_array_name\', \'handle\', \'flow\', \'infer_shape\', \'element_shape\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'True\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "concat"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
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+    argspec: "args=[\'self\', \'indices\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "grad"
+    argspec: "args=[\'self\', \'source\', \'flow\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "identity"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "read"
+    argspec: "args=[\'self\', \'index\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
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+    argspec: "args=[\'self\', \'indices\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "size"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "split"
+    argspec: "args=[\'self\', \'value\', \'lengths\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "stack"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "unstack"
+    argspec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "write"
+    argspec: "args=[\'self\', \'index\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-tensor-info.pbtxt b/tensorflow/tools/api/golden/tensorflow.-tensor-info.pbtxt
new file mode 100644
index 00000000000..87632fb7b9e
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-tensor-info.pbtxt
@@ -0,0 +1,88 @@
+path: "tensorflow.TensorInfo"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.meta_graph_pb2.TensorInfo\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "DTYPE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "NAME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TENSOR_SHAPE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-tensor-shape.pbtxt b/tensorflow/tools/api/golden/tensorflow.-tensor-shape.pbtxt
new file mode 100644
index 00000000000..d5b9cb8f5ed
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-tensor-shape.pbtxt
@@ -0,0 +1,73 @@
+path: "tensorflow.TensorShape"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.tensor_shape.TensorShape\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "dims"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "ndims"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'dims\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "as_list"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "as_proto"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "assert_has_rank"
+    argspec: "args=[\'self\', \'rank\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "assert_is_compatible_with"
+    argspec: "args=[\'self\', \'other\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "assert_is_fully_defined"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "assert_same_rank"
+    argspec: "args=[\'self\', \'other\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "concatenate"
+    argspec: "args=[\'self\', \'other\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "is_compatible_with"
+    argspec: "args=[\'self\', \'other\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "is_fully_defined"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "merge_with"
+    argspec: "args=[\'self\', \'other\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "num_elements"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "with_rank"
+    argspec: "args=[\'self\', \'rank\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "with_rank_at_least"
+    argspec: "args=[\'self\', \'rank\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "with_rank_at_most"
+    argspec: "args=[\'self\', \'rank\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-tensor.pbtxt b/tensorflow/tools/api/golden/tensorflow.-tensor.pbtxt
new file mode 100644
index 00000000000..38d19bb5374
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-tensor.pbtxt
@@ -0,0 +1,58 @@
+path: "tensorflow.Tensor"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.ops.Tensor\'>"
+  is_instance: "<class \'tensorflow.python.framework.ops._TensorLike\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "OVERLOADABLE_OPERATORS"
+    mtype: "<type \'set\'>"
+  }
+  member {
+    name: "device"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "graph"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "shape"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "value_index"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'op\', \'value_index\', \'dtype\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "consumers"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "eval"
+    argspec: "args=[\'self\', \'feed_dict\', \'session\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "get_shape"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "set_shape"
+    argspec: "args=[\'self\', \'shape\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-text-line-reader.pbtxt b/tensorflow/tools/api/golden/tensorflow.-text-line-reader.pbtxt
new file mode 100644
index 00000000000..e9779f07620
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-text-line-reader.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.TextLineReader"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.io_ops.TextLineReader\'>"
+  is_instance: "<class \'tensorflow.python.ops.io_ops.ReaderBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "reader_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "supports_serialize"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'skip_header_lines\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "num_records_produced"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "num_work_units_completed"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read"
+    argspec: "args=[\'self\', \'queue\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read_up_to"
+    argspec: "args=[\'self\', \'queue\', \'num_records\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "reset"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "restore_state"
+    argspec: "args=[\'self\', \'state\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "serialize_state"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-var-len-feature.pbtxt b/tensorflow/tools/api/golden/tensorflow.-var-len-feature.pbtxt
new file mode 100644
index 00000000000..54b66f43f8e
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-var-len-feature.pbtxt
@@ -0,0 +1,19 @@
+path: "tensorflow.VarLenFeature"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.parsing_ops.VarLenFeature\'>"
+  is_instance: "<class \'tensorflow.python.ops.parsing_ops.VarLenFeature\'>"
+  is_instance: "<type \'tuple\'>"
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "count"
+  }
+  member_method {
+    name: "index"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-variable-scope.pbtxt b/tensorflow/tools/api/golden/tensorflow.-variable-scope.pbtxt
new file mode 100644
index 00000000000..c9b2dfd6772
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-variable-scope.pbtxt
@@ -0,0 +1,97 @@
+path: "tensorflow.VariableScope"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.variable_scope.VariableScope\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "caching_device"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "custom_getter"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "initializer"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "original_name_scope"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "partitioner"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "regularizer"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "reuse"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "use_resource"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'reuse\', \'name\', \'initializer\', \'regularizer\', \'caching_device\', \'partitioner\', \'custom_getter\', \'name_scope\', \'dtype\', \'use_resource\'], varargs=None, keywords=None, defaults=[\'\', \'None\', \'None\', \'None\', \'None\', \'None\', \'\', \"<dtype: \'float32\'>\", \'None\'], "
+  }
+  member_method {
+    name: "get_collection"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_variable"
+    argspec: "args=[\'self\', \'var_store\', \'name\', \'shape\', \'dtype\', \'initializer\', \'regularizer\', \'reuse\', \'trainable\', \'collections\', \'caching_device\', \'partitioner\', \'validate_shape\', \'use_resource\', \'custom_getter\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'True\', \'None\', \'None\', \'None\', \'True\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "global_variables"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "reuse_variables"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "set_caching_device"
+    argspec: "args=[\'self\', \'caching_device\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "set_custom_getter"
+    argspec: "args=[\'self\', \'custom_getter\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "set_dtype"
+    argspec: "args=[\'self\', \'dtype\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "set_initializer"
+    argspec: "args=[\'self\', \'initializer\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "set_partitioner"
+    argspec: "args=[\'self\', \'partitioner\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "set_regularizer"
+    argspec: "args=[\'self\', \'regularizer\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "set_use_resource"
+    argspec: "args=[\'self\', \'use_resource\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "trainable_variables"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-variable.-save-slice-info.pbtxt b/tensorflow/tools/api/golden/tensorflow.-variable.-save-slice-info.pbtxt
new file mode 100644
index 00000000000..ac3ccd468b2
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-variable.-save-slice-info.pbtxt
@@ -0,0 +1,17 @@
+path: "tensorflow.Variable.SaveSliceInfo"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.variables.SaveSliceInfo\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "spec"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'full_name\', \'full_shape\', \'var_offset\', \'var_shape\', \'save_slice_info_def\', \'import_scope\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "to_proto"
+    argspec: "args=[\'self\', \'export_scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-variable.pbtxt b/tensorflow/tools/api/golden/tensorflow.-variable.pbtxt
new file mode 100644
index 00000000000..d67a2713f7a
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-variable.pbtxt
@@ -0,0 +1,101 @@
+path: "tensorflow.Variable"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.variables.Variable\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "SaveSliceInfo"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "device"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "dtype"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "graph"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "initial_value"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "initializer"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "shape"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'initial_value\', \'trainable\', \'collections\', \'validate_shape\', \'caching_device\', \'name\', \'variable_def\', \'dtype\', \'expected_shape\', \'import_scope\'], varargs=None, keywords=None, defaults=[\'None\', \'True\', \'None\', \'True\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "assign"
+    argspec: "args=[\'self\', \'value\', \'use_locking\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
+  member_method {
+    name: "assign_add"
+    argspec: "args=[\'self\', \'delta\', \'use_locking\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
+  member_method {
+    name: "assign_sub"
+    argspec: "args=[\'self\', \'delta\', \'use_locking\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
+  member_method {
+    name: "count_up_to"
+    argspec: "args=[\'self\', \'limit\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "eval"
+    argspec: "args=[\'self\', \'session\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "from_proto"
+    argspec: "args=[\'variable_def\', \'import_scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_shape"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "initialized_value"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "load"
+    argspec: "args=[\'self\', \'value\', \'session\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read_value"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "scatter_sub"
+    argspec: "args=[\'self\', \'sparse_delta\', \'use_locking\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
+  member_method {
+    name: "set_shape"
+    argspec: "args=[\'self\', \'shape\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "to_proto"
+    argspec: "args=[\'self\', \'export_scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "value"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.-whole-file-reader.pbtxt b/tensorflow/tools/api/golden/tensorflow.-whole-file-reader.pbtxt
new file mode 100644
index 00000000000..4ac759891c6
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.-whole-file-reader.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.WholeFileReader"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.io_ops.WholeFileReader\'>"
+  is_instance: "<class \'tensorflow.python.ops.io_ops.ReaderBase\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "reader_ref"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "supports_serialize"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "num_records_produced"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "num_work_units_completed"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read"
+    argspec: "args=[\'self\', \'queue\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read_up_to"
+    argspec: "args=[\'self\', \'queue\', \'num_records\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "reset"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "restore_state"
+    argspec: "args=[\'self\', \'state\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "serialize_state"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.app.pbtxt b/tensorflow/tools/api/golden/tensorflow.app.pbtxt
new file mode 100644
index 00000000000..85044a89879
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.app.pbtxt
@@ -0,0 +1,11 @@
+path: "tensorflow.app"
+tf_module {
+  member {
+    name: "flags"
+    mtype: "<type \'module\'>"
+  }
+  member_method {
+    name: "run"
+    argspec: "args=[\'main\', \'argv\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.compat.pbtxt b/tensorflow/tools/api/golden/tensorflow.compat.pbtxt
new file mode 100644
index 00000000000..ccc60314001
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.compat.pbtxt
@@ -0,0 +1,35 @@
+path: "tensorflow.compat"
+tf_module {
+  member {
+    name: "bytes_or_text_types"
+    mtype: "<type \'tuple\'>"
+  }
+  member {
+    name: "complex_types"
+    mtype: "<type \'tuple\'>"
+  }
+  member {
+    name: "integral_types"
+    mtype: "<type \'tuple\'>"
+  }
+  member {
+    name: "real_types"
+    mtype: "<type \'tuple\'>"
+  }
+  member_method {
+    name: "as_bytes"
+    argspec: "args=[\'bytes_or_text\', \'encoding\'], varargs=None, keywords=None, defaults=[\'utf-8\'], "
+  }
+  member_method {
+    name: "as_str"
+    argspec: "args=[\'bytes_or_text\', \'encoding\'], varargs=None, keywords=None, defaults=[\'utf-8\'], "
+  }
+  member_method {
+    name: "as_str_any"
+    argspec: "args=[\'value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "as_text"
+    argspec: "args=[\'bytes_or_text\', \'encoding\'], varargs=None, keywords=None, defaults=[\'utf-8\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.constant_initializer.pbtxt b/tensorflow/tools/api/golden/tensorflow.constant_initializer.pbtxt
new file mode 100644
index 00000000000..d34bfe51479
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.constant_initializer.pbtxt
@@ -0,0 +1,10 @@
+path: "tensorflow.constant_initializer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Constant\'>"
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Initializer\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'value\', \'dtype\', \'verify_shape\'], varargs=None, keywords=None, defaults=[\'0\', \"<dtype: \'float32\'>\", \'False\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-aborted-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-aborted-error.pbtxt
new file mode 100644
index 00000000000..ea9186b0b9d
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-aborted-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.AbortedError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.AbortedError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-already-exists-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-already-exists-error.pbtxt
new file mode 100644
index 00000000000..4e155081dd2
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-already-exists-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.AlreadyExistsError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.AlreadyExistsError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-cancelled-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-cancelled-error.pbtxt
new file mode 100644
index 00000000000..b02a0e023aa
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-cancelled-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.CancelledError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.CancelledError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-data-loss-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-data-loss-error.pbtxt
new file mode 100644
index 00000000000..c1fa66342a7
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-data-loss-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.DataLossError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.DataLossError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-deadline-exceeded-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-deadline-exceeded-error.pbtxt
new file mode 100644
index 00000000000..8e037936191
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-deadline-exceeded-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.DeadlineExceededError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.DeadlineExceededError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-failed-precondition-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-failed-precondition-error.pbtxt
new file mode 100644
index 00000000000..384d4b534c6
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-failed-precondition-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.FailedPreconditionError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.FailedPreconditionError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-internal-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-internal-error.pbtxt
new file mode 100644
index 00000000000..ac5c4d7879b
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-internal-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.InternalError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.InternalError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-invalid-argument-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-invalid-argument-error.pbtxt
new file mode 100644
index 00000000000..161edd4a7c5
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-invalid-argument-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.InvalidArgumentError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.InvalidArgumentError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-not-found-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-not-found-error.pbtxt
new file mode 100644
index 00000000000..1e64730ac6d
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-not-found-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.NotFoundError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.NotFoundError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-op-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-op-error.pbtxt
new file mode 100644
index 00000000000..b1f14c0457d
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-op-error.pbtxt
@@ -0,0 +1,29 @@
+path: "tensorflow.errors.OpError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\', \'error_code\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-out-of-range-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-out-of-range-error.pbtxt
new file mode 100644
index 00000000000..6365e472868
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-out-of-range-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.OutOfRangeError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OutOfRangeError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-permission-denied-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-permission-denied-error.pbtxt
new file mode 100644
index 00000000000..dc8a66f9ead
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-permission-denied-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.PermissionDeniedError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.PermissionDeniedError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-resource-exhausted-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-resource-exhausted-error.pbtxt
new file mode 100644
index 00000000000..85bb384b469
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-resource-exhausted-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.ResourceExhaustedError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.ResourceExhaustedError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-unauthenticated-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-unauthenticated-error.pbtxt
new file mode 100644
index 00000000000..d57d7ac2f20
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-unauthenticated-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.UnauthenticatedError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.UnauthenticatedError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-unavailable-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-unavailable-error.pbtxt
new file mode 100644
index 00000000000..cc33e6ed8d1
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-unavailable-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.UnavailableError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.UnavailableError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-unimplemented-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-unimplemented-error.pbtxt
new file mode 100644
index 00000000000..b8c2e22dbd7
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-unimplemented-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.UnimplementedError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.UnimplementedError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.-unknown-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.-unknown-error.pbtxt
new file mode 100644
index 00000000000..8ffcfae95b8
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.-unknown-error.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.errors.UnknownError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.UnknownError\'>"
+  is_instance: "<class \'tensorflow.python.framework.errors_impl.OpError\'>"
+  is_instance: "<type \'exceptions.Exception\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "error_code"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "node_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'node_def\', \'op\', \'message\', \'error_code\'], varargs=None, keywords=None, defaults=[\'2\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.errors.pbtxt b/tensorflow/tools/api/golden/tensorflow.errors.pbtxt
new file mode 100644
index 00000000000..0ad1c19603b
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.errors.pbtxt
@@ -0,0 +1,151 @@
+path: "tensorflow.errors"
+tf_module {
+  member {
+    name: "ABORTED"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "ALREADY_EXISTS"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "AbortedError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "AlreadyExistsError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "CANCELLED"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "CancelledError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "DATA_LOSS"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DEADLINE_EXCEEDED"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DataLossError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "DeadlineExceededError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "FAILED_PRECONDITION"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "FailedPreconditionError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "INTERNAL"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "INVALID_ARGUMENT"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "InternalError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "InvalidArgumentError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "NOT_FOUND"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "NotFoundError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "OK"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "OUT_OF_RANGE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "OpError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "OutOfRangeError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "PERMISSION_DENIED"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "PermissionDeniedError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "RESOURCE_EXHAUSTED"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "ResourceExhaustedError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "UNAUTHENTICATED"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "UNAVAILABLE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "UNIMPLEMENTED"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "UNKNOWN"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "UnauthenticatedError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "UnavailableError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "UnimplementedError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "UnknownError"
+    mtype: "<type \'type\'>"
+  }
+  member_method {
+    name: "error_code_from_exception_type"
+    argspec: "args=[\'cls\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "exception_type_from_error_code"
+    argspec: "args=[\'error_code\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "raise_exception_on_not_ok_status"
+    argspec: "args=[], varargs=args, keywords=kwds, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.-estimator-spec.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.-estimator-spec.pbtxt
new file mode 100644
index 00000000000..5dbfe217264
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.-estimator-spec.pbtxt
@@ -0,0 +1,47 @@
+path: "tensorflow.estimator.EstimatorSpec"
+tf_class {
+  is_instance: "<class \'tensorflow.python.estimator.model_fn.EstimatorSpec\'>"
+  is_instance: "<class \'tensorflow.python.estimator.model_fn.EstimatorSpec\'>"
+  is_instance: "<type \'tuple\'>"
+  member {
+    name: "eval_metric_ops"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "export_outputs"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "loss"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "predictions"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "scaffold"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "train_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "training_chief_hooks"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "training_hooks"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "count"
+  }
+  member_method {
+    name: "index"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.-estimator.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.-estimator.pbtxt
new file mode 100644
index 00000000000..7a769fd546c
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.-estimator.pbtxt
@@ -0,0 +1,37 @@
+path: "tensorflow.estimator.Estimator"
+tf_class {
+  is_instance: "<class \'tensorflow.python.estimator.estimator.Estimator\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "config"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "model_dir"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "params"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'model_fn\', \'model_dir\', \'config\', \'params\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "evaluate"
+    argspec: "args=[\'self\', \'input_fn\', \'steps\', \'hooks\', \'checkpoint_path\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "export_savedmodel"
+    argspec: "args=[\'self\', \'export_dir_base\', \'serving_input_receiver_fn\', \'assets_extra\', \'as_text\', \'checkpoint_path\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "predict"
+    argspec: "args=[\'self\', \'input_fn\', \'predict_keys\', \'hooks\', \'checkpoint_path\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "train"
+    argspec: "args=[\'self\', \'input_fn\', \'hooks\', \'steps\', \'max_steps\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.-mode-keys.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.-mode-keys.pbtxt
new file mode 100644
index 00000000000..6a1c24fa63f
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.-mode-keys.pbtxt
@@ -0,0 +1,20 @@
+path: "tensorflow.estimator.ModeKeys"
+tf_class {
+  is_instance: "<class \'tensorflow.python.estimator.model_fn.ModeKeys\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "EVAL"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "PREDICT"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "TRAIN"
+    mtype: "<type \'str\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.-run-config.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.-run-config.pbtxt
new file mode 100644
index 00000000000..8fd991a317b
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.-run-config.pbtxt
@@ -0,0 +1,68 @@
+path: "tensorflow.estimator.RunConfig"
+tf_class {
+  is_instance: "<class \'tensorflow.python.estimator.run_config.RunConfig\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "cluster_spec"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "evaluation_master"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "is_chief"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "keep_checkpoint_every_n_hours"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "keep_checkpoint_max"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "master"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "num_ps_replicas"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "num_worker_replicas"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "save_checkpoints_secs"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "save_checkpoints_steps"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "save_summary_steps"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "session_config"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "task_id"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "task_type"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "tf_random_seed"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.export.-classification-output.__metaclass__.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.export.-classification-output.__metaclass__.pbtxt
new file mode 100644
index 00000000000..3cf7af8da95
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.export.-classification-output.__metaclass__.pbtxt
@@ -0,0 +1,14 @@
+path: "tensorflow.estimator.export.ClassificationOutput.__metaclass__"
+tf_class {
+  is_instance: "<class \'abc.ABCMeta\'>"
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "mro"
+  }
+  member_method {
+    name: "register"
+    argspec: "args=[\'cls\', \'subclass\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.export.-classification-output.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.export.-classification-output.pbtxt
new file mode 100644
index 00000000000..2df1840c4a4
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.export.-classification-output.pbtxt
@@ -0,0 +1,22 @@
+path: "tensorflow.estimator.export.ClassificationOutput"
+tf_class {
+  is_instance: "<class \'tensorflow.python.estimator.export.export_output.ClassificationOutput\'>"
+  is_instance: "<class \'tensorflow.python.estimator.export.export_output.ExportOutput\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "classes"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "scores"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'scores\', \'classes\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "as_signature_def"
+    argspec: "args=[\'self\', \'receiver_tensors\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.export.-export-output.__metaclass__.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.export.-export-output.__metaclass__.pbtxt
new file mode 100644
index 00000000000..5d165ccbf91
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.export.-export-output.__metaclass__.pbtxt
@@ -0,0 +1,14 @@
+path: "tensorflow.estimator.export.ExportOutput.__metaclass__"
+tf_class {
+  is_instance: "<class \'abc.ABCMeta\'>"
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "mro"
+  }
+  member_method {
+    name: "register"
+    argspec: "args=[\'cls\', \'subclass\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.export.-export-output.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.export.-export-output.pbtxt
new file mode 100644
index 00000000000..fa62e8ced80
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.export.-export-output.pbtxt
@@ -0,0 +1,12 @@
+path: "tensorflow.estimator.export.ExportOutput"
+tf_class {
+  is_instance: "<class \'tensorflow.python.estimator.export.export_output.ExportOutput\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "as_signature_def"
+    argspec: "args=[\'self\', \'receiver_tensors\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.export.-predict-output.__metaclass__.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.export.-predict-output.__metaclass__.pbtxt
new file mode 100644
index 00000000000..743495ba98c
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.export.-predict-output.__metaclass__.pbtxt
@@ -0,0 +1,14 @@
+path: "tensorflow.estimator.export.PredictOutput.__metaclass__"
+tf_class {
+  is_instance: "<class \'abc.ABCMeta\'>"
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "mro"
+  }
+  member_method {
+    name: "register"
+    argspec: "args=[\'cls\', \'subclass\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.export.-predict-output.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.export.-predict-output.pbtxt
new file mode 100644
index 00000000000..e0160b10ce1
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.export.-predict-output.pbtxt
@@ -0,0 +1,18 @@
+path: "tensorflow.estimator.export.PredictOutput"
+tf_class {
+  is_instance: "<class \'tensorflow.python.estimator.export.export_output.PredictOutput\'>"
+  is_instance: "<class \'tensorflow.python.estimator.export.export_output.ExportOutput\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "outputs"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'outputs\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "as_signature_def"
+    argspec: "args=[\'self\', \'receiver_tensors\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.export.-regression-output.__metaclass__.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.export.-regression-output.__metaclass__.pbtxt
new file mode 100644
index 00000000000..dbf4e3dec85
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.export.-regression-output.__metaclass__.pbtxt
@@ -0,0 +1,14 @@
+path: "tensorflow.estimator.export.RegressionOutput.__metaclass__"
+tf_class {
+  is_instance: "<class \'abc.ABCMeta\'>"
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "mro"
+  }
+  member_method {
+    name: "register"
+    argspec: "args=[\'cls\', \'subclass\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.export.-regression-output.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.export.-regression-output.pbtxt
new file mode 100644
index 00000000000..905f0e05535
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.export.-regression-output.pbtxt
@@ -0,0 +1,18 @@
+path: "tensorflow.estimator.export.RegressionOutput"
+tf_class {
+  is_instance: "<class \'tensorflow.python.estimator.export.export_output.RegressionOutput\'>"
+  is_instance: "<class \'tensorflow.python.estimator.export.export_output.ExportOutput\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "value"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "as_signature_def"
+    argspec: "args=[\'self\', \'receiver_tensors\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.export.-serving-input-receiver.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.export.-serving-input-receiver.pbtxt
new file mode 100644
index 00000000000..0d9e0443088
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.export.-serving-input-receiver.pbtxt
@@ -0,0 +1,23 @@
+path: "tensorflow.estimator.export.ServingInputReceiver"
+tf_class {
+  is_instance: "<class \'tensorflow.python.estimator.export.export.ServingInputReceiver\'>"
+  is_instance: "<class \'tensorflow.python.estimator.export.export.ServingInputReceiver\'>"
+  is_instance: "<type \'tuple\'>"
+  member {
+    name: "features"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "receiver_tensors"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "count"
+  }
+  member_method {
+    name: "index"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.export.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.export.pbtxt
new file mode 100644
index 00000000000..4d0dddb3bc0
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.export.pbtxt
@@ -0,0 +1,31 @@
+path: "tensorflow.estimator.export"
+tf_module {
+  member {
+    name: "ClassificationOutput"
+    mtype: "<class \'abc.ABCMeta\'>"
+  }
+  member {
+    name: "ExportOutput"
+    mtype: "<class \'abc.ABCMeta\'>"
+  }
+  member {
+    name: "PredictOutput"
+    mtype: "<class \'abc.ABCMeta\'>"
+  }
+  member {
+    name: "RegressionOutput"
+    mtype: "<class \'abc.ABCMeta\'>"
+  }
+  member {
+    name: "ServingInputReceiver"
+    mtype: "<type \'type\'>"
+  }
+  member_method {
+    name: "build_parsing_serving_input_receiver_fn"
+    argspec: "args=[\'feature_spec\', \'default_batch_size\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "build_raw_serving_input_receiver_fn"
+    argspec: "args=[\'features\', \'default_batch_size\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.inputs.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.inputs.pbtxt
new file mode 100644
index 00000000000..b318fea1f82
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.inputs.pbtxt
@@ -0,0 +1,11 @@
+path: "tensorflow.estimator.inputs"
+tf_module {
+  member_method {
+    name: "numpy_input_fn"
+    argspec: "args=[\'x\', \'y\', \'batch_size\', \'num_epochs\', \'shuffle\', \'queue_capacity\', \'num_threads\'], varargs=None, keywords=None, defaults=[\'None\', \'128\', \'1\', \'None\', \'1000\', \'1\'], "
+  }
+  member_method {
+    name: "pandas_input_fn"
+    argspec: "args=[\'x\', \'y\', \'batch_size\', \'num_epochs\', \'shuffle\', \'queue_capacity\', \'num_threads\', \'target_column\'], varargs=None, keywords=None, defaults=[\'None\', \'128\', \'1\', \'None\', \'1000\', \'1\', \'target\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.estimator.pbtxt b/tensorflow/tools/api/golden/tensorflow.estimator.pbtxt
new file mode 100644
index 00000000000..0d5dc73271d
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.estimator.pbtxt
@@ -0,0 +1,27 @@
+path: "tensorflow.estimator"
+tf_module {
+  member {
+    name: "Estimator"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "EstimatorSpec"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "ModeKeys"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "RunConfig"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "export"
+    mtype: "<type \'module\'>"
+  }
+  member {
+    name: "inputs"
+    mtype: "<type \'module\'>"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.gfile.-fast-g-file.pbtxt b/tensorflow/tools/api/golden/tensorflow.gfile.-fast-g-file.pbtxt
new file mode 100644
index 00000000000..41497dc8699
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.gfile.-fast-g-file.pbtxt
@@ -0,0 +1,58 @@
+path: "tensorflow.gfile.FastGFile"
+tf_class {
+  is_instance: "<class \'tensorflow.python.platform.gfile.FastGFile\'>"
+  is_instance: "<class \'tensorflow.python.lib.io.file_io.FileIO\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "mode"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'name\', \'mode\'], varargs=None, keywords=None, defaults=[\'r\'], "
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "flush"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "next"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "read"
+    argspec: "args=[\'self\', \'n\'], varargs=None, keywords=None, defaults=[\'-1\'], "
+  }
+  member_method {
+    name: "readline"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "readlines"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "seek"
+    argspec: "args=[\'self\', \'position\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "size"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "tell"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "write"
+    argspec: "args=[\'self\', \'file_content\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.gfile.-g-file.pbtxt b/tensorflow/tools/api/golden/tensorflow.gfile.-g-file.pbtxt
new file mode 100644
index 00000000000..bab0f279b24
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.gfile.-g-file.pbtxt
@@ -0,0 +1,58 @@
+path: "tensorflow.gfile.GFile"
+tf_class {
+  is_instance: "<class \'tensorflow.python.platform.gfile.GFile\'>"
+  is_instance: "<class \'tensorflow.python.lib.io.file_io.FileIO\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "mode"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'name\', \'mode\'], varargs=None, keywords=None, defaults=[\'r\'], "
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "flush"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "next"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "read"
+    argspec: "args=[\'self\', \'n\'], varargs=None, keywords=None, defaults=[\'-1\'], "
+  }
+  member_method {
+    name: "readline"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "readlines"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "seek"
+    argspec: "args=[\'self\', \'position\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "size"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "tell"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "write"
+    argspec: "args=[\'self\', \'file_content\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.gfile.-open.pbtxt b/tensorflow/tools/api/golden/tensorflow.gfile.-open.pbtxt
new file mode 100644
index 00000000000..86e577c19a8
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.gfile.-open.pbtxt
@@ -0,0 +1,58 @@
+path: "tensorflow.gfile.Open"
+tf_class {
+  is_instance: "<class \'tensorflow.python.platform.gfile.GFile\'>"
+  is_instance: "<class \'tensorflow.python.lib.io.file_io.FileIO\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "mode"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'name\', \'mode\'], varargs=None, keywords=None, defaults=[\'r\'], "
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "flush"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "next"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "read"
+    argspec: "args=[\'self\', \'n\'], varargs=None, keywords=None, defaults=[\'-1\'], "
+  }
+  member_method {
+    name: "readline"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "readlines"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "seek"
+    argspec: "args=[\'self\', \'position\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "size"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "tell"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "write"
+    argspec: "args=[\'self\', \'file_content\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.gfile.pbtxt b/tensorflow/tools/api/golden/tensorflow.gfile.pbtxt
new file mode 100644
index 00000000000..65b55a8b7c4
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.gfile.pbtxt
@@ -0,0 +1,63 @@
+path: "tensorflow.gfile"
+tf_module {
+  member {
+    name: "FastGFile"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "GFile"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Open"
+    mtype: "<type \'type\'>"
+  }
+  member_method {
+    name: "Copy"
+    argspec: "args=[\'oldpath\', \'newpath\', \'overwrite\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
+  member_method {
+    name: "DeleteRecursively"
+    argspec: "args=[\'dirname\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "Exists"
+    argspec: "args=[\'filename\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "Glob"
+    argspec: "args=[\'filename\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "IsDirectory"
+    argspec: "args=[\'dirname\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "ListDirectory"
+    argspec: "args=[\'dirname\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "MakeDirs"
+    argspec: "args=[\'dirname\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "MkDir"
+    argspec: "args=[\'dirname\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "Remove"
+    argspec: "args=[\'filename\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "Rename"
+    argspec: "args=[\'oldname\', \'newname\', \'overwrite\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
+  member_method {
+    name: "Stat"
+    argspec: "args=[\'filename\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "Walk"
+    argspec: "args=[\'top\', \'in_order\'], varargs=None, keywords=None, defaults=[\'True\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.graph_util.pbtxt b/tensorflow/tools/api/golden/tensorflow.graph_util.pbtxt
new file mode 100644
index 00000000000..76a2df757e7
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.graph_util.pbtxt
@@ -0,0 +1,23 @@
+path: "tensorflow.graph_util"
+tf_module {
+  member_method {
+    name: "convert_variables_to_constants"
+    argspec: "args=[\'sess\', \'input_graph_def\', \'output_node_names\', \'variable_names_whitelist\', \'variable_names_blacklist\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "extract_sub_graph"
+    argspec: "args=[\'graph_def\', \'dest_nodes\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "must_run_on_cpu"
+    argspec: "args=[\'node\', \'pin_variables_on_cpu\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
+  member_method {
+    name: "remove_training_nodes"
+    argspec: "args=[\'input_graph\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "tensor_shape_from_node_def_name"
+    argspec: "args=[\'graph\', \'input_name\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.image.-resize-method.pbtxt b/tensorflow/tools/api/golden/tensorflow.image.-resize-method.pbtxt
new file mode 100644
index 00000000000..dbc360b13ee
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.image.-resize-method.pbtxt
@@ -0,0 +1,24 @@
+path: "tensorflow.image.ResizeMethod"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.image_ops_impl.ResizeMethod\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "AREA"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "BICUBIC"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "BILINEAR"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "NEAREST_NEIGHBOR"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.image.pbtxt b/tensorflow/tools/api/golden/tensorflow.image.pbtxt
new file mode 100644
index 00000000000..6002f36bacb
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.image.pbtxt
@@ -0,0 +1,175 @@
+path: "tensorflow.image"
+tf_module {
+  member {
+    name: "ResizeMethod"
+    mtype: "<type \'type\'>"
+  }
+  member_method {
+    name: "adjust_brightness"
+    argspec: "args=[\'image\', \'delta\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "adjust_contrast"
+    argspec: "args=[\'images\', \'contrast_factor\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "adjust_gamma"
+    argspec: "args=[\'image\', \'gamma\', \'gain\'], varargs=None, keywords=None, defaults=[\'1\', \'1\'], "
+  }
+  member_method {
+    name: "adjust_hue"
+    argspec: "args=[\'image\', \'delta\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "adjust_saturation"
+    argspec: "args=[\'image\', \'saturation_factor\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "central_crop"
+    argspec: "args=[\'image\', \'central_fraction\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "convert_image_dtype"
+    argspec: "args=[\'image\', \'dtype\', \'saturate\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
+  member_method {
+    name: "crop_and_resize"
+    argspec: "args=[\'image\', \'boxes\', \'box_ind\', \'crop_size\', \'method\', \'extrapolation_value\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "crop_to_bounding_box"
+    argspec: "args=[\'image\', \'offset_height\', \'offset_width\', \'target_height\', \'target_width\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "decode_gif"
+    argspec: "args=[\'contents\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "decode_image"
+    argspec: "args=[\'contents\', \'channels\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "decode_jpeg"
+    argspec: "args=[\'contents\', \'channels\', \'ratio\', \'fancy_upscaling\', \'try_recover_truncated\', \'acceptable_fraction\', \'dct_method\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "decode_png"
+    argspec: "args=[\'contents\', \'channels\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "draw_bounding_boxes"
+    argspec: "args=[\'images\', \'boxes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "encode_jpeg"
+    argspec: "args=[\'image\', \'format\', \'quality\', \'progressive\', \'optimize_size\', \'chroma_downsampling\', \'density_unit\', \'x_density\', \'y_density\', \'xmp_metadata\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "encode_png"
+    argspec: "args=[\'image\', \'compression\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "extract_glimpse"
+    argspec: "args=[\'input\', \'size\', \'offsets\', \'centered\', \'normalized\', \'uniform_noise\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "flip_left_right"
+    argspec: "args=[\'image\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "flip_up_down"
+    argspec: "args=[\'image\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "grayscale_to_rgb"
+    argspec: "args=[\'images\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "hsv_to_rgb"
+    argspec: "args=[\'images\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "non_max_suppression"
+    argspec: "args=[\'boxes\', \'scores\', \'max_output_size\', \'iou_threshold\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "pad_to_bounding_box"
+    argspec: "args=[\'image\', \'offset_height\', \'offset_width\', \'target_height\', \'target_width\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "per_image_standardization"
+    argspec: "args=[\'image\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "random_brightness"
+    argspec: "args=[\'image\', \'max_delta\', \'seed\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "random_contrast"
+    argspec: "args=[\'image\', \'lower\', \'upper\', \'seed\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "random_flip_left_right"
+    argspec: "args=[\'image\', \'seed\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "random_flip_up_down"
+    argspec: "args=[\'image\', \'seed\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "random_hue"
+    argspec: "args=[\'image\', \'max_delta\', \'seed\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "random_saturation"
+    argspec: "args=[\'image\', \'lower\', \'upper\', \'seed\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "resize_area"
+    argspec: "args=[\'images\', \'size\', \'align_corners\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "resize_bicubic"
+    argspec: "args=[\'images\', \'size\', \'align_corners\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "resize_bilinear"
+    argspec: "args=[\'images\', \'size\', \'align_corners\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "resize_image_with_crop_or_pad"
+    argspec: "args=[\'image\', \'target_height\', \'target_width\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "resize_images"
+    argspec: "args=[\'images\', \'size\', \'method\', \'align_corners\'], varargs=None, keywords=None, defaults=[\'0\', \'False\'], "
+  }
+  member_method {
+    name: "resize_nearest_neighbor"
+    argspec: "args=[\'images\', \'size\', \'align_corners\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "rgb_to_grayscale"
+    argspec: "args=[\'images\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "rgb_to_hsv"
+    argspec: "args=[\'images\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "rot90"
+    argspec: "args=[\'image\', \'k\', \'name\'], varargs=None, keywords=None, defaults=[\'1\', \'None\'], "
+  }
+  member_method {
+    name: "sample_distorted_bounding_box"
+    argspec: "args=[\'image_size\', \'bounding_boxes\', \'seed\', \'seed2\', \'min_object_covered\', \'aspect_ratio_range\', \'area_range\', \'max_attempts\', \'use_image_if_no_bounding_boxes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "total_variation"
+    argspec: "args=[\'images\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "transpose_image"
+    argspec: "args=[\'image\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.layers.pbtxt b/tensorflow/tools/api/golden/tensorflow.layers.pbtxt
new file mode 100644
index 00000000000..6ca38e259bf
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.layers.pbtxt
@@ -0,0 +1,59 @@
+path: "tensorflow.layers"
+tf_module {
+  member_method {
+    name: "average_pooling1d"
+    argspec: "args=[\'inputs\', \'pool_size\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'valid\', \'channels_last\', \'None\'], "
+  }
+  member_method {
+    name: "average_pooling2d"
+    argspec: "args=[\'inputs\', \'pool_size\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'valid\', \'channels_last\', \'None\'], "
+  }
+  member_method {
+    name: "average_pooling3d"
+    argspec: "args=[\'inputs\', \'pool_size\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'valid\', \'channels_last\', \'None\'], "
+  }
+  member_method {
+    name: "batch_normalization"
+    argspec: "args=[\'inputs\', \'axis\', \'momentum\', \'epsilon\', \'center\', \'scale\', \'beta_initializer\', \'gamma_initializer\', \'moving_mean_initializer\', \'moving_variance_initializer\', \'beta_regularizer\', \'gamma_regularizer\', \'training\', \'trainable\', \'name\', \'reuse\', \'renorm\', \'renorm_clipping\', \'renorm_momentum\'], varargs=None, keywords=None, defaults=[\'-1\', \'0.99\', \'0.001\', \'True\', \'True\', \'<tensorflow.python.ops.init_ops.Zeros object instance>\', \'<tensorflow.python.ops.init_ops.Ones object instance>\', \'<tensorflow.python.ops.init_ops.Zeros object instance>\', \'<tensorflow.python.ops.init_ops.Ones object instance>\', \'None\', \'None\', \'False\', \'True\', \'None\', \'None\', \'False\', \'None\', \'0.99\'], "
+  }
+  member_method {
+    name: "conv1d"
+    argspec: "args=[\'inputs\', \'filters\', \'kernel_size\', \'strides\', \'padding\', \'data_format\', \'dilation_rate\', \'activation\', \'use_bias\', \'kernel_initializer\', \'bias_initializer\', \'kernel_regularizer\', \'bias_regularizer\', \'activity_regularizer\', \'trainable\', \'name\', \'reuse\'], varargs=None, keywords=None, defaults=[\'1\', \'valid\', \'channels_last\', \'1\', \'None\', \'True\', \'None\', \'<tensorflow.python.ops.init_ops.Zeros object instance>\', \'None\', \'None\', \'None\', \'True\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "conv2d"
+    argspec: "args=[\'inputs\', \'filters\', \'kernel_size\', \'strides\', \'padding\', \'data_format\', \'dilation_rate\', \'activation\', \'use_bias\', \'kernel_initializer\', \'bias_initializer\', \'kernel_regularizer\', \'bias_regularizer\', \'activity_regularizer\', \'trainable\', \'name\', \'reuse\'], varargs=None, keywords=None, defaults=[\'(1, 1)\', \'valid\', \'channels_last\', \'(1, 1)\', \'None\', \'True\', \'None\', \'<tensorflow.python.ops.init_ops.Zeros object instance>\', \'None\', \'None\', \'None\', \'True\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "conv2d_transpose"
+    argspec: "args=[\'inputs\', \'filters\', \'kernel_size\', \'strides\', \'padding\', \'data_format\', \'activation\', \'use_bias\', \'kernel_initializer\', \'bias_initializer\', \'kernel_regularizer\', \'bias_regularizer\', \'activity_regularizer\', \'trainable\', \'name\', \'reuse\'], varargs=None, keywords=None, defaults=[\'(1, 1)\', \'valid\', \'channels_last\', \'None\', \'True\', \'None\', \'<tensorflow.python.ops.init_ops.Zeros object instance>\', \'None\', \'None\', \'None\', \'True\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "conv3d"
+    argspec: "args=[\'inputs\', \'filters\', \'kernel_size\', \'strides\', \'padding\', \'data_format\', \'dilation_rate\', \'activation\', \'use_bias\', \'kernel_initializer\', \'bias_initializer\', \'kernel_regularizer\', \'bias_regularizer\', \'activity_regularizer\', \'trainable\', \'name\', \'reuse\'], varargs=None, keywords=None, defaults=[\'(1, 1, 1)\', \'valid\', \'channels_last\', \'(1, 1, 1)\', \'None\', \'True\', \'None\', \'<tensorflow.python.ops.init_ops.Zeros object instance>\', \'None\', \'None\', \'None\', \'True\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "dense"
+    argspec: "args=[\'inputs\', \'units\', \'activation\', \'use_bias\', \'kernel_initializer\', \'bias_initializer\', \'kernel_regularizer\', \'bias_regularizer\', \'activity_regularizer\', \'trainable\', \'name\', \'reuse\'], varargs=None, keywords=None, defaults=[\'None\', \'True\', \'None\', \'<tensorflow.python.ops.init_ops.Zeros object instance>\', \'None\', \'None\', \'None\', \'True\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "dropout"
+    argspec: "args=[\'inputs\', \'rate\', \'noise_shape\', \'seed\', \'training\', \'name\'], varargs=None, keywords=None, defaults=[\'0.5\', \'None\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "max_pooling1d"
+    argspec: "args=[\'inputs\', \'pool_size\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'valid\', \'channels_last\', \'None\'], "
+  }
+  member_method {
+    name: "max_pooling2d"
+    argspec: "args=[\'inputs\', \'pool_size\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'valid\', \'channels_last\', \'None\'], "
+  }
+  member_method {
+    name: "max_pooling3d"
+    argspec: "args=[\'inputs\', \'pool_size\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'valid\', \'channels_last\', \'None\'], "
+  }
+  member_method {
+    name: "separable_conv2d"
+    argspec: "args=[\'inputs\', \'filters\', \'kernel_size\', \'strides\', \'padding\', \'data_format\', \'dilation_rate\', \'depth_multiplier\', \'activation\', \'use_bias\', \'depthwise_initializer\', \'pointwise_initializer\', \'bias_initializer\', \'depthwise_regularizer\', \'pointwise_regularizer\', \'bias_regularizer\', \'activity_regularizer\', \'trainable\', \'name\', \'reuse\'], varargs=None, keywords=None, defaults=[\'(1, 1)\', \'valid\', \'channels_last\', \'(1, 1)\', \'1\', \'None\', \'True\', \'None\', \'None\', \'<tensorflow.python.ops.init_ops.Zeros object instance>\', \'None\', \'None\', \'None\', \'None\', \'True\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.logging.pbtxt b/tensorflow/tools/api/golden/tensorflow.logging.pbtxt
new file mode 100644
index 00000000000..85bb15455da
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.logging.pbtxt
@@ -0,0 +1,83 @@
+path: "tensorflow.logging"
+tf_module {
+  member {
+    name: "DEBUG"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "ERROR"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "FATAL"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "INFO"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "WARN"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "TaskLevelStatusMessage"
+    argspec: "args=[\'msg\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "debug"
+    argspec: "args=[\'msg\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "error"
+    argspec: "args=[\'msg\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "fatal"
+    argspec: "args=[\'msg\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "flush"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_verbosity"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "info"
+    argspec: "args=[\'msg\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "log"
+    argspec: "args=[\'level\', \'msg\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "log_every_n"
+    argspec: "args=[\'level\', \'msg\', \'n\'], varargs=args, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "log_first_n"
+    argspec: "args=[\'level\', \'msg\', \'n\'], varargs=args, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "log_if"
+    argspec: "args=[\'level\', \'msg\', \'condition\'], varargs=args, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "set_verbosity"
+    argspec: "args=[\'v\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "vlog"
+    argspec: "args=[\'level\', \'msg\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "warn"
+    argspec: "args=[\'msg\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "warning"
+    argspec: "args=[\'msg\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.losses.pbtxt b/tensorflow/tools/api/golden/tensorflow.losses.pbtxt
new file mode 100644
index 00000000000..5477ac58174
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.losses.pbtxt
@@ -0,0 +1,63 @@
+path: "tensorflow.losses"
+tf_module {
+  member_method {
+    name: "absolute_difference"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\'], "
+  }
+  member_method {
+    name: "add_loss"
+    argspec: "args=[\'loss\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'losses\'], "
+  }
+  member_method {
+    name: "compute_weighted_loss"
+    argspec: "args=[\'losses\', \'weights\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\'], "
+  }
+  member_method {
+    name: "cosine_distance"
+    argspec: "args=[\'labels\', \'predictions\', \'dim\', \'weights\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'None\', \'1.0\', \'None\', \'losses\'], "
+  }
+  member_method {
+    name: "get_losses"
+    argspec: "args=[\'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'None\', \'losses\'], "
+  }
+  member_method {
+    name: "get_regularization_loss"
+    argspec: "args=[\'scope\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'total_regularization_loss\'], "
+  }
+  member_method {
+    name: "get_regularization_losses"
+    argspec: "args=[\'scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_total_loss"
+    argspec: "args=[\'add_regularization_losses\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'total_loss\'], "
+  }
+  member_method {
+    name: "hinge_loss"
+    argspec: "args=[\'labels\', \'logits\', \'weights\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\'], "
+  }
+  member_method {
+    name: "log_loss"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'epsilon\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'1.0\', \'1e-07\', \'None\', \'losses\'], "
+  }
+  member_method {
+    name: "mean_pairwise_squared_error"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\'], "
+  }
+  member_method {
+    name: "mean_squared_error"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\'], "
+  }
+  member_method {
+    name: "sigmoid_cross_entropy"
+    argspec: "args=[\'multi_class_labels\', \'logits\', \'weights\', \'label_smoothing\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'1.0\', \'0\', \'None\', \'losses\'], "
+  }
+  member_method {
+    name: "softmax_cross_entropy"
+    argspec: "args=[\'onehot_labels\', \'logits\', \'weights\', \'label_smoothing\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'1.0\', \'0\', \'None\', \'losses\'], "
+  }
+  member_method {
+    name: "sparse_softmax_cross_entropy"
+    argspec: "args=[\'labels\', \'logits\', \'weights\', \'scope\', \'loss_collection\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \'losses\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.metrics.pbtxt b/tensorflow/tools/api/golden/tensorflow.metrics.pbtxt
new file mode 100644
index 00000000000..262d11c38e1
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.metrics.pbtxt
@@ -0,0 +1,99 @@
+path: "tensorflow.metrics"
+tf_module {
+  member_method {
+    name: "accuracy"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "auc"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'num_thresholds\', \'metrics_collections\', \'updates_collections\', \'curve\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'200\', \'None\', \'None\', \'ROC\', \'None\'], "
+  }
+  member_method {
+    name: "false_negatives"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "false_positives"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "mean"
+    argspec: "args=[\'values\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "mean_absolute_error"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "mean_cosine_distance"
+    argspec: "args=[\'labels\', \'predictions\', \'dim\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "mean_iou"
+    argspec: "args=[\'labels\', \'predictions\', \'num_classes\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "mean_per_class_accuracy"
+    argspec: "args=[\'labels\', \'predictions\', \'num_classes\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "mean_relative_error"
+    argspec: "args=[\'labels\', \'predictions\', \'normalizer\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "mean_squared_error"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "mean_tensor"
+    argspec: "args=[\'values\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "percentage_below"
+    argspec: "args=[\'values\', \'threshold\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "precision"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "precision_at_thresholds"
+    argspec: "args=[\'labels\', \'predictions\', \'thresholds\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "recall"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "recall_at_k"
+    argspec: "args=[\'labels\', \'predictions\', \'k\', \'class_id\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "recall_at_thresholds"
+    argspec: "args=[\'labels\', \'predictions\', \'thresholds\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "root_mean_squared_error"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "sensitivity_at_specificity"
+    argspec: "args=[\'labels\', \'predictions\', \'specificity\', \'weights\', \'num_thresholds\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'200\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "sparse_average_precision_at_k"
+    argspec: "args=[\'labels\', \'predictions\', \'k\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "sparse_precision_at_k"
+    argspec: "args=[\'labels\', \'predictions\', \'k\', \'class_id\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "specificity_at_sensitivity"
+    argspec: "args=[\'labels\', \'predictions\', \'sensitivity\', \'weights\', \'num_thresholds\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'200\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "true_positives"
+    argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.nn.pbtxt b/tensorflow/tools/api/golden/tensorflow.nn.pbtxt
new file mode 100644
index 00000000000..192ceac2ddf
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.nn.pbtxt
@@ -0,0 +1,323 @@
+path: "tensorflow.nn"
+tf_module {
+  member_method {
+    name: "all_candidate_sampler"
+    argspec: "args=[\'true_classes\', \'num_true\', \'num_sampled\', \'unique\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "atrous_conv2d"
+    argspec: "args=[\'value\', \'filters\', \'rate\', \'padding\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "atrous_conv2d_transpose"
+    argspec: "args=[\'value\', \'filters\', \'output_shape\', \'rate\', \'padding\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "avg_pool"
+    argspec: "args=[\'value\', \'ksize\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'NHWC\', \'None\'], "
+  }
+  member_method {
+    name: "avg_pool3d"
+    argspec: "args=[\'input\', \'ksize\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "batch_norm_with_global_normalization"
+    argspec: "args=[\'t\', \'m\', \'v\', \'beta\', \'gamma\', \'variance_epsilon\', \'scale_after_normalization\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "batch_normalization"
+    argspec: "args=[\'x\', \'mean\', \'variance\', \'offset\', \'scale\', \'variance_epsilon\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "bias_add"
+    argspec: "args=[\'value\', \'bias\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "bidirectional_dynamic_rnn"
+    argspec: "args=[\'cell_fw\', \'cell_bw\', \'inputs\', \'sequence_length\', \'initial_state_fw\', \'initial_state_bw\', \'dtype\', \'parallel_iterations\', \'swap_memory\', \'time_major\', \'scope\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'False\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "compute_accidental_hits"
+    argspec: "args=[\'true_classes\', \'sampled_candidates\', \'num_true\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "conv1d"
+    argspec: "args=[\'value\', \'filters\', \'stride\', \'padding\', \'use_cudnn_on_gpu\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "conv2d"
+    argspec: "args=[\'input\', \'filter\', \'strides\', \'padding\', \'use_cudnn_on_gpu\', \'data_format\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "conv2d_backprop_filter"
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+  }
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+  }
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+  }
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+  }
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+  }
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+  }
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+  }
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+  }
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+  }
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+  }
+  member_method {
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+  member_method {
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+  }
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+    argspec: "args=[\'targets\', \'log_input\', \'compute_full_loss\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
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+  }
+  member_method {
+    name: "log_uniform_candidate_sampler"
+    argspec: "args=[\'true_classes\', \'num_true\', \'num_sampled\', \'unique\', \'range_max\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
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+  }
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+    argspec: "args=[\'x\', \'axes\', \'shift\', \'name\', \'keep_dims\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'False\'], "
+  }
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+    argspec: "args=[\'weights\', \'biases\', \'labels\', \'inputs\', \'num_sampled\', \'num_classes\', \'num_true\', \'sampled_values\', \'remove_accidental_hits\', \'partition_strategy\', \'name\'], varargs=None, keywords=None, defaults=[\'1\', \'None\', \'False\', \'mod\', \'nce_loss\'], "
+  }
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+  }
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+  }
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+  }
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+  }
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+  }
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+  }
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+  }
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+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
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+    argspec: "args=[\'input\', \'k\', \'sorted\', \'name\'], varargs=None, keywords=None, defaults=[\'1\', \'True\', \'None\'], "
+  }
+  member_method {
+    name: "uniform_candidate_sampler"
+    argspec: "args=[\'true_classes\', \'num_true\', \'num_sampled\', \'unique\', \'range_max\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
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+    argspec: "args=[\'targets\', \'logits\', \'pos_weight\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
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+    argspec: "args=[\'x\', \'axes\', \'frequency_weights\', \'name\', \'keep_dims\'], varargs=None, keywords=None, defaults=[\'None\', \'False\'], "
+  }
+  member_method {
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+    argspec: "args=[\'input\', \'dilation_rate\', \'padding\', \'op\', \'filter_shape\', \'spatial_dims\', \'data_format\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
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+    argspec: "args=[\'x\', \'weights\', \'biases\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "zero_fraction"
+    argspec: "args=[\'value\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.ones_initializer.pbtxt b/tensorflow/tools/api/golden/tensorflow.ones_initializer.pbtxt
new file mode 100644
index 00000000000..d84ddc6eb00
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.ones_initializer.pbtxt
@@ -0,0 +1,10 @@
+path: "tensorflow.ones_initializer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Ones\'>"
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Initializer\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'dtype\'], varargs=None, keywords=None, defaults=[\"<dtype: \'float32\'>\"], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.orthogonal_initializer.pbtxt b/tensorflow/tools/api/golden/tensorflow.orthogonal_initializer.pbtxt
new file mode 100644
index 00000000000..c8e266e70cf
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.orthogonal_initializer.pbtxt
@@ -0,0 +1,10 @@
+path: "tensorflow.orthogonal_initializer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Orthogonal\'>"
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Initializer\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'gain\', \'dtype\', \'seed\'], varargs=None, keywords=None, defaults=[\'1.0\', \"<dtype: \'float32\'>\", \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.pbtxt b/tensorflow/tools/api/golden/tensorflow.pbtxt
new file mode 100644
index 00000000000..7a1a7e7949d
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.pbtxt
@@ -0,0 +1,1947 @@
+path: "tensorflow"
+tf_module {
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+  member_method {
+    name: "count_nonzero"
+    argspec: "args=[\'input_tensor\', \'axis\', \'keep_dims\', \'dtype\', \'name\', \'reduction_indices\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \"<dtype: \'int64\'>\", \'None\', \'None\'], "
+  }
+  member_method {
+    name: "count_up_to"
+    argspec: "args=[\'ref\', \'limit\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "create_partitioned_variables"
+    argspec: "args=[\'shape\', \'slicing\', \'initializer\', \'dtype\', \'trainable\', \'collections\', \'name\', \'reuse\'], varargs=None, keywords=None, defaults=[\"<dtype: \'float32\'>\", \'True\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "cross"
+    argspec: "args=[\'a\', \'b\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "cumprod"
+    argspec: "args=[\'x\', \'axis\', \'exclusive\', \'reverse\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'False\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "cumsum"
+    argspec: "args=[\'x\', \'axis\', \'exclusive\', \'reverse\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'False\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "decode_base64"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "decode_csv"
+    argspec: "args=[\'records\', \'record_defaults\', \'field_delim\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "decode_json_example"
+    argspec: "args=[\'json_examples\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "decode_raw"
+    argspec: "args=[\'bytes\', \'out_type\', \'little_endian\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "delete_session_tensor"
+    argspec: "args=[\'handle\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "depth_to_space"
+    argspec: "args=[\'input\', \'block_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "dequantize"
+    argspec: "args=[\'input\', \'min_range\', \'max_range\', \'mode\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "deserialize_many_sparse"
+    argspec: "args=[\'serialized_sparse\', \'dtype\', \'rank\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "device"
+    argspec: "args=[\'device_name_or_function\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "diag"
+    argspec: "args=[\'diagonal\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "diag_part"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "digamma"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "div"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "divide"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "dynamic_partition"
+    argspec: "args=[\'data\', \'partitions\', \'num_partitions\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "dynamic_stitch"
+    argspec: "args=[\'indices\', \'data\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "edit_distance"
+    argspec: "args=[\'hypothesis\', \'truth\', \'normalize\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'edit_distance\'], "
+  }
+  member_method {
+    name: "einsum"
+    argspec: "args=[\'equation\'], varargs=inputs, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "encode_base64"
+    argspec: "args=[\'input\', \'pad\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "equal"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "erf"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "erfc"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "exp"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "expand_dims"
+    argspec: "args=[\'input\', \'axis\', \'name\', \'dim\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "expm1"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "extract_image_patches"
+    argspec: "args=[\'images\', \'ksizes\', \'strides\', \'rates\', \'padding\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "eye"
+    argspec: "args=[\'num_rows\', \'num_columns\', \'batch_shape\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \"<dtype: \'float32\'>\", \'None\'], "
+  }
+  member_method {
+    name: "fake_quant_with_min_max_args"
+    argspec: "args=[\'inputs\', \'min\', \'max\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "fake_quant_with_min_max_args_gradient"
+    argspec: "args=[\'gradients\', \'inputs\', \'min\', \'max\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "fake_quant_with_min_max_vars"
+    argspec: "args=[\'inputs\', \'min\', \'max\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "fake_quant_with_min_max_vars_gradient"
+    argspec: "args=[\'gradients\', \'inputs\', \'min\', \'max\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "fake_quant_with_min_max_vars_per_channel"
+    argspec: "args=[\'inputs\', \'min\', \'max\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "fake_quant_with_min_max_vars_per_channel_gradient"
+    argspec: "args=[\'gradients\', \'inputs\', \'min\', \'max\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "fft"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "fft2d"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "fft3d"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "fill"
+    argspec: "args=[\'dims\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "fixed_size_partitioner"
+    argspec: "args=[\'num_shards\', \'axis\'], varargs=None, keywords=None, defaults=[\'0\'], "
+  }
+  member_method {
+    name: "floor"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "floor_div"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "floordiv"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "floormod"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "foldl"
+    argspec: "args=[\'fn\', \'elems\', \'initializer\', \'parallel_iterations\', \'back_prop\', \'swap_memory\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'10\', \'True\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "foldr"
+    argspec: "args=[\'fn\', \'elems\', \'initializer\', \'parallel_iterations\', \'back_prop\', \'swap_memory\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'10\', \'True\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "gather"
+    argspec: "args=[\'params\', \'indices\', \'validate_indices\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "gather_nd"
+    argspec: "args=[\'params\', \'indices\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_collection"
+    argspec: "args=[\'key\', \'scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_collection_ref"
+    argspec: "args=[\'key\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_default_graph"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_default_session"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_local_variable"
+    argspec: "args=[], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "get_seed"
+    argspec: "args=[\'op_seed\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_session_handle"
+    argspec: "args=[\'data\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_session_tensor"
+    argspec: "args=[\'handle\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_variable"
+    argspec: "args=[\'name\', \'shape\', \'dtype\', \'initializer\', \'regularizer\', \'trainable\', \'collections\', \'caching_device\', \'partitioner\', \'validate_shape\', \'use_resource\', \'custom_getter\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'True\', \'None\', \'None\', \'None\', \'True\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "get_variable_scope"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "global_norm"
+    argspec: "args=[\'t_list\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "global_variables"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "global_variables_initializer"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "gradients"
+    argspec: "args=[\'ys\', \'xs\', \'grad_ys\', \'name\', \'colocate_gradients_with_ops\', \'gate_gradients\', \'aggregation_method\'], varargs=None, keywords=None, defaults=[\'None\', \'gradients\', \'False\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "greater"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "greater_equal"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "group"
+    argspec: "args=[], varargs=inputs, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "hessians"
+    argspec: "args=[\'ys\', \'xs\', \'name\', \'colocate_gradients_with_ops\', \'gate_gradients\', \'aggregation_method\'], varargs=None, keywords=None, defaults=[\'hessians\', \'False\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "histogram_fixed_width"
+    argspec: "args=[\'values\', \'value_range\', \'nbins\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'100\', \"<dtype: \'int32\'>\", \'None\'], "
+  }
+  member_method {
+    name: "identity"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "ifft"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "ifft2d"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "ifft3d"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "igamma"
+    argspec: "args=[\'a\', \'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "igammac"
+    argspec: "args=[\'a\', \'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "imag"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "import_graph_def"
+    argspec: "args=[\'graph_def\', \'input_map\', \'return_elements\', \'name\', \'op_dict\', \'producer_op_list\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "initialize_all_tables"
+    argspec: "args=[], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "initialize_all_variables"
+    argspec: "args=[], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "initialize_local_variables"
+    argspec: "args=[], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "initialize_variables"
+    argspec: "args=[], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "invert_permutation"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "is_finite"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "is_inf"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "is_nan"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "is_non_decreasing"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "is_numeric_tensor"
+    argspec: "args=[\'tensor\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "is_strictly_increasing"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "is_variable_initialized"
+    argspec: "args=[\'variable\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "lbeta"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'lbeta\'], "
+  }
+  member_method {
+    name: "less"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "less_equal"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "lgamma"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "lin_space"
+    argspec: "args=[\'start\', \'stop\', \'num\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "linspace"
+    argspec: "args=[\'start\', \'stop\', \'num\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "load_file_system_library"
+    argspec: "args=[\'library_filename\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "load_op_library"
+    argspec: "args=[\'library_filename\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "local_variables"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "local_variables_initializer"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "log"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "log1p"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "logical_and"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "logical_not"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "logical_or"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "logical_xor"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'LogicalXor\'], "
+  }
+  member_method {
+    name: "make_template"
+    argspec: "args=[\'name_\', \'func_\', \'create_scope_now_\', \'unique_name_\', \'custom_getter_\'], varargs=None, keywords=kwargs, defaults=[\'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "map_fn"
+    argspec: "args=[\'fn\', \'elems\', \'dtype\', \'parallel_iterations\', \'back_prop\', \'swap_memory\', \'infer_shape\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'10\', \'True\', \'False\', \'True\', \'None\'], "
+  }
+  member_method {
+    name: "matching_files"
+    argspec: "args=[\'pattern\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "matmul"
+    argspec: "args=[\'a\', \'b\', \'transpose_a\', \'transpose_b\', \'adjoint_a\', \'adjoint_b\', \'a_is_sparse\', \'b_is_sparse\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'False\', \'False\', \'False\', \'False\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "matrix_band_part"
+    argspec: "args=[\'input\', \'num_lower\', \'num_upper\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "matrix_determinant"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "matrix_diag"
+    argspec: "args=[\'diagonal\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "matrix_diag_part"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "matrix_inverse"
+    argspec: "args=[\'input\', \'adjoint\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "matrix_set_diag"
+    argspec: "args=[\'input\', \'diagonal\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "matrix_solve"
+    argspec: "args=[\'matrix\', \'rhs\', \'adjoint\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "matrix_solve_ls"
+    argspec: "args=[\'matrix\', \'rhs\', \'l2_regularizer\', \'fast\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'True\', \'None\'], "
+  }
+  member_method {
+    name: "matrix_transpose"
+    argspec: "args=[\'a\', \'name\'], varargs=None, keywords=None, defaults=[\'matrix_transpose\'], "
+  }
+  member_method {
+    name: "matrix_triangular_solve"
+    argspec: "args=[\'matrix\', \'rhs\', \'lower\', \'adjoint\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "maximum"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "meshgrid"
+    argspec: "args=[], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "min_max_variable_partitioner"
+    argspec: "args=[\'max_partitions\', \'axis\', \'min_slice_size\', \'bytes_per_string_element\'], varargs=None, keywords=None, defaults=[\'1\', \'0\', \'262144\', \'16\'], "
+  }
+  member_method {
+    name: "minimum"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "mod"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "model_variables"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "moving_average_variables"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "multinomial"
+    argspec: "args=[\'logits\', \'num_samples\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "multiply"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "name_scope"
+    argspec: "args=[], varargs=args, keywords=kwds, defaults=None"
+  }
+  member_method {
+    name: "negative"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "no_op"
+    argspec: "args=[\'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "no_regularizer"
+    argspec: "args=[\'_\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "norm"
+    argspec: "args=[\'tensor\', \'ord\', \'axis\', \'keep_dims\', \'name\'], varargs=None, keywords=None, defaults=[\'euclidean\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "not_equal"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "one_hot"
+    argspec: "args=[\'indices\', \'depth\', \'on_value\', \'off_value\', \'axis\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "ones"
+    argspec: "args=[\'shape\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'float32\'>\", \'None\'], "
+  }
+  member_method {
+    name: "ones_like"
+    argspec: "args=[\'tensor\', \'dtype\', \'name\', \'optimize\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\'], "
+  }
+  member_method {
+    name: "op_scope"
+    argspec: "args=[], varargs=args, keywords=kwds, defaults=None"
+  }
+  member_method {
+    name: "pad"
+    argspec: "args=[\'tensor\', \'paddings\', \'mode\', \'name\'], varargs=None, keywords=None, defaults=[\'CONSTANT\', \'None\'], "
+  }
+  member_method {
+    name: "parallel_stack"
+    argspec: "args=[\'values\', \'name\'], varargs=None, keywords=None, defaults=[\'parallel_stack\'], "
+  }
+  member_method {
+    name: "parse_example"
+    argspec: "args=[\'serialized\', \'features\', \'name\', \'example_names\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "parse_single_example"
+    argspec: "args=[\'serialized\', \'features\', \'name\', \'example_names\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "parse_single_sequence_example"
+    argspec: "args=[\'serialized\', \'context_features\', \'sequence_features\', \'example_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "parse_tensor"
+    argspec: "args=[\'serialized\', \'out_type\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "placeholder"
+    argspec: "args=[\'dtype\', \'shape\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "placeholder_with_default"
+    argspec: "args=[\'input\', \'shape\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "polygamma"
+    argspec: "args=[\'a\', \'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "pow"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "py_func"
+    argspec: "args=[\'func\', \'inp\', \'Tout\', \'stateful\', \'name\'], varargs=None, keywords=None, defaults=[\'True\', \'None\'], "
+  }
+  member_method {
+    name: "qr"
+    argspec: "args=[\'input\', \'full_matrices\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "quantize_v2"
+    argspec: "args=[\'input\', \'min_range\', \'max_range\', \'T\', \'mode\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "quantized_concat"
+    argspec: "args=[\'concat_dim\', \'values\', \'input_mins\', \'input_maxes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "random_crop"
+    argspec: "args=[\'value\', \'size\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "random_gamma"
+    argspec: "args=[\'shape\', \'alpha\', \'beta\', \'dtype\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \"<dtype: \'float32\'>\", \'None\', \'None\'], "
+  }
+  member_method {
+    name: "random_normal"
+    argspec: "args=[\'shape\', \'mean\', \'stddev\', \'dtype\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'1.0\', \"<dtype: \'float32\'>\", \'None\', \'None\'], "
+  }
+  member_method {
+    name: "random_poisson"
+    argspec: "args=[\'lam\', \'shape\', \'dtype\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'float32\'>\", \'None\', \'None\'], "
+  }
+  member_method {
+    name: "random_shuffle"
+    argspec: "args=[\'value\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "random_uniform"
+    argspec: "args=[\'shape\', \'minval\', \'maxval\', \'dtype\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'None\', \"<dtype: \'float32\'>\", \'None\', \'None\'], "
+  }
+  member_method {
+    name: "range"
+    argspec: "args=[\'start\', \'limit\', \'delta\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'range\'], "
+  }
+  member_method {
+    name: "rank"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "read_file"
+    argspec: "args=[\'filename\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "real"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "realdiv"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "reciprocal"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "reduce_all"
+    argspec: "args=[\'input_tensor\', \'axis\', \'keep_dims\', \'name\', \'reduction_indices\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "reduce_any"
+    argspec: "args=[\'input_tensor\', \'axis\', \'keep_dims\', \'name\', \'reduction_indices\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "reduce_join"
+    argspec: "args=[\'inputs\', \'axis\', \'keep_dims\', \'separator\', \'name\', \'reduction_indices\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "reduce_logsumexp"
+    argspec: "args=[\'input_tensor\', \'axis\', \'keep_dims\', \'name\', \'reduction_indices\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "reduce_max"
+    argspec: "args=[\'input_tensor\', \'axis\', \'keep_dims\', \'name\', \'reduction_indices\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "reduce_mean"
+    argspec: "args=[\'input_tensor\', \'axis\', \'keep_dims\', \'name\', \'reduction_indices\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "reduce_min"
+    argspec: "args=[\'input_tensor\', \'axis\', \'keep_dims\', \'name\', \'reduction_indices\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "reduce_prod"
+    argspec: "args=[\'input_tensor\', \'axis\', \'keep_dims\', \'name\', \'reduction_indices\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "reduce_sum"
+    argspec: "args=[\'input_tensor\', \'axis\', \'keep_dims\', \'name\', \'reduction_indices\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "register_tensor_conversion_function"
+    argspec: "args=[\'base_type\', \'conversion_func\', \'priority\'], varargs=None, keywords=None, defaults=[\'100\'], "
+  }
+  member_method {
+    name: "report_uninitialized_variables"
+    argspec: "args=[\'var_list\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'report_uninitialized_variables\'], "
+  }
+  member_method {
+    name: "required_space_to_batch_paddings"
+    argspec: "args=[\'input_shape\', \'block_shape\', \'base_paddings\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "reset_default_graph"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "reshape"
+    argspec: "args=[\'tensor\', \'shape\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "reverse"
+    argspec: "args=[\'tensor\', \'axis\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "reverse_sequence"
+    argspec: "args=[\'input\', \'seq_lengths\', \'seq_axis\', \'batch_axis\', \'name\', \'seq_dim\', \'batch_dim\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "reverse_v2"
+    argspec: "args=[\'tensor\', \'axis\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "rint"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "round"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "rsqrt"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "saturate_cast"
+    argspec: "args=[\'value\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "scalar_mul"
+    argspec: "args=[\'scalar\', \'x\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "scan"
+    argspec: "args=[\'fn\', \'elems\', \'initializer\', \'parallel_iterations\', \'back_prop\', \'swap_memory\', \'infer_shape\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'10\', \'True\', \'False\', \'True\', \'None\'], "
+  }
+  member_method {
+    name: "scatter_add"
+    argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "scatter_div"
+    argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "scatter_mul"
+    argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "scatter_nd"
+    argspec: "args=[\'indices\', \'updates\', \'shape\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "scatter_nd_add"
+    argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "scatter_nd_sub"
+    argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "scatter_nd_update"
+    argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "scatter_sub"
+    argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "scatter_update"
+    argspec: "args=[\'ref\', \'indices\', \'updates\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "segment_max"
+    argspec: "args=[\'data\', \'segment_ids\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "segment_mean"
+    argspec: "args=[\'data\', \'segment_ids\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "segment_min"
+    argspec: "args=[\'data\', \'segment_ids\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "segment_prod"
+    argspec: "args=[\'data\', \'segment_ids\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "segment_sum"
+    argspec: "args=[\'data\', \'segment_ids\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "self_adjoint_eig"
+    argspec: "args=[\'tensor\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "self_adjoint_eigvals"
+    argspec: "args=[\'tensor\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sequence_mask"
+    argspec: "args=[\'lengths\', \'maxlen\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \"<dtype: \'bool\'>\", \'None\'], "
+  }
+  member_method {
+    name: "serialize_many_sparse"
+    argspec: "args=[\'sp_input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "serialize_sparse"
+    argspec: "args=[\'sp_input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "set_random_seed"
+    argspec: "args=[\'seed\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "setdiff1d"
+    argspec: "args=[\'x\', \'y\', \'index_dtype\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'int32\'>\", \'None\'], "
+  }
+  member_method {
+    name: "shape"
+    argspec: "args=[\'input\', \'name\', \'out_type\'], varargs=None, keywords=None, defaults=[\'None\', \"<dtype: \'int32\'>\"], "
+  }
+  member_method {
+    name: "shape_n"
+    argspec: "args=[\'input\', \'out_type\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "sigmoid"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sign"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sin"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "size"
+    argspec: "args=[\'input\', \'name\', \'out_type\'], varargs=None, keywords=None, defaults=[\'None\', \"<dtype: \'int32\'>\"], "
+  }
+  member_method {
+    name: "slice"
+    argspec: "args=[\'input_\', \'begin\', \'size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "space_to_batch"
+    argspec: "args=[\'input\', \'paddings\', \'block_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "space_to_batch_nd"
+    argspec: "args=[\'input\', \'block_shape\', \'paddings\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "space_to_depth"
+    argspec: "args=[\'input\', \'block_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_add"
+    argspec: "args=[\'a\', \'b\', \'thresh\'], varargs=None, keywords=None, defaults=[\'0\'], "
+  }
+  member_method {
+    name: "sparse_concat"
+    argspec: "args=[\'axis\', \'sp_inputs\', \'name\', \'expand_nonconcat_dim\', \'concat_dim\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "sparse_fill_empty_rows"
+    argspec: "args=[\'sp_input\', \'default_value\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_mask"
+    argspec: "args=[\'a\', \'mask_indices\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_matmul"
+    argspec: "args=[\'a\', \'b\', \'transpose_a\', \'transpose_b\', \'a_is_sparse\', \'b_is_sparse\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "sparse_maximum"
+    argspec: "args=[\'sp_a\', \'sp_b\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_merge"
+    argspec: "args=[\'sp_ids\', \'sp_values\', \'vocab_size\', \'name\', \'already_sorted\'], varargs=None, keywords=None, defaults=[\'None\', \'False\'], "
+  }
+  member_method {
+    name: "sparse_minimum"
+    argspec: "args=[\'sp_a\', \'sp_b\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_placeholder"
+    argspec: "args=[\'dtype\', \'shape\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "sparse_reduce_sum"
+    argspec: "args=[\'sp_input\', \'axis\', \'keep_dims\', \'reduction_axes\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "sparse_reduce_sum_sparse"
+    argspec: "args=[\'sp_input\', \'axis\', \'keep_dims\', \'reduction_axes\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "sparse_reorder"
+    argspec: "args=[\'sp_input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_reset_shape"
+    argspec: "args=[\'sp_input\', \'new_shape\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_reshape"
+    argspec: "args=[\'sp_input\', \'shape\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_retain"
+    argspec: "args=[\'sp_input\', \'to_retain\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "sparse_segment_mean"
+    argspec: "args=[\'data\', \'indices\', \'segment_ids\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_segment_sqrt_n"
+    argspec: "args=[\'data\', \'indices\', \'segment_ids\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_segment_sum"
+    argspec: "args=[\'data\', \'indices\', \'segment_ids\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_softmax"
+    argspec: "args=[\'sp_input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_split"
+    argspec: "args=[\'keyword_required\', \'sp_input\', \'num_split\', \'axis\', \'name\', \'split_dim\'], varargs=None, keywords=None, defaults=[\'KeywordRequired()\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "sparse_tensor_dense_matmul"
+    argspec: "args=[\'sp_a\', \'b\', \'adjoint_a\', \'adjoint_b\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "sparse_tensor_to_dense"
+    argspec: "args=[\'sp_input\', \'default_value\', \'validate_indices\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'True\', \'None\'], "
+  }
+  member_method {
+    name: "sparse_to_dense"
+    argspec: "args=[\'sparse_indices\', \'output_shape\', \'sparse_values\', \'default_value\', \'validate_indices\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'True\', \'None\'], "
+  }
+  member_method {
+    name: "sparse_to_indicator"
+    argspec: "args=[\'sp_input\', \'vocab_size\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "sparse_transpose"
+    argspec: "args=[\'sp_input\', \'perm\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "split"
+    argspec: "args=[\'value\', \'num_or_size_splits\', \'axis\', \'num\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'None\', \'split\'], "
+  }
+  member_method {
+    name: "sqrt"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "square"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "squared_difference"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "squeeze"
+    argspec: "args=[\'input\', \'axis\', \'name\', \'squeeze_dims\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "stack"
+    argspec: "args=[\'values\', \'axis\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'stack\'], "
+  }
+  member_method {
+    name: "stop_gradient"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "strided_slice"
+    argspec: "args=[\'input_\', \'begin\', \'end\', \'strides\', \'begin_mask\', \'end_mask\', \'ellipsis_mask\', \'new_axis_mask\', \'shrink_axis_mask\', \'var\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'0\', \'0\', \'0\', \'0\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "string_join"
+    argspec: "args=[\'inputs\', \'separator\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "string_split"
+    argspec: "args=[\'source\', \'delimiter\'], varargs=None, keywords=None, defaults=[\' \'], "
+  }
+  member_method {
+    name: "string_to_hash_bucket"
+    argspec: "args=[\'string_tensor\', \'num_buckets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "string_to_hash_bucket_fast"
+    argspec: "args=[\'input\', \'num_buckets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "string_to_hash_bucket_strong"
+    argspec: "args=[\'input\', \'num_buckets\', \'key\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "string_to_number"
+    argspec: "args=[\'string_tensor\', \'out_type\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "substr"
+    argspec: "args=[\'input\', \'pos\', \'len\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "subtract"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "svd"
+    argspec: "args=[\'tensor\', \'full_matrices\', \'compute_uv\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'True\', \'None\'], "
+  }
+  member_method {
+    name: "tables_initializer"
+    argspec: "args=[\'name\'], varargs=None, keywords=None, defaults=[\'init_all_tables\'], "
+  }
+  member_method {
+    name: "tan"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "tanh"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "tensordot"
+    argspec: "args=[\'a\', \'b\', \'axes\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "tile"
+    argspec: "args=[\'input\', \'multiples\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "to_bfloat16"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'ToBFloat16\'], "
+  }
+  member_method {
+    name: "to_double"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'ToDouble\'], "
+  }
+  member_method {
+    name: "to_float"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'ToFloat\'], "
+  }
+  member_method {
+    name: "to_int32"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'ToInt32\'], "
+  }
+  member_method {
+    name: "to_int64"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'ToInt64\'], "
+  }
+  member_method {
+    name: "trace"
+    argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "trainable_variables"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "transpose"
+    argspec: "args=[\'a\', \'perm\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'transpose\'], "
+  }
+  member_method {
+    name: "truediv"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "truncated_normal"
+    argspec: "args=[\'shape\', \'mean\', \'stddev\', \'dtype\', \'seed\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'1.0\', \"<dtype: \'float32\'>\", \'None\', \'None\'], "
+  }
+  member_method {
+    name: "truncatediv"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "truncatemod"
+    argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "tuple"
+    argspec: "args=[\'tensors\', \'name\', \'control_inputs\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "unique"
+    argspec: "args=[\'x\', \'out_idx\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "unique_with_counts"
+    argspec: "args=[\'x\', \'out_idx\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "unsorted_segment_max"
+    argspec: "args=[\'data\', \'segment_ids\', \'num_segments\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "unsorted_segment_sum"
+    argspec: "args=[\'data\', \'segment_ids\', \'num_segments\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "unstack"
+    argspec: "args=[\'value\', \'num\', \'axis\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'unstack\'], "
+  }
+  member_method {
+    name: "variable_axis_size_partitioner"
+    argspec: "args=[\'max_shard_bytes\', \'axis\', \'bytes_per_string_element\', \'max_shards\'], varargs=None, keywords=None, defaults=[\'0\', \'16\', \'None\'], "
+  }
+  member_method {
+    name: "variable_op_scope"
+    argspec: "args=[], varargs=args, keywords=kwds, defaults=None"
+  }
+  member_method {
+    name: "variable_scope"
+    argspec: "args=[], varargs=args, keywords=kwds, defaults=None"
+  }
+  member_method {
+    name: "variables_initializer"
+    argspec: "args=[\'var_list\', \'name\'], varargs=None, keywords=None, defaults=[\'init\'], "
+  }
+  member_method {
+    name: "verify_tensor_all_finite"
+    argspec: "args=[\'t\', \'msg\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "where"
+    argspec: "args=[\'condition\', \'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "while_loop"
+    argspec: "args=[\'cond\', \'body\', \'loop_vars\', \'shape_invariants\', \'parallel_iterations\', \'back_prop\', \'swap_memory\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'10\', \'True\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "write_file"
+    argspec: "args=[\'filename\', \'contents\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "zeros"
+    argspec: "args=[\'shape\', \'dtype\', \'name\'], varargs=None, keywords=None, defaults=[\"<dtype: \'float32\'>\", \'None\'], "
+  }
+  member_method {
+    name: "zeros_like"
+    argspec: "args=[\'tensor\', \'dtype\', \'name\', \'optimize\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\'], "
+  }
+  member_method {
+    name: "zeta"
+    argspec: "args=[\'x\', \'q\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.python_io.-t-f-record-compression-type.pbtxt b/tensorflow/tools/api/golden/tensorflow.python_io.-t-f-record-compression-type.pbtxt
new file mode 100644
index 00000000000..4941dda50e4
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.python_io.-t-f-record-compression-type.pbtxt
@@ -0,0 +1,20 @@
+path: "tensorflow.python_io.TFRecordCompressionType"
+tf_class {
+  is_instance: "<class \'tensorflow.python.lib.io.tf_record.TFRecordCompressionType\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GZIP"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "ZLIB"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.python_io.-t-f-record-options.pbtxt b/tensorflow/tools/api/golden/tensorflow.python_io.-t-f-record-options.pbtxt
new file mode 100644
index 00000000000..0853716023a
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.python_io.-t-f-record-options.pbtxt
@@ -0,0 +1,17 @@
+path: "tensorflow.python_io.TFRecordOptions"
+tf_class {
+  is_instance: "<class \'tensorflow.python.lib.io.tf_record.TFRecordOptions\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "compression_type_map"
+    mtype: "<type \'dict\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'compression_type\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_compression_type_string"
+    argspec: "args=[\'cls\', \'options\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.python_io.-t-f-record-writer.pbtxt b/tensorflow/tools/api/golden/tensorflow.python_io.-t-f-record-writer.pbtxt
new file mode 100644
index 00000000000..af0c11ca14d
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.python_io.-t-f-record-writer.pbtxt
@@ -0,0 +1,17 @@
+path: "tensorflow.python_io.TFRecordWriter"
+tf_class {
+  is_instance: "<class \'tensorflow.python.lib.io.tf_record.TFRecordWriter\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'path\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "write"
+    argspec: "args=[\'self\', \'record\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.python_io.pbtxt b/tensorflow/tools/api/golden/tensorflow.python_io.pbtxt
new file mode 100644
index 00000000000..7c9953e5fe3
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.python_io.pbtxt
@@ -0,0 +1,19 @@
+path: "tensorflow.python_io"
+tf_module {
+  member {
+    name: "TFRecordCompressionType"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "TFRecordOptions"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "TFRecordWriter"
+    mtype: "<type \'type\'>"
+  }
+  member_method {
+    name: "tf_record_iterator"
+    argspec: "args=[\'path\', \'options\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.random_normal_initializer.pbtxt b/tensorflow/tools/api/golden/tensorflow.random_normal_initializer.pbtxt
new file mode 100644
index 00000000000..70308bc6014
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.random_normal_initializer.pbtxt
@@ -0,0 +1,10 @@
+path: "tensorflow.random_normal_initializer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.init_ops.RandomNormal\'>"
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Initializer\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'mean\', \'stddev\', \'seed\', \'dtype\'], varargs=None, keywords=None, defaults=[\'0.0\', \'1.0\', \'None\', \"<dtype: \'float32\'>\"], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.random_uniform_initializer.pbtxt b/tensorflow/tools/api/golden/tensorflow.random_uniform_initializer.pbtxt
new file mode 100644
index 00000000000..37bb1956e82
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.random_uniform_initializer.pbtxt
@@ -0,0 +1,10 @@
+path: "tensorflow.random_uniform_initializer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.init_ops.RandomUniform\'>"
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Initializer\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'minval\', \'maxval\', \'seed\', \'dtype\'], varargs=None, keywords=None, defaults=[\'0\', \'None\', \'None\', \"<dtype: \'float32\'>\"], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.resource_loader.pbtxt b/tensorflow/tools/api/golden/tensorflow.resource_loader.pbtxt
new file mode 100644
index 00000000000..288b78b4cd0
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.resource_loader.pbtxt
@@ -0,0 +1,23 @@
+path: "tensorflow.resource_loader"
+tf_module {
+  member_method {
+    name: "get_data_files_path"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_path_to_datafile"
+    argspec: "args=[\'path\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_root_dir_with_all_resources"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "load_resource"
+    argspec: "args=[\'path\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "readahead_file_path"
+    argspec: "args=[\'path\', \'readahead\'], varargs=None, keywords=None, defaults=[\'128M\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.saved_model.builder.-saved-model-builder.pbtxt b/tensorflow/tools/api/golden/tensorflow.saved_model.builder.-saved-model-builder.pbtxt
new file mode 100644
index 00000000000..56d76902fd0
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.saved_model.builder.-saved-model-builder.pbtxt
@@ -0,0 +1,21 @@
+path: "tensorflow.saved_model.builder.SavedModelBuilder"
+tf_class {
+  is_instance: "<class \'tensorflow.python.saved_model.builder_impl.SavedModelBuilder\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'export_dir\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "add_meta_graph"
+    argspec: "args=[\'self\', \'tags\', \'signature_def_map\', \'assets_collection\', \'legacy_init_op\', \'clear_devices\', \'main_op\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "add_meta_graph_and_variables"
+    argspec: "args=[\'self\', \'sess\', \'tags\', \'signature_def_map\', \'assets_collection\', \'legacy_init_op\', \'clear_devices\', \'main_op\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "save"
+    argspec: "args=[\'self\', \'as_text\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.saved_model.builder.pbtxt b/tensorflow/tools/api/golden/tensorflow.saved_model.builder.pbtxt
new file mode 100644
index 00000000000..adc697ad1c0
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.saved_model.builder.pbtxt
@@ -0,0 +1,7 @@
+path: "tensorflow.saved_model.builder"
+tf_module {
+  member {
+    name: "SavedModelBuilder"
+    mtype: "<type \'type\'>"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.saved_model.constants.pbtxt b/tensorflow/tools/api/golden/tensorflow.saved_model.constants.pbtxt
new file mode 100644
index 00000000000..20e10aa094f
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.saved_model.constants.pbtxt
@@ -0,0 +1,39 @@
+path: "tensorflow.saved_model.constants"
+tf_module {
+  member {
+    name: "ASSETS_DIRECTORY"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "ASSETS_KEY"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "LEGACY_INIT_OP_KEY"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "MAIN_OP_KEY"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "SAVED_MODEL_FILENAME_PB"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "SAVED_MODEL_FILENAME_PBTXT"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "SAVED_MODEL_SCHEMA_VERSION"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "VARIABLES_DIRECTORY"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "VARIABLES_FILENAME"
+    mtype: "<type \'str\'>"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.saved_model.loader.pbtxt b/tensorflow/tools/api/golden/tensorflow.saved_model.loader.pbtxt
new file mode 100644
index 00000000000..896e2160c69
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.saved_model.loader.pbtxt
@@ -0,0 +1,11 @@
+path: "tensorflow.saved_model.loader"
+tf_module {
+  member_method {
+    name: "load"
+    argspec: "args=[\'sess\', \'tags\', \'export_dir\'], varargs=None, keywords=saver_kwargs, defaults=None"
+  }
+  member_method {
+    name: "maybe_saved_model_directory"
+    argspec: "args=[\'export_dir\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.saved_model.main_op.pbtxt b/tensorflow/tools/api/golden/tensorflow.saved_model.main_op.pbtxt
new file mode 100644
index 00000000000..176cb788c24
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.saved_model.main_op.pbtxt
@@ -0,0 +1,11 @@
+path: "tensorflow.saved_model.main_op"
+tf_module {
+  member_method {
+    name: "main_op"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "main_op_with_restore"
+    argspec: "args=[\'restore_op_name\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.saved_model.pbtxt b/tensorflow/tools/api/golden/tensorflow.saved_model.pbtxt
new file mode 100644
index 00000000000..5683766b289
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.saved_model.pbtxt
@@ -0,0 +1,35 @@
+path: "tensorflow.saved_model"
+tf_module {
+  member {
+    name: "builder"
+    mtype: "<type \'module\'>"
+  }
+  member {
+    name: "constants"
+    mtype: "<type \'module\'>"
+  }
+  member {
+    name: "loader"
+    mtype: "<type \'module\'>"
+  }
+  member {
+    name: "main_op"
+    mtype: "<type \'module\'>"
+  }
+  member {
+    name: "signature_constants"
+    mtype: "<type \'module\'>"
+  }
+  member {
+    name: "signature_def_utils"
+    mtype: "<type \'module\'>"
+  }
+  member {
+    name: "tag_constants"
+    mtype: "<type \'module\'>"
+  }
+  member {
+    name: "utils"
+    mtype: "<type \'module\'>"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.saved_model.signature_constants.pbtxt b/tensorflow/tools/api/golden/tensorflow.saved_model.signature_constants.pbtxt
new file mode 100644
index 00000000000..478d410e066
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.saved_model.signature_constants.pbtxt
@@ -0,0 +1,47 @@
+path: "tensorflow.saved_model.signature_constants"
+tf_module {
+  member {
+    name: "CLASSIFY_INPUTS"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "CLASSIFY_METHOD_NAME"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "CLASSIFY_OUTPUT_CLASSES"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "CLASSIFY_OUTPUT_SCORES"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "DEFAULT_SERVING_SIGNATURE_DEF_KEY"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "PREDICT_INPUTS"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "PREDICT_METHOD_NAME"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "PREDICT_OUTPUTS"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "REGRESS_INPUTS"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "REGRESS_METHOD_NAME"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "REGRESS_OUTPUTS"
+    mtype: "<type \'str\'>"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.saved_model.signature_def_utils.pbtxt b/tensorflow/tools/api/golden/tensorflow.saved_model.signature_def_utils.pbtxt
new file mode 100644
index 00000000000..e9867d84c3e
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.saved_model.signature_def_utils.pbtxt
@@ -0,0 +1,19 @@
+path: "tensorflow.saved_model.signature_def_utils"
+tf_module {
+  member_method {
+    name: "build_signature_def"
+    argspec: "args=[\'inputs\', \'outputs\', \'method_name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "classification_signature_def"
+    argspec: "args=[\'examples\', \'classes\', \'scores\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "predict_signature_def"
+    argspec: "args=[\'inputs\', \'outputs\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "regression_signature_def"
+    argspec: "args=[\'examples\', \'predictions\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.saved_model.tag_constants.pbtxt b/tensorflow/tools/api/golden/tensorflow.saved_model.tag_constants.pbtxt
new file mode 100644
index 00000000000..7c24b7ad3cf
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.saved_model.tag_constants.pbtxt
@@ -0,0 +1,11 @@
+path: "tensorflow.saved_model.tag_constants"
+tf_module {
+  member {
+    name: "SERVING"
+    mtype: "<type \'str\'>"
+  }
+  member {
+    name: "TRAINING"
+    mtype: "<type \'str\'>"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.saved_model.utils.pbtxt b/tensorflow/tools/api/golden/tensorflow.saved_model.utils.pbtxt
new file mode 100644
index 00000000000..bc150e56a36
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.saved_model.utils.pbtxt
@@ -0,0 +1,7 @@
+path: "tensorflow.saved_model.utils"
+tf_module {
+  member_method {
+    name: "build_tensor_info"
+    argspec: "args=[\'tensor\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.sdca.pbtxt b/tensorflow/tools/api/golden/tensorflow.sdca.pbtxt
new file mode 100644
index 00000000000..7c9e6a25c7a
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.sdca.pbtxt
@@ -0,0 +1,3 @@
+path: "tensorflow.sdca"
+tf_module {
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.sets.pbtxt b/tensorflow/tools/api/golden/tensorflow.sets.pbtxt
new file mode 100644
index 00000000000..8a196b1a556
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.sets.pbtxt
@@ -0,0 +1,19 @@
+path: "tensorflow.sets"
+tf_module {
+  member_method {
+    name: "set_difference"
+    argspec: "args=[\'a\', \'b\', \'aminusb\', \'validate_indices\'], varargs=None, keywords=None, defaults=[\'True\', \'True\'], "
+  }
+  member_method {
+    name: "set_intersection"
+    argspec: "args=[\'a\', \'b\', \'validate_indices\'], varargs=None, keywords=None, defaults=[\'True\'], "
+  }
+  member_method {
+    name: "set_size"
+    argspec: "args=[\'a\', \'validate_indices\'], varargs=None, keywords=None, defaults=[\'True\'], "
+  }
+  member_method {
+    name: "set_union"
+    argspec: "args=[\'a\', \'b\', \'validate_indices\'], varargs=None, keywords=None, defaults=[\'True\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.spectral.pbtxt b/tensorflow/tools/api/golden/tensorflow.spectral.pbtxt
new file mode 100644
index 00000000000..84883c1a395
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.spectral.pbtxt
@@ -0,0 +1,51 @@
+path: "tensorflow.spectral"
+tf_module {
+  member_method {
+    name: "fft"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "fft2d"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "fft3d"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "ifft"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "ifft2d"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "ifft3d"
+    argspec: "args=[\'input\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "irfft"
+    argspec: "args=[\'input_tensor\', \'fft_length\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "irfft2d"
+    argspec: "args=[\'input_tensor\', \'fft_length\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "irfft3d"
+    argspec: "args=[\'input_tensor\', \'fft_length\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "rfft"
+    argspec: "args=[\'input_tensor\', \'fft_length\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "rfft2d"
+    argspec: "args=[\'input_tensor\', \'fft_length\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "rfft3d"
+    argspec: "args=[\'input_tensor\', \'fft_length\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.summary.-event.pbtxt b/tensorflow/tools/api/golden/tensorflow.summary.-event.pbtxt
new file mode 100644
index 00000000000..ab3449d80f6
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.summary.-event.pbtxt
@@ -0,0 +1,112 @@
+path: "tensorflow.summary.Event"
+tf_class {
+  is_instance: "<class \'tensorflow.core.util.event_pb2.Event\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FILE_VERSION_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GRAPH_DEF_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "LOG_MESSAGE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "META_GRAPH_DEF_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SESSION_LOG_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "STEP_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SUMMARY_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TAGGED_RUN_METADATA_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "WALL_TIME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.summary.-file-writer-cache.pbtxt b/tensorflow/tools/api/golden/tensorflow.summary.-file-writer-cache.pbtxt
new file mode 100644
index 00000000000..2a5b63dceae
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.summary.-file-writer-cache.pbtxt
@@ -0,0 +1,16 @@
+path: "tensorflow.summary.FileWriterCache"
+tf_class {
+  is_instance: "<class \'tensorflow.python.summary.writer.writer_cache.FileWriterCache\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "clear"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get"
+    argspec: "args=[\'logdir\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.summary.-file-writer.pbtxt b/tensorflow/tools/api/golden/tensorflow.summary.-file-writer.pbtxt
new file mode 100644
index 00000000000..502c35ee7bb
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.summary.-file-writer.pbtxt
@@ -0,0 +1,50 @@
+path: "tensorflow.summary.FileWriter"
+tf_class {
+  is_instance: "<class \'tensorflow.python.summary.writer.writer.FileWriter\'>"
+  is_instance: "<class \'tensorflow.python.summary.writer.writer.SummaryToEventTransformer\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'logdir\', \'graph\', \'max_queue\', \'flush_secs\', \'graph_def\'], varargs=None, keywords=None, defaults=[\'None\', \'10\', \'120\', \'None\'], "
+  }
+  member_method {
+    name: "add_event"
+    argspec: "args=[\'self\', \'event\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "add_graph"
+    argspec: "args=[\'self\', \'graph\', \'global_step\', \'graph_def\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "add_meta_graph"
+    argspec: "args=[\'self\', \'meta_graph_def\', \'global_step\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "add_run_metadata"
+    argspec: "args=[\'self\', \'run_metadata\', \'tag\', \'global_step\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "add_session_log"
+    argspec: "args=[\'self\', \'session_log\', \'global_step\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "add_summary"
+    argspec: "args=[\'self\', \'summary\', \'global_step\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "flush"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_logdir"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "reopen"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.summary.-session-log.pbtxt b/tensorflow/tools/api/golden/tensorflow.summary.-session-log.pbtxt
new file mode 100644
index 00000000000..92ca4872caf
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.summary.-session-log.pbtxt
@@ -0,0 +1,108 @@
+path: "tensorflow.summary.SessionLog"
+tf_class {
+  is_instance: "<class \'tensorflow.core.util.event_pb2.SessionLog\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "CHECKPOINT"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "CHECKPOINT_PATH_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "MSG_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "START"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "STATUS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "STATUS_UNSPECIFIED"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "STOP"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SessionStatus"
+    mtype: "<class \'google.protobuf.internal.enum_type_wrapper.EnumTypeWrapper\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.summary.-summary-description.pbtxt b/tensorflow/tools/api/golden/tensorflow.summary.-summary-description.pbtxt
new file mode 100644
index 00000000000..f93da2196ad
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.summary.-summary-description.pbtxt
@@ -0,0 +1,80 @@
+path: "tensorflow.summary.SummaryDescription"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.summary_pb2.SummaryDescription\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "TYPE_HINT_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.summary.-summary.-audio.pbtxt b/tensorflow/tools/api/golden/tensorflow.summary.-summary.-audio.pbtxt
new file mode 100644
index 00000000000..605e305e82c
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.summary.-summary.-audio.pbtxt
@@ -0,0 +1,96 @@
+path: "tensorflow.summary.Summary.Audio"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.summary_pb2.Audio\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "CONTENT_TYPE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "ENCODED_AUDIO_STRING_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "LENGTH_FRAMES_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "NUM_CHANNELS_FIELD_NUMBER"
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+  member_method {
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+  member_method {
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+  member_method {
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+  member_method {
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+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.summary.-summary.-image.pbtxt b/tensorflow/tools/api/golden/tensorflow.summary.-summary.-image.pbtxt
new file mode 100644
index 00000000000..0646972196d
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.summary.-summary.-image.pbtxt
@@ -0,0 +1,92 @@
+path: "tensorflow.summary.Summary.Image"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.summary_pb2.Image\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "COLORSPACE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
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+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "ENCODED_IMAGE_STRING_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
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+    mtype: "<type \'int\'>"
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+  member_method {
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+  member_method {
+    name: "FromString"
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+  member_method {
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+  member_method {
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+  member_method {
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+  member_method {
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+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.summary.-summary.-value.pbtxt b/tensorflow/tools/api/golden/tensorflow.summary.-summary.-value.pbtxt
new file mode 100644
index 00000000000..5294b37f577
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.summary.-summary.-value.pbtxt
@@ -0,0 +1,108 @@
+path: "tensorflow.summary.Summary.Value"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.summary_pb2.Value\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "AUDIO_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "HISTO_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "IMAGE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "NODE_NAME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "OBSOLETE_OLD_STYLE_HISTOGRAM_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SIMPLE_VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TAG_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TENSOR_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
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+    name: "ByteSize"
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+  member_method {
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+  member_method {
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+  member_method {
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+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
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+  member_method {
+    name: "MergeFrom"
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+  member_method {
+    name: "MergeFromString"
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+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.summary.-summary.pbtxt b/tensorflow/tools/api/golden/tensorflow.summary.-summary.pbtxt
new file mode 100644
index 00000000000..132ef1b7d2e
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.summary.-summary.pbtxt
@@ -0,0 +1,92 @@
+path: "tensorflow.summary.Summary"
+tf_class {
+  is_instance: "<class \'tensorflow.core.framework.summary_pb2.Summary\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "Audio"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "Image"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
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+    name: "Value"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
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+  }
+  member_method {
+    name: "FromString"
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+  member_method {
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+  }
+  member_method {
+    name: "HasField"
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+    name: "IsInitialized"
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+  member_method {
+    name: "MergeFrom"
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+  member_method {
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+  }
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+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.summary.-tagged-run-metadata.pbtxt b/tensorflow/tools/api/golden/tensorflow.summary.-tagged-run-metadata.pbtxt
new file mode 100644
index 00000000000..4dce20819de
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.summary.-tagged-run-metadata.pbtxt
@@ -0,0 +1,84 @@
+path: "tensorflow.summary.TaggedRunMetadata"
+tf_class {
+  is_instance: "<class \'tensorflow.core.util.event_pb2.TaggedRunMetadata\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "RUN_METADATA_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TAG_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
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+  member_method {
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+  member_method {
+    name: "ClearExtension"
+  }
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+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
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+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
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+  member_method {
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+    name: "MergeFromString"
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+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
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+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
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+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.summary.pbtxt b/tensorflow/tools/api/golden/tensorflow.summary.pbtxt
new file mode 100644
index 00000000000..c3d0bea10cb
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.summary.pbtxt
@@ -0,0 +1,67 @@
+path: "tensorflow.summary"
+tf_module {
+  member {
+    name: "Event"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "FileWriter"
+    mtype: "<type \'type\'>"
+  }
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+    name: "FileWriterCache"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SessionLog"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "Summary"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "SummaryDescription"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "TaggedRunMetadata"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member_method {
+    name: "audio"
+    argspec: "args=[\'name\', \'tensor\', \'sample_rate\', \'max_outputs\', \'collections\'], varargs=None, keywords=None, defaults=[\'3\', \'None\'], "
+  }
+  member_method {
+    name: "get_summary_description"
+    argspec: "args=[\'node_def\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "histogram"
+    argspec: "args=[\'name\', \'values\', \'collections\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "image"
+    argspec: "args=[\'name\', \'tensor\', \'max_outputs\', \'collections\'], varargs=None, keywords=None, defaults=[\'3\', \'None\'], "
+  }
+  member_method {
+    name: "merge"
+    argspec: "args=[\'inputs\', \'collections\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "merge_all"
+    argspec: "args=[\'key\'], varargs=None, keywords=None, defaults=[\'summaries\'], "
+  }
+  member_method {
+    name: "scalar"
+    argspec: "args=[\'name\', \'tensor\', \'collections\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "tensor_summary"
+    argspec: "args=[\'name\', \'tensor\', \'summary_description\', \'collections\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "text"
+    argspec: "args=[\'name\', \'tensor\', \'collections\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.sysconfig.pbtxt b/tensorflow/tools/api/golden/tensorflow.sysconfig.pbtxt
new file mode 100644
index 00000000000..02dec04b9cc
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.sysconfig.pbtxt
@@ -0,0 +1,11 @@
+path: "tensorflow.sysconfig"
+tf_module {
+  member_method {
+    name: "get_include"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_lib"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.test.-benchmark.pbtxt b/tensorflow/tools/api/golden/tensorflow.test.-benchmark.pbtxt
new file mode 100644
index 00000000000..df528e26b60
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.test.-benchmark.pbtxt
@@ -0,0 +1,21 @@
+path: "tensorflow.test.Benchmark"
+tf_class {
+  is_instance: "<class \'tensorflow.python.platform.benchmark.TensorFlowBenchmark\'>"
+  is_instance: "<class \'tensorflow.python.platform.benchmark.Benchmark\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "is_abstract"
+    argspec: "args=[\'cls\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "report_benchmark"
+    argspec: "args=[\'self\', \'iters\', \'cpu_time\', \'wall_time\', \'throughput\', \'extras\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "run_op_benchmark"
+    argspec: "args=[\'self\', \'sess\', \'op_or_tensor\', \'feed_dict\', \'burn_iters\', \'min_iters\', \'store_trace\', \'store_memory_usage\', \'name\', \'extras\', \'mbs\'], varargs=None, keywords=None, defaults=[\'None\', \'2\', \'10\', \'False\', \'True\', \'None\', \'None\', \'0\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.test.pbtxt b/tensorflow/tools/api/golden/tensorflow.test.pbtxt
new file mode 100644
index 00000000000..c4768a68bfb
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.test.pbtxt
@@ -0,0 +1,51 @@
+path: "tensorflow.test"
+tf_module {
+  member {
+    name: "Benchmark"
+    mtype: "<class \'tensorflow.python.platform.benchmark._BenchmarkRegistrar\'>"
+  }
+  member {
+    name: "TestCase"
+    mtype: "<type \'type\'>"
+  }
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+    name: "mock"
+    mtype: "<type \'module\'>"
+  }
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+    name: "assert_equal_graph_def"
+    argspec: "args=[\'actual\', \'expected\', \'checkpoint_v2\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
+  member_method {
+    name: "compute_gradient"
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+  }
+  member_method {
+    name: "compute_gradient_error"
+    argspec: "args=[\'x\', \'x_shape\', \'y\', \'y_shape\', \'x_init_value\', \'delta\', \'init_targets\', \'extra_feed_dict\'], varargs=None, keywords=None, defaults=[\'None\', \'0.001\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "get_temp_dir"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "gpu_device_name"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "is_built_with_cuda"
+    argspec: "args=[], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "is_gpu_available"
+    argspec: "args=[\'cuda_only\'], varargs=None, keywords=None, defaults=[\'False\'], "
+  }
+  member_method {
+    name: "main"
+    argspec: "args=[\'argv\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "test_src_dir_path"
+    argspec: "args=[\'relative_path\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-adadelta-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-adadelta-optimizer.pbtxt
new file mode 100644
index 00000000000..8c91c5b4d9e
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-adadelta-optimizer.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.train.AdadeltaOptimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.adadelta.AdadeltaOptimizer\'>"
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'rho\', \'epsilon\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'0.001\', \'0.95\', \'1e-08\', \'False\', \'Adadelta\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-adagrad-d-a-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-adagrad-d-a-optimizer.pbtxt
new file mode 100644
index 00000000000..05d38d62ccd
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-adagrad-d-a-optimizer.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.train.AdagradDAOptimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.adagrad_da.AdagradDAOptimizer\'>"
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'global_step\', \'initial_gradient_squared_accumulator_value\', \'l1_regularization_strength\', \'l2_regularization_strength\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'0.1\', \'0.0\', \'0.0\', \'False\', \'AdagradDA\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-adagrad-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-adagrad-optimizer.pbtxt
new file mode 100644
index 00000000000..19ca9f57637
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-adagrad-optimizer.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.train.AdagradOptimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.adagrad.AdagradOptimizer\'>"
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'initial_accumulator_value\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'0.1\', \'False\', \'Adagrad\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-adam-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-adam-optimizer.pbtxt
new file mode 100644
index 00000000000..c8144e2db78
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-adam-optimizer.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.train.AdamOptimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.adam.AdamOptimizer\'>"
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'beta1\', \'beta2\', \'epsilon\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'0.001\', \'0.9\', \'0.999\', \'1e-08\', \'False\', \'Adam\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-bytes-list.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-bytes-list.pbtxt
new file mode 100644
index 00000000000..8cf52b817f3
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-bytes-list.pbtxt
@@ -0,0 +1,80 @@
+path: "tensorflow.train.BytesList"
+tf_class {
+  is_instance: "<class \'tensorflow.core.example.feature_pb2.BytesList\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-checkpoint-saver-hook.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-checkpoint-saver-hook.pbtxt
new file mode 100644
index 00000000000..c3037baa8c9
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-checkpoint-saver-hook.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.train.CheckpointSaverHook"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.CheckpointSaverHook\'>"
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunHook\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'checkpoint_dir\', \'save_secs\', \'save_steps\', \'saver\', \'checkpoint_basename\', \'scaffold\', \'listeners\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'model.ckpt\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "after_create_session"
+    argspec: "args=[\'self\', \'session\', \'coord\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_run"
+    argspec: "args=[\'self\', \'run_context\', \'run_values\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "before_run"
+    argspec: "args=[\'self\', \'run_context\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "begin"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "end"
+    argspec: "args=[\'self\', \'session\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-checkpoint-saver-listener.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-checkpoint-saver-listener.pbtxt
new file mode 100644
index 00000000000..9d3688e5657
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-checkpoint-saver-listener.pbtxt
@@ -0,0 +1,24 @@
+path: "tensorflow.train.CheckpointSaverListener"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.CheckpointSaverListener\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "after_save"
+    argspec: "args=[\'self\', \'session\', \'global_step_value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "before_save"
+    argspec: "args=[\'self\', \'session\', \'global_step_value\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "begin"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "end"
+    argspec: "args=[\'self\', \'session\', \'global_step_value\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-chief-session-creator.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-chief-session-creator.pbtxt
new file mode 100644
index 00000000000..abbe273be32
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-chief-session-creator.pbtxt
@@ -0,0 +1,14 @@
+path: "tensorflow.train.ChiefSessionCreator"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.monitored_session.ChiefSessionCreator\'>"
+  is_instance: "<class \'tensorflow.python.training.monitored_session.SessionCreator\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'scaffold\', \'master\', \'config\', \'checkpoint_dir\', \'checkpoint_filename_with_path\'], varargs=None, keywords=None, defaults=[\'None\', \'\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "create_session"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-cluster-def.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-cluster-def.pbtxt
new file mode 100644
index 00000000000..feb73bd7d4f
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-cluster-def.pbtxt
@@ -0,0 +1,80 @@
+path: "tensorflow.train.ClusterDef"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.tensorflow_server_pb2.ClusterDef\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "JOB_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-cluster-spec.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-cluster-spec.pbtxt
new file mode 100644
index 00000000000..1658b15a5f8
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-cluster-spec.pbtxt
@@ -0,0 +1,37 @@
+path: "tensorflow.train.ClusterSpec"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.server_lib.ClusterSpec\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "jobs"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'cluster\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "as_cluster_def"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "as_dict"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "job_tasks"
+    argspec: "args=[\'self\', \'job_name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "num_tasks"
+    argspec: "args=[\'self\', \'job_name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "task_address"
+    argspec: "args=[\'self\', \'job_name\', \'task_index\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "task_indices"
+    argspec: "args=[\'self\', \'job_name\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-coordinator.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-coordinator.pbtxt
new file mode 100644
index 00000000000..11277f077ee
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-coordinator.pbtxt
@@ -0,0 +1,45 @@
+path: "tensorflow.train.Coordinator"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.coordinator.Coordinator\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "joined"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'clean_stop_exception_types\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "clear_stop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "join"
+    argspec: "args=[\'self\', \'threads\', \'stop_grace_period_secs\', \'ignore_live_threads\'], varargs=None, keywords=None, defaults=[\'None\', \'120\', \'False\'], "
+  }
+  member_method {
+    name: "raise_requested_exception"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "register_thread"
+    argspec: "args=[\'self\', \'thread\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "request_stop"
+    argspec: "args=[\'self\', \'ex\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "should_stop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "stop_on_exception"
+    argspec: "args=[], varargs=args, keywords=kwds, defaults=None"
+  }
+  member_method {
+    name: "wait_for_stop"
+    argspec: "args=[\'self\', \'timeout\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-example.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-example.pbtxt
new file mode 100644
index 00000000000..f7215a20372
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-example.pbtxt
@@ -0,0 +1,80 @@
+path: "tensorflow.train.Example"
+tf_class {
+  is_instance: "<class \'tensorflow.core.example.example_pb2.Example\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FEATURES_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-exponential-moving-average.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-exponential-moving-average.pbtxt
new file mode 100644
index 00000000000..737acbe07c9
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-exponential-moving-average.pbtxt
@@ -0,0 +1,25 @@
+path: "tensorflow.train.ExponentialMovingAverage"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.moving_averages.ExponentialMovingAverage\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'decay\', \'num_updates\', \'zero_debias\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'ExponentialMovingAverage\'], "
+  }
+  member_method {
+    name: "apply"
+    argspec: "args=[\'self\', \'var_list\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "average"
+    argspec: "args=[\'self\', \'var\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "average_name"
+    argspec: "args=[\'self\', \'var\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "variables_to_restore"
+    argspec: "args=[\'self\', \'moving_avg_variables\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-feature-list.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-feature-list.pbtxt
new file mode 100644
index 00000000000..3ad98354d69
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-feature-list.pbtxt
@@ -0,0 +1,80 @@
+path: "tensorflow.train.FeatureList"
+tf_class {
+  is_instance: "<class \'tensorflow.core.example.feature_pb2.FeatureList\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FEATURE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-feature-lists.-feature-list-entry.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-feature-lists.-feature-list-entry.pbtxt
new file mode 100644
index 00000000000..cd171f4ca3e
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-feature-lists.-feature-list-entry.pbtxt
@@ -0,0 +1,84 @@
+path: "tensorflow.train.FeatureLists.FeatureListEntry"
+tf_class {
+  is_instance: "<class \'tensorflow.core.example.feature_pb2.FeatureListEntry\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "KEY_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-feature-lists.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-feature-lists.pbtxt
new file mode 100644
index 00000000000..3d95017d584
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-feature-lists.pbtxt
@@ -0,0 +1,84 @@
+path: "tensorflow.train.FeatureLists"
+tf_class {
+  is_instance: "<class \'tensorflow.core.example.feature_pb2.FeatureLists\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FEATURE_LIST_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "FeatureListEntry"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-feature.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-feature.pbtxt
new file mode 100644
index 00000000000..9cca132bba9
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-feature.pbtxt
@@ -0,0 +1,88 @@
+path: "tensorflow.train.Feature"
+tf_class {
+  is_instance: "<class \'tensorflow.core.example.feature_pb2.Feature\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "BYTES_LIST_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FLOAT_LIST_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "INT64_LIST_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-features.-feature-entry.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-features.-feature-entry.pbtxt
new file mode 100644
index 00000000000..858aee03415
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-features.-feature-entry.pbtxt
@@ -0,0 +1,84 @@
+path: "tensorflow.train.Features.FeatureEntry"
+tf_class {
+  is_instance: "<class \'tensorflow.core.example.feature_pb2.FeatureEntry\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "KEY_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-features.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-features.pbtxt
new file mode 100644
index 00000000000..49cd12153bf
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-features.pbtxt
@@ -0,0 +1,84 @@
+path: "tensorflow.train.Features"
+tf_class {
+  is_instance: "<class \'tensorflow.core.example.feature_pb2.Features\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FEATURE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "FeatureEntry"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-feed-fn-hook.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-feed-fn-hook.pbtxt
new file mode 100644
index 00000000000..7bec4d032ce
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-feed-fn-hook.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.train.FeedFnHook"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.FeedFnHook\'>"
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunHook\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'feed_fn\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_create_session"
+    argspec: "args=[\'self\', \'session\', \'coord\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_run"
+    argspec: "args=[\'self\', \'run_context\', \'run_values\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "before_run"
+    argspec: "args=[\'self\', \'run_context\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "begin"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "end"
+    argspec: "args=[\'self\', \'session\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-final-ops-hook.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-final-ops-hook.pbtxt
new file mode 100644
index 00000000000..31cf9aaeb2c
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-final-ops-hook.pbtxt
@@ -0,0 +1,34 @@
+path: "tensorflow.train.FinalOpsHook"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.FinalOpsHook\'>"
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunHook\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "final_ops_values"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'final_ops\', \'final_ops_feed_dict\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "after_create_session"
+    argspec: "args=[\'self\', \'session\', \'coord\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_run"
+    argspec: "args=[\'self\', \'run_context\', \'run_values\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "before_run"
+    argspec: "args=[\'self\', \'run_context\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "begin"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "end"
+    argspec: "args=[\'self\', \'session\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-float-list.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-float-list.pbtxt
new file mode 100644
index 00000000000..e3f01334b54
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-float-list.pbtxt
@@ -0,0 +1,80 @@
+path: "tensorflow.train.FloatList"
+tf_class {
+  is_instance: "<class \'tensorflow.core.example.feature_pb2.FloatList\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-ftrl-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-ftrl-optimizer.pbtxt
new file mode 100644
index 00000000000..0252474a1d5
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-ftrl-optimizer.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.train.FtrlOptimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.ftrl.FtrlOptimizer\'>"
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'learning_rate_power\', \'initial_accumulator_value\', \'l1_regularization_strength\', \'l2_regularization_strength\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'-0.5\', \'0.1\', \'0.0\', \'0.0\', \'False\', \'Ftrl\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-global-step-waiter-hook.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-global-step-waiter-hook.pbtxt
new file mode 100644
index 00000000000..147448618e2
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-global-step-waiter-hook.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.train.GlobalStepWaiterHook"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.GlobalStepWaiterHook\'>"
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunHook\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'wait_until_step\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_create_session"
+    argspec: "args=[\'self\', \'session\', \'coord\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_run"
+    argspec: "args=[\'self\', \'run_context\', \'run_values\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "before_run"
+    argspec: "args=[\'self\', \'run_context\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "begin"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "end"
+    argspec: "args=[\'self\', \'session\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-gradient-descent-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-gradient-descent-optimizer.pbtxt
new file mode 100644
index 00000000000..bdd4c525685
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-gradient-descent-optimizer.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.train.GradientDescentOptimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.gradient_descent.GradientDescentOptimizer\'>"
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'GradientDescent\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-int64-list.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-int64-list.pbtxt
new file mode 100644
index 00000000000..8917dc122cf
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-int64-list.pbtxt
@@ -0,0 +1,80 @@
+path: "tensorflow.train.Int64List"
+tf_class {
+  is_instance: "<class \'tensorflow.core.example.feature_pb2.Int64List\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-job-def.-tasks-entry.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-job-def.-tasks-entry.pbtxt
new file mode 100644
index 00000000000..2d7fcbe5456
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-job-def.-tasks-entry.pbtxt
@@ -0,0 +1,84 @@
+path: "tensorflow.train.JobDef.TasksEntry"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.tensorflow_server_pb2.TasksEntry\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "KEY_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "VALUE_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-job-def.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-job-def.pbtxt
new file mode 100644
index 00000000000..fc5b76341d2
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-job-def.pbtxt
@@ -0,0 +1,88 @@
+path: "tensorflow.train.JobDef"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.tensorflow_server_pb2.JobDef\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "NAME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TASKS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TasksEntry"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-logging-tensor-hook.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-logging-tensor-hook.pbtxt
new file mode 100644
index 00000000000..e55c47b3567
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-logging-tensor-hook.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.train.LoggingTensorHook"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.LoggingTensorHook\'>"
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunHook\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'tensors\', \'every_n_iter\', \'every_n_secs\', \'formatter\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "after_create_session"
+    argspec: "args=[\'self\', \'session\', \'coord\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_run"
+    argspec: "args=[\'self\', \'run_context\', \'run_values\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "before_run"
+    argspec: "args=[\'self\', \'run_context\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "begin"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "end"
+    argspec: "args=[\'self\', \'session\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-looper-thread.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-looper-thread.pbtxt
new file mode 100644
index 00000000000..c61859004e8
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-looper-thread.pbtxt
@@ -0,0 +1,73 @@
+path: "tensorflow.train.LooperThread"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.coordinator.LooperThread\'>"
+  is_instance: "<class \'threading.Thread\'>"
+  member {
+    name: "daemon"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "ident"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'coord\', \'timer_interval_secs\', \'target\', \'args\', \'kwargs\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "getName"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "isAlive"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "isDaemon"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "is_alive"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "join"
+    argspec: "args=[\'self\', \'timeout\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "loop"
+    argspec: "args=[\'coord\', \'timer_interval_secs\', \'target\', \'args\', \'kwargs\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "run"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "run_loop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "setDaemon"
+    argspec: "args=[\'self\', \'daemonic\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "setName"
+    argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "start"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "start_loop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "stop_loop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-momentum-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-momentum-optimizer.pbtxt
new file mode 100644
index 00000000000..7cf5488a15e
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-momentum-optimizer.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.train.MomentumOptimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.momentum.MomentumOptimizer\'>"
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'momentum\', \'use_locking\', \'name\', \'use_nesterov\'], varargs=None, keywords=None, defaults=[\'False\', \'Momentum\', \'False\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-monitored-session.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-monitored-session.pbtxt
new file mode 100644
index 00000000000..3a5cc015b4d
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-monitored-session.pbtxt
@@ -0,0 +1,26 @@
+path: "tensorflow.train.MonitoredSession"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.monitored_session.MonitoredSession\'>"
+  is_instance: "<class \'tensorflow.python.training.monitored_session._MonitoredSession\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "graph"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'session_creator\', \'hooks\', \'stop_grace_period_secs\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'120\'], "
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "run"
+    argspec: "args=[\'self\', \'fetches\', \'feed_dict\', \'options\', \'run_metadata\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "should_stop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-nan-loss-during-training-error.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-nan-loss-during-training-error.pbtxt
new file mode 100644
index 00000000000..25fd5e75a79
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-nan-loss-during-training-error.pbtxt
@@ -0,0 +1,16 @@
+path: "tensorflow.train.NanLossDuringTrainingError"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.NanLossDuringTrainingError\'>"
+  is_instance: "<type \'exceptions.RuntimeError\'>"
+  member {
+    name: "args"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "message"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-nan-tensor-hook.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-nan-tensor-hook.pbtxt
new file mode 100644
index 00000000000..7d1c89f9b37
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-nan-tensor-hook.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.train.NanTensorHook"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.NanTensorHook\'>"
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunHook\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'loss_tensor\', \'fail_on_nan_loss\'], varargs=None, keywords=None, defaults=[\'True\'], "
+  }
+  member_method {
+    name: "after_create_session"
+    argspec: "args=[\'self\', \'session\', \'coord\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_run"
+    argspec: "args=[\'self\', \'run_context\', \'run_values\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "before_run"
+    argspec: "args=[\'self\', \'run_context\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "begin"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "end"
+    argspec: "args=[\'self\', \'session\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-optimizer.pbtxt
new file mode 100644
index 00000000000..20b0c4d1b56
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-optimizer.pbtxt
@@ -0,0 +1,45 @@
+path: "tensorflow.train.Optimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-proximal-adagrad-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-proximal-adagrad-optimizer.pbtxt
new file mode 100644
index 00000000000..571d846b6c5
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-proximal-adagrad-optimizer.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.train.ProximalAdagradOptimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.proximal_adagrad.ProximalAdagradOptimizer\'>"
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'initial_accumulator_value\', \'l1_regularization_strength\', \'l2_regularization_strength\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'0.1\', \'0.0\', \'0.0\', \'False\', \'ProximalAdagrad\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-proximal-gradient-descent-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-proximal-gradient-descent-optimizer.pbtxt
new file mode 100644
index 00000000000..1feb136e7f7
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-proximal-gradient-descent-optimizer.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.train.ProximalGradientDescentOptimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.proximal_gradient_descent.ProximalGradientDescentOptimizer\'>"
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'l1_regularization_strength\', \'l2_regularization_strength\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0\', \'0.0\', \'False\', \'ProximalGradientDescent\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-queue-runner.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-queue-runner.pbtxt
new file mode 100644
index 00000000000..d84d0058eea
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-queue-runner.pbtxt
@@ -0,0 +1,49 @@
+path: "tensorflow.train.QueueRunner"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.queue_runner_impl.QueueRunner\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "cancel_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "close_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "enqueue_ops"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "exceptions_raised"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "queue"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "queue_closed_exception_types"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'queue\', \'enqueue_ops\', \'close_op\', \'cancel_op\', \'queue_closed_exception_types\', \'queue_runner_def\', \'import_scope\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "create_threads"
+    argspec: "args=[\'self\', \'sess\', \'coord\', \'daemon\', \'start\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'False\'], "
+  }
+  member_method {
+    name: "from_proto"
+    argspec: "args=[\'queue_runner_def\', \'import_scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "to_proto"
+    argspec: "args=[\'self\', \'export_scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-r-m-s-prop-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-r-m-s-prop-optimizer.pbtxt
new file mode 100644
index 00000000000..2aa4ae6d2d2
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-r-m-s-prop-optimizer.pbtxt
@@ -0,0 +1,46 @@
+path: "tensorflow.train.RMSPropOptimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.rmsprop.RMSPropOptimizer\'>"
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'learning_rate\', \'decay\', \'momentum\', \'epsilon\', \'use_locking\', \'centered\', \'name\'], varargs=None, keywords=None, defaults=[\'0.9\', \'0.0\', \'1e-10\', \'False\', \'False\', \'RMSProp\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-saver-def.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-saver-def.pbtxt
new file mode 100644
index 00000000000..84498a64f5b
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-saver-def.pbtxt
@@ -0,0 +1,120 @@
+path: "tensorflow.train.SaverDef"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.saver_pb2.SaverDef\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "CheckpointFormatVersion"
+    mtype: "<class \'google.protobuf.internal.enum_type_wrapper.EnumTypeWrapper\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FILENAME_TENSOR_NAME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "KEEP_CHECKPOINT_EVERY_N_HOURS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "LEGACY"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "MAX_TO_KEEP_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "RESTORE_OP_NAME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SAVE_TENSOR_NAME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "SHARDED_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "V1"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "V2"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "VERSION_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-saver.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-saver.pbtxt
new file mode 100644
index 00000000000..7494fe1cc84
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-saver.pbtxt
@@ -0,0 +1,53 @@
+path: "tensorflow.train.Saver"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.saver.Saver\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "last_checkpoints"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'var_list\', \'reshape\', \'sharded\', \'max_to_keep\', \'keep_checkpoint_every_n_hours\', \'name\', \'restore_sequentially\', \'saver_def\', \'builder\', \'defer_build\', \'allow_empty\', \'write_version\', \'pad_step_number\', \'save_relative_paths\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'False\', \'5\', \'10000.0\', \'None\', \'False\', \'None\', \'None\', \'False\', \'False\', \'2\', \'False\', \'False\'], "
+  }
+  member_method {
+    name: "as_saver_def"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "build"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "export_meta_graph"
+    argspec: "args=[\'self\', \'filename\', \'collection_list\', \'as_text\', \'export_scope\', \'clear_devices\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'False\', \'None\', \'False\'], "
+  }
+  member_method {
+    name: "from_proto"
+    argspec: "args=[\'saver_def\', \'import_scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "recover_last_checkpoints"
+    argspec: "args=[\'self\', \'checkpoint_paths\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "restore"
+    argspec: "args=[\'self\', \'sess\', \'save_path\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "save"
+    argspec: "args=[\'self\', \'sess\', \'save_path\', \'global_step\', \'latest_filename\', \'meta_graph_suffix\', \'write_meta_graph\', \'write_state\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'meta\', \'True\', \'True\'], "
+  }
+  member_method {
+    name: "set_last_checkpoints"
+    argspec: "args=[\'self\', \'last_checkpoints\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "set_last_checkpoints_with_time"
+    argspec: "args=[\'self\', \'last_checkpoints_with_time\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "to_proto"
+    argspec: "args=[\'self\', \'export_scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-scaffold.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-scaffold.pbtxt
new file mode 100644
index 00000000000..21234fe7391
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-scaffold.pbtxt
@@ -0,0 +1,49 @@
+path: "tensorflow.train.Scaffold"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.monitored_session.Scaffold\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "init_feed_dict"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "init_fn"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "init_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "local_init_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "ready_for_local_init_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "ready_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "saver"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "summary_op"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'init_op\', \'init_feed_dict\', \'init_fn\', \'ready_op\', \'ready_for_local_init_op\', \'local_init_op\', \'summary_op\', \'saver\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "finalize"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_or_default"
+    argspec: "args=[\'arg_name\', \'collection_key\', \'default_constructor\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-second-or-step-timer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-second-or-step-timer.pbtxt
new file mode 100644
index 00000000000..45528d4e87e
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-second-or-step-timer.pbtxt
@@ -0,0 +1,21 @@
+path: "tensorflow.train.SecondOrStepTimer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.SecondOrStepTimer\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'every_secs\', \'every_steps\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "last_triggered_step"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "should_trigger_for_step"
+    argspec: "args=[\'self\', \'step\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "update_last_triggered_step"
+    argspec: "args=[\'self\', \'step\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-sequence-example.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-sequence-example.pbtxt
new file mode 100644
index 00000000000..9ab95537021
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-sequence-example.pbtxt
@@ -0,0 +1,84 @@
+path: "tensorflow.train.SequenceExample"
+tf_class {
+  is_instance: "<class \'tensorflow.core.example.example_pb2.SequenceExample\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "CONTEXT_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "FEATURE_LISTS_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-server-def.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-server-def.pbtxt
new file mode 100644
index 00000000000..af0a3b73cc2
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-server-def.pbtxt
@@ -0,0 +1,96 @@
+path: "tensorflow.train.ServerDef"
+tf_class {
+  is_instance: "<class \'tensorflow.core.protobuf.tensorflow_server_pb2.ServerDef\'>"
+  is_instance: "<type \'google.protobuf.pyext._message.CMessage\'>"
+  member {
+    name: "CLUSTER_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DEFAULT_SESSION_CONFIG_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "DESCRIPTOR"
+    mtype: "<type \'google.protobuf.pyext._message.MessageDescriptor\'>"
+  }
+  member {
+    name: "Extensions"
+    mtype: "<type \'getset_descriptor\'>"
+  }
+  member {
+    name: "JOB_NAME_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "PROTOCOL_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "TASK_INDEX_FIELD_NUMBER"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "ByteSize"
+  }
+  member_method {
+    name: "Clear"
+  }
+  member_method {
+    name: "ClearExtension"
+  }
+  member_method {
+    name: "ClearField"
+  }
+  member_method {
+    name: "CopyFrom"
+  }
+  member_method {
+    name: "DiscardUnknownFields"
+  }
+  member_method {
+    name: "FindInitializationErrors"
+  }
+  member_method {
+    name: "FromString"
+  }
+  member_method {
+    name: "HasExtension"
+  }
+  member_method {
+    name: "HasField"
+  }
+  member_method {
+    name: "IsInitialized"
+  }
+  member_method {
+    name: "ListFields"
+  }
+  member_method {
+    name: "MergeFrom"
+  }
+  member_method {
+    name: "MergeFromString"
+  }
+  member_method {
+    name: "ParseFromString"
+  }
+  member_method {
+    name: "RegisterExtension"
+  }
+  member_method {
+    name: "SerializePartialToString"
+  }
+  member_method {
+    name: "SerializeToString"
+  }
+  member_method {
+    name: "SetInParent"
+  }
+  member_method {
+    name: "WhichOneof"
+  }
+  member_method {
+    name: "__init__"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-server.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-server.pbtxt
new file mode 100644
index 00000000000..9b8f185f5b6
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-server.pbtxt
@@ -0,0 +1,29 @@
+path: "tensorflow.train.Server"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.server_lib.Server\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "server_def"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "target"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'server_or_cluster_def\', \'job_name\', \'task_index\', \'protocol\', \'config\', \'start\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'True\'], "
+  }
+  member_method {
+    name: "create_local_server"
+    argspec: "args=[\'config\', \'start\'], varargs=None, keywords=None, defaults=[\'None\', \'True\'], "
+  }
+  member_method {
+    name: "join"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "start"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-session-creator.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-session-creator.pbtxt
new file mode 100644
index 00000000000..beb232715f7
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-session-creator.pbtxt
@@ -0,0 +1,12 @@
+path: "tensorflow.train.SessionCreator"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.monitored_session.SessionCreator\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "create_session"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-session-manager.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-session-manager.pbtxt
new file mode 100644
index 00000000000..cc31bb4e4b3
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-session-manager.pbtxt
@@ -0,0 +1,21 @@
+path: "tensorflow.train.SessionManager"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.session_manager.SessionManager\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'local_init_op\', \'ready_op\', \'ready_for_local_init_op\', \'graph\', \'recovery_wait_secs\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'30\'], "
+  }
+  member_method {
+    name: "prepare_session"
+    argspec: "args=[\'self\', \'master\', \'init_op\', \'saver\', \'checkpoint_dir\', \'checkpoint_filename_with_path\', \'wait_for_checkpoint\', \'max_wait_secs\', \'config\', \'init_feed_dict\', \'init_fn\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'False\', \'7200\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "recover_session"
+    argspec: "args=[\'self\', \'master\', \'saver\', \'checkpoint_dir\', \'checkpoint_filename_with_path\', \'wait_for_checkpoint\', \'max_wait_secs\', \'config\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'False\', \'7200\', \'None\'], "
+  }
+  member_method {
+    name: "wait_for_session"
+    argspec: "args=[\'self\', \'master\', \'config\', \'max_wait_secs\'], varargs=None, keywords=None, defaults=[\'None\', \'inf\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-session-run-args.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-session-run-args.pbtxt
new file mode 100644
index 00000000000..442990893e3
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-session-run-args.pbtxt
@@ -0,0 +1,27 @@
+path: "tensorflow.train.SessionRunArgs"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunArgs\'>"
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunArgs\'>"
+  is_instance: "<type \'tuple\'>"
+  member {
+    name: "feed_dict"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "fetches"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "options"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "count"
+  }
+  member_method {
+    name: "index"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-session-run-context.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-session-run-context.pbtxt
new file mode 100644
index 00000000000..d5adb15c95f
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-session-run-context.pbtxt
@@ -0,0 +1,25 @@
+path: "tensorflow.train.SessionRunContext"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunContext\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "original_args"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "session"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "stop_requested"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'original_args\', \'session\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "request_stop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-session-run-hook.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-session-run-hook.pbtxt
new file mode 100644
index 00000000000..db1aa24acf0
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-session-run-hook.pbtxt
@@ -0,0 +1,28 @@
+path: "tensorflow.train.SessionRunHook"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunHook\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "after_create_session"
+    argspec: "args=[\'self\', \'session\', \'coord\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_run"
+    argspec: "args=[\'self\', \'run_context\', \'run_values\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "before_run"
+    argspec: "args=[\'self\', \'run_context\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "begin"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "end"
+    argspec: "args=[\'self\', \'session\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-session-run-values.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-session-run-values.pbtxt
new file mode 100644
index 00000000000..0b401d59c40
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-session-run-values.pbtxt
@@ -0,0 +1,27 @@
+path: "tensorflow.train.SessionRunValues"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunValues\'>"
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunValues\'>"
+  is_instance: "<type \'tuple\'>"
+  member {
+    name: "options"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "results"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "run_metadata"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+  }
+  member_method {
+    name: "count"
+  }
+  member_method {
+    name: "index"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-singular-monitored-session.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-singular-monitored-session.pbtxt
new file mode 100644
index 00000000000..62bfdab40bb
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-singular-monitored-session.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.train.SingularMonitoredSession"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.monitored_session.SingularMonitoredSession\'>"
+  is_instance: "<class \'tensorflow.python.training.monitored_session._MonitoredSession\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "graph"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'hooks\', \'scaffold\', \'master\', \'config\', \'checkpoint_dir\', \'stop_grace_period_secs\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'\', \'None\', \'None\', \'120\'], "
+  }
+  member_method {
+    name: "close"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "raw_session"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "run"
+    argspec: "args=[\'self\', \'fetches\', \'feed_dict\', \'options\', \'run_metadata\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "should_stop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-step-counter-hook.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-step-counter-hook.pbtxt
new file mode 100644
index 00000000000..13261f6dde1
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-step-counter-hook.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.train.StepCounterHook"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.StepCounterHook\'>"
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunHook\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'every_n_steps\', \'every_n_secs\', \'output_dir\', \'summary_writer\'], varargs=None, keywords=None, defaults=[\'100\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "after_create_session"
+    argspec: "args=[\'self\', \'session\', \'coord\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_run"
+    argspec: "args=[\'self\', \'run_context\', \'run_values\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "before_run"
+    argspec: "args=[\'self\', \'run_context\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "begin"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "end"
+    argspec: "args=[\'self\', \'session\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-stop-at-step-hook.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-stop-at-step-hook.pbtxt
new file mode 100644
index 00000000000..e388599b0bf
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-stop-at-step-hook.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.train.StopAtStepHook"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.StopAtStepHook\'>"
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunHook\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'num_steps\', \'last_step\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "after_create_session"
+    argspec: "args=[\'self\', \'session\', \'coord\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_run"
+    argspec: "args=[\'self\', \'run_context\', \'run_values\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "before_run"
+    argspec: "args=[\'self\', \'run_context\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "begin"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "end"
+    argspec: "args=[\'self\', \'session\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-summary-saver-hook.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-summary-saver-hook.pbtxt
new file mode 100644
index 00000000000..697c3667b09
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-summary-saver-hook.pbtxt
@@ -0,0 +1,30 @@
+path: "tensorflow.train.SummarySaverHook"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.basic_session_run_hooks.SummarySaverHook\'>"
+  is_instance: "<class \'tensorflow.python.training.session_run_hook.SessionRunHook\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'save_steps\', \'save_secs\', \'output_dir\', \'summary_writer\', \'scaffold\', \'summary_op\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "after_create_session"
+    argspec: "args=[\'self\', \'session\', \'coord\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "after_run"
+    argspec: "args=[\'self\', \'run_context\', \'run_values\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "before_run"
+    argspec: "args=[\'self\', \'run_context\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "begin"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "end"
+    argspec: "args=[\'self\', \'session\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-supervisor.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-supervisor.pbtxt
new file mode 100644
index 00000000000..cc9bd5c136b
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-supervisor.pbtxt
@@ -0,0 +1,153 @@
+path: "tensorflow.train.Supervisor"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.supervisor.Supervisor\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "USE_DEFAULT"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "coord"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "global_step"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "init_feed_dict"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "init_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "is_chief"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "ready_for_local_init_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "ready_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "save_model_secs"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "save_path"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "save_summaries_secs"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "saver"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "session_manager"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "summary_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "summary_writer"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "Loop"
+    argspec: "args=[\'self\', \'timer_interval_secs\', \'target\', \'args\', \'kwargs\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "PrepareSession"
+    argspec: "args=[\'self\', \'master\', \'config\', \'wait_for_checkpoint\', \'max_wait_secs\', \'start_standard_services\'], varargs=None, keywords=None, defaults=[\'\', \'None\', \'False\', \'7200\', \'True\'], "
+  }
+  member_method {
+    name: "RequestStop"
+    argspec: "args=[\'self\', \'ex\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "ShouldStop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "StartQueueRunners"
+    argspec: "args=[\'self\', \'sess\', \'queue_runners\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "StartStandardServices"
+    argspec: "args=[\'self\', \'sess\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "Stop"
+    argspec: "args=[\'self\', \'threads\', \'close_summary_writer\'], varargs=None, keywords=None, defaults=[\'None\', \'True\'], "
+  }
+  member_method {
+    name: "StopOnException"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "SummaryComputed"
+    argspec: "args=[\'self\', \'sess\', \'summary\', \'global_step\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "WaitForStop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'graph\', \'ready_op\', \'ready_for_local_init_op\', \'is_chief\', \'init_op\', \'init_feed_dict\', \'local_init_op\', \'logdir\', \'summary_op\', \'saver\', \'global_step\', \'save_summaries_secs\', \'save_model_secs\', \'recovery_wait_secs\', \'stop_grace_secs\', \'checkpoint_basename\', \'session_manager\', \'summary_writer\', \'init_fn\'], varargs=None, keywords=None, defaults=[\'None\', \'0\', \'0\', \'True\', \'0\', \'None\', \'0\', \'None\', \'0\', \'0\', \'0\', \'120\', \'600\', \'30\', \'120\', \'model.ckpt\', \'None\', \'0\', \'None\'], "
+  }
+  member_method {
+    name: "loop"
+    argspec: "args=[\'self\', \'timer_interval_secs\', \'target\', \'args\', \'kwargs\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "managed_session"
+    argspec: "args=[], varargs=args, keywords=kwds, defaults=None"
+  }
+  member_method {
+    name: "prepare_or_wait_for_session"
+    argspec: "args=[\'self\', \'master\', \'config\', \'wait_for_checkpoint\', \'max_wait_secs\', \'start_standard_services\'], varargs=None, keywords=None, defaults=[\'\', \'None\', \'False\', \'7200\', \'True\'], "
+  }
+  member_method {
+    name: "request_stop"
+    argspec: "args=[\'self\', \'ex\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "should_stop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "start_queue_runners"
+    argspec: "args=[\'self\', \'sess\', \'queue_runners\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "start_standard_services"
+    argspec: "args=[\'self\', \'sess\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "stop"
+    argspec: "args=[\'self\', \'threads\', \'close_summary_writer\'], varargs=None, keywords=None, defaults=[\'None\', \'True\'], "
+  }
+  member_method {
+    name: "stop_on_exception"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "summary_computed"
+    argspec: "args=[\'self\', \'sess\', \'summary\', \'global_step\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "wait_for_stop"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-sync-replicas-optimizer.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-sync-replicas-optimizer.pbtxt
new file mode 100644
index 00000000000..915d8501af0
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-sync-replicas-optimizer.pbtxt
@@ -0,0 +1,58 @@
+path: "tensorflow.train.SyncReplicasOptimizer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.sync_replicas_optimizer.SyncReplicasOptimizer\'>"
+  is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "GATE_GRAPH"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_NONE"
+    mtype: "<type \'int\'>"
+  }
+  member {
+    name: "GATE_OP"
+    mtype: "<type \'int\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'opt\', \'replicas_to_aggregate\', \'total_num_replicas\', \'variable_averages\', \'variables_to_average\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'False\', \'sync_replicas\'], "
+  }
+  member_method {
+    name: "apply_gradients"
+    argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "compute_gradients"
+    argspec: "args=[\'self\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "get_chief_queue_runner"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_init_tokens_op"
+    argspec: "args=[\'self\', \'num_tokens\'], varargs=None, keywords=None, defaults=[\'-1\'], "
+  }
+  member_method {
+    name: "get_name"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_slot"
+    argspec: "args=[\'self\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "get_slot_names"
+    argspec: "args=[\'self\'], varargs=args, keywords=kwargs, defaults=None"
+  }
+  member_method {
+    name: "make_session_run_hook"
+    argspec: "args=[\'self\', \'is_chief\', \'num_tokens\'], varargs=None, keywords=None, defaults=[\'-1\'], "
+  }
+  member_method {
+    name: "minimize"
+    argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.-worker-session-creator.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.-worker-session-creator.pbtxt
new file mode 100644
index 00000000000..140407651a9
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.-worker-session-creator.pbtxt
@@ -0,0 +1,14 @@
+path: "tensorflow.train.WorkerSessionCreator"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.monitored_session.WorkerSessionCreator\'>"
+  is_instance: "<class \'tensorflow.python.training.monitored_session.SessionCreator\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'scaffold\', \'master\', \'config\'], varargs=None, keywords=None, defaults=[\'None\', \'\', \'None\'], "
+  }
+  member_method {
+    name: "create_session"
+    argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.pbtxt
new file mode 100644
index 00000000000..79fd49d0adf
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.pbtxt
@@ -0,0 +1,395 @@
+path: "tensorflow.train"
+tf_module {
+  member {
+    name: "AdadeltaOptimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "AdagradDAOptimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "AdagradOptimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "AdamOptimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "BytesList"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "CheckpointSaverHook"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "CheckpointSaverListener"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "ChiefSessionCreator"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "ClusterDef"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "ClusterSpec"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Coordinator"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Example"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "ExponentialMovingAverage"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Feature"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "FeatureList"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "FeatureLists"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "Features"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "FeedFnHook"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "FinalOpsHook"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "FloatList"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "FtrlOptimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "GlobalStepWaiterHook"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "GradientDescentOptimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Int64List"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "JobDef"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "LoggingTensorHook"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "LooperThread"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "MomentumOptimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "MonitoredSession"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "NanLossDuringTrainingError"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "NanTensorHook"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Optimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "ProximalAdagradOptimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "ProximalGradientDescentOptimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "QueueRunner"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "RMSPropOptimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Saver"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SaverDef"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "Scaffold"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SecondOrStepTimer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SequenceExample"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "Server"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "ServerDef"
+    mtype: "<class \'google.protobuf.pyext.cpp_message.GeneratedProtocolMessageType\'>"
+  }
+  member {
+    name: "SessionCreator"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SessionManager"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SessionRunArgs"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SessionRunContext"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SessionRunHook"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SessionRunValues"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SingularMonitoredSession"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "StepCounterHook"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "StopAtStepHook"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SummarySaverHook"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "Supervisor"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "SyncReplicasOptimizer"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "WorkerSessionCreator"
+    mtype: "<type \'type\'>"
+  }
+  member {
+    name: "queue_runner"
+    mtype: "<type \'module\'>"
+  }
+  member_method {
+    name: "MonitoredTrainingSession"
+    argspec: "args=[\'master\', \'is_chief\', \'checkpoint_dir\', \'scaffold\', \'hooks\', \'chief_only_hooks\', \'save_checkpoint_secs\', \'save_summaries_steps\', \'save_summaries_secs\', \'config\', \'stop_grace_period_secs\', \'log_step_count_steps\'], varargs=None, keywords=None, defaults=[\'\', \'True\', \'None\', \'None\', \'None\', \'None\', \'600\', \'100\', \'None\', \'None\', \'120\', \'100\'], "
+  }
+  member_method {
+    name: "NewCheckpointReader"
+    argspec: "args=[\'filepattern\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "add_queue_runner"
+    argspec: "args=[\'qr\', \'collection\'], varargs=None, keywords=None, defaults=[\'queue_runners\'], "
+  }
+  member_method {
+    name: "assert_global_step"
+    argspec: "args=[\'global_step_tensor\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "basic_train_loop"
+    argspec: "args=[\'supervisor\', \'train_step_fn\', \'args\', \'kwargs\', \'master\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'\'], "
+  }
+  member_method {
+    name: "batch"
+    argspec: "args=[\'tensors\', \'batch_size\', \'num_threads\', \'capacity\', \'enqueue_many\', \'shapes\', \'dynamic_pad\', \'allow_smaller_final_batch\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'1\', \'32\', \'False\', \'None\', \'False\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "batch_join"
+    argspec: "args=[\'tensors_list\', \'batch_size\', \'capacity\', \'enqueue_many\', \'shapes\', \'dynamic_pad\', \'allow_smaller_final_batch\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'32\', \'False\', \'None\', \'False\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "checkpoint_exists"
+    argspec: "args=[\'checkpoint_prefix\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "create_global_step"
+    argspec: "args=[\'graph\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "do_quantize_training_on_graphdef"
+    argspec: "args=[\'input_graph\', \'num_bits\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "exponential_decay"
+    argspec: "args=[\'learning_rate\', \'global_step\', \'decay_steps\', \'decay_rate\', \'staircase\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
+  member_method {
+    name: "export_meta_graph"
+    argspec: "args=[\'filename\', \'meta_info_def\', \'graph_def\', \'saver_def\', \'collection_list\', \'as_text\', \'graph\', \'export_scope\', \'clear_devices\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'False\', \'None\', \'None\', \'False\'], "
+  }
+  member_method {
+    name: "generate_checkpoint_state_proto"
+    argspec: "args=[\'save_dir\', \'model_checkpoint_path\', \'all_model_checkpoint_paths\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_checkpoint_mtimes"
+    argspec: "args=[\'checkpoint_prefixes\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "get_checkpoint_state"
+    argspec: "args=[\'checkpoint_dir\', \'latest_filename\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_global_step"
+    argspec: "args=[\'graph\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "get_or_create_global_step"
+    argspec: "args=[\'graph\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "global_step"
+    argspec: "args=[\'sess\', \'global_step_tensor\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "import_meta_graph"
+    argspec: "args=[\'meta_graph_or_file\', \'clear_devices\', \'import_scope\'], varargs=None, keywords=kwargs, defaults=[\'False\', \'None\'], "
+  }
+  member_method {
+    name: "input_producer"
+    argspec: "args=[\'input_tensor\', \'element_shape\', \'num_epochs\', \'shuffle\', \'seed\', \'capacity\', \'shared_name\', \'summary_name\', \'name\', \'cancel_op\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'None\', \'32\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "inverse_time_decay"
+    argspec: "args=[\'learning_rate\', \'global_step\', \'decay_steps\', \'decay_rate\', \'staircase\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
+  member_method {
+    name: "latest_checkpoint"
+    argspec: "args=[\'checkpoint_dir\', \'latest_filename\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "limit_epochs"
+    argspec: "args=[\'tensor\', \'num_epochs\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "match_filenames_once"
+    argspec: "args=[\'pattern\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "maybe_batch"
+    argspec: "args=[\'tensors\', \'keep_input\', \'batch_size\', \'num_threads\', \'capacity\', \'enqueue_many\', \'shapes\', \'dynamic_pad\', \'allow_smaller_final_batch\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'1\', \'32\', \'False\', \'None\', \'False\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "maybe_batch_join"
+    argspec: "args=[\'tensors_list\', \'keep_input\', \'batch_size\', \'capacity\', \'enqueue_many\', \'shapes\', \'dynamic_pad\', \'allow_smaller_final_batch\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'32\', \'False\', \'None\', \'False\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "maybe_shuffle_batch"
+    argspec: "args=[\'tensors\', \'batch_size\', \'capacity\', \'min_after_dequeue\', \'keep_input\', \'num_threads\', \'seed\', \'enqueue_many\', \'shapes\', \'allow_smaller_final_batch\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'1\', \'None\', \'False\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "maybe_shuffle_batch_join"
+    argspec: "args=[\'tensors_list\', \'batch_size\', \'capacity\', \'min_after_dequeue\', \'keep_input\', \'seed\', \'enqueue_many\', \'shapes\', \'allow_smaller_final_batch\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "natural_exp_decay"
+    argspec: "args=[\'learning_rate\', \'global_step\', \'decay_steps\', \'decay_rate\', \'staircase\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
+  }
+  member_method {
+    name: "piecewise_constant"
+    argspec: "args=[\'x\', \'boundaries\', \'values\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "polynomial_decay"
+    argspec: "args=[\'learning_rate\', \'global_step\', \'decay_steps\', \'end_learning_rate\', \'power\', \'cycle\', \'name\'], varargs=None, keywords=None, defaults=[\'0.0001\', \'1.0\', \'False\', \'None\'], "
+  }
+  member_method {
+    name: "range_input_producer"
+    argspec: "args=[\'limit\', \'num_epochs\', \'shuffle\', \'seed\', \'capacity\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'True\', \'None\', \'32\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "replica_device_setter"
+    argspec: "args=[\'ps_tasks\', \'ps_device\', \'worker_device\', \'merge_devices\', \'cluster\', \'ps_ops\', \'ps_strategy\'], varargs=None, keywords=None, defaults=[\'0\', \'/job:ps\', \'/job:worker\', \'True\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "shuffle_batch"
+    argspec: "args=[\'tensors\', \'batch_size\', \'capacity\', \'min_after_dequeue\', \'num_threads\', \'seed\', \'enqueue_many\', \'shapes\', \'allow_smaller_final_batch\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'1\', \'None\', \'False\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "shuffle_batch_join"
+    argspec: "args=[\'tensors_list\', \'batch_size\', \'capacity\', \'min_after_dequeue\', \'seed\', \'enqueue_many\', \'shapes\', \'allow_smaller_final_batch\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'None\', \'False\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "slice_input_producer"
+    argspec: "args=[\'tensor_list\', \'num_epochs\', \'shuffle\', \'seed\', \'capacity\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'True\', \'None\', \'32\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "start_queue_runners"
+    argspec: "args=[\'sess\', \'coord\', \'daemon\', \'start\', \'collection\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'True\', \'queue_runners\'], "
+  }
+  member_method {
+    name: "string_input_producer"
+    argspec: "args=[\'string_tensor\', \'num_epochs\', \'shuffle\', \'seed\', \'capacity\', \'shared_name\', \'name\', \'cancel_op\'], varargs=None, keywords=None, defaults=[\'None\', \'True\', \'None\', \'32\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "summary_iterator"
+    argspec: "args=[\'path\'], varargs=None, keywords=None, defaults=None"
+  }
+  member_method {
+    name: "update_checkpoint_state"
+    argspec: "args=[\'save_dir\', \'model_checkpoint_path\', \'all_model_checkpoint_paths\', \'latest_filename\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
+  }
+  member_method {
+    name: "write_graph"
+    argspec: "args=[\'graph_or_graph_def\', \'logdir\', \'name\', \'as_text\'], varargs=None, keywords=None, defaults=[\'True\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.queue_runner.-queue-runner.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.queue_runner.-queue-runner.pbtxt
new file mode 100644
index 00000000000..23d402de308
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.queue_runner.-queue-runner.pbtxt
@@ -0,0 +1,49 @@
+path: "tensorflow.train.queue_runner.QueueRunner"
+tf_class {
+  is_instance: "<class \'tensorflow.python.training.queue_runner_impl.QueueRunner\'>"
+  is_instance: "<type \'object\'>"
+  member {
+    name: "cancel_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "close_op"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "enqueue_ops"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "exceptions_raised"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "name"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "queue"
+    mtype: "<type \'property\'>"
+  }
+  member {
+    name: "queue_closed_exception_types"
+    mtype: "<type \'property\'>"
+  }
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'queue\', \'enqueue_ops\', \'close_op\', \'cancel_op\', \'queue_closed_exception_types\', \'queue_runner_def\', \'import_scope\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\'], "
+  }
+  member_method {
+    name: "create_threads"
+    argspec: "args=[\'self\', \'sess\', \'coord\', \'daemon\', \'start\'], varargs=None, keywords=None, defaults=[\'None\', \'False\', \'False\'], "
+  }
+  member_method {
+    name: "from_proto"
+    argspec: "args=[\'queue_runner_def\', \'import_scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+  member_method {
+    name: "to_proto"
+    argspec: "args=[\'self\', \'export_scope\'], varargs=None, keywords=None, defaults=[\'None\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.train.queue_runner.pbtxt b/tensorflow/tools/api/golden/tensorflow.train.queue_runner.pbtxt
new file mode 100644
index 00000000000..6e2d0430496
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.train.queue_runner.pbtxt
@@ -0,0 +1,15 @@
+path: "tensorflow.train.queue_runner"
+tf_module {
+  member {
+    name: "QueueRunner"
+    mtype: "<type \'type\'>"
+  }
+  member_method {
+    name: "add_queue_runner"
+    argspec: "args=[\'qr\', \'collection\'], varargs=None, keywords=None, defaults=[\'queue_runners\'], "
+  }
+  member_method {
+    name: "start_queue_runners"
+    argspec: "args=[\'sess\', \'coord\', \'daemon\', \'start\', \'collection\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'True\', \'True\', \'queue_runners\'], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.truncated_normal_initializer.pbtxt b/tensorflow/tools/api/golden/tensorflow.truncated_normal_initializer.pbtxt
new file mode 100644
index 00000000000..7c48f4af076
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.truncated_normal_initializer.pbtxt
@@ -0,0 +1,10 @@
+path: "tensorflow.truncated_normal_initializer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.init_ops.TruncatedNormal\'>"
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Initializer\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'mean\', \'stddev\', \'seed\', \'dtype\'], varargs=None, keywords=None, defaults=[\'0.0\', \'1.0\', \'None\', \"<dtype: \'float32\'>\"], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.uniform_unit_scaling_initializer.pbtxt b/tensorflow/tools/api/golden/tensorflow.uniform_unit_scaling_initializer.pbtxt
new file mode 100644
index 00000000000..4558db619e8
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.uniform_unit_scaling_initializer.pbtxt
@@ -0,0 +1,10 @@
+path: "tensorflow.uniform_unit_scaling_initializer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.init_ops.UniformUnitScaling\'>"
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Initializer\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'factor\', \'seed\', \'dtype\'], varargs=None, keywords=None, defaults=[\'1.0\', \'None\', \"<dtype: \'float32\'>\"], "
+  }
+}
diff --git a/tensorflow/tools/api/golden/tensorflow.zeros_initializer.pbtxt b/tensorflow/tools/api/golden/tensorflow.zeros_initializer.pbtxt
new file mode 100644
index 00000000000..8313009a68c
--- /dev/null
+++ b/tensorflow/tools/api/golden/tensorflow.zeros_initializer.pbtxt
@@ -0,0 +1,10 @@
+path: "tensorflow.zeros_initializer"
+tf_class {
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Zeros\'>"
+  is_instance: "<class \'tensorflow.python.ops.init_ops.Initializer\'>"
+  is_instance: "<type \'object\'>"
+  member_method {
+    name: "__init__"
+    argspec: "args=[\'self\', \'dtype\'], varargs=None, keywords=None, defaults=[\"<dtype: \'float32\'>\"], "
+  }
+}
diff --git a/tensorflow/tools/api/lib/BUILD b/tensorflow/tools/api/lib/BUILD
new file mode 100644
index 00000000000..cdfa0e7be52
--- /dev/null
+++ b/tensorflow/tools/api/lib/BUILD
@@ -0,0 +1,39 @@
+# Helper libraries for TensorFlow API compatibility test.
+
+package(
+    default_visibility = ["//tensorflow/tools/api:__subpackages__"],
+)
+
+licenses(["notice"])  # Apache 2.0
+
+load(
+    "//tensorflow/core:platform/default/build_config.bzl",
+    "tf_proto_library",
+)
+
+tf_proto_library(
+    name = "api_objects_proto",
+    srcs = ["api_objects.proto"],
+)
+
+py_library(
+    name = "python_object_to_proto_visitor",
+    srcs = ["python_object_to_proto_visitor.py"],
+    srcs_version = "PY2AND3",
+    deps = [
+        ":api_objects_proto_py",
+        "//tensorflow/tools/common:traverse",
+    ],
+)
+
+filegroup(
+    name = "all_files",
+    srcs = glob(
+        ["**/*"],
+        exclude = [
+            "**/METADATA",
+            "**/OWNERS",
+        ],
+    ),
+    visibility = ["//tensorflow:__subpackages__"],
+)
diff --git a/tensorflow/tools/api/lib/api_objects.proto b/tensorflow/tools/api/lib/api_objects.proto
new file mode 100644
index 00000000000..0966a5f1d53
--- /dev/null
+++ b/tensorflow/tools/api/lib/api_objects.proto
@@ -0,0 +1,31 @@
+syntax = "proto2";
+
+package third_party.tensorflow.tools.api;
+
+message TFAPIMember {
+  optional string name = 1;
+  optional string mtype = 2;
+};
+
+message TFAPIMethod {
+  optional string name = 1;
+  optional string path = 2;
+  optional string argspec = 3;
+};
+
+message TFAPIModule {
+  repeated TFAPIMember member = 1;
+  repeated TFAPIMethod member_method = 2;
+};
+
+message TFAPIClass {
+  repeated string is_instance = 1;
+  repeated TFAPIMember member = 2;
+  repeated TFAPIMethod member_method = 3;
+};
+
+message TFAPIObject {
+  optional string path = 1;
+  optional TFAPIModule tf_module = 2;
+  optional TFAPIClass tf_class = 3;
+};
diff --git a/tensorflow/tools/api/lib/python_object_to_proto_visitor.py b/tensorflow/tools/api/lib/python_object_to_proto_visitor.py
new file mode 100644
index 00000000000..64092a6441b
--- /dev/null
+++ b/tensorflow/tools/api/lib/python_object_to_proto_visitor.py
@@ -0,0 +1,168 @@
+# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# ==============================================================================
+"""A visitor class that generates protobufs for each pyton object."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import inspect
+
+from tensorflow.python.platform import tf_logging as logging
+from tensorflow.tools.api.lib import api_objects_pb2
+
+
+# Following object need to be handled individually.
+_CORNER_CASES = {
+    '': {'contrib': {'name': 'contrib',
+                     'mtype': '<class \'_LazyContribLoader\'>'},
+         'tools': {}},
+    'test.TestCase': {},
+    'test.TestCase.failureException': {},
+}
+
+
+def _SanitizedArgSpec(obj):
+  """Get an ArgSpec string that is free of addresses.
+
+  We have callables as function arg defaults. This results in addresses in
+  getargspec output. This function returns a sanitized string list of base
+  classes.
+
+  Args:
+    obj: A python routine for us the create the sanitized arspec of.
+
+  Returns:
+    string, a string representation of the argspec.
+  """
+  output_string = ''
+  unsanitized_arg_spec = inspect.getargspec(obj)
+
+  for clean_attr in ('args', 'varargs', 'keywords'):
+    output_string += '%s=%s, ' % (clean_attr,
+                                  getattr(unsanitized_arg_spec, clean_attr))
+
+  if unsanitized_arg_spec.defaults:
+    sanitized_defaults = []
+    for val in unsanitized_arg_spec.defaults:
+      str_val = str(val)
+      if ' object at 0x' in str_val:
+        sanitized_defaults.append('%s instance>' % str_val.split(' at ')[0])
+      else:
+        sanitized_defaults.append(str_val)
+
+    output_string += 'defaults=%s, ' % sanitized_defaults
+
+  else:
+    output_string += 'defaults=None'
+
+  return output_string
+
+
+def _SanitizedMRO(obj):
+  """Get a list of superclasses with minimal amount of non-TF classes.
+
+  Based on many parameters like python version, OS, protobuf implementation
+  or changes in google core libraries the list of superclasses of a class
+  can change. We only return the first non-TF class to be robust to non API
+  affecting changes. The Method Resolution Order returned by inspect.getmro
+  is still maintained in the return value.
+
+  Args:
+    obj: A python routine for us the create the sanitized arspec of.
+
+  Returns:
+    list of strings, string representation of the class names.
+  """
+  return_list = []
+  for cls in inspect.getmro(obj):
+    str_repr = str(cls)
+    return_list.append(str_repr)
+    if 'tensorflow' not in str_repr:
+      break
+
+  return return_list
+
+
+class PythonObjectToProtoVisitor(object):
+  """A visitor that summarizes given python objects as protobufs."""
+
+  def __init__(self):
+    # A dict to store all protocol buffers.
+    # Keyed by "path" to the object.
+    self._protos = {}
+
+  def GetProtos(self):
+    """Return the list of protos stored."""
+    return self._protos
+
+  def __call__(self, path, parent, children):
+    # The path to the object.
+    lib_path = 'tensorflow.%s' % path if path else 'tensorflow'
+
+    # A small helper method to construct members(children) protos.
+    def _AddMember(member_name, member_obj, proto):
+      """Add the child object to the object being constructed."""
+      if member_name == '__init__' or not member_name.startswith('_'):
+        if inspect.isroutine(member_obj):
+          new_method = proto.member_method.add()
+          new_method.name = member_name
+          # If member_obj is a python builtin, there is no way to get its
+          # argspec, because it is implemented on the C side. It also has no
+          # func_code.
+          if getattr(member_obj, 'func_code', None):
+            new_method.argspec = _SanitizedArgSpec(member_obj)
+        else:
+          new_member = proto.member.add()
+          new_member.name = member_name
+          new_member.mtype = str(type(member_obj))
+
+    parent_corner_cases = _CORNER_CASES.get(path, {})
+
+    if path not in _CORNER_CASES or parent_corner_cases:
+      # Decide if we have a module or a class.
+      if inspect.ismodule(parent):
+        # Create a module object.
+        module_obj = api_objects_pb2.TFAPIModule()
+        for name, child in children:
+          if name in parent_corner_cases:
+            # If we have an empty entry, skip this object.
+            if parent_corner_cases[name]:
+              module_obj.member.add(**(parent_corner_cases[name]))
+          else:
+            _AddMember(name, child, module_obj)
+
+        # Store the constructed module object.
+        self._protos[lib_path] = api_objects_pb2.TFAPIObject(
+            path=lib_path, tf_module=module_obj)
+      elif inspect.isclass(parent):
+        # Construct a class.
+        class_obj = api_objects_pb2.TFAPIClass()
+        class_obj.is_instance.extend(_SanitizedMRO(parent))
+        for name, child in children:
+          if name in parent_corner_cases:
+            # If we have an empty entry, skip this object.
+            if parent_corner_cases[name]:
+              module_obj.member.add(**(parent_corner_cases[name]))
+          else:
+            _AddMember(name, child, class_obj)
+
+        # Store the constructed class object.
+        self._protos[lib_path] = api_objects_pb2.TFAPIObject(
+            path=lib_path, tf_class=class_obj)
+      else:
+        logging.error('Illegal call to ApiProtoDump::_py_obj_to_proto.'
+                      'Object is neither a module nor a class: %s', path)
diff --git a/tensorflow/tools/api/tests/API_UPDATE_WARNING.txt b/tensorflow/tools/api/tests/API_UPDATE_WARNING.txt
new file mode 100644
index 00000000000..54b0cfcb3c1
--- /dev/null
+++ b/tensorflow/tools/api/tests/API_UPDATE_WARNING.txt
@@ -0,0 +1,7 @@
+Golden file update requested!
+All test failures have been skipped, see the logs for detected diffs.
+This test is now going to write new golden files.
+Make sure to package the updates together with your change.
+
+You will need an explicit API approval. This may take longer than a normal
+review.
diff --git a/tensorflow/tools/api/tests/BUILD b/tensorflow/tools/api/tests/BUILD
new file mode 100644
index 00000000000..bfee211dca4
--- /dev/null
+++ b/tensorflow/tools/api/tests/BUILD
@@ -0,0 +1,43 @@
+# TensorFlow API backwards compatibility tests.
+
+package(
+    default_visibility = ["//tensorflow/tools/api:__subpackages__"],
+)
+
+licenses(["notice"])  # Apache 2.0
+
+exports_files([
+    "README.txt",
+    "API_UPDATE_WARNING.txt",
+])
+
+py_test(
+    name = "api_compatibility_test",
+    srcs = ["api_compatibility_test.py"],
+    data = [
+        "//tensorflow/tools/api/golden:api_golden",
+        "//tensorflow/tools/api/tests:API_UPDATE_WARNING.txt",
+        "//tensorflow/tools/api/tests:README.txt",
+    ],
+    srcs_version = "PY2AND3",
+    deps = [
+        "//tensorflow:tensorflow_py",
+        "//tensorflow/python:platform",
+        "//tensorflow/tools/api/lib:python_object_to_proto_visitor",
+        "//tensorflow/tools/common:public_api",
+        "//tensorflow/tools/common:traverse",
+        "@protobuf//:protobuf_python",
+    ],
+)
+
+filegroup(
+    name = "all_files",
+    srcs = glob(
+        ["**/*"],
+        exclude = [
+            "**/METADATA",
+            "**/OWNERS",
+        ],
+    ),
+    visibility = ["//tensorflow:__subpackages__"],
+)
diff --git a/tensorflow/tools/api/tests/README.txt b/tensorflow/tools/api/tests/README.txt
new file mode 100644
index 00000000000..3463eeec6fe
--- /dev/null
+++ b/tensorflow/tools/api/tests/README.txt
@@ -0,0 +1,13 @@
+TensorFlow API backwards compatibility test
+This test ensures all changes to the public API of TensorFlow are intended.
+
+If this test fails, it means a change has been made to the public API. Backwards
+incompatible changes are not allowed. You can run the test as follows to update
+test goldens and package them with your change.
+
+    $ bazel build tensorflow/tools/api/tests:api_compatibility_test
+    $ bazel-bin/tensorflow/tools/api/tests/api_compatibility_test \
+          --update_goldens True
+
+You will need an API approval to make changes to the public TensorFlow API. This
+includes additions to the API.
diff --git a/tensorflow/tools/api/tests/api_compatibility_test.py b/tensorflow/tools/api/tests/api_compatibility_test.py
new file mode 100644
index 00000000000..27865fdc89b
--- /dev/null
+++ b/tensorflow/tools/api/tests/api_compatibility_test.py
@@ -0,0 +1,238 @@
+# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# ==============================================================================
+"""TensorFlow API compatibility tests.
+
+This test ensures all changes to the public API of TensorFlow are intended.
+
+If this test fails, it means a change has been made to the public API. Backwards
+incompatible changes are not allowed. You can run the test with
+"--update_goldens" flag set to "True" to update goldens when making changes to
+the public TF python API.
+"""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import argparse
+import os
+import re
+import sys
+import unittest
+
+import tensorflow as tf
+
+from google.protobuf import text_format
+
+from tensorflow.python.lib.io import file_io
+from tensorflow.python.platform import resource_loader
+from tensorflow.python.platform import test
+from tensorflow.python.platform import tf_logging as logging
+from tensorflow.tools.api.lib import api_objects_pb2
+from tensorflow.tools.api.lib import python_object_to_proto_visitor
+from tensorflow.tools.common import public_api
+from tensorflow.tools.common import traverse
+
+# FLAGS defined at the bottom:
+FLAGS = None
+# DEFINE_boolean, update_goldens, default False:
+_UPDATE_GOLDENS_HELP = """
+     Update stored golden files if API is updated. WARNING: All API changes
+     have to be authorized by TensorFlow leads.
+"""
+
+# DEFINE_boolean, verbose_diffs, default False:
+_VERBOSE_DIFFS_HELP = """
+     If set to true, print line by line diffs on all libraries. If set to
+     false, only print which libraries have differences.
+"""
+
+_API_GOLDEN_FOLDER = 'tensorflow/tools/api/golden'
+_TEST_README_FILE = 'tensorflow/tools/api/tests/README.txt'
+_UPDATE_WARNING_FILE = 'tensorflow/tools/api/tests/API_UPDATE_WARNING.txt'
+
+
+def _KeyToFilePath(key):
+  """From a given key, construct a filepath."""
+  def _ReplaceCapsWithDash(matchobj):
+    match = matchobj.group(0)
+    return '-%s' % (match.lower())
+
+  case_insensitive_key = re.sub('([A-Z]{1})', _ReplaceCapsWithDash, key)
+  return os.path.join(_API_GOLDEN_FOLDER, '%s.pbtxt' % case_insensitive_key)
+
+
+def _FileNameToKey(filename):
+  """From a given filename, construct a key we use for api objects."""
+  def _ReplaceDashWithCaps(matchobj):
+    match = matchobj.group(0)
+    return match[1].upper()
+
+  base_filename = os.path.basename(filename)
+  base_filename_without_ext = os.path.splitext(base_filename)[0]
+  api_object_key = re.sub(
+      '((-[a-z]){1})', _ReplaceDashWithCaps, base_filename_without_ext)
+  return api_object_key
+
+
+class ApiCompatibilityTest(test.TestCase):
+
+  def __init__(self, *args, **kwargs):
+    super(ApiCompatibilityTest, self).__init__(*args, **kwargs)
+
+    golden_update_warning_filename = os.path.join(
+        resource_loader.get_root_dir_with_all_resources(),
+        _UPDATE_WARNING_FILE)
+    self._update_golden_warning = file_io.read_file_to_string(
+        golden_update_warning_filename)
+
+    test_readme_filename = os.path.join(
+        resource_loader.get_root_dir_with_all_resources(),
+        _TEST_README_FILE)
+    self._test_readme_message = file_io.read_file_to_string(
+        test_readme_filename)
+
+  def _AssertProtoDictEquals(self,
+                             expected_dict,
+                             actual_dict,
+                             verbose=False,
+                             update_goldens=False):
+    """Diff given dicts of protobufs and report differences a readable way.
+
+    Args:
+      expected_dict: a dict of TFAPIObject protos constructed from golden
+          files.
+      actual_dict: a ict of TFAPIObject protos constructed by reading from the
+          TF package linked to the test.
+      verbose: Whether to log the full diffs, or simply report which files were
+          different.
+      update_goldens: Whether to update goldens when there are diffs found.
+    """
+    diffs = []
+    verbose_diffs = []
+
+    expected_keys = set(expected_dict.keys())
+    actual_keys = set(actual_dict.keys())
+    only_in_expected = expected_keys - actual_keys
+    only_in_actual = actual_keys - expected_keys
+    all_keys = expected_keys | actual_keys
+
+    # This will be populated below.
+    updated_keys = []
+
+    for key in all_keys:
+      diff_message = ''
+      verbose_diff_message = ''
+      # First check if the key is not found in one or the other.
+      if key in only_in_expected:
+        diff_message = 'Object %s expected but not found (removed).' % key
+        verbose_diff_message = diff_message
+      elif key in only_in_actual:
+        diff_message = 'New object %s found (added).' % key
+        verbose_diff_message = diff_message
+      else:
+        # Now we can run an actual proto diff.
+        try:
+          self.assertProtoEquals(expected_dict[key], actual_dict[key])
+        except AssertionError as e:
+          updated_keys.append(key)
+          diff_message = 'Change detected in python object: %s.' % key
+          verbose_diff_message = str(e)
+
+      # All difference cases covered above. If any difference found, add to the
+      # list.
+      if diff_message:
+        diffs.append(diff_message)
+        verbose_diffs.append(verbose_diff_message)
+
+    # If diffs are found, handle them based on flags.
+    if diffs:
+      diff_count = len(diffs)
+      logging.error(self._test_readme_message)
+      logging.error('%d differences found between API and golden.', diff_count)
+      messages = verbose_diffs if verbose else diffs
+      for i in range(diff_count):
+        logging.error('Issue %d\t: %s', i + 1, messages[i])
+
+      if update_goldens:
+        # Write files if requested.
+        logging.warning(self._update_golden_warning)
+
+        # If the keys are only in expected, some objects are deleted.
+        # Remove files.
+        for key in only_in_expected:
+          filepath = _KeyToFilePath(key)
+          file_io.delete_file(filepath)
+
+        # If the files are only in actual (current library), these are new
+        # modules. Write them to files. Also record all updates in files.
+        for key in only_in_actual | set(updated_keys):
+          filepath = _KeyToFilePath(key)
+          file_io.write_string_to_file(
+              filepath, text_format.MessageToString(actual_dict[key]))
+      else:
+        # Fail if we cannot fix the test by updating goldens.
+        self.fail('%d differences found between API and golden.' % diff_count)
+
+    else:
+      logging.info('No differences found between API and golden.')
+
+  @unittest.skipUnless(
+      sys.version_info.major == 2 and os.uname()[0] == 'Linux',
+      'API compabitility test goldens are generated using python2 on Linux.')
+  def testAPIBackwardsCompatibility(self):
+    # Extract all API stuff.
+    visitor = python_object_to_proto_visitor.PythonObjectToProtoVisitor()
+    traverse.traverse(tf, public_api.PublicAPIVisitor(visitor))
+    proto_dict = visitor.GetProtos()
+
+    # Read all golden files.
+    expression = os.path.join(
+        resource_loader.get_root_dir_with_all_resources(),
+        _KeyToFilePath('*'))
+    golden_file_list = file_io.get_matching_files(expression)
+
+    def _ReadFileToProto(filename):
+      """Read a filename, create a protobuf from its contents."""
+      ret_val = api_objects_pb2.TFAPIObject()
+      text_format.Merge(file_io.read_file_to_string(filename), ret_val)
+      return ret_val
+
+    golden_proto_dict = {
+        _FileNameToKey(filename): _ReadFileToProto(filename)
+        for filename in golden_file_list
+    }
+
+    # Diff them. Do not fail if called with update.
+    # If the test is run to update goldens, only report diffs but do not fail.
+    self._AssertProtoDictEquals(
+        golden_proto_dict,
+        proto_dict,
+        verbose=FLAGS.verbose_diffs,
+        update_goldens=FLAGS.update_goldens)
+
+
+if __name__ == '__main__':
+  parser = argparse.ArgumentParser()
+  parser.add_argument(
+      '--update_goldens', type=bool, default=False, help=_UPDATE_GOLDENS_HELP)
+  parser.add_argument(
+      '--verbose_diffs', type=bool, default=False, help=_VERBOSE_DIFFS_HELP)
+  FLAGS, unparsed = parser.parse_known_args()
+
+  # Now update argv, so that unittest library does not get confused.
+  sys.argv = [sys.argv[0]] + unparsed
+  test.main()
diff --git a/tensorflow/tools/ci_build/pylintrc b/tensorflow/tools/ci_build/pylintrc
index 0779ed91bc3..e71017e621c 100644
--- a/tensorflow/tools/ci_build/pylintrc
+++ b/tensorflow/tools/ci_build/pylintrc
@@ -38,7 +38,7 @@ enable=indexing-exception,old-raise-syntax
 # --enable=similarities". If you want to run only the classes checker, but have
 # no Warning level messages displayed, use"--disable=all --enable=classes
 # --disable=W"
-disable=design,similarities,no-self-use,attribute-defined-outside-init,locally-disabled,star-args,pointless-except,bad-option-value,global-statement,fixme,suppressed-message,useless-suppression,locally-enabled,no-member,no-name-in-module,import-error,unsubscriptable-object,unbalanced-tuple-unpacking,undefined-variable
+disable=design,similarities,no-self-use,attribute-defined-outside-init,locally-disabled,star-args,pointless-except,bad-option-value,global-statement,fixme,suppressed-message,useless-suppression,locally-enabled,no-member,no-name-in-module,import-error,unsubscriptable-object,unbalanced-tuple-unpacking,undefined-variable,not-context-manager
 
 
 # Set the cache size for astng objects.
@@ -322,4 +322,4 @@ indent-after-paren=4
 [GOOGLE LINES]
 
 # Regexp for a proper copyright notice.
-copyright=Copyright \d{4} The TensorFlow Authors\. +All [Rr]ights [Rr]eserved\.
\ No newline at end of file
+copyright=Copyright \d{4} The TensorFlow Authors\. +All [Rr]ights [Rr]eserved\.
diff --git a/tensorflow/tools/common/public_api.py b/tensorflow/tools/common/public_api.py
index 3364ff6bc9a..173b39c538a 100644
--- a/tensorflow/tools/common/public_api.py
+++ b/tensorflow/tools/common/public_api.py
@@ -48,7 +48,8 @@ class PublicAPIVisitor(object):
           'pywrap_tensorflow',  # TODO(drpng): This can be removed once sealed.
           'user_ops',  # TODO(drpng): This can be removed once sealed.
           'python',
-          'tools'
+          'tools',
+          'tensorboard',
       ],
 
       # Some implementations have this internal module that we shouldn't expose.
diff --git a/tensorflow/tools/docs/BUILD b/tensorflow/tools/docs/BUILD
index b425e93aa10..8e27b133c2f 100644
--- a/tensorflow/tools/docs/BUILD
+++ b/tensorflow/tools/docs/BUILD
@@ -99,6 +99,20 @@ py_binary(
     ],
 )
 
+py_test(
+    name = "build_docs_test",
+    size = "small",
+    srcs = ["build_docs_test.py"],
+    data = ["//tensorflow:docs_src"],
+    srcs_version = "PY2AND3",
+    tags = ["manual"],
+    deps = [
+        ":generate_lib",
+        "//tensorflow:tensorflow_py",
+        "//tensorflow/python/debug:debug_py",
+    ],
+)
+
 py_binary(
     name = "generate_1_0",
     srcs = ["generate_1_0.py"],
diff --git a/tensorflow/tools/docs/build_docs_test.py b/tensorflow/tools/docs/build_docs_test.py
new file mode 100644
index 00000000000..08c27729a78
--- /dev/null
+++ b/tensorflow/tools/docs/build_docs_test.py
@@ -0,0 +1,52 @@
+# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Run the python doc generator and fail if there are any broken links."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import os
+
+import tensorflow as tf
+from tensorflow.python import debug as tf_debug
+from tensorflow.python.platform import googletest
+from tensorflow.python.platform import resource_loader
+from tensorflow.tools.docs import generate_lib
+
+
+class Flags(object):
+  resource_root = resource_loader.get_root_dir_with_all_resources()
+  src_dir = os.path.join(resource_root, 'third_party/tensorflow/docs_src')
+  base_dir = os.path.join(resource_root, 'third_party/tensorflow/')
+  output_dir = googletest.GetTempDir()
+
+
+class BuildDocsTest(googletest.TestCase):
+
+  def testBuildDocs(self):
+    doc_generator = generate_lib.DocGenerator()
+
+    doc_generator.set_py_modules([('tf', tf), ('tfdbg', tf_debug)])
+    doc_generator.load_contrib()
+
+    status = doc_generator.build(Flags())
+
+    if status:
+      self.fail('Found %s Errors!' % status)
+
+
+if __name__ == '__main__':
+  googletest.main()