diff --git a/.gitignore b/.gitignore index 9ae0d9c96f1..d11a504bdc5 100644 --- a/.gitignore +++ b/.gitignore @@ -22,3 +22,8 @@ Pods Podfile.lock *.pbxproj *.xcworkspacedata +/tensorflow/contrib/lite/downloads/** +/tensorflow/contrib/lite/gen/** +/tensorflow/contrib/lite/examples/ios/simple/data/*.txt +/tensorflow/contrib/lite/examples/ios/simple/data/*.tflite +xcuserdata/** \ No newline at end of file diff --git a/tensorflow/compiler/tf2xla/xla_op_kernel.cc b/tensorflow/compiler/tf2xla/xla_op_kernel.cc index f16472cac83..79d501b511b 100644 --- a/tensorflow/compiler/tf2xla/xla_op_kernel.cc +++ b/tensorflow/compiler/tf2xla/xla_op_kernel.cc @@ -346,9 +346,9 @@ void XlaOpKernelContext::SetConstantOutput(int index, const Tensor& constant) { } void XlaOpKernelContext::SetInvalidOutput(int index) { - const TensorShape shape; Tensor* output = nullptr; - OP_REQUIRES_OK(context_, context_->allocate_output(index, shape, &output)); + OP_REQUIRES_OK(context_, + context_->allocate_output(index, TensorShape({}), &output)); XlaExpression* expression = CastExpressionFromUninitializedTensor(output); xla::ComputationDataHandle handle; handle.set_handle(0); diff --git a/tensorflow/compiler/xla/BUILD b/tensorflow/compiler/xla/BUILD index 515b572b0eb..d3f292207fe 100644 --- a/tensorflow/compiler/xla/BUILD +++ b/tensorflow/compiler/xla/BUILD @@ -175,6 +175,7 @@ cc_library( ":types", ":xla_data_proto", "//tensorflow/core:lib", + "//tensorflow/core:ptr_util", ], ) diff --git a/tensorflow/compiler/xla/ptr_util.h b/tensorflow/compiler/xla/ptr_util.h index fa670303136..c58c19db2ca 100644 --- a/tensorflow/compiler/xla/ptr_util.h +++ b/tensorflow/compiler/xla/ptr_util.h @@ -16,7 +16,8 @@ limitations under the License. #ifndef TENSORFLOW_COMPILER_XLA_PTR_UTIL_H_ #define TENSORFLOW_COMPILER_XLA_PTR_UTIL_H_ -// Utility functions for pointers. +// As this was moved to tensorflow/core/util, provide indirections here to +// maintain current functionality of the library. #include @@ -24,55 +25,27 @@ limitations under the License. #include #include +#include "tensorflow/core/util/ptr_util.h" + namespace xla { -namespace internal { - -// Trait to select overloads and return types for MakeUnique. -template -struct MakeUniqueResult { - using scalar = std::unique_ptr; -}; -template -struct MakeUniqueResult { - using array = std::unique_ptr; -}; -template -struct MakeUniqueResult { - using invalid = void; -}; - -} // namespace internal - -// Transfers ownership of a raw pointer to a std::unique_ptr of deduced type. -// Example: -// X* NewX(int, int); -// auto x = WrapUnique(NewX(1, 2)); // 'x' is std::unique_ptr. -// -// WrapUnique is useful for capturing the output of a raw pointer factory. -// However, prefer 'MakeUnique(args...) over 'WrapUnique(new T(args...))'. -// auto x = WrapUnique(new X(1, 2)); // works, but nonideal. -// auto x = MakeUnique(1, 2); // safer, standard, avoids raw 'new'. -// -// Note: Cannot wrap pointers to array of unknown bound (i.e. U(*)[]). template std::unique_ptr WrapUnique(T* ptr) { - static_assert(!std::is_array::value || std::extent::value != 0, - "types T[0] or T[] are unsupported"); - return std::unique_ptr(ptr); + return tensorflow::WrapUnique(ptr); } template -typename internal::MakeUniqueResult::scalar MakeUnique(Args&&... args) { - return std::unique_ptr(new T(std::forward(args)...)); +typename tensorflow::helper::MakeUniqueResult::scalar MakeUnique( + Args&&... args) { + return tensorflow::MakeUnique(std::forward(args)...); } // Overload for array of unknown bound. // The allocation of arrays needs to use the array form of new, // and cannot take element constructor arguments. template -typename internal::MakeUniqueResult::array MakeUnique(size_t n) { - return std::unique_ptr(new typename std::remove_extent::type[n]()); +typename tensorflow::helper::MakeUniqueResult::array MakeUnique(size_t n) { + return tensorflow::MakeUnique(n); } } // namespace xla diff --git a/tensorflow/compiler/xla/service/buffer_assignment_test.cc b/tensorflow/compiler/xla/service/buffer_assignment_test.cc index 75c71dfeb17..09681b34e7d 100644 --- a/tensorflow/compiler/xla/service/buffer_assignment_test.cc +++ b/tensorflow/compiler/xla/service/buffer_assignment_test.cc @@ -85,7 +85,7 @@ class BufferAssignmentTest : public HloTestBase { std::unique_ptr RunBufferAssignment(HloModule* module, int64 alignment = 1) { return BufferAssigner::Run( - module, MakeUnique(module), + module, xla::MakeUnique(module), backend().compiler()->BufferSizeBytesFunction(), [alignment](LogicalBuffer::Color) { return alignment; }) .ConsumeValueOrDie(); @@ -94,7 +94,7 @@ class BufferAssignmentTest : public HloTestBase { std::unique_ptr RunColoredBufferAssignment( HloModule* module, BufferLiveness::Colorer colorer, int64 alignment = 1) { return BufferAssigner::Run( - module, MakeUnique(module), + module, xla::MakeUnique(module), backend().compiler()->BufferSizeBytesFunction(), [alignment](LogicalBuffer::Color) { return alignment; }, false, std::move(colorer)) @@ -1451,7 +1451,7 @@ class WhileBufferAssignmentTest : public HloTestBase { auto sequence = CreateMemoryMinimizingSequence(*module, ByteSizeOf).ConsumeValueOrDie(); return BufferAssigner::Run( - module, MakeUnique(module, sequence), + module, xla::MakeUnique(module, sequence), ByteSizeOf, [alignment](LogicalBuffer::Color) { return alignment; }) .ConsumeValueOrDie(); @@ -1472,7 +1472,7 @@ static void RunCopyInsertion(HloModule* module) { } TEST_F(WhileBufferAssignmentTest, TwoForwardWhileLoops) { - auto module = MakeUnique(TestName()); + auto module = xla::MakeUnique(TestName()); auto builder = HloComputation::Builder("entry"); auto input0 = builder.AddInstruction( @@ -1529,7 +1529,7 @@ TEST_F(WhileBufferAssignmentTest, TwoForwardWhileLoops) { } TEST_F(WhileBufferAssignmentTest, OneForwardBackwardWhileLoopSet) { - auto module = MakeUnique(TestName()); + auto module = xla::MakeUnique(TestName()); auto builder = HloComputation::Builder("entry"); auto input0 = builder.AddInstruction( @@ -1574,7 +1574,7 @@ TEST_F(WhileBufferAssignmentTest, OneForwardBackwardWhileLoopSet) { } TEST_F(BufferAssignmentTest, TwoCalls) { - auto module = MakeUnique(TestName()); + auto module = xla::MakeUnique(TestName()); Shape r0f32 = ShapeUtil::MakeShape(xla::F32, {}); HloComputation* sub_computation; { @@ -1639,7 +1639,7 @@ static bool IsPostOrderTraversal( } TEST_F(WhileBufferAssignmentTest, WhileLoopsInterferingResultRange) { - auto module = MakeUnique(TestName()); + auto module = xla::MakeUnique(TestName()); auto builder = HloComputation::Builder(TestName()); auto zero = builder.AddInstruction( @@ -1710,15 +1710,15 @@ TEST_F(WhileBufferAssignmentTest, WhileLoopsInterferingResultRange) { auto assignment = BufferAssigner::Run( module.get(), - MakeUnique(module.get(), sequence), ByteSizeOf, - [](LogicalBuffer::Color) { return 1; }) + xla::MakeUnique(module.get(), sequence), + ByteSizeOf, [](LogicalBuffer::Color) { return 1; }) .ConsumeValueOrDie(); EXPECT_TRUE(BuffersDistinct({while0}, {while1}, *assignment)); } TEST_F(WhileBufferAssignmentTest, WhilesDontShareEntryParamIfLiveOut) { - auto module = MakeUnique(TestName()); + auto module = xla::MakeUnique(TestName()); auto builder = HloComputation::Builder("entry"); auto input0 = builder.AddInstruction( diff --git a/tensorflow/compiler/xla/service/buffer_liveness_test.cc b/tensorflow/compiler/xla/service/buffer_liveness_test.cc index 56600b58380..13825fe05bb 100644 --- a/tensorflow/compiler/xla/service/buffer_liveness_test.cc +++ b/tensorflow/compiler/xla/service/buffer_liveness_test.cc @@ -120,7 +120,7 @@ TEST_F(BufferLivenessTest, ElementwiseChain) { auto liveness = BufferLiveness::Run(module.get(), - MakeUnique(module.get())) + xla::MakeUnique(module.get())) .ConsumeValueOrDie(); EXPECT_FALSE(InstructionsMayInterfere(*liveness, param, negate)); @@ -167,10 +167,10 @@ TEST_F(BufferLivenessTest, MultipleEntryParameters_Sequential) { SequentialHloOrdering::HloModuleSequence sequence; sequence.insert({entry, {param0, negate, param1, exp, add}}); - auto liveness = BufferLiveness::Run( - module.get(), - MakeUnique(module.get(), sequence)) - .ConsumeValueOrDie(); + auto liveness = + BufferLiveness::Run(module.get(), xla::MakeUnique( + module.get(), sequence)) + .ConsumeValueOrDie(); // Entry parameters interfere as if they are defined simultaneously at // the very beginning. @@ -216,7 +216,7 @@ TEST_F(BufferLivenessTest, NonElementwiseOperand) { auto liveness = BufferLiveness::Run(module.get(), - MakeUnique(module.get())) + xla::MakeUnique(module.get())) .ConsumeValueOrDie(); EXPECT_FALSE(InstructionsMayInterfere(*liveness, param, exp)); @@ -250,7 +250,7 @@ TEST_F(BufferLivenessTest, OverlappedBuffers) { auto liveness = BufferLiveness::Run(module.get(), - MakeUnique(module.get())) + xla::MakeUnique(module.get())) .ConsumeValueOrDie(); EXPECT_TRUE(InstructionsMayInterfere(*liveness, param, negate)); @@ -294,7 +294,7 @@ TEST_F(BufferLivenessTest, OverlappedBuffersSequentialOrder) { std::vector order = {param, negate, exp, add}; module_sequence.emplace(computation, order); auto liveness = - BufferLiveness::Run(module.get(), MakeUnique( + BufferLiveness::Run(module.get(), xla::MakeUnique( module.get(), module_sequence)) .ConsumeValueOrDie(); @@ -334,7 +334,7 @@ TEST_F(BufferLivenessTest, TupleLiveOut) { auto liveness = BufferLiveness::Run(module.get(), - MakeUnique(module.get())) + xla::MakeUnique(module.get())) .ConsumeValueOrDie(); // All buffers should be live out except the param @@ -370,7 +370,7 @@ TEST_F(BufferLivenessTest, EmbeddedComputation) { auto liveness = BufferLiveness::Run(module.get(), - MakeUnique(module.get())) + xla::MakeUnique(module.get())) .ConsumeValueOrDie(); // Buffers in different computations should always interfere. @@ -409,7 +409,7 @@ TEST_F(BufferLivenessTest, TupleConstantLiveOut) { auto liveness = BufferLiveness::Run(module.get(), - MakeUnique(module.get())) + xla::MakeUnique(module.get())) .ConsumeValueOrDie(); // Only the element buffers of the tuple constant which are pointed to by @@ -474,7 +474,7 @@ TEST_F(BufferLivenessTest, IndependentTupleElements) { auto liveness = BufferLiveness::Run(module.get(), - MakeUnique(module.get())) + xla::MakeUnique(module.get())) .ConsumeValueOrDie(); // We compare tuple element pairs that are input/output to the computation: @@ -536,7 +536,7 @@ TEST_F(BufferLivenessTest, DependentTupleElements) { auto liveness = BufferLiveness::Run(module.get(), - MakeUnique(module.get())) + xla::MakeUnique(module.get())) .ConsumeValueOrDie(); // We compare tuple element pairs that are input/output to the computation: @@ -624,8 +624,8 @@ class FusedDynamicUpdateSliceLivenessTest : public BufferLivenessTest { // Run BufferLiveness on 'module'. auto liveness = - BufferLiveness::Run(module.get(), - MakeUnique(module.get())) + BufferLiveness::Run( + module.get(), xla::MakeUnique(module.get())) .ConsumeValueOrDie(); // Return whether or not buffers interference is detected between // 'tuple_param0' and 'tuple_root' at shape index '{1}'. @@ -736,8 +736,8 @@ class DynamicUpdateSliceLivenessTest : public BufferLivenessTest { module->AddEmbeddedComputation(builder.Build()); // Run BufferLiveness on 'module'. auto liveness = - BufferLiveness::Run(module.get(), - MakeUnique(module.get())) + BufferLiveness::Run( + module.get(), xla::MakeUnique(module.get())) .ConsumeValueOrDie(); // Return whether or not buffers interference is detected between // 'tuple_param0' and 'tuple_root' at shape index '{1}'. diff --git a/tensorflow/compiler/xla/service/cpu/cpu_compiler.cc b/tensorflow/compiler/xla/service/cpu/cpu_compiler.cc index 99dae793abf..988f6327486 100644 --- a/tensorflow/compiler/xla/service/cpu/cpu_compiler.cc +++ b/tensorflow/compiler/xla/service/cpu/cpu_compiler.cc @@ -469,11 +469,11 @@ StatusOr> CpuCompiler::RunBackend( &pre_optimization_ir_hook, &post_optimization_ir_hook)); // Compile must be thread-safe so create a new LLVM context for the module. - auto llvm_context = MakeUnique(); + auto llvm_context = xla::MakeUnique(); auto llvm_module = - MakeUnique("__compute_module", *llvm_context); + xla::MakeUnique("__compute_module", *llvm_context); - auto jit = MakeUnique( + auto jit = xla::MakeUnique( CompilerTargetOptions(module->config()), CodeGenOptLevel(module->config()), options::OptimizeForSizeRequested(module->config()), @@ -528,9 +528,9 @@ StatusOr> CpuCompiler::RunBackend( // uses data dependencies for determining order. TF_ASSIGN_OR_RETURN( std::unique_ptr assignment, - BufferAssigner::Run(module.get(), - MakeUnique(module.get()), - BufferSizeBytesFunction(), memory_alignment)); + BufferAssigner::Run( + module.get(), xla::MakeUnique(module.get()), + BufferSizeBytesFunction(), memory_alignment)); // BufferAssignment::ToString() includes a header, so no need for us to // print one ourselves. XLA_VLOG_LINES(2, assignment->ToString()); @@ -557,7 +557,7 @@ StatusOr> CpuCompiler::RunBackend( const void* data = instruction->literal().InternalData(); int64 size = CpuExecutable::ShapeSizeBytes(instruction->shape()); auto iter = aligned_constants.emplace( - instruction, MakeUnique(size)); + instruction, xla::MakeUnique(size)); CHECK_EQ(iter.second, true); unsigned char* aligned_data = iter.first->second.get(); memcpy(aligned_data, data, size); @@ -642,10 +642,10 @@ StatusOr> CpuCompiler::RunBackend( // temporary buffers are required to run the computation. TF_ASSIGN_OR_RETURN( std::unique_ptr assignment, - BufferAssigner::Run( - module.get(), - MakeUnique(module.get(), module_sequence), - BufferSizeBytesFunction(), memory_alignment)); + BufferAssigner::Run(module.get(), + xla::MakeUnique( + module.get(), module_sequence), + BufferSizeBytesFunction(), memory_alignment)); // BufferAssignment::ToString() includes a header, so no need for us to // print one ourselves. XLA_VLOG_LINES(2, assignment->ToString()); @@ -824,7 +824,8 @@ CpuCompiler::CompileAheadOfTime(std::vector> modules, TF_ASSIGN_OR_RETURN( std::unique_ptr assignment, BufferAssigner::Run( - module, MakeUnique(module, module_sequence), + module, + xla::MakeUnique(module, module_sequence), BufferSizeBytesFunction(), memory_alignment)); // BufferAssignment::ToString() includes a header, so no need for us to // print one ourselves. diff --git a/tensorflow/compiler/xla/service/cpu/simple_orc_jit.cc b/tensorflow/compiler/xla/service/cpu/simple_orc_jit.cc index db6c201876b..cda27833079 100644 --- a/tensorflow/compiler/xla/service/cpu/simple_orc_jit.cc +++ b/tensorflow/compiler/xla/service/cpu/simple_orc_jit.cc @@ -213,71 +213,75 @@ bool RegisterKnownJITSymbols() { #undef REGISTER_CPU_RUNTIME_SYMBOL -#define REGISTER_LIBM_SYMBOL(name) \ - do { \ - /* Register both the F32 and F64 variants of the libm symbol. */ \ - registry->Register(#name "f", reinterpret_cast(name##f)); \ - registry->Register(#name, reinterpret_cast(name)); \ +// Register both the f32 (float) and f64 (double) versions of a libm symbol. +// Unfortunately the double versions are overloaded on some systems, e.g. +// Mac so we need an explicit cast. This requires passing the function signature +// for that case. +#define REGISTER_LIBM_SYMBOL(name, double_sig) \ + do { \ + registry->Register(#name "f", reinterpret_cast(name##f)); \ + registry->Register( \ + #name, reinterpret_cast(static_cast(name))); \ } while (false) - REGISTER_LIBM_SYMBOL(acos); - REGISTER_LIBM_SYMBOL(acosh); - REGISTER_LIBM_SYMBOL(asin); - REGISTER_LIBM_SYMBOL(asinh); - REGISTER_LIBM_SYMBOL(atan); - REGISTER_LIBM_SYMBOL(atan2); - REGISTER_LIBM_SYMBOL(atanh); - REGISTER_LIBM_SYMBOL(cbrt); - REGISTER_LIBM_SYMBOL(ceil); - REGISTER_LIBM_SYMBOL(copysign); - REGISTER_LIBM_SYMBOL(cos); - REGISTER_LIBM_SYMBOL(cosh); - REGISTER_LIBM_SYMBOL(erf); - REGISTER_LIBM_SYMBOL(erfc); - REGISTER_LIBM_SYMBOL(exp); - REGISTER_LIBM_SYMBOL(exp2); - REGISTER_LIBM_SYMBOL(expm1); - REGISTER_LIBM_SYMBOL(fabs); - REGISTER_LIBM_SYMBOL(fdim); - REGISTER_LIBM_SYMBOL(floor); - REGISTER_LIBM_SYMBOL(fma); - REGISTER_LIBM_SYMBOL(fmax); - REGISTER_LIBM_SYMBOL(fmin); - REGISTER_LIBM_SYMBOL(fmod); - REGISTER_LIBM_SYMBOL(frexp); - REGISTER_LIBM_SYMBOL(hypot); - REGISTER_LIBM_SYMBOL(ilogb); - REGISTER_LIBM_SYMBOL(ldexp); - REGISTER_LIBM_SYMBOL(lgamma); - REGISTER_LIBM_SYMBOL(llrint); - REGISTER_LIBM_SYMBOL(llround); - REGISTER_LIBM_SYMBOL(log); - REGISTER_LIBM_SYMBOL(log10); - REGISTER_LIBM_SYMBOL(log1p); - REGISTER_LIBM_SYMBOL(log2); - REGISTER_LIBM_SYMBOL(logb); - REGISTER_LIBM_SYMBOL(lrint); - REGISTER_LIBM_SYMBOL(lround); - REGISTER_LIBM_SYMBOL(modf); - REGISTER_LIBM_SYMBOL(nan); - REGISTER_LIBM_SYMBOL(nearbyint); - REGISTER_LIBM_SYMBOL(nextafter); - REGISTER_LIBM_SYMBOL(nexttoward); - REGISTER_LIBM_SYMBOL(pow); - REGISTER_LIBM_SYMBOL(remainder); - REGISTER_LIBM_SYMBOL(remquo); - REGISTER_LIBM_SYMBOL(rint); - REGISTER_LIBM_SYMBOL(round); - REGISTER_LIBM_SYMBOL(scalbln); - REGISTER_LIBM_SYMBOL(scalbn); - REGISTER_LIBM_SYMBOL(sin); - REGISTER_LIBM_SYMBOL(sincos); - REGISTER_LIBM_SYMBOL(sinh); - REGISTER_LIBM_SYMBOL(sqrt); - REGISTER_LIBM_SYMBOL(tan); - REGISTER_LIBM_SYMBOL(tanh); - REGISTER_LIBM_SYMBOL(tgamma); - REGISTER_LIBM_SYMBOL(trunc); + REGISTER_LIBM_SYMBOL(acos, double (*)(double)); + REGISTER_LIBM_SYMBOL(acosh, double (*)(double)); + REGISTER_LIBM_SYMBOL(asin, double (*)(double)); + REGISTER_LIBM_SYMBOL(asinh, double (*)(double)); + REGISTER_LIBM_SYMBOL(atan, double (*)(double)); + REGISTER_LIBM_SYMBOL(atan2, double (*)(double, double)); + REGISTER_LIBM_SYMBOL(atanh, double (*)(double)); + REGISTER_LIBM_SYMBOL(cbrt, double (*)(double)); + REGISTER_LIBM_SYMBOL(ceil, double (*)(double)); + REGISTER_LIBM_SYMBOL(copysign, double (*)(double, double)); + REGISTER_LIBM_SYMBOL(cos, double (*)(double)); + REGISTER_LIBM_SYMBOL(cosh, double (*)(double)); + REGISTER_LIBM_SYMBOL(erf, double (*)(double)); + REGISTER_LIBM_SYMBOL(erfc, double (*)(double)); + REGISTER_LIBM_SYMBOL(exp, double (*)(double)); + REGISTER_LIBM_SYMBOL(exp2, double (*)(double)); + REGISTER_LIBM_SYMBOL(expm1, double (*)(double)); + REGISTER_LIBM_SYMBOL(fabs, double (*)(double)); + REGISTER_LIBM_SYMBOL(fdim, double (*)(double, double)); + REGISTER_LIBM_SYMBOL(floor, double (*)(double)); + REGISTER_LIBM_SYMBOL(fma, double (*)(double, double, double)); + REGISTER_LIBM_SYMBOL(fmax, double (*)(double, double)); + REGISTER_LIBM_SYMBOL(fmin, double (*)(double, double)); + REGISTER_LIBM_SYMBOL(fmod, double (*)(double, double)); + REGISTER_LIBM_SYMBOL(frexp, double (*)(double, int*)); + REGISTER_LIBM_SYMBOL(hypot, double (*)(double, double)); + REGISTER_LIBM_SYMBOL(ilogb, int (*)(double)); + REGISTER_LIBM_SYMBOL(ldexp, double (*)(double, int)); + REGISTER_LIBM_SYMBOL(lgamma, double (*)(double)); + REGISTER_LIBM_SYMBOL(llrint, long long (*)(double)); + REGISTER_LIBM_SYMBOL(llround, long long (*)(double)); + REGISTER_LIBM_SYMBOL(log, double (*)(double)); + REGISTER_LIBM_SYMBOL(log10, double (*)(double)); + REGISTER_LIBM_SYMBOL(log1p, double (*)(double)); + REGISTER_LIBM_SYMBOL(log2, double (*)(double)); + REGISTER_LIBM_SYMBOL(logb, double (*)(double)); + REGISTER_LIBM_SYMBOL(lrint, long (*)(double)); + REGISTER_LIBM_SYMBOL(lround, long (*)(double)); + REGISTER_LIBM_SYMBOL(modf, double (*)(double, double*)); + REGISTER_LIBM_SYMBOL(nan, double (*)(const char*)); + REGISTER_LIBM_SYMBOL(nearbyint, double (*)(double)); + REGISTER_LIBM_SYMBOL(nextafter, double (*)(double, double)); + REGISTER_LIBM_SYMBOL(nexttoward, double (*)(double, long double)); + REGISTER_LIBM_SYMBOL(pow, double (*)(double, double)); + REGISTER_LIBM_SYMBOL(remainder, double (*)(double, double)); + REGISTER_LIBM_SYMBOL(remquo, double (*)(double, double, int*)); + REGISTER_LIBM_SYMBOL(rint, double (*)(double)); + REGISTER_LIBM_SYMBOL(round, double (*)(double)); + REGISTER_LIBM_SYMBOL(scalbln, double (*)(double, long)); + REGISTER_LIBM_SYMBOL(scalbn, double (*)(double, int)); + REGISTER_LIBM_SYMBOL(sin, double (*)(double)); + REGISTER_LIBM_SYMBOL(sincos, void (*)(double, double*, double*)); + REGISTER_LIBM_SYMBOL(sinh, double (*)(double)); + REGISTER_LIBM_SYMBOL(sqrt, double (*)(double)); + REGISTER_LIBM_SYMBOL(tan, double (*)(double)); + REGISTER_LIBM_SYMBOL(tanh, double (*)(double)); + REGISTER_LIBM_SYMBOL(tgamma, double (*)(double)); + REGISTER_LIBM_SYMBOL(trunc, double (*)(double)); #undef REGISTER_LIBM_SYMBOL diff --git a/tensorflow/compiler/xla/xla_data.proto b/tensorflow/compiler/xla/xla_data.proto index 7efdf8552e7..6800c3d7fae 100644 --- a/tensorflow/compiler/xla/xla_data.proto +++ b/tensorflow/compiler/xla/xla_data.proto @@ -450,7 +450,7 @@ message ConvolutionDimensionNumbers { message ConvolveRequest { ComputationDataHandle lhs = 2; ComputationDataHandle rhs = 3; // This is the filter/kernel. - Window window = 4; // Describes the filter/kenel. + Window window = 4; // Describes the filter/kernel. ConvolutionDimensionNumbers dimension_numbers = 5; } diff --git a/tensorflow/contrib/boosted_trees/lib/utils/batch_features.h b/tensorflow/contrib/boosted_trees/lib/utils/batch_features.h index 7a550d6f732..badc629a118 100644 --- a/tensorflow/contrib/boosted_trees/lib/utils/batch_features.h +++ b/tensorflow/contrib/boosted_trees/lib/utils/batch_features.h @@ -56,7 +56,7 @@ class BatchFeatures { *num_sparse_int_features = sparse_int_feature_columns_.size(); if (*num_dense_float_features == 0 && *num_sparse_float_features == 0 && *num_sparse_int_features == 0) { - return errors::FailedPrecondition("Not intialized yet."); + return errors::FailedPrecondition("Not initialized yet."); } return Status::OK(); } diff --git a/tensorflow/contrib/boosted_trees/lib/utils/example.h b/tensorflow/contrib/boosted_trees/lib/utils/example.h index e388cf332c3..54f60e1dee4 100644 --- a/tensorflow/contrib/boosted_trees/lib/utils/example.h +++ b/tensorflow/contrib/boosted_trees/lib/utils/example.h @@ -63,7 +63,7 @@ class SparseFloatFeatureColumn { public: void Reserve(const int32 size) { if (!single_dimensional_) { - mutlidimensional_values.Reserve(size); + multidimensional_values.Reserve(size); } } @@ -76,7 +76,7 @@ class SparseFloatFeatureColumn { DCHECK_EQ(0, feature_idx); single_value_ = value; } else { - mutlidimensional_values.Add(feature_idx, value); + multidimensional_values.Add(feature_idx, value); } initialized_ = true; } @@ -84,7 +84,7 @@ class SparseFloatFeatureColumn { void Clear() { single_dimensional_ = false; initialized_ = false; - mutlidimensional_values.Clear(); + multidimensional_values.Clear(); } OptionalValue operator[](int feature_idx) const { @@ -94,7 +94,7 @@ class SparseFloatFeatureColumn { if (single_dimensional_) { return OptionalValue(single_value_); } else { - return mutlidimensional_values[feature_idx]; + return multidimensional_values[feature_idx]; } } @@ -102,7 +102,7 @@ class SparseFloatFeatureColumn { bool single_dimensional_; bool initialized_; T single_value_; - SparseMultidimensionalValues mutlidimensional_values; + SparseMultidimensionalValues multidimensional_values; }; // Holds data for one example and enables lookup by feature column. diff --git a/tensorflow/contrib/boosted_trees/lib/utils/sparse_column_iterable.cc b/tensorflow/contrib/boosted_trees/lib/utils/sparse_column_iterable.cc index bc0a93db8c3..ccee9530b68 100644 --- a/tensorflow/contrib/boosted_trees/lib/utils/sparse_column_iterable.cc +++ b/tensorflow/contrib/boosted_trees/lib/utils/sparse_column_iterable.cc @@ -96,6 +96,10 @@ class IndicesRowIterator return (row_idx_ != other.row_idx_); } + bool operator<(const IndicesRowIterator& other) const { + return (row_idx_ < other.row_idx_); + } + bool operator==(const IndicesRowIterator& other) const { QCHECK_EQ(iter_, other.iter_); return (row_idx_ == other.row_idx_); diff --git a/tensorflow/contrib/cmake/external/re2.cmake b/tensorflow/contrib/cmake/external/re2.cmake index b56f4b08981..d10f5959f71 100644 --- a/tensorflow/contrib/cmake/external/re2.cmake +++ b/tensorflow/contrib/cmake/external/re2.cmake @@ -45,4 +45,5 @@ ExternalProject_Add(re2 endif() -DCMAKE_BUILD_TYPE:STRING=Release -DCMAKE_INSTALL_PREFIX:STRING=${re2_INSTALL} + -DRE2_BUILD_TESTING:BOOL=OFF ) diff --git a/tensorflow/contrib/cmake/tf_shared_lib.cmake b/tensorflow/contrib/cmake/tf_shared_lib.cmake index dcedabb333d..571d2b0decb 100644 --- a/tensorflow/contrib/cmake/tf_shared_lib.cmake +++ b/tensorflow/contrib/cmake/tf_shared_lib.cmake @@ -95,10 +95,18 @@ if(WIN32) add_dependencies(tensorflow tensorflow_static) endif(WIN32) -install(TARGETS tensorflow +target_include_directories(tensorflow PUBLIC + $ + $) + +install(TARGETS tensorflow EXPORT tensorflow_export RUNTIME DESTINATION bin LIBRARY DESTINATION lib ARCHIVE DESTINATION lib) + +install(EXPORT tensorflow_export + FILE TensorflowConfig.cmake + DESTINATION lib/cmake) # install necessary headers # tensorflow headers diff --git a/tensorflow/contrib/cmake/tf_tests.cmake b/tensorflow/contrib/cmake/tf_tests.cmake index 5d6ba9ca8d8..2e3ee2c96ba 100644 --- a/tensorflow/contrib/cmake/tf_tests.cmake +++ b/tensorflow/contrib/cmake/tf_tests.cmake @@ -153,7 +153,7 @@ if (tensorflow_BUILD_PYTHON_TESTS) "${tensorflow_source_dir}/tensorflow/contrib/data/*_test.py" "${tensorflow_source_dir}/tensorflow/contrib/factorization/*_test.py" "${tensorflow_source_dir}/tensorflow/contrib/image/*_test.py" - "${tensorflow_source_dir}/tensorflow/contrib/keras/python/keras/integration_test.py" + "${tensorflow_source_dir}/tensorflow/python/keras/_impl/keras/*_test.py" "${tensorflow_source_dir}/tensorflow/contrib/nearest_neighbor/python/kernel_tests/*_test.py" "${tensorflow_source_dir}/tensorflow/contrib/seq2seq/python/kernel_tests/*_test.py" "${tensorflow_source_dir}/tensorflow/contrib/stateless/python/kernel_tests/*_test.py" @@ -171,7 +171,6 @@ if (tensorflow_BUILD_PYTHON_TESTS) "${tensorflow_source_dir}/tensorflow/contrib/graph_editor/*_test.py" "${tensorflow_source_dir}/tensorflow/contrib/bayesflow/*_test.py" "${tensorflow_source_dir}/tensorflow/contrib/framework/*_test.py" - "${tensorflow_source_dir}/tensorflow/contrib/keras/*_test.py" "${tensorflow_source_dir}/tensorflow/contrib/distributions/*_test.py" "${tensorflow_source_dir}/tensorflow/contrib/learn/*_test.py" ) @@ -225,6 +224,9 @@ if (tensorflow_BUILD_PYTHON_TESTS) # Numerical issues, calculations off. "${tensorflow_source_dir}/tensorflow/python/kernel_tests/concat_op_test.py" "${tensorflow_source_dir}/tensorflow/contrib/factorization/python/ops/wals_test.py" + "${tensorflow_source_dir}/tensorflow/python/keras/_impl/keras/utils/data_utils_test.py" + "${tensorflow_source_dir}/tensorflow/python/keras/_impl/keras/backend_test.py" + "${tensorflow_source_dir}/tensorflow/python/keras/_impl/keras/preprocessing/image_test.py" # Float division by zero "${tensorflow_source_dir}/tensorflow/python/kernel_tests/benchmark_test.py" # Flaky, for unknown reasons. Cannot reproduce in terminal. Revisit once we can get stack traces. diff --git a/tensorflow/contrib/crf/python/ops/crf.py b/tensorflow/contrib/crf/python/ops/crf.py index ec395e41d08..7f5ae937b26 100644 --- a/tensorflow/contrib/crf/python/ops/crf.py +++ b/tensorflow/contrib/crf/python/ops/crf.py @@ -420,7 +420,7 @@ class CrfDecodeBackwardRnnCell(rnn_cell.RNNCell): """Initialize the CrfDecodeBackwardRnnCell. Args: - num_tags: The number of tags. + num_tags: An integer. The number of tags. """ self._num_tags = num_tags diff --git a/tensorflow/contrib/data/python/kernel_tests/BUILD b/tensorflow/contrib/data/python/kernel_tests/BUILD index 43431ca2c5a..ffb5655c3e1 100644 --- a/tensorflow/contrib/data/python/kernel_tests/BUILD +++ b/tensorflow/contrib/data/python/kernel_tests/BUILD @@ -161,6 +161,7 @@ py_test( size = "small", srcs = ["flat_map_dataset_op_test.py"], srcs_version = "PY2AND3", + tags = ["no_pip"], deps = [ ":dataset_serialization_test", "//tensorflow/contrib/data/python/ops:dataset_ops", @@ -278,6 +279,7 @@ py_test( size = "medium", srcs = ["map_dataset_op_test.py"], srcs_version = "PY2AND3", + tags = ["no_pip"], deps = [ ":dataset_serialization_test", "//tensorflow/contrib/data/python/ops:dataset_ops", @@ -348,6 +350,7 @@ py_test( size = "medium", srcs = ["reader_dataset_ops_test.py"], srcs_version = "PY2AND3", + tags = ["no_pip"], deps = [ ":dataset_serialization_test", "//tensorflow/contrib/data/python/ops:readers", diff --git a/tensorflow/contrib/distributions/python/ops/poisson_lognormal.py b/tensorflow/contrib/distributions/python/ops/poisson_lognormal.py index 96dff856650..2701c36fb53 100644 --- a/tensorflow/contrib/distributions/python/ops/poisson_lognormal.py +++ b/tensorflow/contrib/distributions/python/ops/poisson_lognormal.py @@ -293,7 +293,7 @@ class PoissonLogNormalQuadratureCompound(distribution_lib.Distribution): # where, # # Z|v ~ interpolate_affine[v](distribution) - # V ~ mixture_distrubution + # V ~ mixture_distribution # # thus, # diff --git a/tensorflow/contrib/eager/python/metrics_impl.py b/tensorflow/contrib/eager/python/metrics_impl.py index aa359b7a0d7..2f8016ede3c 100644 --- a/tensorflow/contrib/eager/python/metrics_impl.py +++ b/tensorflow/contrib/eager/python/metrics_impl.py @@ -73,7 +73,7 @@ class Metric(object): * `result()`: Computes and returns a final value for the metric from the variables in `self`. - Decendants may override `aggregate()`, but usually won't need to. It + Descendants may override `aggregate()`, but usually won't need to. It adds in the state from a list of metrics of the same type as `self`. (Default is to sum all the variables.) Note that users should not call `aggregate()`, it is for use by TensorFlow infrastructure. diff --git a/tensorflow/contrib/factorization/python/ops/wals.py b/tensorflow/contrib/factorization/python/ops/wals.py index 2bde3e0dd71..4fe22ea26ec 100644 --- a/tensorflow/contrib/factorization/python/ops/wals.py +++ b/tensorflow/contrib/factorization/python/ops/wals.py @@ -183,7 +183,7 @@ def _wals_factorization_model_function(features, labels, mode, params): # TRAIN mode: if mode == model_fn.ModeKeys.TRAIN: - # Training consists of the folowing ops (controlled using a SweepHook). + # Training consists of the following ops (controlled using a SweepHook). # Before a row sweep: # row_update_prep_gramian_op # initialize_row_update_op diff --git a/tensorflow/contrib/ffmpeg/BUILD b/tensorflow/contrib/ffmpeg/BUILD index 7a5a4cb8c94..eccce99071d 100644 --- a/tensorflow/contrib/ffmpeg/BUILD +++ b/tensorflow/contrib/ffmpeg/BUILD @@ -47,10 +47,25 @@ cc_library( alwayslink = 1, ) +cc_library( + name = "decode_video_op_cc", + srcs = ["decode_video_op.cc"], + copts = tf_copts(), + linkstatic = 1, + visibility = ["//visibility:private"], + deps = [ + "//tensorflow/contrib/ffmpeg/default:ffmpeg_lib", + "//tensorflow/core:framework_headers_lib", + "//third_party/eigen3", + ], + alwayslink = 1, +) + tf_custom_op_library( name = "ffmpeg.so", deps = [ ":decode_audio_op_cc", + ":decode_video_op_cc", ":encode_audio_op_cc", ], ) @@ -59,6 +74,7 @@ cc_library( name = "ffmpeg_op_lib", deps = [ ":decode_audio_op_cc", + ":decode_video_op_cc", ":encode_audio_op_cc", ], ) @@ -81,6 +97,15 @@ tf_gen_op_wrapper_py( ], ) +tf_gen_op_wrapper_py( + name = "decode_video_op_py", + require_shape_functions = True, + visibility = ["//visibility:private"], + deps = [ + ":decode_video_op_cc", + ], +) + tf_py_test( name = "decode_audio_op_test", srcs = ["decode_audio_op_test.py"], @@ -115,6 +140,27 @@ tf_py_test( tags = ["manual"], ) +tf_py_test( + name = "decode_video_op_test", + size = "small", + srcs = ["decode_video_op_test.py"], + additional_deps = [ + ":ffmpeg_ops_py", + "@six_archive//:six", + "//tensorflow/python:array_ops", + "//tensorflow/python:client_testlib", + "//tensorflow/python:platform", + "//tensorflow/python:image_ops", + ], + data = [ + ":test_data", + ], + tags = [ + "manual", + "notap", + ], +) + py_library( name = "ffmpeg_ops_py", srcs = [ @@ -126,6 +172,7 @@ py_library( visibility = ["//visibility:public"], deps = [ ":decode_audio_op_py", + ":decode_video_op_py", ":encode_audio_op_py", "//tensorflow/contrib/util:util_py", "//tensorflow/python:framework_for_generated_wrappers", diff --git a/tensorflow/contrib/ffmpeg/__init__.py b/tensorflow/contrib/ffmpeg/__init__.py index 2bcb7284e10..484ffee3e7a 100644 --- a/tensorflow/contrib/ffmpeg/__init__.py +++ b/tensorflow/contrib/ffmpeg/__init__.py @@ -26,9 +26,10 @@ from __future__ import division from __future__ import print_function from tensorflow.contrib.ffmpeg.ffmpeg_ops import decode_audio +from tensorflow.contrib.ffmpeg.ffmpeg_ops import decode_video from tensorflow.contrib.ffmpeg.ffmpeg_ops import encode_audio from tensorflow.python.util.all_util import remove_undocumented -_allowed_symbols = ['decode_audio', 'encode_audio'] +_allowed_symbols = ['decode_audio', 'encode_audio', 'decode_video'] remove_undocumented(__name__, _allowed_symbols) diff --git a/tensorflow/contrib/ffmpeg/decode_audio_op.cc b/tensorflow/contrib/ffmpeg/decode_audio_op.cc index 4b1c8a337e1..92fad70b1f9 100644 --- a/tensorflow/contrib/ffmpeg/decode_audio_op.cc +++ b/tensorflow/contrib/ffmpeg/decode_audio_op.cc @@ -37,29 +37,6 @@ namespace { // https://www.ffmpeg.org/ffmpeg-formats.html const char* kValidFileFormats[] = {"mp3", "mp4", "ogg", "wav"}; -// Writes binary data to a file. -Status WriteFile(const string& filename, tensorflow::StringPiece contents) { - Env& env = *Env::Default(); - std::unique_ptr file; - TF_RETURN_IF_ERROR(env.NewWritableFile(filename, &file)); - TF_RETURN_IF_ERROR(file->Append(contents)); - TF_RETURN_IF_ERROR(file->Close()); - return Status::OK(); -} - -// Cleans up a file on destruction. -class FileDeleter { - public: - explicit FileDeleter(const string& filename) : filename_(filename) {} - ~FileDeleter() { - Env& env = *Env::Default(); - env.DeleteFile(filename_).IgnoreError(); - } - - private: - const string filename_; -}; - /* * Decoding implementation, shared across V1 and V2 ops. Creates a new * output in the context. @@ -69,7 +46,7 @@ void Decode(OpKernelContext* context, const string& file_format, const int32 samples_per_second, const int32 channel_count) { // Write the input data to a temp file. - const string temp_filename = GetTempFilename(file_format); + const string temp_filename = io::GetTempFilename(file_format); OP_REQUIRES_OK(context, WriteFile(temp_filename, file_contents)); FileDeleter deleter(temp_filename); diff --git a/tensorflow/contrib/ffmpeg/decode_video_op.cc b/tensorflow/contrib/ffmpeg/decode_video_op.cc new file mode 100644 index 00000000000..d44032968d5 --- /dev/null +++ b/tensorflow/contrib/ffmpeg/decode_video_op.cc @@ -0,0 +1,118 @@ +// 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. +// ============================================================================= + +#include + +#include +#include + +#include "tensorflow/contrib/ffmpeg/ffmpeg_lib.h" +#include "tensorflow/core/framework/op.h" +#include "tensorflow/core/framework/op_kernel.h" +#include "tensorflow/core/framework/shape_inference.h" +#include "tensorflow/core/lib/io/path.h" +#include "tensorflow/core/lib/strings/str_util.h" +#include "tensorflow/core/lib/strings/strcat.h" +#include "tensorflow/core/platform/env.h" +#include "tensorflow/core/platform/logging.h" + +namespace tensorflow { +namespace ffmpeg { + +class DecodeVideoOp : public OpKernel { + public: + explicit DecodeVideoOp(OpKernelConstruction* context) : OpKernel(context) {} + + void Compute(OpKernelContext* context) override { + OP_REQUIRES( + context, context->num_inputs() == 1, + errors::InvalidArgument("DecodeVideo requires exactly 1 input.")); + const Tensor& contents_tensor = context->input(0); + + OP_REQUIRES(context, TensorShapeUtils::IsScalar(contents_tensor.shape()), + errors::InvalidArgument( + "contents must be a rank-0 tensor but got shape ", + contents_tensor.shape().DebugString())); + const tensorflow::StringPiece contents = contents_tensor.scalar()(); + + // Write the input data to a temp file. + string extension; + const string temp_filename = io::GetTempFilename(extension); + OP_REQUIRES_OK(context, WriteFile(temp_filename, contents)); + FileDeleter deleter(temp_filename); + + uint32 width = 0; + uint32 height = 0; + uint32 frames = 0; + + // Run FFmpeg on the data and verify results. + std::vector output_data; + const Status result = ffmpeg::ReadVideoFile(temp_filename, &output_data, + &width, &height, &frames); + if (result.code() == error::Code::NOT_FOUND) { + OP_REQUIRES( + context, result.ok(), + errors::Unavailable("FFmpeg must be installed to run this op. FFmpeg " + "can be found at http://www.ffmpeg.org.")); + } else if (result.code() == error::UNKNOWN) { + LOG(ERROR) << "Ffmpeg failed with error '" << result.error_message() + << "'. Returning empty tensor."; + Tensor* output = nullptr; + OP_REQUIRES_OK(context, + context->allocate_output(0, TensorShape({0, 0}), &output)); + return; + } else { + OP_REQUIRES_OK(context, result); + } + OP_REQUIRES(context, !output_data.empty(), + errors::Unknown("No output created by FFmpeg.")); + OP_REQUIRES( + context, output_data.size() == (frames * height * width * 3), + errors::Unknown("Output created by FFmpeg [", output_data.size(), + "] does not match description [", frames, ", ", height, + ", ", width, ", 3]")); + Tensor* output = nullptr; + OP_REQUIRES_OK(context, + context->allocate_output( + 0, TensorShape({frames, height, width, 3}), &output)); + auto output_flat = output->flat(); + std::copy_n(output_data.begin(), output_data.size(), &output_flat(0)); + } +}; + +REGISTER_KERNEL_BUILDER(Name("DecodeVideo").Device(DEVICE_CPU), DecodeVideoOp); + +REGISTER_OP("DecodeVideo") + .Input("contents: string") + .Output("output: uint8") + .SetShapeFn([](shape_inference::InferenceContext* c) { + c->set_output(0, c->UnknownShapeOfRank(4)); + return Status::OK(); + }) + .Doc(R"doc( +Processes the contents of an audio file into a tensor using FFmpeg to decode +the file. + +One row of the tensor is created for each channel in the audio file. Each +channel contains audio samples starting at the beginning of the audio and +having `1/samples_per_second` time between them. If the `channel_count` is +different from the contents of the file, channels will be merged or created. + +contents: The binary audio file contents, as a string or rank-0 string + tensor. +)doc"); + +} // namespace ffmpeg +} // namespace tensorflow diff --git a/tensorflow/contrib/ffmpeg/decode_video_op_test.py b/tensorflow/contrib/ffmpeg/decode_video_op_test.py new file mode 100644 index 00000000000..b43b6b89192 --- /dev/null +++ b/tensorflow/contrib/ffmpeg/decode_video_op_test.py @@ -0,0 +1,69 @@ +# 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 third_party.tensorflow.contrib.ffmpeg.decode_video_op.""" + +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import os.path + +import six # pylint: disable=unused-import + +from tensorflow.contrib import ffmpeg +from tensorflow.python.ops import image_ops +from tensorflow.python.platform import resource_loader +from tensorflow.python.platform import test + + +class DecodeVideoOpTest(test.TestCase): + + def _loadFileAndTest(self, filename, width, height, frames, bmp_filename, + index): + """Loads an video file and validates the output tensor. + + Args: + filename: The filename of the input file. + width: The width of the video. + height: The height of the video. + frames: The frames of the video. + bmp_filename: The filename for the bmp file. + index: Index location inside the video. + """ + with self.test_session(): + path = os.path.join(resource_loader.get_data_files_path(), 'testdata', + filename) + with open(path, 'rb') as f: + contents = f.read() + + bmp_path = os.path.join(resource_loader.get_data_files_path(), 'testdata', + bmp_filename) + with open(bmp_path, 'rb') as f: + bmp_contents = f.read() + + image_op = image_ops.decode_bmp(bmp_contents) + image = image_op.eval() + self.assertEqual(image.shape, (height, width, 3)) + video_op = ffmpeg.decode_video(contents) + video = video_op.eval() + self.assertEqual(video.shape, (frames, height, width, 3)) + self.assertAllEqual(video[index, :, :, :], image) + + def testMp4(self): + self._loadFileAndTest('small.mp4', 560, 320, 166, 'small_100.bmp', 99) + + +if __name__ == '__main__': + test.main() diff --git a/tensorflow/contrib/ffmpeg/default/ffmpeg_lib.cc b/tensorflow/contrib/ffmpeg/default/ffmpeg_lib.cc index 545a4386d04..1245f515fe8 100644 --- a/tensorflow/contrib/ffmpeg/default/ffmpeg_lib.cc +++ b/tensorflow/contrib/ffmpeg/default/ffmpeg_lib.cc @@ -16,6 +16,7 @@ #include "tensorflow/contrib/ffmpeg/ffmpeg_lib.h" #include +#include #include #include #include @@ -25,6 +26,7 @@ #include #include "tensorflow/core/lib/io/path.h" +#include "tensorflow/core/lib/strings/numbers.h" #include "tensorflow/core/lib/strings/str_util.h" #include "tensorflow/core/platform/cpu_info.h" #include "tensorflow/core/platform/env.h" @@ -38,28 +40,45 @@ namespace { const char kFfmpegExecutable[] = "ffmpeg"; const int32 kDefaultProbeSize = 5000000; // 5MB -std::vector FfmpegCommandLine(const string& input_filename, - const string& output_filename, - const string& input_format_id, - int32 samples_per_second, - int32 channel_count) { - return { - "-nostats", // No additional progress display. - "-nostdin", // No interactive commands accepted. - "-f", input_format_id, // eg: "mp3" - "-probesize", StrCat(kDefaultProbeSize), - "-i", input_filename, - "-loglevel", "info", // Enable verbose logging to support debugging. - "-map_metadata", "-1", // Copy global metadata from input to output. - "-vn", // No video recording. - "-ac:a:0", StrCat(channel_count), - "-ar:a:0", StrCat(samples_per_second), - // Output set (in several ways) to signed 16-bit little-endian ints. - "-codec:a:0", "pcm_s16le", "-sample_fmt", "s16", "-f", "s16le", - "-sn", // No subtitle recording. - "-y", // Overwrite output file. - StrCat(output_filename) - }; +std::vector FfmpegAudioCommandLine(const string& input_filename, + const string& output_filename, + const string& input_format_id, + int32 samples_per_second, + int32 channel_count) { + return {"-nostats", // No additional progress display. + "-nostdin", // No interactive commands accepted. + "-f", input_format_id, // eg: "mp3" + "-probesize", StrCat(kDefaultProbeSize), "-i", input_filename, + "-loglevel", "info", // Enable verbose logging to support debugging. + "-map_metadata", "-1", // Copy global metadata from input to output. + "-vn", // No video recording. + "-ac:a:0", StrCat(channel_count), "-ar:a:0", + StrCat(samples_per_second), + // Output set (in several ways) to signed 16-bit little-endian ints. + "-codec:a:0", "pcm_s16le", "-sample_fmt", "s16", "-f", "s16le", + "-sn", // No subtitle recording. + "-y", // Overwrite output file. + StrCat(output_filename)}; +} + +std::vector FfmpegVideoCommandLine(const string& input_filename, + const string& output_filename) { + return {"-nostats", // No additional progress display. + "-nostdin", // No interactive commands accepted. + "-i", + input_filename, + "-f", + "image2pipe", + "-probesize", + StrCat(kDefaultProbeSize), + "-loglevel", + "info", // Enable verbose logging to support debugging. + "-vcodec", + "rawvideo", + "-pix_fmt", + "rgb24", + "-y", // Overwrite output file. + StrCat(output_filename)}; } // Is a named binary installed and executable by the current process? @@ -106,7 +125,7 @@ bool IsBinaryInstalled(const string& binary_name) { ::execvp(kFfmpegExecutable, args_chars.data()); // exec only returns on error. const int error = errno; - LOG(ERROR) << "FFmpeg could not be executed: " << error; + LOG(ERROR) << "FFmpeg could not be executed: " << strerror(error); ::_exit(error); } @@ -198,52 +217,101 @@ string BuildWavFile(int32 samples_per_second, int32 channel_count, return data; } -// Returns a unique number every time it is called. -int64 UniqueId() { - static mutex mu(LINKER_INITIALIZED); - static int64 id = 0; - mutex_lock l(mu); - return ++id; +Status ReadInfoFile(const string& filename, uint32* width, uint32* height, + uint32* frames) { + string data; + TF_QCHECK_OK(ReadFileToString(Env::Default(), filename, &data)) + << "Could not read FFmpeg file: " << filename; + bool in_output = false; + bool in_mapping = false; + uint32 frames_value = 0; + uint32 height_value = 0; + uint32 width_value = 0; + for (const string& line : str_util::Split(data, '\n')) { + // Output starts with the first line of `Output #..`. + // Further processing output region starts next line so we could continue + // the loop. + if (!in_output && line.find("Output #") == 0) { + in_output = true; + in_mapping = false; + continue; + } + // Stream mapping starts with the first line of `Stream mapping`, it also + // signals the end of Output section. + // Further processing of stream mapping region starts next line so we could + // continue the loop. + if (!in_mapping && line.find("Stream mapping:") == 0) { + in_output = false; + in_mapping = true; + continue; + } + if (in_output) { + // We only look for the first stream in output `Stream #0`. + // Once processed we will not further process output section. + if (line.find(" Stream #") == 0) { + size_t p = line.find(", rgb24, ", 24); + if (p != std::string::npos) { + string rgb24 = line.substr(p + 9, line.find(" ", p + 9)); + rgb24 = rgb24.substr(0, rgb24.find(",")); + string rgb24_width = rgb24.substr(0, rgb24.find("x")); + string rgb24_height = rgb24.substr(rgb24_width.length() + 1); + if (strings::safe_strtou32(rgb24_width, &width_value) && + strings::safe_strtou32(rgb24_height, &height_value)) { + in_output = false; + } + } + } + continue; + } + if (in_mapping) { + // We only look for the first stream mapping to have the number of the + // frames. + // Once processed we will not further process stream mapping section. + if (line.find("frame= ") == 0) { + string number = line.substr(8, line.find(" ", 8)); + number = number.substr(0, number.find(" ")); + if (strings::safe_strtou32(number, &frames_value)) { + in_mapping = false; + } + } + continue; + } + } + if (frames_value == 0 || height_value == 0 || width_value == 0) { + return errors::Unknown("Not enough video info returned by FFmpeg [", + frames_value, ", ", height_value, ", ", width_value, + ", 3]"); + } + *width = width_value; + *height = height_value; + *frames = frames_value; + return Status::OK(); } } // namespace -string GetTempFilename(const string& extension) { - for (const char* dir : std::vector( - {getenv("TEST_TMPDIR"), getenv("TMPDIR"), getenv("TMP"), "/tmp"})) { - if (!dir || !dir[0]) { - continue; - } - struct stat statbuf; - if (!stat(dir, &statbuf) && S_ISDIR(statbuf.st_mode)) { - // UniqueId is added here because mkstemps is not as thread safe as it - // looks. https://github.com/tensorflow/tensorflow/issues/5804 shows - // the problem. - string tmp_filepath = io::JoinPath( - dir, - StrCat("tmp_file_tensorflow_", UniqueId(), "_XXXXXX.", extension)); - int fd = mkstemps(&tmp_filepath[0], extension.length() + 1); - if (fd < 0) { - LOG(FATAL) << "Failed to create temp file."; - } else { - close(fd); - return tmp_filepath; - } - } - } - LOG(FATAL) << "No temp directory found."; +FileDeleter::~FileDeleter() { + Env& env = *Env::Default(); + env.DeleteFile(filename_).IgnoreError(); } -Status ReadAudioFile(const string& filename, - const string& audio_format_id, - int32 samples_per_second, - int32 channel_count, +Status WriteFile(const string& filename, StringPiece contents) { + Env& env = *Env::Default(); + std::unique_ptr file; + TF_RETURN_IF_ERROR(env.NewWritableFile(filename, &file)); + TF_RETURN_IF_ERROR(file->Append(contents)); + TF_RETURN_IF_ERROR(file->Close()); + return Status::OK(); +} + +Status ReadAudioFile(const string& filename, const string& audio_format_id, + int32 samples_per_second, int32 channel_count, std::vector* output_samples) { // Create an argument list. - string output_filename = GetTempFilename("raw"); + string output_filename = io::GetTempFilename("raw"); const std::vector args = - FfmpegCommandLine(filename, output_filename, audio_format_id, - samples_per_second, channel_count); + FfmpegAudioCommandLine(filename, output_filename, audio_format_id, + samples_per_second, channel_count); // Unfortunately, it's impossible to differentiate an exec failure due to the // binary being missing and an error from the binary's execution. Therefore, @@ -256,7 +324,8 @@ Status ReadAudioFile(const string& filename, // Execute ffmpeg and report errors. pid_t child_pid = ::fork(); if (child_pid < 0) { - return Status(error::Code::UNKNOWN, StrCat("fork failed: ", errno)); + return Status(error::Code::UNKNOWN, + StrCat("fork failed: ", strerror(errno))); } if (child_pid == 0) { ExecuteFfmpeg(args); @@ -285,5 +354,63 @@ Status CreateAudioFile(const string& audio_format_id, int32 bits_per_second, return Status::OK(); } +Status ReadVideoFile(const string& filename, std::vector* output_data, + uint32* width, uint32* height, uint32* frames) { + if (!IsBinaryInstalled(kFfmpegExecutable)) { + return Status(error::Code::NOT_FOUND, StrCat("FFmpeg could not be found.")); + } + + string output_filename = io::GetTempFilename("raw"); + string stderr_filename = io::GetTempFilename("err"); + + // Create an argument list. + const std::vector args = + FfmpegVideoCommandLine(filename, output_filename); + + // Execute ffmpeg and report errors. + pid_t child_pid = ::fork(); + if (child_pid < 0) { + return Status(error::Code::UNKNOWN, + StrCat("fork failed: ", strerror(errno))); + } + if (child_pid == 0) { + const int fd = + open(stderr_filename.c_str(), O_RDWR | O_CREAT | O_APPEND, 0600); + if (fd < 0) { + const int error = errno; + LOG(ERROR) << "FFmpeg stderr file could not be created: " + << strerror(error); + ::_exit(error); + } + close(STDERR_FILENO); + dup2(fd, STDERR_FILENO); + ExecuteFfmpeg(args); + } else { + int status_code; + if (::waitpid(child_pid, &status_code, 0) < 0) { + return Status(error::Code::UNKNOWN, + StrCat("waitpid failed: ", strerror(errno))); + } + if (status_code) { + return Status(error::Code::UNKNOWN, + StrCat("FFmpeg execution failed: ", status_code)); + } + + TF_QCHECK_OK(ReadInfoFile(stderr_filename, width, height, frames)) + << "Could not read FFmpeg stderr file: " << stderr_filename; + + string raw_data; + TF_QCHECK_OK(ReadFileToString(Env::Default(), output_filename, &raw_data)) + << "Could not read FFmpeg output file: " << output_filename; + output_data->resize(raw_data.size()); + std::copy_n(raw_data.data(), raw_data.size(), output_data->begin()); + + TF_QCHECK_OK(Env::Default()->DeleteFile(output_filename)) + << output_filename; + TF_QCHECK_OK(Env::Default()->DeleteFile(stderr_filename)) + << stderr_filename; + return Status::OK(); + } +} } // namespace ffmpeg } // namespace tensorflow diff --git a/tensorflow/contrib/ffmpeg/default/ffmpeg_lib_utility_test.cc b/tensorflow/contrib/ffmpeg/default/ffmpeg_lib_utility_test.cc index 7176f3b5506..d6c885a3242 100644 --- a/tensorflow/contrib/ffmpeg/default/ffmpeg_lib_utility_test.cc +++ b/tensorflow/contrib/ffmpeg/default/ffmpeg_lib_utility_test.cc @@ -21,6 +21,7 @@ #include #include "tensorflow/core/lib/core/threadpool.h" +#include "tensorflow/core/lib/io/path.h" #include "tensorflow/core/platform/env.h" #include "tensorflow/core/platform/mutex.h" #include "tensorflow/core/platform/test.h" @@ -49,7 +50,7 @@ TEST(FfmpegLibTest, TestTempDirectoryThreading) { pool.Schedule([&mu, &temp_filenames, environment]() { std::array buffer; for (int32 j = 0; j < kStringsPerItem; ++j) { - buffer[j] = GetTempFilename("mp3"); + buffer[j] = io::GetTempFilename("mp3"); TF_QCHECK_OK(environment->DeleteFile(buffer[j])); } mutex_lock l(mu); diff --git a/tensorflow/contrib/ffmpeg/ffmpeg_lib.h b/tensorflow/contrib/ffmpeg/ffmpeg_lib.h index f64007c81d7..c5ea1432bf8 100644 --- a/tensorflow/contrib/ffmpeg/ffmpeg_lib.h +++ b/tensorflow/contrib/ffmpeg/ffmpeg_lib.h @@ -24,16 +24,24 @@ namespace tensorflow { namespace ffmpeg { -// Gets a temp filename in an appropriate location. -string GetTempFilename(const string& extension); +// Cleans up a file on destruction. +class FileDeleter { + public: + explicit FileDeleter(const string& filename) : filename_(filename) {} + ~FileDeleter(); + + private: + const string filename_; +}; + +// Writes binary data to a file. +Status WriteFile(const string& filename, tensorflow::StringPiece contents); // Reads an audio file using ffmpeg and converts it into an array of samples in // [-1.0, 1.0]. If there are multiple channels in the audio then each frame will // contain a separate sample for each channel. Frames are ordered by time. -Status ReadAudioFile(const string& filename, - const string& audio_format_id, - int32 samples_per_second, - int32 channel_count, +Status ReadAudioFile(const string& filename, const string& audio_format_id, + int32 samples_per_second, int32 channel_count, std::vector* output_samples); // Creates an audio file using ffmpeg in a specific format. The samples are in @@ -45,6 +53,11 @@ Status CreateAudioFile(const string& audio_format_id, int32 bits_per_second, int32 samples_per_second, int32 channel_count, const std::vector& samples, string* output_data); +// Reads an video file using ffmpeg adn converts it into a RGB24 in uint8 +// [frames, height, width, 3]. The w, h, and frames are obtained from ffmpeg. +Status ReadVideoFile(const string& filename, std::vector* output_data, + uint32* width, uint32* height, uint32* frames); + } // namespace ffmpeg } // namespace tensorflow diff --git a/tensorflow/contrib/ffmpeg/ffmpeg_ops.py b/tensorflow/contrib/ffmpeg/ffmpeg_ops.py index 18b0b8b812c..5bb011f41c7 100644 --- a/tensorflow/contrib/ffmpeg/ffmpeg_ops.py +++ b/tensorflow/contrib/ffmpeg/ffmpeg_ops.py @@ -19,6 +19,7 @@ from __future__ import division from __future__ import print_function from tensorflow.contrib.ffmpeg.ops import gen_decode_audio_op_py +from tensorflow.contrib.ffmpeg.ops import gen_decode_video_op_py from tensorflow.contrib.ffmpeg.ops import gen_encode_audio_op_py from tensorflow.contrib.util import loader from tensorflow.python.framework import ops @@ -89,3 +90,19 @@ def encode_audio(audio, file_format=None, samples_per_second=None): ops.NotDifferentiable('EncodeAudio') + + +def decode_video(contents): + """Create an op that decodes the contents of a video file. + + Args: + contents: The binary contents of the video file to decode. This is a + scalar. + + Returns: + A rank-4 `Tensor` that has `[frames, height, width, 3]` RGB as output. + """ + return gen_decode_video_op_py.decode_video(contents) + + +ops.NotDifferentiable('DecodeVideo') diff --git a/tensorflow/contrib/ffmpeg/testdata/small.mp4 b/tensorflow/contrib/ffmpeg/testdata/small.mp4 new file mode 100644 index 00000000000..1fc478842f5 Binary files /dev/null and b/tensorflow/contrib/ffmpeg/testdata/small.mp4 differ diff --git a/tensorflow/contrib/ffmpeg/testdata/small_100.bmp b/tensorflow/contrib/ffmpeg/testdata/small_100.bmp new file mode 100644 index 00000000000..61f53a2a21c Binary files /dev/null and b/tensorflow/contrib/ffmpeg/testdata/small_100.bmp differ diff --git a/tensorflow/contrib/framework/python/framework/graph_util.py b/tensorflow/contrib/framework/python/framework/graph_util.py index 9ba9c77b923..a18ff2320d9 100644 --- a/tensorflow/contrib/framework/python/framework/graph_util.py +++ b/tensorflow/contrib/framework/python/framework/graph_util.py @@ -24,12 +24,14 @@ import six # pylint: disable=unused-import from tensorflow.core.framework import graph_pb2 from tensorflow.core.framework import node_def_pb2 +from tensorflow.python.framework import ops from tensorflow.python.framework.graph_util_impl import _assert_nodes_are_present from tensorflow.python.framework.graph_util_impl import _bfs_for_reachable_nodes from tensorflow.python.framework.graph_util_impl import _extract_graph_summary from tensorflow.python.framework.graph_util_impl import _node_name -__all__ = ["fuse_op"] + +__all__ = ["fuse_op", "get_placeholders"] def fuse_op(graph_def, input_nodes, output_nodes, output_dtypes, @@ -126,3 +128,27 @@ def fuse_op(graph_def, input_nodes, output_nodes, output_dtypes, out.library.CopyFrom(graph_def.library) out.versions.CopyFrom(graph_def.versions) return out + + +def get_placeholders(graph): + """Get placeholders of a graph. + + Args: + graph: A tf.Graph. + Returns: + A list contains all placeholders of given graph. + + Raises: + TypeError: If `graph` is not a tensorflow graph. + """ + + if not isinstance(graph, ops.Graph): + raise TypeError("Input graph needs to be a Graph: %s" % graph) + + # For each placeholder() call, there is a corresponding + # operation of type 'Placeholder' registered to the graph. + # The return value (a Tensor) of placeholder() is the + # first output of this operation in fact. + operations = graph.get_operations() + result = [i.outputs[0] for i in operations if i.type == "Placeholder"] + return result diff --git a/tensorflow/contrib/framework/python/framework/graph_util_test.py b/tensorflow/contrib/framework/python/framework/graph_util_test.py index 0c531fb290b..b8a6d109e19 100644 --- a/tensorflow/contrib/framework/python/framework/graph_util_test.py +++ b/tensorflow/contrib/framework/python/framework/graph_util_test.py @@ -21,6 +21,9 @@ from tensorflow.contrib.framework.python.framework import graph_util from tensorflow.core.framework import graph_pb2 from tensorflow.core.framework import node_def_pb2 from tensorflow.core.framework import types_pb2 +from tensorflow.python.framework import dtypes +from tensorflow.python.framework import ops +from tensorflow.python.ops import array_ops from tensorflow.python.platform import test @@ -81,5 +84,16 @@ class GraphUtilTest(test.TestCase): self.assertEqual(fused_graph_def.node[4].name, 'E') +class GetPlaceholdersTest(test.TestCase): + + def test_get_placeholders(self): + with ops.Graph().as_default() as g: + placeholders = [array_ops.placeholder(dtypes.float32) for _ in range(5)] + results = graph_util.get_placeholders(g) + self.assertEqual( + sorted(placeholders, key=lambda x: x._id), # pylint: disable=protected-access + sorted(results, key=lambda x: x._id)) # pylint: disable=protected-access + + if __name__ == '__main__': test.main() diff --git a/tensorflow/contrib/gan/python/train.py b/tensorflow/contrib/gan/python/train.py index ad2d5eb86cd..e9443f766bd 100644 --- a/tensorflow/contrib/gan/python/train.py +++ b/tensorflow/contrib/gan/python/train.py @@ -422,7 +422,7 @@ def gan_loss( ac_disc_loss = tfgan_losses.acgan_discriminator_loss( model, add_summaries=add_summaries) dis_loss += aux_cond_discriminator_weight * ac_disc_loss - # Gathers auxilliary losses. + # Gathers auxiliary losses. if model.generator_scope: gen_reg_loss = losses.get_regularization_loss(model.generator_scope.name) else: diff --git a/tensorflow/contrib/layers/python/layers/layers.py b/tensorflow/contrib/layers/python/layers/layers.py index f1debc85905..2d42875b468 100644 --- a/tensorflow/contrib/layers/python/layers/layers.py +++ b/tensorflow/contrib/layers/python/layers/layers.py @@ -2561,7 +2561,10 @@ def separable_convolution2d( regularizer=weights_regularizer, trainable=trainable, collections=weights_collections) - strides = [1, stride_h, stride_w, 1] + strides = [1, 1, stride_h, + stride_w] if data_format.startswith('NC') else [ + 1, stride_h, stride_w, 1 + ] outputs = nn.depthwise_conv2d(inputs, depthwise_weights, strides, padding, rate=utils.two_element_tuple(rate), diff --git a/tensorflow/contrib/layers/python/layers/layers_test.py b/tensorflow/contrib/layers/python/layers/layers_test.py index 27bd3172d65..ae64b75d939 100644 --- a/tensorflow/contrib/layers/python/layers/layers_test.py +++ b/tensorflow/contrib/layers/python/layers/layers_test.py @@ -3326,16 +3326,24 @@ class SeparableConv2dTest(test.TestCase): for model_variable in model_variables: self.assertEqual(trainable, model_variable in trainable_variables) - def testConvNCHW(self): - for num_filters, correct_output_filters in [(None, 6), (8, 8)]: + def testSepConvNCHW(self): + for num_filters, correct_output_filters in zip((None, 5), (6, 5)): with self.test_session(): - batch, height, width = 4, 5, 6 + batch, height, width = 4, 10, 12 + kernel_dim, stride = 3, 2 images = random_ops.random_uniform((batch, 3, height, width), seed=1) output = layers_lib.separable_conv2d( - images, num_filters, [3, 3], 2, padding='VALID', data_format='NCHW') - self.assertListEqual( - output.get_shape().as_list(), [batch, correct_output_filters, - height - 2, width - 2]) + images, + num_outputs=num_filters, + kernel_size=[kernel_dim, kernel_dim], + depth_multiplier=2, + stride=stride, + padding='VALID', + data_format='NCHW') + self.assertListEqual(output.get_shape().as_list(), [ + batch, correct_output_filters, (height - kernel_dim + 1) // stride, + (width - kernel_dim + 1) // stride + ]) class ScaleGradientTests(test.TestCase): diff --git a/tensorflow/contrib/lite/BUILD b/tensorflow/contrib/lite/BUILD index 96a9e281ad1..52460123cc1 100644 --- a/tensorflow/contrib/lite/BUILD +++ b/tensorflow/contrib/lite/BUILD @@ -191,6 +191,9 @@ filegroup( exclude = [ "**/METADATA", "**/OWNERS", + "downloads", + "examples", + "gen", ], ), visibility = ["//tensorflow:__subpackages__"], diff --git a/tensorflow/contrib/lite/Makefile b/tensorflow/contrib/lite/Makefile new file mode 100644 index 00000000000..78402727abd --- /dev/null +++ b/tensorflow/contrib/lite/Makefile @@ -0,0 +1,147 @@ + +# Find where we're running from, so we can store generated files here. +ifeq ($(origin MAKEFILE_DIR), undefined) + MAKEFILE_DIR := $(shell dirname $(realpath $(lastword $(MAKEFILE_LIST)))) +endif + +# Try to figure out the host system +HOST_OS := +ifeq ($(OS),Windows_NT) + HOST_OS = WINDOWS +else + UNAME_S := $(shell uname -s) + ifeq ($(UNAME_S),Linux) + HOST_OS := LINUX + endif + ifeq ($(UNAME_S),Darwin) + HOST_OS := OSX + endif +endif + +ARCH := $(shell if [[ $(shell uname -m) =~ i[345678]86 ]]; then echo x86_32; else echo $(shell uname -m); fi) + +# Where compiled objects are stored. +OBJDIR := $(MAKEFILE_DIR)/gen/obj/ +BINDIR := $(MAKEFILE_DIR)/gen/bin/ +LIBDIR := $(MAKEFILE_DIR)/gen/lib/ +GENDIR := $(MAKEFILE_DIR)/gen/obj/ + +# Settings for the host compiler. +CXX := $(CC_PREFIX) gcc +CXXFLAGS := --std=c++11 -O3 -DNDEBUG +CC := $(CC_PREFIX) gcc +CFLAGS := +LDOPTS := +LDOPTS += -L/usr/local/lib +ARFLAGS := -r + +INCLUDES := \ +-I. \ +-I$(MAKEFILE_DIR)/../../../ \ +-I$(MAKEFILE_DIR)/downloads/ \ +-I$(MAKEFILE_DIR)/downloads/eigen \ +-I$(MAKEFILE_DIR)/downloads/gemmlowp \ +-I$(MAKEFILE_DIR)/downloads/neon_2_sse \ +-I$(MAKEFILE_DIR)/downloads/farmhash/src \ +-I$(MAKEFILE_DIR)/downloads/flatbuffers/include \ +-I$(GENDIR) +# This is at the end so any globally-installed frameworks like protobuf don't +# override local versions in the source tree. +INCLUDES += -I/usr/local/include + +LIBS := \ +-lstdc++ \ +-lpthread \ +-lm \ +-lz + +# If we're on Linux, also link in the dl library. +ifeq ($(OS),LINUX) + LIBS += -ldl -lpthread +endif + +include $(MAKEFILE_DIR)/ios_makefile.inc + +# This library is the main target for this makefile. It will contain a minimal +# runtime that can be linked in to other programs. +LIB_NAME := libtensorflow-lite.a +LIB_PATH := $(LIBDIR)$(LIB_NAME) + +# A small example program that shows how to link against the library. +BENCHMARK_PATH := $(BINDIR)benchmark_model + +BENCHMARK_SRCS := \ +tensorflow/contrib/lite/tools/benchmark_model.cc +BENCHMARK_OBJS := $(addprefix $(OBJDIR), \ +$(patsubst %.cc,%.o,$(patsubst %.c,%.o,$(BENCHMARK_SRCS)))) + +# What sources we want to compile, must be kept in sync with the main Bazel +# build files. + +CORE_CC_ALL_SRCS := \ +$(wildcard tensorflow/contrib/lite/*.cc) \ +$(wildcard tensorflow/contrib/lite/kernels/*.cc) \ +$(wildcard tensorflow/contrib/lite/kernels/internal/*.cc) \ +$(wildcard tensorflow/contrib/lite/kernels/internal/optimized/*.cc) \ +$(wildcard tensorflow/contrib/lite/kernels/internal/reference/*.cc) \ +$(wildcard tensorflow/contrib/lite/*.c) \ +$(wildcard tensorflow/contrib/lite/kernels/*.c) \ +$(wildcard tensorflow/contrib/lite/kernels/internal/*.c) \ +$(wildcard tensorflow/contrib/lite/kernels/internal/optimized/*.c) \ +$(wildcard tensorflow/contrib/lite/kernels/internal/reference/*.c) \ +$(wildcard tensorflow/contrib/lite/downloads/farmhash/src/farmhash.cc) +# Remove any duplicates. +CORE_CC_ALL_SRCS := $(sort $(CORE_CC_ALL_SRCS)) +CORE_CC_EXCLUDE_SRCS := \ +$(wildcard tensorflow/contrib/lite/*test.cc) \ +$(wildcard tensorflow/contrib/lite/*/*test.cc) \ +$(wildcard tensorflow/contrib/lite/*/*/*test.cc) \ +$(wildcard tensorflow/contrib/lite/*/*/*/*test.cc) \ +$(wildcard tensorflow/contrib/lite/kernels/test_util.cc) \ +$(BENCHMARK_SRCS) +# Filter out all the excluded files. +TF_LITE_CC_SRCS := $(filter-out $(CORE_CC_EXCLUDE_SRCS), $(CORE_CC_ALL_SRCS)) +# File names of the intermediate files target compilation generates. +TF_LITE_CC_OBJS := $(addprefix $(OBJDIR), \ +$(patsubst %.cc,%.o,$(patsubst %.c,%.o,$(TF_LITE_CC_SRCS)))) +LIB_OBJS := $(TF_LITE_CC_OBJS) + +# For normal manually-created TensorFlow C++ source files. +$(OBJDIR)%.o: %.cc + @mkdir -p $(dir $@) + $(CXX) $(CXXFLAGS) $(INCLUDES) -c $< -o $@ + +# For normal manually-created TensorFlow C++ source files. +$(OBJDIR)%.o: %.c + @mkdir -p $(dir $@) + $(CC) $(CCFLAGS) $(INCLUDES) -c $< -o $@ + +# The target that's compiled if there's no command-line arguments. +all: $(LIB_PATH) $(BENCHMARK_PATH) + +# Gathers together all the objects we've compiled into a single '.a' archive. +$(LIB_PATH): $(LIB_OBJS) + @mkdir -p $(dir $@) + $(AR) $(ARFLAGS) $(LIB_PATH) $(LIB_OBJS) + +$(BENCHMARK_PATH): $(BENCHMARK_OBJS) $(LIB_PATH) + @mkdir -p $(dir $@) + $(CXX) $(CXXFLAGS) $(INCLUDES) \ + -o $(BENCHMARK_PATH) $(BENCHMARK_OBJS) \ + $(LIBFLAGS) $(LIB_PATH) $(LDFLAGS) $(LIBS) + +# Gets rid of all generated files. +clean: + rm -rf $(MAKEFILE_DIR)/gen + +# Gets rid of target files only, leaving the host alone. Also leaves the lib +# directory untouched deliberately, so we can persist multiple architectures +# across builds for iOS and Android. +cleantarget: + rm -rf $(OBJDIR) + rm -rf $(BINDIR) + +$(DEPDIR)/%.d: ; +.PRECIOUS: $(DEPDIR)/%.d + +-include $(patsubst %,$(DEPDIR)/%.d,$(basename $(TF_CC_SRCS))) diff --git a/tensorflow/contrib/lite/README.md b/tensorflow/contrib/lite/README.md index 385ccf4680e..c7464bcc9d3 100644 --- a/tensorflow/contrib/lite/README.md +++ b/tensorflow/contrib/lite/README.md @@ -1,5 +1,5 @@ # TensorFlow Lite -TensorFlow Lite is TensorFlow’s lightweight solution for mobile and embedded devices. It enables low-latency inference of on-device machine learning models with a small binary size and fast performance supporting hardware acceleration. +TensorFlow Lite is TensorFlow's lightweight solution for mobile and embedded devices. It enables low-latency inference of on-device machine learning models with a small binary size and fast performance supporting hardware acceleration. TensorFlow Lite uses many techniques for achieving low latency like optimizing the kernels for specific mobile apps, pre-fused activations, quantized kernels that allow smaller and faster (fixed-point math) models, and in the future, leverage specialized machine learning hardware to get the best possible performance for a particular model on a particular device. @@ -20,18 +20,18 @@ In the demo app, inference is done using the TensorFlow Lite Java API. The demo The fastest path to trying the demo, is to download the pre-built binary [TfLiteCameraDemo.apk](https://storage.googleapis.com/download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk) -Once the apk is installed, click the app icon to start the app. The first-time the app is opened, the app asks for runtime permissions to access the device camera. The demo app opens the back-camera of the device and recognizes the objects in the camera’s field of view. At the bottom of the image (or at the left of the image if the device is in landscape mode), it shows the latency of classification and the top three objects classified. +Once the apk is installed, click the app icon to start the app. The first-time the app is opened, the app asks for runtime permissions to access the device camera. The demo app opens the back-camera of the device and recognizes the objects in the camera's field of view. At the bottom of the image (or at the left of the image if the device is in landscape mode), it shows the latency of classification and the top three objects classified. ## Building in Android Studio using TensorFlow Lite AAR from JCenter The simplest way to compile the demo app, and try out changes to the project code is to use AndroidStudio. - Install the latest version of Android Studio 3 as specified [here](https://developer.android.com/studio/index.html). - Make sure the Android SDK version is greater than 26 and NDK version is greater than 14 (in the Android Studio Settings). - - Import the tensorflow/contrib/lite/java/demo directory as a new Android Studio project. + - Import the `tensorflow/contrib/lite/java/demo` directory as a new Android Studio project. - Click through installing all the Gradle extensions it requests. - Download the quantized Mobilenet TensorFlow Lite model from [here](https://storage.googleapis.com/download.tensorflow.org/models/tflite/mobilenet_v1_224_android_quant_2017_11_08.zip) - unzip and copy mobilenet_quant_v1_224.tflite to the assets directory: - tensorflow/contrib/lite/java/demo/app/src/main/assets/ + `tensorflow/contrib/lite/java/demo/app/src/main/assets/` - Build and run the demo app ## Building TensorFlow Lite and the demo app from source @@ -43,39 +43,45 @@ The simplest way to compile the demo app, and try out changes to the project cod ### Install Bazel If bazel is not installed on your system, install it now by following [these directions](https://bazel.build/versions/master/docs/install.html) -NOTE: Bazel does not currently support building for Android on Windows. Full support for gradle/cmake builds is coming soon, but in the meantime Windows users should download the [prebuilt binary](https://storage.googleapis.com/download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk) instead. +NOTE: Bazel does not fully support building Android on Windows yet. Full support for Gradle/CMake builds is coming soon, but in the meantime Windows users should download the [prebuilt binary](https://storage.googleapis.com/download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk) instead. ### Install Android NDK and SDK Bazel is the primary build system for TensorFlow. Bazel and the Android NDK and SDK must be installed on your system. - Install the latest version of Bazel as per the instructions on the [Bazel website](https://bazel.build/versions/master/docs/install.html) - - The Android NDK is required to build the native (C/C++) TensorFlow code. The current recommended version is 14b, which may be found [here](https://developer.android.com/tools/revisions/build-tools.html). - - The Android SDK and build tools may be obtained [here](https://developer.android.com/tools/revisions/build-tools.html), or alternatively as part of [Android Studio](https://developer.android.com/studio/index.html). Build tools API >= 23 is required to build the TensorFlow Android demo (though it will run on API >= 21 devices). - - The Android NDK is required to build the native (C/C++) TensorFlow Lite code. The current recommended version is 14b, which can be found [here](https://developer.android.com/ndk/downloads/older_releases.html#ndk-14b-downloads). - - The Android SDK and build tools may be obtained [here](https://developer.android.com/tools/revisions/build-tools.html), or alternatively as part of [Android Studio](https://developer.android.com/studio/index.html). Build tools API >= 23 is required to build the TF Android demo (though it will run on API >= 21 devices). - In the root of the TensorFlow repository update the `WORKSPACE` file with the `api_level` and location of the SDK and NDK. If you installed it with AndroidStudio the SDK path can be found in the SDK manager, and the default NDK path is:`{SDK path}/ndk-bundle.` ``` - Android_sdk_repository ( - name = "androidsdk", - api_level = 23, - build_tools_version = "23.0.2", - path = "/home/xxxx/android-sdk-linux/", ) +android_sdk_repository ( + name = "androidsdk", + api_level = 23, + build_tools_version = "23.0.2", + path = "/home/xxxx/android-sdk-linux/", +) android_ndk_repository( - name="androidndk", - path="/home/xxxx/android-ndk-r10e/", - api_level=19) - + name = "androidndk", + path = "/home/xxxx/android-ndk-r10e/", + api_level = 19, +) ``` -Additional details on building with Android can be found [here](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/java/demo/README.md) + +Additional details on building with Android can be found [here](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/java/demo/README.md). ### Build the source code Run bazel with the following command to build the demo. Build the demo app: -bazel build --cxxopt='--std=c++11' //tensorflow/contrib/lite/java/demo/app/src/main:TfLiteCameraDemo + +``` +bazel build --cxxopt=--std=c++11 //tensorflow/contrib/lite/java/demo/app/src/main:TfLiteCameraDemo +``` + +### Note + +Currently, we only support building the Android demo app within a Python 2 +environment (due to a Bazel bug). ### More about the demo The demo is resizing each camera image frame to (224 width * 224 height) to match the quantized Mobilenet model being used. The resized image is converted into a ByteBuffer row by row of size 1 * 224 * 224 * 3 bytes, where 1 is the number of images in a batch 224 * 224 is the width and height of the image 3 bytes represents three colors of a pixel. This demo uses the TensorFlow Lite Java inference API for models which take a single input and provide a single output. This outputs a two-dimensional array, with the first dimension being the category index and the second dimension being the confidence of classification. The Mobilenet model has 1001 unique categories and the app sorts the probabilities of all the categories and displays the top three. The Mobilenet quantized model is bundled within the assets directory of the app. @@ -95,7 +101,7 @@ The demo is resizing each camera image frame to (224 width * 224 height) to matc [On Device Smart Reply](https://research.googleblog.com/2017/02/on-device-machine-intelligence.html) is an on-device model which provides one-touch replies for an incoming text message by suggesting contextually relevant messages. The model is built specifically for memory constrained devices such as watches & phones and it has been successfully used to surface [Smart Replies on Android Wear](https://research.googleblog.com/2017/02/on-device-machine-intelligence.html). Note that this model only works on Android as of now. -These pre-trained models can be downloaded from [here](models.md). +These pre-trained models can be downloaded from [here](g3doc/models.md). ### Retrain Inception-V3 or MobileNet for a custom data set The above pre-trained models have been trained on the ImageNet data set, which consists of 1000 predefined classes. A model will need to be re-trained if these classes are not relevant or useful for a given use case. This technique is called transfer learning, which starts with a model that has been already trained on a problem and will then be retrained on a similar problem. Deep learning from scratch can take days, but transfer learning can be done fairly quickly. In order to do this, a developer will need to generate their custom data set labeled with the relevant classes. @@ -104,7 +110,7 @@ The [TensorFlow for Poets](https://codelabs.developers.google.com/codelabs/tenso ### Train a custom model -A developer may choose to train a custom model using Tensorflow. TensorFlow documentation has [several tutorials](https://www.tensorflow.org/tutorials/) for building and training models. If the user has written a model using TensorFlow’s Slim Framework the first step is to export this to a GraphDef file. This is necessary because Slim does not store the model structure outside the code, so to communicate with other parts of the framework it needs to be exported. Documentation for the export can be found [here](https://github.com/tensorflow/models/tree/master/research/slim#Export). The output of this step will be a .pb file for the custom model. +A developer may choose to train a custom model using Tensorflow. TensorFlow documentation has [several tutorials](https://www.tensorflow.org/tutorials/) for building and training models. If the user has written a model using TensorFlow's Slim Framework the first step is to export this to a GraphDef file. This is necessary because Slim does not store the model structure outside the code, so to communicate with other parts of the framework it needs to be exported. Documentation for the export can be found [here](https://github.com/tensorflow/models/tree/master/research/slim#Export). The output of this step will be a .pb file for the custom model. TensorFlow Lite currently supports a subset of TensorFlow operators. Please refer to [this document](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/g3doc/tf_ops_compatibility.md) for details of supported operators and their usage. This set will continue to expand in future releases of Tensorflow Lite. @@ -128,9 +134,9 @@ Since we employ several formats, the following definitions may be useful: - TensorFlow lite model (.lite) - a serialized flatbuffer, containing TensorFlow lite operators and Tensors for the TensorFlow lite interpreter. This is most analogous to TensorFlow frozen GraphDefs. ### Freeze Graph -To use this .pb GraphDef file within TensorFlow Lite, the application developer will need checkpoints containing trained weight parameters. The .pb contains only the structure of the graph. The process of merging the checkpoint values with the graph structure is known as “freezing” the graph. +To use this .pb GraphDef file within TensorFlow Lite, the application developer will need checkpoints containing trained weight parameters. The .pb contains only the structure of the graph. The process of merging the checkpoint values with the graph structure is known as "freezing" the graph. -The developer should know where the checkpoints folder is present or checkpoints can also be downloaded for a pre-trained model (Example: Here is a link to the [MobileNets](https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md) +The developer should know where the checkpoints folder is present or checkpoints can also be downloaded for a pre-trained model (Example: Here is a link to the [MobileNets](https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md)). Graph freezing can be done using the command below (and modifying the arguments appropriately) @@ -155,7 +161,7 @@ Here is a sample command line to convert the frozen Graphdef to '.lite' format f bazel build tensorflow/contrib/lite/toco:toco bazel-bin/tensorflow/contrib/lite/toco/toco -- \ - --input_file=(pwd)/mobilenet_v1_1.0_224/frozen_graph.pb \ + --input_file=$(pwd)/mobilenet_v1_1.0_224/frozen_graph.pb \ --input_format=TENSORFLOW_GRAPHDEF --output_format=TFLITE \ --output_file=/tmp/mobilenet_v1_1.0_224.lite --inference_type=FLOAT \ --input_type=FLOAT --input_arrays=input \ @@ -183,18 +189,18 @@ with tf.Session() as sess: ``` For detailed instructions on how to use the Tensorflow Optimizing Converter, please see [here](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/toco/g3doc/cmdline_examples.md). -You may refer to the [Ops compatibility guide](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/tf_ops_compatibility.md) for troubleshooting help. If that doesn’t help, please file an [issue](https://github.com/tensorflow/tensorflow/issues). +You may refer to the [Ops compatibility guide](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/g3doc/tf_ops_compatibility.md) for troubleshooting help. If that doesn't help, please file an [issue](https://github.com/tensorflow/tensorflow/issues). ## Step 3. Use the TensorFlow Lite model for inference in a mobile app After completion of Step 2 the developer should have a .lite model. ### For Android -Because Android apps need to be written in Java, and core TensorFlow is in C++, a JNI library is provided to interface between the two. Its interface is aimed only at inference, so it provides the ability to load a graph, set up inputs, and run the model to calculate particular outputs. The full documentation for the set of methods can be seen [here](https://github.com/TensorFlow/TensorFlow/blob/master/TensorFlow/contrib/lite/g3doc/). The demo app is also open sourced on [github](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/java/demo/app). +Because Android apps need to be written in Java, and core TensorFlow is in C++, a JNI library is provided to interface between the two. Its interface is aimed only at inference, so it provides the ability to load a graph, set up inputs, and run the model to calculate particular outputs. The full documentation for the set of methods can be seen [here](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/lite/g3doc/). The demo app is also open sourced on [github](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/java/demo/app). -The [demo app] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/java/demo/app) uses this interface, so it’s a good place to look for example usage. You can also download the prebuilt binary [here](http://download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk). +The [demo app](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/java/demo/app) uses this interface, so it's a good place to look for example usage. You can also download the prebuilt binary [here](http://download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk). -Note that you’d need to follow instructions for installing TensorFlow on Android, setting up bazel and Android Studio outlined [here](https://www.tensorflow.org/mobile/android_build). +Note that you'd need to follow instructions for installing TensorFlow on Android, setting up bazel and Android Studio outlined [here](https://www.tensorflow.org/mobile/android_build). ### For iOS -Follow the documentation [here](https://github.com/TensorFlow/TensorFlow/blob/master/TensorFlow/contrib/lite/g3doc/ios.md) to get integrate a TFLite model into your app. +Follow the documentation [here](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/g3doc/ios.md) to get integrate a TFLite model into your app. diff --git a/tensorflow/contrib/lite/build_ios_universal_lib.sh b/tensorflow/contrib/lite/build_ios_universal_lib.sh new file mode 100755 index 00000000000..cbc96e6edd4 --- /dev/null +++ b/tensorflow/contrib/lite/build_ios_universal_lib.sh @@ -0,0 +1,31 @@ +#!/bin/bash -x +# 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. +# ============================================================================== + +set -e +make -f tensorflow/contrib/lite/Makefile TARGET=IOS IOS_ARCH=x86_64 -j 8 +make -f tensorflow/contrib/lite/Makefile TARGET=IOS IOS_ARCH=i386 -j 8 +make -f tensorflow/contrib/lite/Makefile TARGET=IOS IOS_ARCH=armv7 -j 8 +make -f tensorflow/contrib/lite/Makefile TARGET=IOS IOS_ARCH=armv7s -j 8 +make -f tensorflow/contrib/lite/Makefile TARGET=IOS IOS_ARCH=arm64 -j 8 + +lipo \ +tensorflow/contrib/lite/gen/lib/ios_x86_64/libtensorflow-lite.a \ +tensorflow/contrib/lite/gen/lib/ios_i386/libtensorflow-lite.a \ +tensorflow/contrib/lite/gen/lib/ios_armv7/libtensorflow-lite.a \ +tensorflow/contrib/lite/gen/lib/ios_armv7s/libtensorflow-lite.a \ +tensorflow/contrib/lite/gen/lib/ios_arm64/libtensorflow-lite.a \ +-create \ +-output tensorflow/contrib/lite/gen/lib/libtensorflow-lite.a diff --git a/tensorflow/contrib/lite/download_dependencies.sh b/tensorflow/contrib/lite/download_dependencies.sh new file mode 100755 index 00000000000..778d618361e --- /dev/null +++ b/tensorflow/contrib/lite/download_dependencies.sh @@ -0,0 +1,99 @@ +#!/bin/bash +# 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. +# ============================================================================== + +set -e + +DOWNLOADS_DIR=tensorflow/contrib/lite/downloads +BZL_FILE_PATH=tensorflow/workspace.bzl + +EIGEN_URL="$(grep -o 'http.*bitbucket.org/eigen/eigen/get/.*tar\.gz' "${BZL_FILE_PATH}" | grep -v bazel-mirror | head -n1)" +GEMMLOWP_URL="$(grep -o 'https://mirror.bazel.build/github.com/google/gemmlowp/.*zip' "${BZL_FILE_PATH}" | head -n1)" +GOOGLETEST_URL="https://github.com/google/googletest/archive/release-1.8.0.tar.gz" +ABSL_URL="$(grep -o 'https://github.com/abseil/abseil-cpp/.*tar.gz' "${BZL_FILE_PATH}" | head -n1)" +NEON_2_SSE_URL="https://github.com/intel/ARM_NEON_2_x86_SSE/archive/master.zip" +FARMHASH_URL="https://mirror.bazel.build/github.com/google/farmhash/archive/816a4ae622e964763ca0862d9dbd19324a1eaf45.tar.gz" +FLATBUFFERS_URL="https://github.com/google/flatbuffers/archive/master.zip" +MODELS_URL="https://storage.googleapis.com/download.tensorflow.org/models/tflite/mobilenet_v1_1.0_224_ios_lite_float_2017_11_08.zip" +QUANTIZED_MODELS_URL="https://storage.googleapis.com/download.tensorflow.org/models/tflite/mobilenet_v1_224_android_quant_2017_11_08.zip" + +# TODO(petewarden): Some new code in Eigen triggers a clang bug with iOS arm64, +# so work around it by patching the source. +replace_by_sed() { + local regex="${1}" + shift + # Detect the version of sed by the return value of "--version" flag. GNU-sed + # supports "--version" while BSD-sed doesn't. + if ! sed --version >/dev/null 2>&1; then + # BSD-sed. + sed -i '' -e "${regex}" "$@" + else + # GNU-sed. + sed -i -e "${regex}" "$@" + fi +} + +download_and_extract() { + local usage="Usage: download_and_extract URL DIR" + local url="${1:?${usage}}" + local dir="${2:?${usage}}" + echo "downloading ${url}" >&2 + mkdir -p "${dir}" + if [[ "${url}" == *gz ]]; then + curl -Ls "${url}" | tar -C "${dir}" --strip-components=1 -xz + elif [[ "${url}" == *zip ]]; then + tempdir=$(mktemp -d) + tempdir2=$(mktemp -d) + + curl -L ${url} > ${tempdir}/zipped.zip + unzip ${tempdir}/zipped.zip -d ${tempdir2} + + # If the zip file contains nested directories, extract the files from the + # inner directory. + if ls ${tempdir2}/*/* 1> /dev/null 2>&1; then + # unzip has no strip components, so unzip to a temp dir, and move the + # files we want from the tempdir to destination. + cp -R ${tempdir2}/*/* ${dir}/ + else + cp -R ${tempdir2}/* ${dir}/ + fi + rm -rf ${tempdir2} ${tempdir} + fi + + # Delete any potential BUILD files, which would interfere with Bazel builds. + find "${dir}" -type f -name '*BUILD' -delete +} + +download_and_extract "${EIGEN_URL}" "${DOWNLOADS_DIR}/eigen" +download_and_extract "${GEMMLOWP_URL}" "${DOWNLOADS_DIR}/gemmlowp" +download_and_extract "${GOOGLETEST_URL}" "${DOWNLOADS_DIR}/googletest" +download_and_extract "${ABSL_URL}" "${DOWNLOADS_DIR}/absl" +download_and_extract "${NEON_2_SSE_URL}" "${DOWNLOADS_DIR}/neon_2_sse" +download_and_extract "${FARMHASH_URL}" "${DOWNLOADS_DIR}/farmhash" +download_and_extract "${FLATBUFFERS_URL}" "${DOWNLOADS_DIR}/flatbuffers" +download_and_extract "${MODELS_URL}" "${DOWNLOADS_DIR}/models" +download_and_extract "${QUANTIZED_MODELS_URL}" "${DOWNLOADS_DIR}/quantized_models" + +replace_by_sed 's#static uint32x4_t p4ui_CONJ_XOR = vld1q_u32( conj_XOR_DATA );#static uint32x4_t p4ui_CONJ_XOR; // = vld1q_u32( conj_XOR_DATA ); - Removed by script#' \ + "${DOWNLOADS_DIR}/eigen/Eigen/src/Core/arch/NEON/Complex.h" +replace_by_sed 's#static uint32x2_t p2ui_CONJ_XOR = vld1_u32( conj_XOR_DATA );#static uint32x2_t p2ui_CONJ_XOR;// = vld1_u32( conj_XOR_DATA ); - Removed by scripts#' \ + "${DOWNLOADS_DIR}/eigen/Eigen/src/Core/arch/NEON/Complex.h" +replace_by_sed 's#static uint64x2_t p2ul_CONJ_XOR = vld1q_u64( p2ul_conj_XOR_DATA );#static uint64x2_t p2ul_CONJ_XOR;// = vld1q_u64( p2ul_conj_XOR_DATA ); - Removed by script#' \ + "${DOWNLOADS_DIR}/eigen/Eigen/src/Core/arch/NEON/Complex.h" + +cp ${DOWNLOADS_DIR}/models/models/* tensorflow/contrib/lite/examples/ios/simple/data/ +cp ${DOWNLOADS_DIR}/quantized_models/* tensorflow/contrib/lite/examples/ios/camera/data/ + +echo "download_dependencies.sh completed successfully." >&2 diff --git a/tensorflow/contrib/lite/examples/ios/camera/.gitignore b/tensorflow/contrib/lite/examples/ios/camera/.gitignore new file mode 100644 index 00000000000..9e8962f4c63 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/camera/.gitignore @@ -0,0 +1,2 @@ +/data/*.txt +/data/*.tflite diff --git a/tensorflow/contrib/lite/examples/ios/camera/CameraExampleAppDelegate.h b/tensorflow/contrib/lite/examples/ios/camera/CameraExampleAppDelegate.h new file mode 100644 index 00000000000..55891c3ee18 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/camera/CameraExampleAppDelegate.h @@ -0,0 +1,21 @@ +// 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. + +#import + +@interface CameraExampleAppDelegate : UIResponder + +@property(strong, nonatomic) UIWindow* window; + +@end diff --git a/tensorflow/contrib/lite/examples/ios/camera/CameraExampleAppDelegate.m b/tensorflow/contrib/lite/examples/ios/camera/CameraExampleAppDelegate.m new file mode 100644 index 00000000000..128266d53f5 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/camera/CameraExampleAppDelegate.m @@ -0,0 +1,44 @@ +// 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. + +#import "CameraExampleAppDelegate.h" + +@implementation CameraExampleAppDelegate + +@synthesize window = _window; + +- (BOOL)application:(UIApplication *)application + didFinishLaunchingWithOptions:(NSDictionary *)launchOptions { + [self.window makeKeyAndVisible]; + return YES; +} + +- (void)applicationWillResignActive:(UIApplication *)application { + [[UIApplication sharedApplication] setIdleTimerDisabled:NO]; +} + +- (void)applicationDidEnterBackground:(UIApplication *)application { +} + +- (void)applicationWillEnterForeground:(UIApplication *)application { +} + +- (void)applicationDidBecomeActive:(UIApplication *)application { + [[UIApplication sharedApplication] setIdleTimerDisabled:YES]; +} + +- (void)applicationWillTerminate:(UIApplication *)application { +} + +@end diff --git a/tensorflow/contrib/lite/examples/ios/camera/CameraExampleViewController.h b/tensorflow/contrib/lite/examples/ios/camera/CameraExampleViewController.h new file mode 100644 index 00000000000..fb5800e86d3 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/camera/CameraExampleViewController.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. + +#import +#import + +#include + +#include "tensorflow/contrib/lite/kernels/register.h" +#include "tensorflow/contrib/lite/model.h" + +@interface CameraExampleViewController + : UIViewController { + IBOutlet UIView* previewView; + AVCaptureVideoPreviewLayer* previewLayer; + AVCaptureVideoDataOutput* videoDataOutput; + dispatch_queue_t videoDataOutputQueue; + UIView* flashView; + BOOL isUsingFrontFacingCamera; + NSMutableDictionary* oldPredictionValues; + NSMutableArray* labelLayers; + AVCaptureSession* session; + + std::vector labels; + std::unique_ptr model; + tflite::ops::builtin::BuiltinOpResolver resolver; + std::unique_ptr interpreter; + + double total_latency; + int total_count; +} +@property(strong, nonatomic) CATextLayer* predictionTextLayer; + +- (IBAction)takePicture:(id)sender; +- (IBAction)switchCameras:(id)sender; + +@end diff --git a/tensorflow/contrib/lite/examples/ios/camera/CameraExampleViewController.mm b/tensorflow/contrib/lite/examples/ios/camera/CameraExampleViewController.mm new file mode 100644 index 00000000000..ea398ad14e8 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/camera/CameraExampleViewController.mm @@ -0,0 +1,506 @@ +// 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. + +#import "CameraExampleViewController.h" +#import +#import +#import +#import + +#include +#include +#include +#include + +#include "tensorflow/contrib/lite/kernels/register.h" +#include "tensorflow/contrib/lite/model.h" +#include "tensorflow/contrib/lite/string_util.h" +#include "tensorflow/contrib/lite/tools/mutable_op_resolver.h" + +#define LOG(x) std::cerr + +// If you have your own model, modify this to the file name, and make sure +// you've added the file to your app resources too. +static NSString* model_file_name = @"mobilenet_quant_v1_224"; +static NSString* model_file_type = @"tflite"; + +// If you have your own model, point this to the labels file. +static NSString* labels_file_name = @"labels"; +static NSString* labels_file_type = @"txt"; + +// These dimensions need to match those the model was trained with. +static const int wanted_input_width = 224; +static const int wanted_input_height = 224; +static const int wanted_input_channels = 3; + +static NSString* FilePathForResourceName(NSString* name, NSString* extension) { + NSString* file_path = [[NSBundle mainBundle] pathForResource:name ofType:extension]; + if (file_path == NULL) { + LOG(FATAL) << "Couldn't find '" << [name UTF8String] << "." << [extension UTF8String] + << "' in bundle."; + } + return file_path; +} + +static void LoadLabels(NSString* file_name, NSString* file_type, + std::vector* label_strings) { + NSString* labels_path = FilePathForResourceName(file_name, file_type); + if (!labels_path) { + LOG(ERROR) << "Failed to find model proto at" << [file_name UTF8String] + << [file_type UTF8String]; + } + std::ifstream t; + t.open([labels_path UTF8String]); + std::string line; + while (t) { + std::getline(t, line); + label_strings->push_back(line); + } + t.close(); +} + +// Returns the top N confidence values over threshold in the provided vector, +// sorted by confidence in descending order. +static void GetTopN(const uint8_t* prediction, const int prediction_size, const int num_results, + const float threshold, std::vector>* top_results) { + // Will contain top N results in ascending order. + std::priority_queue, std::vector>, + std::greater>> + top_result_pq; + + const long count = prediction_size; + for (int i = 0; i < count; ++i) { + const float value = prediction[i] / 255.0; + // Only add it if it beats the threshold and has a chance at being in + // the top N. + if (value < threshold) { + continue; + } + + top_result_pq.push(std::pair(value, i)); + + // If at capacity, kick the smallest value out. + if (top_result_pq.size() > num_results) { + top_result_pq.pop(); + } + } + + // Copy to output vector and reverse into descending order. + while (!top_result_pq.empty()) { + top_results->push_back(top_result_pq.top()); + top_result_pq.pop(); + } + std::reverse(top_results->begin(), top_results->end()); +} + +@interface CameraExampleViewController (InternalMethods) +- (void)setupAVCapture; +- (void)teardownAVCapture; +@end + +@implementation CameraExampleViewController + +- (void)setupAVCapture { + NSError* error = nil; + + session = [AVCaptureSession new]; + if ([[UIDevice currentDevice] userInterfaceIdiom] == UIUserInterfaceIdiomPhone) + [session setSessionPreset:AVCaptureSessionPreset640x480]; + else + [session setSessionPreset:AVCaptureSessionPresetPhoto]; + + AVCaptureDevice* device = [AVCaptureDevice defaultDeviceWithMediaType:AVMediaTypeVideo]; + AVCaptureDeviceInput* deviceInput = + [AVCaptureDeviceInput deviceInputWithDevice:device error:&error]; + assert(error == nil); + + if ([session canAddInput:deviceInput]) [session addInput:deviceInput]; + + videoDataOutput = [AVCaptureVideoDataOutput new]; + + NSDictionary* rgbOutputSettings = + [NSDictionary dictionaryWithObject:[NSNumber numberWithInt:kCMPixelFormat_32BGRA] + forKey:(id)kCVPixelBufferPixelFormatTypeKey]; + [videoDataOutput setVideoSettings:rgbOutputSettings]; + [videoDataOutput setAlwaysDiscardsLateVideoFrames:YES]; + videoDataOutputQueue = dispatch_queue_create("VideoDataOutputQueue", DISPATCH_QUEUE_SERIAL); + [videoDataOutput setSampleBufferDelegate:self queue:videoDataOutputQueue]; + + if ([session canAddOutput:videoDataOutput]) [session addOutput:videoDataOutput]; + [[videoDataOutput connectionWithMediaType:AVMediaTypeVideo] setEnabled:YES]; + + previewLayer = [[AVCaptureVideoPreviewLayer alloc] initWithSession:session]; + [previewLayer setBackgroundColor:[[UIColor blackColor] CGColor]]; + [previewLayer setVideoGravity:AVLayerVideoGravityResizeAspect]; + CALayer* rootLayer = [previewView layer]; + [rootLayer setMasksToBounds:YES]; + [previewLayer setFrame:[rootLayer bounds]]; + [rootLayer addSublayer:previewLayer]; + [session startRunning]; + + if (error) { + NSString* title = [NSString stringWithFormat:@"Failed with error %d", (int)[error code]]; + UIAlertController* alertController = + [UIAlertController alertControllerWithTitle:title + message:[error localizedDescription] + preferredStyle:UIAlertControllerStyleAlert]; + UIAlertAction* dismiss = + [UIAlertAction actionWithTitle:@"Dismiss" style:UIAlertActionStyleDefault handler:nil]; + [alertController addAction:dismiss]; + [self presentViewController:alertController animated:YES completion:nil]; + [self teardownAVCapture]; + } +} + +- (void)teardownAVCapture { + [previewLayer removeFromSuperlayer]; +} + +- (AVCaptureVideoOrientation)avOrientationForDeviceOrientation: + (UIDeviceOrientation)deviceOrientation { + AVCaptureVideoOrientation result = (AVCaptureVideoOrientation)(deviceOrientation); + if (deviceOrientation == UIDeviceOrientationLandscapeLeft) + result = AVCaptureVideoOrientationLandscapeRight; + else if (deviceOrientation == UIDeviceOrientationLandscapeRight) + result = AVCaptureVideoOrientationLandscapeLeft; + return result; +} + +- (IBAction)takePicture:(id)sender { + if ([session isRunning]) { + [session stopRunning]; + [sender setTitle:@"Continue" forState:UIControlStateNormal]; + + flashView = [[UIView alloc] initWithFrame:[previewView frame]]; + [flashView setBackgroundColor:[UIColor whiteColor]]; + [flashView setAlpha:0.f]; + [[[self view] window] addSubview:flashView]; + + [UIView animateWithDuration:.2f + animations:^{ + [flashView setAlpha:1.f]; + } + completion:^(BOOL finished) { + [UIView animateWithDuration:.2f + animations:^{ + [flashView setAlpha:0.f]; + } + completion:^(BOOL finished) { + [flashView removeFromSuperview]; + flashView = nil; + }]; + }]; + + } else { + [session startRunning]; + [sender setTitle:@"Freeze Frame" forState:UIControlStateNormal]; + } +} + +- (void)captureOutput:(AVCaptureOutput*)captureOutput + didOutputSampleBuffer:(CMSampleBufferRef)sampleBuffer + fromConnection:(AVCaptureConnection*)connection { + CVPixelBufferRef pixelBuffer = CMSampleBufferGetImageBuffer(sampleBuffer); + CFRetain(pixelBuffer); + [self runModelOnFrame:pixelBuffer]; + CFRelease(pixelBuffer); +} + +- (void)runModelOnFrame:(CVPixelBufferRef)pixelBuffer { + assert(pixelBuffer != NULL); + + OSType sourcePixelFormat = CVPixelBufferGetPixelFormatType(pixelBuffer); + int doReverseChannels; + if (kCVPixelFormatType_32ARGB == sourcePixelFormat) { + doReverseChannels = 1; + } else if (kCVPixelFormatType_32BGRA == sourcePixelFormat) { + doReverseChannels = 0; + } else { + assert(false); // Unknown source format + } + + const int sourceRowBytes = (int)CVPixelBufferGetBytesPerRow(pixelBuffer); + const int image_width = (int)CVPixelBufferGetWidth(pixelBuffer); + const int fullHeight = (int)CVPixelBufferGetHeight(pixelBuffer); + + CVPixelBufferLockFlags unlockFlags = kNilOptions; + CVPixelBufferLockBaseAddress(pixelBuffer, unlockFlags); + + unsigned char* sourceBaseAddr = (unsigned char*)(CVPixelBufferGetBaseAddress(pixelBuffer)); + int image_height; + unsigned char* sourceStartAddr; + if (fullHeight <= image_width) { + image_height = fullHeight; + sourceStartAddr = sourceBaseAddr; + } else { + image_height = image_width; + const int marginY = ((fullHeight - image_width) / 2); + sourceStartAddr = (sourceBaseAddr + (marginY * sourceRowBytes)); + } + const int image_channels = 4; + assert(image_channels >= wanted_input_channels); + uint8_t* in = sourceStartAddr; + + int input = interpreter->inputs()[0]; + + uint8_t* out = interpreter->typed_tensor(input); + for (int y = 0; y < wanted_input_height; ++y) { + uint8_t* out_row = out + (y * wanted_input_width * wanted_input_channels); + for (int x = 0; x < wanted_input_width; ++x) { + const int in_x = (y * image_width) / wanted_input_width; + const int in_y = (x * image_height) / wanted_input_height; + uint8_t* in_pixel = in + (in_y * image_width * image_channels) + (in_x * image_channels); + uint8_t* out_pixel = out_row + (x * wanted_input_channels); + for (int c = 0; c < wanted_input_channels; ++c) { + out_pixel[c] = in_pixel[c]; + } + } + } + + double startTimestamp = [[NSDate new] timeIntervalSince1970]; + if (interpreter->Invoke() != kTfLiteOk) { + LOG(FATAL) << "Failed to invoke!"; + } + double endTimestamp = [[NSDate new] timeIntervalSince1970]; + total_latency += (endTimestamp - startTimestamp); + total_count += 1; + NSLog(@"Time: %.4lf, avg: %.4lf, count: %d", endTimestamp - startTimestamp, + total_latency / total_count, total_count); + + const int output_size = 1000; + const int kNumResults = 5; + const float kThreshold = 0.1f; + + std::vector> top_results; + + uint8_t* output = interpreter->typed_output_tensor(0); + GetTopN(output, output_size, kNumResults, kThreshold, &top_results); + + NSMutableDictionary* newValues = [NSMutableDictionary dictionary]; + for (const auto& result : top_results) { + const float confidence = result.first; + const int index = result.second; + NSString* labelObject = [NSString stringWithUTF8String:labels[index].c_str()]; + NSNumber* valueObject = [NSNumber numberWithFloat:confidence]; + [newValues setObject:valueObject forKey:labelObject]; + } + dispatch_async(dispatch_get_main_queue(), ^(void) { + [self setPredictionValues:newValues]; + }); + + CVPixelBufferUnlockBaseAddress(pixelBuffer, unlockFlags); + + CVPixelBufferUnlockBaseAddress(pixelBuffer, 0); +} + +- (void)dealloc { + [self teardownAVCapture]; +} + +- (void)didReceiveMemoryWarning { + [super didReceiveMemoryWarning]; +} + +- (void)viewDidLoad { + [super viewDidLoad]; + labelLayers = [[NSMutableArray alloc] init]; + oldPredictionValues = [[NSMutableDictionary alloc] init]; + + NSString* graph_path = FilePathForResourceName(model_file_name, @"tflite"); + model = tflite::FlatBufferModel::BuildFromFile([graph_path UTF8String]); + if (!model) { + LOG(FATAL) << "Failed to mmap model " << graph_path; + } + LOG(INFO) << "Loaded model " << graph_path; + model->error_reporter(); + LOG(INFO) << "resolved reporter"; + + tflite::ops::builtin::BuiltinOpResolver resolver; + LoadLabels(labels_file_name, labels_file_type, &labels); + + tflite::InterpreterBuilder(*model, resolver)(&interpreter); + if (!interpreter) { + LOG(FATAL) << "Failed to construct interpreter"; + } + if (interpreter->AllocateTensors() != kTfLiteOk) { + LOG(FATAL) << "Failed to allocate tensors!"; + } + + [self setupAVCapture]; +} + +- (void)viewDidUnload { + [super viewDidUnload]; +} + +- (void)viewWillAppear:(BOOL)animated { + [super viewWillAppear:animated]; +} + +- (void)viewDidAppear:(BOOL)animated { + [super viewDidAppear:animated]; +} + +- (void)viewWillDisappear:(BOOL)animated { + [super viewWillDisappear:animated]; +} + +- (void)viewDidDisappear:(BOOL)animated { + [super viewDidDisappear:animated]; +} + +- (BOOL)shouldAutorotateToInterfaceOrientation:(UIInterfaceOrientation)interfaceOrientation { + return (interfaceOrientation == UIInterfaceOrientationPortrait); +} + +- (BOOL)prefersStatusBarHidden { + return YES; +} + +- (void)setPredictionValues:(NSDictionary*)newValues { + const float decayValue = 0.75f; + const float updateValue = 0.25f; + const float minimumThreshold = 0.01f; + + NSMutableDictionary* decayedPredictionValues = [[NSMutableDictionary alloc] init]; + for (NSString* label in oldPredictionValues) { + NSNumber* oldPredictionValueObject = [oldPredictionValues objectForKey:label]; + const float oldPredictionValue = [oldPredictionValueObject floatValue]; + const float decayedPredictionValue = (oldPredictionValue * decayValue); + if (decayedPredictionValue > minimumThreshold) { + NSNumber* decayedPredictionValueObject = [NSNumber numberWithFloat:decayedPredictionValue]; + [decayedPredictionValues setObject:decayedPredictionValueObject forKey:label]; + } + } + oldPredictionValues = decayedPredictionValues; + + for (NSString* label in newValues) { + NSNumber* newPredictionValueObject = [newValues objectForKey:label]; + NSNumber* oldPredictionValueObject = [oldPredictionValues objectForKey:label]; + if (!oldPredictionValueObject) { + oldPredictionValueObject = [NSNumber numberWithFloat:0.0f]; + } + const float newPredictionValue = [newPredictionValueObject floatValue]; + const float oldPredictionValue = [oldPredictionValueObject floatValue]; + const float updatedPredictionValue = (oldPredictionValue + (newPredictionValue * updateValue)); + NSNumber* updatedPredictionValueObject = [NSNumber numberWithFloat:updatedPredictionValue]; + [oldPredictionValues setObject:updatedPredictionValueObject forKey:label]; + } + NSArray* candidateLabels = [NSMutableArray array]; + for (NSString* label in oldPredictionValues) { + NSNumber* oldPredictionValueObject = [oldPredictionValues objectForKey:label]; + const float oldPredictionValue = [oldPredictionValueObject floatValue]; + if (oldPredictionValue > 0.05f) { + NSDictionary* entry = @{@"label" : label, @"value" : oldPredictionValueObject}; + candidateLabels = [candidateLabels arrayByAddingObject:entry]; + } + } + NSSortDescriptor* sort = [NSSortDescriptor sortDescriptorWithKey:@"value" ascending:NO]; + NSArray* sortedLabels = + [candidateLabels sortedArrayUsingDescriptors:[NSArray arrayWithObject:sort]]; + + const float leftMargin = 10.0f; + const float topMargin = 10.0f; + + const float valueWidth = 48.0f; + const float valueHeight = 18.0f; + + const float labelWidth = 246.0f; + const float labelHeight = 18.0f; + + const float labelMarginX = 5.0f; + const float labelMarginY = 5.0f; + + [self removeAllLabelLayers]; + + int labelCount = 0; + for (NSDictionary* entry in sortedLabels) { + NSString* label = [entry objectForKey:@"label"]; + NSNumber* valueObject = [entry objectForKey:@"value"]; + const float value = [valueObject floatValue]; + const float originY = topMargin + ((labelHeight + labelMarginY) * labelCount); + const int valuePercentage = (int)roundf(value * 100.0f); + + const float valueOriginX = leftMargin; + NSString* valueText = [NSString stringWithFormat:@"%d%%", valuePercentage]; + + [self addLabelLayerWithText:valueText + originX:valueOriginX + originY:originY + width:valueWidth + height:valueHeight + alignment:kCAAlignmentRight]; + + const float labelOriginX = (leftMargin + valueWidth + labelMarginX); + + [self addLabelLayerWithText:[label capitalizedString] + originX:labelOriginX + originY:originY + width:labelWidth + height:labelHeight + alignment:kCAAlignmentLeft]; + + labelCount += 1; + if (labelCount > 4) { + break; + } + } +} + +- (void)removeAllLabelLayers { + for (CATextLayer* layer in labelLayers) { + [layer removeFromSuperlayer]; + } + [labelLayers removeAllObjects]; +} + +- (void)addLabelLayerWithText:(NSString*)text + originX:(float)originX + originY:(float)originY + width:(float)width + height:(float)height + alignment:(NSString*)alignment { + CFTypeRef font = (CFTypeRef) @"Menlo-Regular"; + const float fontSize = 12.0; + const float marginSizeX = 5.0f; + const float marginSizeY = 2.0f; + + const CGRect backgroundBounds = CGRectMake(originX, originY, width, height); + const CGRect textBounds = CGRectMake((originX + marginSizeX), (originY + marginSizeY), + (width - (marginSizeX * 2)), (height - (marginSizeY * 2))); + + CATextLayer* background = [CATextLayer layer]; + [background setBackgroundColor:[UIColor blackColor].CGColor]; + [background setOpacity:0.5f]; + [background setFrame:backgroundBounds]; + background.cornerRadius = 5.0f; + + [[self.view layer] addSublayer:background]; + [labelLayers addObject:background]; + + CATextLayer* layer = [CATextLayer layer]; + [layer setForegroundColor:[UIColor whiteColor].CGColor]; + [layer setFrame:textBounds]; + [layer setAlignmentMode:alignment]; + [layer setWrapped:YES]; + [layer setFont:font]; + [layer setFontSize:fontSize]; + layer.contentsScale = [[UIScreen mainScreen] scale]; + [layer setString:text]; + + [[self.view layer] addSublayer:layer]; + [labelLayers addObject:layer]; +} + +@end diff --git a/tensorflow/contrib/lite/examples/ios/camera/Info.plist b/tensorflow/contrib/lite/examples/ios/camera/Info.plist new file mode 100644 index 00000000000..f3d96bab162 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/camera/Info.plist @@ -0,0 +1,44 @@ + + + + + CFBundleDevelopmentRegion + en + CFBundleDisplayName + tflite_camera_example + CFBundleExecutable + ${EXECUTABLE_NAME} + CFBundleIdentifier + $(PRODUCT_BUNDLE_IDENTIFIER) + CFBundleInfoDictionaryVersion + 6.0 + CFBundleName + ${PRODUCT_NAME} + CFBundlePackageType + APPL + CFBundleShortVersionString + 1.0 + CFBundleSignature + ???? + CFBundleVersion + 1.0 + LSRequiresIPhoneOS + + NSCameraUsageDescription + Capture images to detect object + UIMainStoryboardFile + MainStoryboard_iPhone + UIRequiresFullScreen + + UIStatusBarHidden + + UISupportedInterfaceOrientations + + UIInterfaceOrientationPortrait + + UISupportedInterfaceOrientations~ipad + + UIInterfaceOrientationPortrait + + + diff --git a/tensorflow/contrib/lite/examples/ios/camera/MainStoryboard_iPhone.storyboard b/tensorflow/contrib/lite/examples/ios/camera/MainStoryboard_iPhone.storyboard new file mode 100644 index 00000000000..0f10a22e415 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/camera/MainStoryboard_iPhone.storyboard @@ -0,0 +1,46 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tensorflow/contrib/lite/examples/ios/camera/Podfile b/tensorflow/contrib/lite/examples/ios/camera/Podfile new file mode 100644 index 00000000000..4ae6fb6b94e --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/camera/Podfile @@ -0,0 +1,5 @@ +platform :ios, '8.0' +inhibit_all_warnings! + +target 'tflite_camera_example' + pod 'TensorFlow-experimental' diff --git a/tensorflow/contrib/lite/examples/ios/camera/data/.gitignore b/tensorflow/contrib/lite/examples/ios/camera/data/.gitignore new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tensorflow/contrib/lite/examples/ios/camera/main.mm b/tensorflow/contrib/lite/examples/ios/camera/main.mm new file mode 100644 index 00000000000..1a9e542f7c9 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/camera/main.mm @@ -0,0 +1,28 @@ +// 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. + +#import + +#import "CameraExampleAppDelegate.h" + +int main(int argc, char* argv[]) { + int retVal = 0; + + @autoreleasepool { + retVal = + UIApplicationMain(argc, argv, nil, NSStringFromClass([CameraExampleAppDelegate class])); + } + return retVal; +} diff --git a/tensorflow/contrib/lite/examples/ios/camera/tflite_camera_example.xcodeproj/project.pbxproj b/tensorflow/contrib/lite/examples/ios/camera/tflite_camera_example.xcodeproj/project.pbxproj new file mode 100644 index 00000000000..c98183276bd --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/camera/tflite_camera_example.xcodeproj/project.pbxproj @@ -0,0 +1,419 @@ +// !$*UTF8*$! +{ + archiveVersion = 1; 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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. + +#import + +@interface AppDelegate : UIResponder + +@property(strong, nonatomic) UIWindow *window; + +@end diff --git a/tensorflow/contrib/lite/examples/ios/simple/AppDelegate.mm b/tensorflow/contrib/lite/examples/ios/simple/AppDelegate.mm new file mode 100644 index 00000000000..fe26ceec427 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/simple/AppDelegate.mm @@ -0,0 +1,47 @@ +// Copyright 2015 Google Inc. 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. + +#import "AppDelegate.h" + +#import "RunModelViewController.h" + +@implementation AppDelegate + +- (BOOL)application:(UIApplication *)application + didFinishLaunchingWithOptions:(NSDictionary *)launchOptions { + UITabBarController *bar = [[UITabBarController alloc] init]; + [bar setViewControllers:@[ [[RunModelViewController alloc] init] ]]; + bar.selectedIndex = 0; + self.window = [[UIWindow alloc] initWithFrame:[[UIScreen mainScreen] bounds]]; + self.window.rootViewController = bar; + [self.window makeKeyAndVisible]; + return YES; +} + +- (void)applicationWillResignActive:(UIApplication *)application { +} + +- (void)applicationDidEnterBackground:(UIApplication *)application { +} + +- (void)applicationWillEnterForeground:(UIApplication *)application { +} + +- (void)applicationDidBecomeActive:(UIApplication *)application { +} + +- (void)applicationWillTerminate:(UIApplication *)application { +} + +@end diff --git a/tensorflow/contrib/lite/examples/ios/simple/Podfile b/tensorflow/contrib/lite/examples/ios/simple/Podfile new file mode 100644 index 00000000000..1740ad64573 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/simple/Podfile @@ -0,0 +1,5 @@ +platform :ios, '8.0' +inhibit_all_warnings! + +target 'tf_simple_example' + pod 'TensorFlow-experimental' diff --git a/tensorflow/contrib/lite/examples/ios/simple/RunModel-Info.plist b/tensorflow/contrib/lite/examples/ios/simple/RunModel-Info.plist new file mode 100644 index 00000000000..1a3eaa8a2c1 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/simple/RunModel-Info.plist @@ -0,0 +1,47 @@ + + + + + CFBundleDevelopmentRegion + en + CFBundleDisplayName + tflite-simple-example + CFBundleExecutable + tf_simple_example + CFBundleIdentifier + $(PRODUCT_BUNDLE_IDENTIFIER) + CFBundleInfoDictionaryVersion + 6.0 + CFBundleName + ios-app + CFBundlePackageType + APPL + CFBundleShortVersionString + 1.0 + CFBundleSignature + ???? + CFBundleVersion + 1.0 + LSRequiresIPhoneOS + + UILaunchStoryboardName + RunModelViewController + UIRequiredDeviceCapabilities + + armv7 + + UISupportedInterfaceOrientations + + UIInterfaceOrientationPortrait + UIInterfaceOrientationLandscapeLeft + UIInterfaceOrientationLandscapeRight + + UISupportedInterfaceOrientations~ipad + + UIInterfaceOrientationPortrait + UIInterfaceOrientationPortraitUpsideDown + UIInterfaceOrientationLandscapeLeft + UIInterfaceOrientationLandscapeRight + + + diff --git a/tensorflow/contrib/lite/examples/ios/simple/RunModelViewController.h b/tensorflow/contrib/lite/examples/ios/simple/RunModelViewController.h new file mode 100644 index 00000000000..a4b358b4eb7 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/simple/RunModelViewController.h @@ -0,0 +1,24 @@ +// Copyright 2015 Google Inc. 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. + +#import + +@interface RunModelViewController : UIViewController + +- (IBAction)getUrl:(id)sender; + +@property(weak, nonatomic) IBOutlet UITextView *urlContentTextView; +@property(weak, nonatomic) IBOutlet UITextField *urlTextField; + +@end diff --git a/tensorflow/contrib/lite/examples/ios/simple/RunModelViewController.mm b/tensorflow/contrib/lite/examples/ios/simple/RunModelViewController.mm new file mode 100644 index 00000000000..0dafb1f61e1 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/simple/RunModelViewController.mm @@ -0,0 +1,221 @@ +// Copyright 2015 Google Inc. 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. + +#import "RunModelViewController.h" + +#include +#include +#include +#include +#include +#include +#include + +#include "tensorflow/contrib/lite/kernels/register.h" +#include "tensorflow/contrib/lite/model.h" +#include "tensorflow/contrib/lite/string_util.h" +#include "tensorflow/contrib/lite/tools/mutable_op_resolver.h" + +#include "ios_image_load.h" + +#define LOG(x) std::cerr +#define CHECK(x) \ + if (!(x)) { \ + LOG(ERROR) << #x << "failed"; \ + exit(1); \ + } + +NSString* RunInferenceOnImage(); + +@interface RunModelViewController () +@end + +@implementation RunModelViewController { +} + +- (IBAction)getUrl:(id)sender { + NSString* inference_result = RunInferenceOnImage(); + self.urlContentTextView.text = inference_result; +} + +@end + +// Returns the top N confidence values over threshold in the provided vector, +// sorted by confidence in descending order. +static void GetTopN(const float* prediction, const int prediction_size, const int num_results, + const float threshold, std::vector >* top_results) { + // Will contain top N results in ascending order. + std::priority_queue, std::vector >, + std::greater > > + top_result_pq; + + const long count = prediction_size; + for (int i = 0; i < count; ++i) { + const float value = prediction[i]; + + // Only add it if it beats the threshold and has a chance at being in + // the top N. + if (value < threshold) { + continue; + } + + top_result_pq.push(std::pair(value, i)); + + // If at capacity, kick the smallest value out. + if (top_result_pq.size() > num_results) { + top_result_pq.pop(); + } + } + + // Copy to output vector and reverse into descending order. + while (!top_result_pq.empty()) { + top_results->push_back(top_result_pq.top()); + top_result_pq.pop(); + } + std::reverse(top_results->begin(), top_results->end()); +} + +NSString* FilePathForResourceName(NSString* name, NSString* extension) { + NSString* file_path = [[NSBundle mainBundle] pathForResource:name ofType:extension]; + if (file_path == NULL) { + LOG(FATAL) << "Couldn't find '" << [name UTF8String] << "." << [extension UTF8String] + << "' in bundle."; + } + return file_path; +} + +NSString* RunInferenceOnImage() { + std::string graph; + const int num_threads = 1; + std::string input_layer_type = "float"; + std::vector sizes = {1, 224, 224, 3}; + + NSString* graph_path = FilePathForResourceName(@"mobilenet_v1_1.0_224", @"tflite"); + + std::unique_ptr model( + tflite::FlatBufferModel::BuildFromFile([graph_path UTF8String])); + if (!model) { + LOG(FATAL) << "Failed to mmap model " << graph; + } + LOG(INFO) << "Loaded model " << graph; + model->error_reporter(); + LOG(INFO) << "resolved reporter"; + +#ifdef TFLITE_CUSTOM_OPS_HEADER + tflite::MutableOpResolver resolver; + RegisterSelectedOps(&resolver); +#else + tflite::ops::builtin::BuiltinOpResolver resolver; +#endif + + std::unique_ptr interpreter; + tflite::InterpreterBuilder(*model, resolver)(&interpreter); + if (!interpreter) { + LOG(FATAL) << "Failed to construct interpreter"; + } + + if (num_threads != -1) { + interpreter->SetNumThreads(num_threads); + } + + int input = interpreter->inputs()[0]; + + if (input_layer_type != "string") { + interpreter->ResizeInputTensor(input, sizes); + } + + if (interpreter->AllocateTensors() != kTfLiteOk) { + LOG(FATAL) << "Failed to allocate tensors!"; + } + + // Read the label list + NSString* labels_path = FilePathForResourceName(@"labels", @"txt"); + std::vector label_strings; + std::ifstream t; + t.open([labels_path UTF8String]); + std::string line; + while (t) { + std::getline(t, line); + label_strings.push_back(line); + } + t.close(); + + // Read the Grace Hopper image. + NSString* image_path = FilePathForResourceName(@"grace_hopper", @"jpg"); + int image_width; + int image_height; + int image_channels; + std::vector image_data = + LoadImageFromFile([image_path UTF8String], &image_width, &image_height, &image_channels); + const int wanted_width = 224; + const int wanted_height = 224; + const int wanted_channels = 3; + const float input_mean = 127.5f; + const float input_std = 127.5f; + assert(image_channels >= wanted_channels); + uint8_t* in = image_data.data(); + float* out = interpreter->typed_tensor(input); + for (int y = 0; y < wanted_height; ++y) { + const int in_y = (y * image_height) / wanted_height; + uint8_t* in_row = in + (in_y * image_width * image_channels); + float* out_row = out + (y * wanted_width * wanted_channels); + for (int x = 0; x < wanted_width; ++x) { + const int in_x = (x * image_width) / wanted_width; + uint8_t* in_pixel = in_row + (in_x * image_channels); + float* out_pixel = out_row + (x * wanted_channels); + for (int c = 0; c < wanted_channels; ++c) { + out_pixel[c] = (in_pixel[c] - input_mean) / input_std; + } + } + } + + if (interpreter->Invoke() != kTfLiteOk) { + LOG(FATAL) << "Failed to invoke!"; + } + + float* output = interpreter->typed_output_tensor(0); + const int output_size = 1000; + const int kNumResults = 5; + const float kThreshold = 0.1f; + std::vector > top_results; + GetTopN(output, output_size, kNumResults, kThreshold, &top_results); + + std::stringstream ss; + ss.precision(3); + for (const auto& result : top_results) { + const float confidence = result.first; + const int index = result.second; + + ss << index << " " << confidence << " "; + + // Write out the result as a string + if (index < label_strings.size()) { + // just for safety: theoretically, the output is under 1000 unless there + // is some numerical issues leading to a wrong prediction. + ss << label_strings[index]; + } else { + ss << "Prediction: " << index; + } + + ss << "\n"; + } + + LOG(INFO) << "Predictions: " << ss.str(); + + std::string predictions = ss.str(); + NSString* result = @""; + result = [NSString stringWithFormat:@"%@ - %s", result, predictions.c_str()]; + + return result; +} diff --git a/tensorflow/contrib/lite/examples/ios/simple/RunModelViewController.xib b/tensorflow/contrib/lite/examples/ios/simple/RunModelViewController.xib new file mode 100644 index 00000000000..93f334b9850 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/simple/RunModelViewController.xib @@ -0,0 +1,46 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tensorflow/contrib/lite/examples/ios/simple/data/grace_hopper.jpg b/tensorflow/contrib/lite/examples/ios/simple/data/grace_hopper.jpg new file mode 100644 index 00000000000..d2a427810f6 Binary files /dev/null and b/tensorflow/contrib/lite/examples/ios/simple/data/grace_hopper.jpg differ diff --git a/tensorflow/contrib/lite/examples/ios/simple/ios_image_load.h b/tensorflow/contrib/lite/examples/ios/simple/ios_image_load.h new file mode 100644 index 00000000000..98934ce41d3 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/simple/ios_image_load.h @@ -0,0 +1,23 @@ +// Copyright 2015 Google Inc. 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_EXAMPLES_IOS_IOS_IMAGE_LOAD_H_ +#define TENSORFLOW_EXAMPLES_IOS_IOS_IMAGE_LOAD_H_ + +#include + +std::vector LoadImageFromFile(const char* file_name, int* out_width, + int* out_height, int* out_channels); + +#endif // TENSORFLOW_EXAMPLES_IOS_IOS_IMAGE_LOAD_H_ diff --git a/tensorflow/contrib/lite/examples/ios/simple/ios_image_load.mm b/tensorflow/contrib/lite/examples/ios/simple/ios_image_load.mm new file mode 100644 index 00000000000..cb19377d7e3 --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/simple/ios_image_load.mm @@ -0,0 +1,80 @@ +// Copyright 2015 Google Inc. 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. + +#include "ios_image_load.h" + +#include +#include +#include +#include + +#import +#import + +std::vector LoadImageFromFile(const char* file_name, int* out_width, int* out_height, + int* out_channels) { + FILE* file_handle = fopen(file_name, "rb"); + fseek(file_handle, 0, SEEK_END); + const size_t bytes_in_file = ftell(file_handle); + fseek(file_handle, 0, SEEK_SET); + std::vector file_data(bytes_in_file); + fread(file_data.data(), 1, bytes_in_file, file_handle); + fclose(file_handle); + CFDataRef file_data_ref = + CFDataCreateWithBytesNoCopy(NULL, file_data.data(), bytes_in_file, kCFAllocatorNull); + CGDataProviderRef image_provider = CGDataProviderCreateWithCFData(file_data_ref); + + const char* suffix = strrchr(file_name, '.'); + if (!suffix || suffix == file_name) { + suffix = ""; + } + CGImageRef image; + if (strcasecmp(suffix, ".png") == 0) { + image = CGImageCreateWithPNGDataProvider(image_provider, NULL, true, kCGRenderingIntentDefault); + } else if ((strcasecmp(suffix, ".jpg") == 0) || (strcasecmp(suffix, ".jpeg") == 0)) { + image = + CGImageCreateWithJPEGDataProvider(image_provider, NULL, true, kCGRenderingIntentDefault); + } else { + CFRelease(image_provider); + CFRelease(file_data_ref); + fprintf(stderr, "Unknown suffix for file '%s'\n", file_name); + *out_width = 0; + *out_height = 0; + *out_channels = 0; + return std::vector(); + } + + const int width = (int)CGImageGetWidth(image); + const int height = (int)CGImageGetHeight(image); + const int channels = 4; + CGColorSpaceRef color_space = CGColorSpaceCreateDeviceRGB(); + const int bytes_per_row = (width * channels); + const int bytes_in_image = (bytes_per_row * height); + std::vector result(bytes_in_image); + const int bits_per_component = 8; + CGContextRef context = + CGBitmapContextCreate(result.data(), width, height, bits_per_component, bytes_per_row, + color_space, kCGImageAlphaPremultipliedLast | kCGBitmapByteOrder32Big); + CGColorSpaceRelease(color_space); + CGContextDrawImage(context, CGRectMake(0, 0, width, height), image); + CGContextRelease(context); + CFRelease(image); + CFRelease(image_provider); + CFRelease(file_data_ref); + + *out_width = width; + *out_height = height; + *out_channels = channels; + return result; +} diff --git a/tensorflow/contrib/lite/examples/ios/simple/main.mm b/tensorflow/contrib/lite/examples/ios/simple/main.mm new file mode 100644 index 00000000000..05cb55ddd7a --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/simple/main.mm @@ -0,0 +1,22 @@ +// Copyright 2015 Google Inc. 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. + +#import + +int main(int argc, char *argv[]) { + @autoreleasepool { + NSString *delegateClassName = @"AppDelegate"; + return UIApplicationMain(argc, argv, nil, delegateClassName); + } +} diff --git a/tensorflow/contrib/lite/examples/ios/simple/simple.xcodeproj/project.pbxproj b/tensorflow/contrib/lite/examples/ios/simple/simple.xcodeproj/project.pbxproj new file mode 100644 index 00000000000..9277c230b8c --- /dev/null +++ b/tensorflow/contrib/lite/examples/ios/simple/simple.xcodeproj/project.pbxproj @@ -0,0 +1,359 @@ +// !$*UTF8*$! +{ + archiveVersion = 1; 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In most of the cases, this is the only class an app developer will need. -#### Initializing an `Interpreter` Mith a Model Mile +#### Initializing an `Interpreter` With a Model File The `Interpreter` can be initialized with a model file using the constructor: diff --git a/tensorflow/contrib/lite/g3doc/tf_ops_compatibility.md b/tensorflow/contrib/lite/g3doc/tf_ops_compatibility.md index 121c4c2c959..9ade04eb8c6 100644 --- a/tensorflow/contrib/lite/g3doc/tf_ops_compatibility.md +++ b/tensorflow/contrib/lite/g3doc/tf_ops_compatibility.md @@ -54,7 +54,7 @@ counterparts: * [tf.sigmoid](https://www.tensorflow.org/api_docs/python/tf/sigmoid) * [tf.space_to_depth](https://www.tensorflow.org/api_docs/python/tf/space_to_depth) -## Straighforward Conversions, Constant-Folding and Fusing +## Straightforward Conversions, Constant-Folding and Fusing A number of TensorFlow operations can be processed by TensorFlow Lite even though they have no direct equivalent. This is the case for operations that can diff --git a/tensorflow/contrib/lite/ios_makefile.inc b/tensorflow/contrib/lite/ios_makefile.inc new file mode 100644 index 00000000000..345ed262128 --- /dev/null +++ b/tensorflow/contrib/lite/ios_makefile.inc @@ -0,0 +1,31 @@ +#Settings for iOS. +ifeq($(TARGET), IOS) BUILD_FOR_IOS_SIMULATOR + : = false ifeq($(IOS_ARCH), x86_64) BUILD_FOR_IOS_SIMULATOR + : = true endif ifeq($(IOS_ARCH), i386) BUILD_FOR_IOS_SIMULATOR + : = true endif ifeq($(BUILD_FOR_IOS_SIMULATOR), true) IPHONEOS_PLATFORM + : = $(shell xcrun-- sdk iphonesimulator-- show - sdk - platform - + path) IPHONEOS_SYSROOT + : = $(shell xcrun-- sdk iphonesimulator-- show - sdk - + path) else IPHONEOS_PLATFORM + : = $(shell xcrun-- sdk iphoneos-- show - sdk - platform - + path) IPHONEOS_SYSROOT + : = $(shell xcrun-- sdk iphoneos-- show - sdk - path) endif IOS_SDK_VERSION + : = $(shell xcrun-- sdk iphoneos-- show - sdk - version) MIN_SDK_VERSION + : = 9.0 +#Override IOS_ARCH with armv7, armv7s, arm64, i386, or x86_64. + IOS_ARCH + : = x86_64 CXXFLAGS + += -miphoneos - version + - min = $(MIN_SDK_VERSION) - DGEMMLOWP_ALLOW_SLOW_SCALAR_FALLBACK + - fembed - bitcode - Wno - c++ 11 - narrowing - mno - thumb + - fno - exceptions + - isysroot ${IPHONEOS_SYSROOT} - arch $(IOS_ARCH) - O3 CCFLAGS + += -miphoneos - version + - min = $(MIN_SDK_VERSION) - fembed - bitcode - mno - thumb + - isysroot ${IPHONEOS_SYSROOT} - arch $(IOS_ARCH) - + O3 LDFLAGS + : = -fembed - bitcode - miphoneos - version + - min = ${MIN_SDK_VERSION} - arch $(IOS_ARCH) OBJDIR + : = $(OBJDIR) ios_$(IOS_ARCH) / LIBDIR + : = $(LIBDIR) ios_$(IOS_ARCH) / BINDIR + : = $(BINDIR) ios_$(IOS_ARCH) / DEPDIR : = $(DEPDIR) ios_$(IOS_ARCH) / endif diff --git a/tensorflow/contrib/lite/java/demo/app/build.gradle b/tensorflow/contrib/lite/java/demo/app/build.gradle index e1470fe7179..b76eaad8bb9 100644 --- a/tensorflow/contrib/lite/java/demo/app/build.gradle +++ b/tensorflow/contrib/lite/java/demo/app/build.gradle @@ -36,8 +36,8 @@ android { } repositories { - flatDir { - dirs 'libs' + maven { + url 'https://google.bintray.com/tensorflow' } } diff --git a/tensorflow/contrib/lite/models/testdata/g3doc/README.md b/tensorflow/contrib/lite/models/testdata/g3doc/README.md index 83760e420f7..46b24248f00 100644 --- a/tensorflow/contrib/lite/models/testdata/g3doc/README.md +++ b/tensorflow/contrib/lite/models/testdata/g3doc/README.md @@ -86,25 +86,34 @@ same input. ### Models: -[Speech hotword model (Svdf rank=1)] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/testdata/speech_hotword_model_rank1.tflite) +[Speech hotword model (Svdf +rank=1)](https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_hotword_model_rank1_2017_11_14.tflite) -[Speech hotword model (Svdf rank=2)] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/testdata/speech_hotword_model_rank2.tflite) +[Speech hotword model (Svdf +rank=2)](https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_hotword_model_rank2_2017_11_14.tflite) -[Speaker-id model] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/testdata/speech_speakerid_model.tflite) +[Speaker-id +model](https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_speakerid_model_2017_11_14.tflite) -[TTS model] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/testdata/speech_tts_model.tflite) +[TTS +model](https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_tts_model_2017_11_14.tflite) -[ASR AM model] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/testdata/speech_terse_am_model.tflite) +[ASR AM +model](https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_terse_am_model_2017_11_14.tflite) ### Test benches -[Speech hotword model test] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/speech_hotword_model_test.cc) +[Speech hotword model +test](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/speech_hotword_model_test.cc) -[Speaker-id model test] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/speech_speakerid_model_test.cc) +[Speaker-id model +test](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/speech_speakerid_model_test.cc) -[TTS model test] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/speech_tts_model_test.cc) +[TTS model +test](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/speech_tts_model_test.cc) -[ASR AM model test] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/speech_terse_am_model_test.cc) +[ASR AM model +test](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/speech_terse_am_model_test.cc) ## Android Support The models have been tested on Android phones, using the following tests: @@ -112,5 +121,3 @@ The models have been tested on Android phones, using the following tests: [Hotword] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/android/BUILD?rcl=172930882&l=25) [Speaker-id] (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/android/BUILD?rcl=172930882&l=36) - - diff --git a/tensorflow/contrib/lite/nnapi/NeuralNetworksShim.h b/tensorflow/contrib/lite/nnapi/NeuralNetworksShim.h index 5d061657729..bdb5e015387 100644 --- a/tensorflow/contrib/lite/nnapi/NeuralNetworksShim.h +++ b/tensorflow/contrib/lite/nnapi/NeuralNetworksShim.h @@ -1454,9 +1454,9 @@ inline int ANeuralNetworksModel_finish(ANeuralNetworksModel* model) { * {@link ANeuralNetworksExecution_setOutputFromMemory} and * {@link ANeuralNetworksExecution_setOperandValue}. * - * To build a model that can accomodate inputs of various sizes, as you may want - * to do for a CNN, set the size of the dimensions that will vary at run time to - * 0. If you do so, provide the full dimensions when calling + * To build a model that can accommodate inputs of various sizes, as you may + * want to do for a CNN, set the size of the dimensions that will vary at run + * time to 0. If you do so, provide the full dimensions when calling * {@link ANeuralNetworksExecution_setInput} or {@link * ANeuralNetworksExecution_setInputFromMemory}. * diff --git a/tensorflow/contrib/lite/schema/upgrade_schema_test.py b/tensorflow/contrib/lite/schema/upgrade_schema_test.py index 754400e8887..b5002e6f757 100644 --- a/tensorflow/contrib/lite/schema/upgrade_schema_test.py +++ b/tensorflow/contrib/lite/schema/upgrade_schema_test.py @@ -252,7 +252,7 @@ def JsonDumpAndFlush(data, fp): class TestSchemaUpgrade(test_util.TensorFlowTestCase): - def testNonExistantFile(self): + def testNonExistentFile(self): converter = upgrade_schema_lib.Converter() non_existent = tempfile.mktemp(suffix=".json") with self.assertRaisesRegexp(IOError, "No such file or directory"): diff --git a/tensorflow/contrib/lite/testing/BUILD b/tensorflow/contrib/lite/testing/BUILD index 5e40a13d3cb..ecddb4b807b 100644 --- a/tensorflow/contrib/lite/testing/BUILD +++ b/tensorflow/contrib/lite/testing/BUILD @@ -187,6 +187,7 @@ tf_cc_test( srcs = ["generated_examples_zip_test.cc"], data = [":optest"], shard_count = 10, + tags = ["no_oss"], deps = [ ":parse_testdata_lib", "//tensorflow/contrib/lite:builtin_op_data", diff --git a/tensorflow/contrib/lite/testing/parse_testdata.cc b/tensorflow/contrib/lite/testing/parse_testdata.cc index 2b67052cad2..d745ed27158 100644 --- a/tensorflow/contrib/lite/testing/parse_testdata.cc +++ b/tensorflow/contrib/lite/testing/parse_testdata.cc @@ -232,7 +232,7 @@ TfLiteStatus CheckOutputs(tflite::Interpreter* interpreter, // invoke { // id: xyz // input: 1,2,1,1,1,2,3,4 -// ouput: 4,5,6 +// output: 4,5,6 // } class Invoke : public Message { public: diff --git a/tensorflow/contrib/lite/testing/test_runner.h b/tensorflow/contrib/lite/testing/test_runner.h index 04ee4d9f7da..f4b26949b57 100644 --- a/tensorflow/contrib/lite/testing/test_runner.h +++ b/tensorflow/contrib/lite/testing/test_runner.h @@ -63,7 +63,7 @@ class TestRunner { // Run the model. virtual void Invoke() = 0; - // Verify that the contents of all ouputs conform to the existing + // Verify that the contents of all outputs conform to the existing // expectations. Return true if there are no expectations or they are all // satisfied. virtual bool CheckResults() = 0; diff --git a/tensorflow/contrib/lite/toco/model.h b/tensorflow/contrib/lite/toco/model.h index f2fce2b2495..04b08135234 100644 --- a/tensorflow/contrib/lite/toco/model.h +++ b/tensorflow/contrib/lite/toco/model.h @@ -129,7 +129,7 @@ enum class AxesOrder { // The type of the scalars in an array. // Note that that does not by itself tell whether the values in the array are // real (are literally interpreted as real numbers) or quantized (only acquire -// a meaning as real numbers in conjuction with QuantizationParams). +// a meaning as real numbers in conjunction with QuantizationParams). // // In practice though: // float values are always real diff --git a/tensorflow/contrib/lite/tools/benchmark_model.cc b/tensorflow/contrib/lite/tools/benchmark_model.cc new file mode 100644 index 00000000000..ef43f64131c --- /dev/null +++ b/tensorflow/contrib/lite/tools/benchmark_model.cc @@ -0,0 +1,95 @@ +/* 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. +==============================================================================*/ + +#include +#include +#include +#include +#include +#include +#include + +#include "tensorflow/contrib/lite/kernels/register.h" +#include "tensorflow/contrib/lite/model.h" +#include "tensorflow/contrib/lite/string_util.h" +#include "tensorflow/contrib/lite/tools/mutable_op_resolver.h" + +#ifdef TFLITE_CUSTOM_OPS_HEADER +void RegisterSelectedOps(::tflite::MutableOpResolver* resolver); +#endif + +#define LOG(x) std::cerr +#define CHECK(x) \ + if (!(x)) { \ + LOG(ERROR) << #x << "failed"; \ + exit(1); \ + } + +namespace tensorflow { +namespace benchmark_tflite_model { + +std::unique_ptr model; +std::unique_ptr interpreter; + +void InitImpl(const std::string& graph, const std::vector& sizes, + const std::string& input_layer_type, int num_threads) { + CHECK(graph.c_str()); + + model = tflite::FlatBufferModel::BuildFromFile(graph.c_str()); + if (!model) { + LOG(FATAL) << "Failed to mmap model " << graph; + } + LOG(INFO) << "Loaded model " << graph; + model->error_reporter(); + LOG(INFO) << "resolved reporter"; + +#ifdef TFLITE_CUSTOM_OPS_HEADER + tflite::MutableOpResolver resolver; + RegisterSelectedOps(&resolver); +#else + tflite::ops::builtin::BuiltinOpResolver resolver; +#endif + + tflite::InterpreterBuilder(*model, resolver)(&interpreter); + if (!interpreter) { + LOG(FATAL) << "Failed to construct interpreter"; + } + + if (num_threads != -1) { + interpreter->SetNumThreads(num_threads); + } + + int input = interpreter->inputs()[0]; + + if (input_layer_type != "string") { + interpreter->ResizeInputTensor(input, sizes); + } + + if (interpreter->AllocateTensors() != kTfLiteOk) { + LOG(FATAL) << "Failed to allocate tensors!"; + } +} + +int Main(int argc, char** argv) { + InitImpl("", {}, "", 1); + return 0; +} + +} // namespace benchmark_tflite_model +} // namespace tensorflow + +int main(int argc, char** argv) { + return tensorflow::benchmark_tflite_model::Main(argc, argv); +} diff --git a/tensorflow/contrib/lite/tools/mutable_op_resolver.h b/tensorflow/contrib/lite/tools/mutable_op_resolver.h index cc1a8e27e67..be60cf476da 100644 --- a/tensorflow/contrib/lite/tools/mutable_op_resolver.h +++ b/tensorflow/contrib/lite/tools/mutable_op_resolver.h @@ -19,6 +19,16 @@ limitations under the License. #include "tensorflow/contrib/lite/context.h" #include "tensorflow/contrib/lite/model.h" +// Needed to resolve unordered_set hash on older compilers. +namespace std { +template <> +struct hash { + size_t operator()(const tflite::BuiltinOperator& op) const { + return std::hash()(op); + } +}; +} // namespace std + namespace tflite { // An OpResolver that is mutable, also used as the op in gen_op_registration. diff --git a/tensorflow/contrib/mpi/BUILD b/tensorflow/contrib/mpi/BUILD index 20ceef5004a..d9d55faf50b 100644 --- a/tensorflow/contrib/mpi/BUILD +++ b/tensorflow/contrib/mpi/BUILD @@ -72,6 +72,7 @@ cc_library( "//tensorflow/core:worker_proto_cc", "//tensorflow/core/distributed_runtime:base_rendezvous_mgr", "//tensorflow/core/distributed_runtime:session_mgr", + "//tensorflow/core/distributed_runtime:tensor_coding", "//tensorflow/core/distributed_runtime:worker_env", "//third_party/mpi", ], diff --git a/tensorflow/contrib/nn/python/ops/cross_entropy.py b/tensorflow/contrib/nn/python/ops/cross_entropy.py index 61c1d1c6d9c..5045f2c957f 100644 --- a/tensorflow/contrib/nn/python/ops/cross_entropy.py +++ b/tensorflow/contrib/nn/python/ops/cross_entropy.py @@ -116,7 +116,7 @@ def deprecated_flipped_sparse_softmax_cross_entropy_with_logits(logits, Raises: ValueError: If logits are scalars (need to have rank >= 1) or if the rank - of the labels is not equal to the rank of the labels minus one. + of the labels is not equal to the rank of the logits minus one. """ return nn.sparse_softmax_cross_entropy_with_logits( labels=labels, logits=logits, name=name) diff --git a/tensorflow/contrib/nn/python/ops/sampling_ops.py b/tensorflow/contrib/nn/python/ops/sampling_ops.py index 2ae529e0155..98749cff7ee 100644 --- a/tensorflow/contrib/nn/python/ops/sampling_ops.py +++ b/tensorflow/contrib/nn/python/ops/sampling_ops.py @@ -34,7 +34,7 @@ def _rank_resample(weights, biases, inputs, sampled_values, num_resampled, log(sum_j exp((w_i * x_j + b_i) / resampling_temperature)) - where w_i, b_i are the weight and bias of the i-th class, repsectively, + where w_i, b_i are the weight and bias of the i-th class, respectively, and j ranges over the rows of `inputs`. For efficiency, we rearrange the computation to diff --git a/tensorflow/contrib/rnn/python/ops/rnn_cell.py b/tensorflow/contrib/rnn/python/ops/rnn_cell.py index 289359e5ecc..9685b583921 100644 --- a/tensorflow/contrib/rnn/python/ops/rnn_cell.py +++ b/tensorflow/contrib/rnn/python/ops/rnn_cell.py @@ -114,7 +114,6 @@ class CoupledInputForgetGateLSTMCell(rnn_cell_impl.RNNCell): The class uses optional peep-hole connections, and an optional projection layer. - Layer normalization implementation is based on: https://arxiv.org/abs/1607.06450. diff --git a/tensorflow/contrib/slim/README.md b/tensorflow/contrib/slim/README.md index f7a85557ca3..dc92ae0c859 100644 --- a/tensorflow/contrib/slim/README.md +++ b/tensorflow/contrib/slim/README.md @@ -441,7 +441,8 @@ module. Consider the simple case where we want to train the VGG network: ```python import tensorflow as tf -vgg = tf.contrib.slim.nets.vgg +import tensorflow.contrib.slim.nets as nets +vgg = nets.vgg # Load the images and labels. images, labels = ... @@ -559,9 +560,10 @@ examine the following sample of training the VGG network: ```python import tensorflow as tf +import tensorflow.contrib.slim.nets as nets slim = tf.contrib.slim -vgg = tf.contrib.slim.nets.vgg +vgg = nets.vgg ... @@ -809,9 +811,10 @@ Putting it all together: ```python import tensorflow as tf +import tensorflow.contrib.slim.nets as nets slim = tf.contrib.slim -vgg = tf.contrib.slim.nets.vgg +vgg = nets.vgg # Load the data diff --git a/tensorflow/contrib/slim/python/slim/evaluation.py b/tensorflow/contrib/slim/python/slim/evaluation.py index cdb720b36ba..3caf4e02da3 100644 --- a/tensorflow/contrib/slim/python/slim/evaluation.py +++ b/tensorflow/contrib/slim/python/slim/evaluation.py @@ -34,7 +34,7 @@ the metrics and finally call the `evaluation` method: "mse": slim.metrics.mean_squared_error(predictions, labels), }) - inital_op = tf.group( + initial_op = tf.group( tf.global_variables_initializer(), tf.local_variables_initializer()) @@ -42,7 +42,7 @@ the metrics and finally call the `evaluation` method: metric_values = slim.evaluation( sess, num_evals=1, - inital_op=initial_op, + initial_op=initial_op, eval_op=names_to_updates.values(), final_op=name_to_values.values()) diff --git a/tensorflow/contrib/summary/BUILD b/tensorflow/contrib/summary/BUILD index 45d64545269..f34291c203d 100644 --- a/tensorflow/contrib/summary/BUILD +++ b/tensorflow/contrib/summary/BUILD @@ -25,7 +25,6 @@ py_test( srcs_version = "PY2AND3", deps = [ ":summary_ops", - ":summary_test_internal", ":summary_test_util", "//tensorflow/python:array_ops", "//tensorflow/python:errors", @@ -46,7 +45,6 @@ py_test( srcs_version = "PY2AND3", deps = [ ":summary_ops", - ":summary_test_internal", ":summary_test_util", "//tensorflow/core:protos_all_py", "//tensorflow/python:array_ops", @@ -119,15 +117,3 @@ py_library( "//tensorflow/python:platform", ], ) - -py_library( - name = "summary_test_internal", - testonly = 1, - srcs = ["summary_test_internal.py"], - srcs_version = "PY2AND3", - visibility = ["//visibility:private"], - deps = [ - "//tensorflow/python:lib", - "//tensorflow/python:platform", - ], -) diff --git a/tensorflow/contrib/summary/summary_ops_graph_test.py b/tensorflow/contrib/summary/summary_ops_graph_test.py index fe55bf93e28..703adb7b46c 100644 --- a/tensorflow/contrib/summary/summary_ops_graph_test.py +++ b/tensorflow/contrib/summary/summary_ops_graph_test.py @@ -21,7 +21,6 @@ import tempfile import six from tensorflow.contrib.summary import summary_ops -from tensorflow.contrib.summary import summary_test_internal from tensorflow.contrib.summary import summary_test_util from tensorflow.core.framework import graph_pb2 from tensorflow.core.framework import node_def_pb2 @@ -33,10 +32,10 @@ from tensorflow.python.ops import control_flow_ops from tensorflow.python.platform import test from tensorflow.python.training import training_util -get_all = summary_test_internal.get_all +get_all = summary_test_util.get_all -class DbTest(summary_test_internal.SummaryDbTest): +class DbTest(summary_test_util.SummaryDbTest): def testGraphPassedToGraph_isForbiddenForThineOwnSafety(self): with self.assertRaises(TypeError): diff --git a/tensorflow/contrib/summary/summary_ops_test.py b/tensorflow/contrib/summary/summary_ops_test.py index 3fe421a7e93..54433deb289 100644 --- a/tensorflow/contrib/summary/summary_ops_test.py +++ b/tensorflow/contrib/summary/summary_ops_test.py @@ -21,7 +21,6 @@ import tempfile import six from tensorflow.contrib.summary import summary_ops -from tensorflow.contrib.summary import summary_test_internal from tensorflow.contrib.summary import summary_test_util from tensorflow.core.framework import graph_pb2 from tensorflow.core.framework import node_def_pb2 @@ -35,8 +34,8 @@ from tensorflow.python.ops import state_ops from tensorflow.python.platform import gfile from tensorflow.python.training import training_util -get_all = summary_test_internal.get_all -get_one = summary_test_internal.get_one +get_all = summary_test_util.get_all +get_one = summary_test_util.get_one class TargetTest(test_util.TensorFlowTestCase): @@ -137,7 +136,7 @@ class TargetTest(test_util.TensorFlowTestCase): self.assertEqual(3, get_total()) -class DbTest(summary_test_internal.SummaryDbTest): +class DbTest(summary_test_util.SummaryDbTest): def testIntegerSummaries(self): step = training_util.create_global_step() diff --git a/tensorflow/contrib/summary/summary_test_util.py b/tensorflow/contrib/summary/summary_test_util.py index 794c5b8bab1..915820e05b9 100644 --- a/tensorflow/contrib/summary/summary_test_util.py +++ b/tensorflow/contrib/summary/summary_test_util.py @@ -19,13 +19,38 @@ from __future__ import absolute_import from __future__ import division from __future__ import print_function +import functools import os +import sqlite3 +from tensorflow.contrib.summary import summary_ops from tensorflow.core.util import event_pb2 +from tensorflow.python.framework import test_util from tensorflow.python.lib.io import tf_record from tensorflow.python.platform import gfile +class SummaryDbTest(test_util.TensorFlowTestCase): + """Helper for summary database testing.""" + + def setUp(self): + super(SummaryDbTest, self).setUp() + self.db_path = os.path.join(self.get_temp_dir(), 'DbTest.sqlite') + if os.path.exists(self.db_path): + os.unlink(self.db_path) + self.db = sqlite3.connect(self.db_path) + self.create_summary_db_writer = functools.partial( + summary_ops.create_summary_db_writer, + db_uri=self.db_path, + experiment_name='experiment', + run_name='run', + user_name='user') + + def tearDown(self): + self.db.close() + super(SummaryDbTest, self).tearDown() + + def events_from_file(filepath): """Returns all events in a single event file. @@ -58,5 +83,17 @@ def events_from_logdir(logdir): """ assert gfile.Exists(logdir) files = gfile.ListDirectory(logdir) - assert len(files) == 1, "Found not exactly one file in logdir: %s" % files + assert len(files) == 1, 'Found not exactly one file in logdir: %s' % files return events_from_file(os.path.join(logdir, files[0])) + + +def get_one(db, q, *p): + return db.execute(q, p).fetchone()[0] + + +def get_all(db, q, *p): + return unroll(db.execute(q, p).fetchall()) + + +def unroll(list_of_tuples): + return sum(list_of_tuples, ()) diff --git a/tensorflow/contrib/tensor_forest/hybrid/python/models/decisions_to_data_then_nn_test.py b/tensorflow/contrib/tensor_forest/hybrid/python/models/decisions_to_data_then_nn_test.py index cccf444db80..a56beeeb2c1 100644 --- a/tensorflow/contrib/tensor_forest/hybrid/python/models/decisions_to_data_then_nn_test.py +++ b/tensorflow/contrib/tensor_forest/hybrid/python/models/decisions_to_data_then_nn_test.py @@ -80,7 +80,7 @@ class DecisionsToDataThenNNTest(test_util.TensorFlowTestCase): isinstance(self.params.num_trees, tensor_forest.ForestHParams)) with variable_scope.variable_scope( - "DecisionsToDataThenNNTest_testContructionPollution"): + "DecisionsToDataThenNNTest_testConstructionPollution"): graph_builder = decisions_to_data_then_nn.DecisionsToDataThenNN( self.params) @@ -95,7 +95,7 @@ class DecisionsToDataThenNNTest(test_util.TensorFlowTestCase): for _ in range(100)]) with variable_scope.variable_scope( - "DecisionsToDataThenNNTest_testInferenceContruction"): + "DecisionsToDataThenNNTest_testInferenceConstruction"): graph_builder = decisions_to_data_then_nn.DecisionsToDataThenNN( self.params) graph = graph_builder.inference_graph(data, None) @@ -111,7 +111,7 @@ class DecisionsToDataThenNNTest(test_util.TensorFlowTestCase): labels = [1 for _ in range(100)] with variable_scope.variable_scope( - "DecisionsToDataThenNNTest_testTrainingContruction"): + "DecisionsToDataThenNNTest_testTrainingConstruction"): graph_builder = decisions_to_data_then_nn.DecisionsToDataThenNN( self.params) graph = graph_builder.training_graph(data, labels, None) diff --git a/tensorflow/core/BUILD b/tensorflow/core/BUILD index a1d61a79320..fce0663aa54 100644 --- a/tensorflow/core/BUILD +++ b/tensorflow/core/BUILD @@ -455,6 +455,7 @@ tf_cuda_library( "util/mirror_pad_mode.h", "util/padding.h", "util/port.h", + "util/ptr_util.h", "util/reffed_status_callback.h", "util/saved_tensor_slice_util.h", "util/sparse/group_iterator.h", @@ -493,6 +494,11 @@ cc_library( ], ) +cc_library( + name = "ptr_util", + hdrs = ["util/ptr_util.h"], +) + cc_library( name = "reader_base", srcs = ["framework/reader_base.cc"], diff --git a/tensorflow/core/graph/graph.h b/tensorflow/core/graph/graph.h index 223dd12f8fc..b620127d907 100644 --- a/tensorflow/core/graph/graph.h +++ b/tensorflow/core/graph/graph.h @@ -455,7 +455,6 @@ class Graph { // the corresponding NodeDef to reflect the change. // REQUIRES: The control edge must exist. void RemoveControlEdge(const Edge* e); - // Updates the input to a node. The existing edge to `dst` is removed and an // edge from `new_src` to `dst` is created. The NodeDef associated with `dst` // is also updated. diff --git a/tensorflow/core/grappler/optimizers/arithmetic_optimizer.cc b/tensorflow/core/grappler/optimizers/arithmetic_optimizer.cc index 6861a517954..efe8ac05a34 100644 --- a/tensorflow/core/grappler/optimizers/arithmetic_optimizer.cc +++ b/tensorflow/core/grappler/optimizers/arithmetic_optimizer.cc @@ -1068,7 +1068,7 @@ Status ArithmeticOptimizer::SimplifyArithmeticOps() { if (simplified_node != nullptr) { nodes_to_simplify.PushBack(simplified_node); } - // When `node` is simplifed to another node rather than in-place, the + // When `node` is simplified to another node rather than in-place, the // consumers of `node` are already redirected to `simplified_tensor`. // Re-push the consumers into `nodes_to_simplify` for further // optimizations. diff --git a/tensorflow/core/kernels/BUILD b/tensorflow/core/kernels/BUILD index 9279514e6ba..dcffb28513e 100644 --- a/tensorflow/core/kernels/BUILD +++ b/tensorflow/core/kernels/BUILD @@ -2583,8 +2583,13 @@ tf_kernel_library( tf_kernel_library( name = "batch_matmul_op", + srcs = [] + if_mkl([ + "mkl_batch_matmul_op.cc", + ]), prefix = "batch_matmul_op", - deps = MATH_DEPS, + deps = MATH_DEPS + if_mkl([ + "//third_party/mkl:intel_binary_blob", + ]), ) tf_kernel_library( @@ -6325,11 +6330,11 @@ cc_library( srcs = ["summary_interface.cc"], hdrs = ["summary_interface.h"], deps = [ - "//tensorflow/compiler/xla:util", "//tensorflow/core:framework", "//tensorflow/core:lib", "//tensorflow/core:lib_internal", "//tensorflow/core:protos_all_cc", + "//tensorflow/core:ptr_util", ], ) diff --git a/tensorflow/core/kernels/batch_matmul_op_complex.cc b/tensorflow/core/kernels/batch_matmul_op_complex.cc index a58ec027262..96216764fd4 100644 --- a/tensorflow/core/kernels/batch_matmul_op_complex.cc +++ b/tensorflow/core/kernels/batch_matmul_op_complex.cc @@ -17,8 +17,10 @@ limitations under the License. namespace tensorflow { +#if !defined(INTEL_MKL) TF_CALL_complex64(REGISTER_BATCH_MATMUL_CPU); TF_CALL_complex128(REGISTER_BATCH_MATMUL_CPU); +#endif #if GOOGLE_CUDA TF_CALL_complex64(REGISTER_BATCH_MATMUL_GPU); diff --git a/tensorflow/core/kernels/batch_matmul_op_real.cc b/tensorflow/core/kernels/batch_matmul_op_real.cc index 1900ed8e314..8d155ca62b2 100644 --- a/tensorflow/core/kernels/batch_matmul_op_real.cc +++ b/tensorflow/core/kernels/batch_matmul_op_real.cc @@ -17,8 +17,10 @@ limitations under the License. namespace tensorflow { +#if !defined(INTEL_MKL) TF_CALL_float(REGISTER_BATCH_MATMUL_CPU); TF_CALL_double(REGISTER_BATCH_MATMUL_CPU); +#endif TF_CALL_half(REGISTER_BATCH_MATMUL_CPU); TF_CALL_int32(REGISTER_BATCH_MATMUL_CPU); diff --git a/tensorflow/core/kernels/cwise_op_asinh.cc b/tensorflow/core/kernels/cwise_op_asinh.cc index a7673afd0bf..822d72e0685 100644 --- a/tensorflow/core/kernels/cwise_op_asinh.cc +++ b/tensorflow/core/kernels/cwise_op_asinh.cc @@ -4,7 +4,7 @@ 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 + 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, diff --git a/tensorflow/core/kernels/decode_bmp_op.cc b/tensorflow/core/kernels/decode_bmp_op.cc index 086369a9f12..6d9fdfcf33b 100644 --- a/tensorflow/core/kernels/decode_bmp_op.cc +++ b/tensorflow/core/kernels/decode_bmp_op.cc @@ -34,8 +34,10 @@ class DecodeBmpOp : public OpKernel { explicit DecodeBmpOp(OpKernelConstruction* context) : OpKernel(context) { OP_REQUIRES_OK(context, context->GetAttr("channels", &channels_)); OP_REQUIRES( - context, channels_ == 0 || channels_ == 3 || channels_ == 4, - errors::InvalidArgument("channels must be 0, 3 or 4, got ", channels_)); + context, + channels_ == 0 || channels_ == 1 || channels_ == 3 || channels_ == 4, + errors::InvalidArgument("channels must be 0, 1, 3 or 4, got ", + channels_)); } void Compute(OpKernelContext* context) override { @@ -66,11 +68,11 @@ class DecodeBmpOp : public OpKernel { channels_ = bpp / 8; } - // Current implementation only supports 3 or 4 channel + // Current implementation only supports 1, 3 or 4 channel // bitmaps. - OP_REQUIRES(context, (channels_ == 3 || channels_ == 4), + OP_REQUIRES(context, (channels_ == 1 || channels_ == 3 || channels_ == 4), errors::InvalidArgument( - "Number of channels must be 3 or 4, was ", channels_)); + "Number of channels must be 1, 3 or 4, was ", channels_)); // if height is negative, data layout is top down // otherwise, it's bottom up @@ -117,6 +119,9 @@ uint8* DecodeBmpOp::Decode(const uint8* input, uint8* const output, dst_pos = (i * width + j) * channels; switch (channels) { + case 1: + output[dst_pos] = input[src_pos]; + break; case 3: // BGR -> RGB output[dst_pos] = input[src_pos + 2]; diff --git a/tensorflow/core/kernels/dynamic_partition_op_test.cc b/tensorflow/core/kernels/dynamic_partition_op_test.cc index 0e8fbc0a67b..9a7ed0af217 100644 --- a/tensorflow/core/kernels/dynamic_partition_op_test.cc +++ b/tensorflow/core/kernels/dynamic_partition_op_test.cc @@ -16,6 +16,7 @@ limitations under the License. #include #include +#include "tensorflow/core/common_runtime/kernel_benchmark_testlib.h" #include "tensorflow/core/framework/allocator.h" #include "tensorflow/core/framework/fake_input.h" #include "tensorflow/core/framework/node_def_builder.h" @@ -23,10 +24,14 @@ limitations under the License. #include "tensorflow/core/framework/tensor.h" #include "tensorflow/core/framework/types.h" #include "tensorflow/core/framework/types.pb.h" +#include "tensorflow/core/graph/node_builder.h" +#include "tensorflow/core/graph/testlib.h" #include "tensorflow/core/kernels/ops_testutil.h" #include "tensorflow/core/kernels/ops_util.h" #include "tensorflow/core/lib/core/status_test_util.h" +#include "tensorflow/core/lib/random/simple_philox.h" #include "tensorflow/core/platform/test.h" +#include "tensorflow/core/platform/test_benchmark.h" namespace tensorflow { namespace { @@ -153,5 +158,58 @@ TEST_F(DynamicPartitionOpTest, Error_IndexOutOfRange) { << s; } +Node* DynamicPartitionNode(Graph* g, Node* in0, Node* in1, int num_partitions) { + Node* ret; + TF_CHECK_OK(NodeBuilder(g->NewName("n"), "DynamicPartition") + .Input(in0) + .Input(in1) + .Attr("num_partitions", num_partitions) + .Finalize(g, &ret)); + return ret; +} + +template +static Graph* DynamicPartition(int num_partitions, int dim) { + Graph* g = new Graph(OpRegistry::Global()); + // Always use a 128MB buffer. + const int kRows = ((128 << 20) / sizeof(T)) / dim; + Tensor data(DataTypeToEnum::value, TensorShape({kRows, dim})); + data.flat().setRandom(); + + random::PhiloxRandom philox(301, 17); + random::SimplePhilox rnd(&philox); + Tensor partitions(DT_INT32, TensorShape({kRows})); + for (int i = 0; i < kRows; i++) { + partitions.flat()(i) = rnd.Uniform(num_partitions); + } + DynamicPartitionNode(g, test::graph::Constant(g, data), + test::graph::Constant(g, partitions), num_partitions); + return g; +} + +#define BM_DYNAMIC_PARTITION(DEVICE, T, num) \ + static void BM_##DEVICE##_dynpart_##T##_##num(int iters, int dim) { \ + const int64 items = ((128 << 20) / sizeof(T)); \ + const int64 tot = static_cast(iters) * items; \ + testing::ItemsProcessed(tot); \ + testing::UseRealTime(); \ + test::Benchmark(#DEVICE, DynamicPartition(num, dim)).Run(iters); \ + } \ + BENCHMARK(BM_##DEVICE##_dynpart_##T##_##num)->Arg(1)->Arg(256) + +BM_DYNAMIC_PARTITION(cpu, float, 2); +BM_DYNAMIC_PARTITION(cpu, float, 100); +BM_DYNAMIC_PARTITION(cpu, double, 2); +BM_DYNAMIC_PARTITION(cpu, double, 100); +BM_DYNAMIC_PARTITION(cpu, complex64, 2); +BM_DYNAMIC_PARTITION(cpu, complex64, 100); + +BM_DYNAMIC_PARTITION(gpu, float, 2); +BM_DYNAMIC_PARTITION(gpu, float, 100); +BM_DYNAMIC_PARTITION(gpu, double, 2); +BM_DYNAMIC_PARTITION(gpu, double, 100); +BM_DYNAMIC_PARTITION(gpu, complex64, 2); +BM_DYNAMIC_PARTITION(gpu, complex64, 100); + } // namespace } // namespace tensorflow diff --git a/tensorflow/core/kernels/mkl_batch_matmul_op.cc b/tensorflow/core/kernels/mkl_batch_matmul_op.cc new file mode 100644 index 00000000000..d9713075be6 --- /dev/null +++ b/tensorflow/core/kernels/mkl_batch_matmul_op.cc @@ -0,0 +1,238 @@ +/* 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. +==============================================================================*/ + +// See docs in ../ops/math_ops.cc. + +// This file uses MKL CBLAS batched xGEMM for acceleration of TF Batch +// Matrix-Matrix Multiplication (MatMul) operations. +// We currently register this kernel only for MKL supported data +// types (float, double, complex64, complex128). The macro INTEL_MKL is defined +// by the build system only when MKL is chosen as an option at configure stage +// and when it is undefined at build time, this file becomes an empty +// compilation unit + +#define EIGEN_USE_THREADS + +#if defined(INTEL_MKL) +#include +#include "mkl_cblas.h" +#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor" +#include "tensorflow/core/framework/numeric_types.h" +#include "tensorflow/core/framework/op.h" +#include "tensorflow/core/framework/op_kernel.h" +#include "tensorflow/core/framework/register_types.h" +#include "tensorflow/core/framework/tensor.h" +#include "tensorflow/core/framework/tensor_shape.h" +#include "tensorflow/core/framework/type_traits.h" +#include "tensorflow/core/framework/types.h" +#include "tensorflow/core/kernels/fill_functor.h" +#include "tensorflow/core/platform/logging.h" +#include "tensorflow/core/platform/types.h" + +#define MKL_Complex8 tensorflow::complex64 +#define MKL_Complex16 tensorflow::complex128 + +namespace tensorflow { + +typedef Eigen::ThreadPoolDevice CPUDevice; + +template +class BatchMatMulMkl : public OpKernel { + public: + explicit BatchMatMulMkl(OpKernelConstruction *context) : OpKernel(context) { + OP_REQUIRES_OK(context, context->GetAttr("adj_x", &adj_x_)); + OP_REQUIRES_OK(context, context->GetAttr("adj_y", &adj_y_)); + } + + virtual ~BatchMatMulMkl() {} + + void Compute(OpKernelContext *ctx) override { + const Tensor &lhs = ctx->input(0); + const Tensor &rhs = ctx->input(1); + OP_REQUIRES(ctx, lhs.dims() == rhs.dims(), + errors::InvalidArgument("lhs and rhs has different ndims: ", + lhs.shape().DebugString(), " vs. ", + rhs.shape().DebugString())); + const int ndims = lhs.dims(); + OP_REQUIRES( + ctx, ndims >= 2, + errors::InvalidArgument("lhs and rhs ndims must be >= 2: ", ndims)); + TensorShape out_shape; + for (int i = 0; i < ndims - 2; ++i) { + OP_REQUIRES(ctx, lhs.dim_size(i) == rhs.dim_size(i), + errors::InvalidArgument( + "lhs.dim(", i, ") and rhs.dim(", i, + ") must be the same: ", lhs.shape().DebugString(), " vs ", + rhs.shape().DebugString())); + out_shape.AddDim(lhs.dim_size(i)); + } + auto batch_size = (ndims == 2) ? 1 : out_shape.num_elements(); + auto lhs_rows = lhs.dim_size(ndims - 2); + auto lhs_cols = lhs.dim_size(ndims - 1); + auto rhs_rows = rhs.dim_size(ndims - 2); + auto rhs_cols = rhs.dim_size(ndims - 1); + if (adj_x_) std::swap(lhs_rows, lhs_cols); + if (adj_y_) std::swap(rhs_rows, rhs_cols); + OP_REQUIRES(ctx, lhs_cols == rhs_rows, + errors::InvalidArgument( + "lhs mismatch rhs shape: ", lhs_cols, " vs. ", rhs_rows, + ": ", lhs.shape().DebugString(), " ", + rhs.shape().DebugString(), " ", adj_x_, " ", adj_y_)); + out_shape.AddDim(lhs_rows); + out_shape.AddDim(rhs_cols); + Tensor *out = nullptr; + OP_REQUIRES_OK(ctx, ctx->allocate_output(0, out_shape, &out)); + if (out->NumElements() == 0) { + return; + } + if (lhs.NumElements() == 0 || rhs.NumElements() == 0) { + functor::SetZeroFunctor f; + f(ctx->eigen_device(), out->flat()); + return; + } + + auto rhs_reshaped = rhs.template flat_inner_dims(); + auto lhs_reshaped = lhs.template flat_inner_dims(); + auto out_reshaped = out->template flat_inner_dims(); + const uint64 M = lhs_reshaped.dimension(adj_x_ ? 2 : 1); + const uint64 K = lhs_reshaped.dimension(adj_x_ ? 1 : 2); + const uint64 N = rhs_reshaped.dimension(adj_y_ ? 1 : 2); + + std::vector m_array(batch_size, M); + std::vector n_array(batch_size, N); + std::vector k_array(batch_size, K); + std::vector lda_array(batch_size, adj_x_ ? M : K); + std::vector ldb_array(batch_size, adj_y_ ? K : N); + std::vector ldc_array(batch_size, N); + std::vector group_size(1, batch_size); + std::vector a_array; + std::vector b_array; + std::vector c_array; + a_array.reserve(batch_size); + b_array.reserve(batch_size); + c_array.reserve(batch_size); + for (int64 i = 0; i < batch_size; i++) { + a_array.push_back(&lhs_reshaped(i, 0, 0)); + b_array.push_back(&rhs_reshaped(i, 0, 0)); + c_array.push_back(&out_reshaped(i, 0, 0)); + } + + MklCblasGemmBatch(CblasRowMajor, adj_x_, adj_y_, &m_array[0], &n_array[0], + &k_array[0], &a_array[0], &lda_array[0], &b_array[0], + &ldb_array[0], &c_array[0], &ldc_array[0], 1, + &group_size[0]); + } + + private: + bool adj_x_; + bool adj_y_; + + void MklCblasGemmBatch(const CBLAS_LAYOUT Layout, const bool TransA, + const bool TransB, const MKL_INT *M_Array, + const MKL_INT *N_Array, const MKL_INT *K_Array, + const float **A_Array, const MKL_INT *lda_Array, + const float **B_Array, const MKL_INT *ldb_Array, + float **C_Array, const MKL_INT *ldc_Array, + const MKL_INT group_count, const MKL_INT *group_size) { + std::vector TransA_Array( + group_size[0], TransA ? CblasTrans : CblasNoTrans); + std::vector TransB_Array( + group_size[0], TransB ? CblasTrans : CblasNoTrans); + std::vector alpha_Array(group_size[0], 1.0); + std::vector beta_Array(group_size[0], 0.0); + cblas_sgemm_batch(Layout, &TransA_Array[0], &TransB_Array[0], M_Array, + N_Array, K_Array, &alpha_Array[0], A_Array, lda_Array, + B_Array, ldb_Array, &beta_Array[0], C_Array, ldc_Array, + group_count, group_size); + } + + void MklCblasGemmBatch(const CBLAS_LAYOUT Layout, const bool TransA, + const bool TransB, const MKL_INT *M_Array, + const MKL_INT *N_Array, const MKL_INT *K_Array, + const double **A_Array, const MKL_INT *lda_Array, + const double **B_Array, const MKL_INT *ldb_Array, + double **C_Array, const MKL_INT *ldc_Array, + const MKL_INT group_count, const MKL_INT *group_size) { + std::vector TransA_array( + group_size[0], TransA ? CblasTrans : CblasNoTrans); + std::vector TransB_array( + group_size[0], TransB ? CblasTrans : CblasNoTrans); + std::vector alpha_Array(group_size[0], 1.0); + std::vector beta_Array(group_size[0], 0.0); + cblas_dgemm_batch(Layout, &TransA_array[0], &TransB_array[0], M_Array, + N_Array, K_Array, &alpha_Array[0], A_Array, lda_Array, + B_Array, ldb_Array, &beta_Array[0], C_Array, ldc_Array, + group_count, group_size); + } + + void MklCblasGemmBatch(const CBLAS_LAYOUT Layout, const bool TransA, + const bool TransB, const MKL_INT *M_Array, + const MKL_INT *N_Array, const MKL_INT *K_Array, + const MKL_Complex8 **A_Array, const MKL_INT *lda_Array, + const MKL_Complex8 **B_Array, const MKL_INT *ldb_Array, + MKL_Complex8 **C_Array, const MKL_INT *ldc_Array, + const MKL_INT group_count, const MKL_INT *group_size) { + std::vector TransA_array( + group_size[0], TransA ? CblasConjTrans : CblasNoTrans); + std::vector TransB_array( + group_size[0], TransB ? CblasConjTrans : CblasNoTrans); + std::vector alpha_Array(group_size[0], {1.0f, 0.0f}); + std::vector beta_Array(group_size[0], {0.0f, 0.0f}); + cblas_cgemm_batch( + Layout, &TransA_array[0], &TransB_array[0], M_Array, N_Array, K_Array, + static_cast(&alpha_Array[0]), + reinterpret_cast(A_Array), lda_Array, + reinterpret_cast(B_Array), ldb_Array, + static_cast(&beta_Array[0]), + reinterpret_cast(C_Array), ldc_Array, group_count, group_size); + } + + void MklCblasGemmBatch(const CBLAS_LAYOUT Layout, const bool TransA, + const bool TransB, const MKL_INT *M_Array, + const MKL_INT *N_Array, const MKL_INT *K_Array, + const MKL_Complex16 **A_Array, + const MKL_INT *lda_Array, + const MKL_Complex16 **B_Array, + const MKL_INT *ldb_Array, MKL_Complex16 **C_Array, + const MKL_INT *ldc_Array, const MKL_INT group_count, + const MKL_INT *group_size) { + std::vector TransA_array( + group_size[0], TransA ? CblasConjTrans : CblasNoTrans); + std::vector TransB_array( + group_size[0], TransB ? CblasConjTrans : CblasNoTrans); + std::vector alpha_Array(group_size[0], {1.0f, 0.0f}); + std::vector beta_Array(group_size[0], {0.0f, 0.0f}); + cblas_zgemm_batch( + Layout, &TransA_array[0], &TransB_array[0], M_Array, N_Array, K_Array, + static_cast(&alpha_Array[0]), + reinterpret_cast(A_Array), lda_Array, + reinterpret_cast(B_Array), ldb_Array, + static_cast(&beta_Array[0]), + reinterpret_cast(C_Array), ldc_Array, group_count, group_size); + } +}; + +#define REGISTER_BATCH_MATMUL_MKL(TYPE) \ + REGISTER_KERNEL_BUILDER( \ + Name("BatchMatMul").Device(DEVICE_CPU).TypeConstraint("T"), \ + BatchMatMulMkl) + +TF_CALL_float(REGISTER_BATCH_MATMUL_MKL); +TF_CALL_double(REGISTER_BATCH_MATMUL_MKL); +TF_CALL_complex64(REGISTER_BATCH_MATMUL_MKL); +TF_CALL_complex128(REGISTER_BATCH_MATMUL_MKL); + +} // end namespace tensorflow +#endif diff --git a/tensorflow/core/kernels/prefetch_dataset_op.cc b/tensorflow/core/kernels/prefetch_dataset_op.cc index 1a6b7e078eb..b02269f525a 100644 --- a/tensorflow/core/kernels/prefetch_dataset_op.cc +++ b/tensorflow/core/kernels/prefetch_dataset_op.cc @@ -37,6 +37,8 @@ class PrefetchDatasetOp : public UnaryDatasetOpKernel { int64 buffer_size; OP_REQUIRES_OK( ctx, ParseScalarArgument(ctx, "buffer_size", &buffer_size)); + OP_REQUIRES(ctx, buffer_size > 0, + errors::InvalidArgument("buffer_size must be > 0")); *output = new Dataset(ctx, input, buffer_size); } diff --git a/tensorflow/core/kernels/summary_interface.cc b/tensorflow/core/kernels/summary_interface.cc index ad28d77ffde..97c0c2c099c 100644 --- a/tensorflow/core/kernels/summary_interface.cc +++ b/tensorflow/core/kernels/summary_interface.cc @@ -16,7 +16,6 @@ limitations under the License. #include -#include "tensorflow/compiler/xla/ptr_util.h" #include "tensorflow/core/framework/graph.pb.h" #include "tensorflow/core/framework/op_kernel.h" #include "tensorflow/core/framework/resource_mgr.h" @@ -28,6 +27,7 @@ limitations under the License. #include "tensorflow/core/lib/png/png_io.h" #include "tensorflow/core/lib/wav/wav_io.h" #include "tensorflow/core/util/events_writer.h" +#include "tensorflow/core/util/ptr_util.h" namespace tensorflow { namespace { @@ -229,7 +229,7 @@ class SummaryWriterImpl : public SummaryWriterInterface { } mutex_lock ml(mu_); events_writer_ = - xla::MakeUnique(io::JoinPath(logdir, "events")); + tensorflow::MakeUnique(io::JoinPath(logdir, "events")); if (!events_writer_->InitWithSuffix(filename_suffix)) { return errors::Unknown("Could not initialize events writer."); } diff --git a/tensorflow/core/lib/io/path.cc b/tensorflow/core/lib/io/path.cc index d93dd0296e4..83f15e134d6 100644 --- a/tensorflow/core/lib/io/path.cc +++ b/tensorflow/core/lib/io/path.cc @@ -14,8 +14,22 @@ limitations under the License. ==============================================================================*/ #include "tensorflow/core/lib/io/path.h" + +#include +#include +#include +#include +#include +#if !defined(PLATFORM_WINDOWS) +#include +#endif + +#include + #include "tensorflow/core/lib/strings/scanner.h" +#include "tensorflow/core/lib/strings/str_util.h" #include "tensorflow/core/lib/strings/strcat.h" +#include "tensorflow/core/platform/env.h" namespace tensorflow { namespace io { @@ -60,8 +74,7 @@ std::pair SplitPath(StringPiece uri) { auto pos = path.rfind('/'); #ifdef PLATFORM_WINDOWS - if (pos == StringPiece::npos) - pos = path.rfind('\\'); + if (pos == StringPiece::npos) pos = path.rfind('\\'); #endif // Handle the case with no '/' in 'path'. if (pos == StringPiece::npos) @@ -112,7 +125,7 @@ StringPiece Extension(StringPiece path) { string CleanPath(StringPiece unclean_path) { string path = unclean_path.ToString(); - const char *src = path.c_str(); + const char* src = path.c_str(); string::iterator dst = path.begin(); // Check for absolute path and determine initial backtrack limit. @@ -229,5 +242,52 @@ string CreateURI(StringPiece scheme, StringPiece host, StringPiece path) { return strings::StrCat(scheme, "://", host, path); } +// Returns a unique number every time it is called. +int64 UniqueId() { + static mutex mu(LINKER_INITIALIZED); + static int64 id = 0; + mutex_lock l(mu); + return ++id; +} + +string GetTempFilename(const string& extension) { +#if defined(PLATFORM_WINDOWS) || defined(__ANDROID__) + LOG(FATAL) << "GetTempFilename is not implemented in this platform."; +#else + for (const char* dir : std::vector( + {getenv("TEST_TMPDIR"), getenv("TMPDIR"), getenv("TMP"), "/tmp"})) { + if (!dir || !dir[0]) { + continue; + } + struct stat statbuf; + if (!stat(dir, &statbuf) && S_ISDIR(statbuf.st_mode)) { + // UniqueId is added here because mkstemps is not as thread safe as it + // looks. https://github.com/tensorflow/tensorflow/issues/5804 shows + // the problem. + string tmp_filepath; + int fd; + if (extension.length()) { + tmp_filepath = io::JoinPath( + dir, strings::StrCat("tmp_file_tensorflow_", UniqueId(), "_XXXXXX.", + extension)); + fd = mkstemps(&tmp_filepath[0], extension.length() + 1); + } else { + tmp_filepath = io::JoinPath( + dir, + strings::StrCat("tmp_file_tensorflow_", UniqueId(), "_XXXXXX")); + fd = mkstemp(&tmp_filepath[0]); + } + if (fd < 0) { + LOG(FATAL) << "Failed to create temp file."; + } else { + close(fd); + return tmp_filepath; + } + } + } + LOG(FATAL) << "No temp directory found."; +#endif +} + } // namespace io } // namespace tensorflow diff --git a/tensorflow/core/lib/io/path.h b/tensorflow/core/lib/io/path.h index 8d02baa5bb6..47bb2b998d6 100644 --- a/tensorflow/core/lib/io/path.h +++ b/tensorflow/core/lib/io/path.h @@ -89,6 +89,9 @@ void ParseURI(tensorflow::StringPiece uri, tensorflow::StringPiece* scheme, string CreateURI(tensorflow::StringPiece scheme, tensorflow::StringPiece host, tensorflow::StringPiece path); +// Creates a temporary file name with an extension. +string GetTempFilename(const string& extension); + } // namespace io } // namespace tensorflow diff --git a/tensorflow/core/ops/math_ops.cc b/tensorflow/core/ops/math_ops.cc index d7afd02df6b..ceda11663a8 100644 --- a/tensorflow/core/ops/math_ops.cc +++ b/tensorflow/core/ops/math_ops.cc @@ -2333,11 +2333,25 @@ REGISTER_OP("Cross") .Input("b: T") .Output("product: T") .Attr("T: realnumbertype") - // TODO(cwhipkey): implement these shape inference constraints here: - // * Both inputs have the same shape. - // * Input rank >= 1. - // * input_shape[-1] == 3. - .SetShapeFn(shape_inference::UnchangedShape) + .SetShapeFn([](InferenceContext* c) { + ShapeHandle a_shape; + ShapeHandle b_shape; + // * Input rank >= 1. + TF_RETURN_IF_ERROR(c->WithRankAtLeast(c->input(0), 1, &a_shape)); + TF_RETURN_IF_ERROR(c->WithRankAtLeast(c->input(1), 1, &b_shape)); + + // * Both inputs have the same shape. + TF_RETURN_IF_ERROR(c->Merge(a_shape, b_shape, &a_shape)); + + // * input_shape[-1] == 3. + if (c->RankKnown(a_shape)) { + int rank = c->Rank(a_shape); + auto dim = c->Dim(a_shape, rank - 1); + TF_RETURN_IF_ERROR(c->WithValue(dim, 3, &dim)); + } + c->set_output(0, a_shape); + return Status::OK(); + }) .Doc(R"doc( Compute the pairwise cross product. diff --git a/tensorflow/core/ops/math_ops_test.cc b/tensorflow/core/ops/math_ops_test.cc index 28f9969de56..3dfa776d26f 100644 --- a/tensorflow/core/ops/math_ops_test.cc +++ b/tensorflow/core/ops/math_ops_test.cc @@ -515,4 +515,15 @@ TEST(MathOpstest, RequantizationRange_ShapeFn) { INFER_ERROR("must be rank 0", op, "?;?;[2]"); } +TEST(MathOpsTest, Cross_ShapeFn) { + ShapeInferenceTestOp op("Cross"); + + INFER_ERROR("Shape must be at least rank 1 but is rank 0", op, "[];[]"); + INFER_ERROR("Dimension 0 in both shapes must be equal, but", op, "[3];[5]"); + INFER_ERROR("Dimension must be 3 but", op, "[3,5];[3,5]"); + + INFER_OK(op, "?;?", "?"); + INFER_OK(op, "[?];[?]", "in0"); + INFER_OK(op, "[1,?,3];[?,?,?]", "in0"); +} } // end namespace tensorflow diff --git a/tensorflow/core/platform/default/build_config_root.bzl b/tensorflow/core/platform/default/build_config_root.bzl index c63fb28ff92..6e98f12114e 100644 --- a/tensorflow/core/platform/default/build_config_root.bzl +++ b/tensorflow/core/platform/default/build_config_root.bzl @@ -10,7 +10,9 @@ def tf_sycl_tests_tags(): def tf_additional_plugin_deps(): return select({ - "//tensorflow:with_xla_support": ["//tensorflow/compiler/jit"], + str(Label("//tensorflow:with_xla_support")): [ + str(Label("//tensorflow/compiler/jit")) + ], "//conditions:default": [], }) @@ -19,37 +21,37 @@ def tf_additional_xla_deps_py(): def tf_additional_license_deps(): return select({ - "//tensorflow:with_xla_support": ["@llvm//:LICENSE.TXT"], + str(Label("//tensorflow:with_xla_support")): ["@llvm//:LICENSE.TXT"], "//conditions:default": [], }) def tf_additional_verbs_deps(): return select({ - "//tensorflow:with_verbs_support": [ - "//tensorflow/contrib/verbs:verbs_server_lib", - "//tensorflow/contrib/verbs:grpc_verbs_client", + str(Label("//tensorflow:with_verbs_support")): [ + str(Label("//tensorflow/contrib/verbs:verbs_server_lib")), + str(Label("//tensorflow/contrib/verbs:grpc_verbs_client")), ], "//conditions:default": [], }) def tf_additional_mpi_deps(): return select({ - "//tensorflow:with_mpi_support": [ - "//tensorflow/contrib/mpi:mpi_server_lib", + str(Label("//tensorflow:with_mpi_support")): [ + str(Label("//tensorflow/contrib/mpi:mpi_server_lib")), ], "//conditions:default": [], }) def tf_additional_gdr_deps(): return select({ - "//tensorflow:with_gdr_support": [ - "//tensorflow/contrib/gdr:gdr_server_lib", + str(Label("//tensorflow:with_gdr_support")): [ + str(Label("//tensorflow/contrib/gdr:gdr_server_lib")), ], "//conditions:default": [], }) def if_static(extra_deps, otherwise=[]): return select({ - "//tensorflow:framework_shared_object": otherwise, + str(Label("//tensorflow:framework_shared_object")): otherwise, "//conditions:default": extra_deps, }) diff --git a/tensorflow/core/util/ptr_util.h b/tensorflow/core/util/ptr_util.h new file mode 100644 index 00000000000..f902b3ffa12 --- /dev/null +++ b/tensorflow/core/util/ptr_util.h @@ -0,0 +1,80 @@ +/* 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_CORE_UTIL_PTR_UTIL_H_ +#define TENSORFLOW_CORE_UTIL_PTR_UTIL_H_ + +// Utility functions for pointers. + +#include + +#include +#include +#include + +namespace tensorflow { + +namespace helper { + +// Trait to select overloads and return types for MakeUnique. +template +struct MakeUniqueResult { + using scalar = std::unique_ptr; +}; +template +struct MakeUniqueResult { + using array = std::unique_ptr; +}; +template +struct MakeUniqueResult { + using invalid = void; +}; + +} // namespace helper + +// Transfers ownership of a raw pointer to a std::unique_ptr of deduced type. +// Example: +// X* NewX(int, int); +// auto x = WrapUnique(NewX(1, 2)); // 'x' is std::unique_ptr. +// +// WrapUnique is useful for capturing the output of a raw pointer factory. +// However, prefer 'MakeUnique(args...) over 'WrapUnique(new T(args...))'. +// auto x = WrapUnique(new X(1, 2)); // works, but nonideal. +// auto x = MakeUnique(1, 2); // safer, standard, avoids raw 'new'. +// +// Note: Cannot wrap pointers to array of unknown bound (i.e. U(*)[]). +template +std::unique_ptr WrapUnique(T* ptr) { + static_assert(!std::is_array::value || std::extent::value != 0, + "types T[0] or T[] are unsupported"); + return std::unique_ptr(ptr); +} + +template +typename helper::MakeUniqueResult::scalar MakeUnique(Args&&... args) { + return std::unique_ptr(new T(std::forward(args)...)); +} + +// Overload for array of unknown bound. +// The allocation of arrays needs to use the array form of new, +// and cannot take element constructor arguments. +template +typename helper::MakeUniqueResult::array MakeUnique(size_t n) { + return std::unique_ptr(new typename std::remove_extent::type[n]()); +} + +} // namespace tensorflow + +#endif // TENSORFLOW_CORE_UTIL_PTR_UTIL_H_ diff --git a/tensorflow/docs_src/extend/adding_an_op.md b/tensorflow/docs_src/extend/adding_an_op.md index 15d6d77f5ef..c52279b212f 100644 --- a/tensorflow/docs_src/extend/adding_an_op.md +++ b/tensorflow/docs_src/extend/adding_an_op.md @@ -341,9 +341,9 @@ Assuming you have `g++` installed, here is the sequence of commands you can use to compile your op into a dynamic library. ```bash -TF_INC=$(python -c 'import tensorflow as tf; print(tf.sysconfig.get_include())') -TF_LIB=$(python -c 'import tensorflow as tf; print(tf.sysconfig.get_lib())') -g++ -std=c++11 -shared zero_out.cc -o zero_out.so -fPIC -I$TF_INC -I$TF_INC/external/nsync/public -L$TF_LIB -ltensorflow_framework -O2 +TF_CFLAGS=( $(python -c 'import tensorflow as tf; print(" ".join(tf.sysconfig.get_compile_flags()))') ) +TF_LFLAGS=( $(python -c 'import tensorflow as tf; print(" ".join(tf.sysconfig.get_link_flags()))') ) +g++ -std=c++11 -shared zero_out.cc -o zero_out.so -fPIC ${TF_CFLAGS[@]} ${TF_LFLAGS[@]} -O2 ``` On Mac OS X, the additional flag "-undefined dynamic_lookup" is required when @@ -451,17 +451,17 @@ Now that you know how to build a basic (and somewhat restricted) op and implementation, we'll look at some of the more complicated things you will typically need to build into your op. This includes: -* [Conditional checks and validation](#conditional_checks_and_validation) -* [Op registration](#op_registration) +* [Conditional checks and validation](#conditional-checks-and-validation) +* [Op registration](#op-registration) * [Attrs](#attrs) - * [Attr types](#attr_types) + * [Attr types](#attr-types) * [Polymorphism](#polymorphism) - * [Inputs and outputs](#inputs_and_outputs) - * [Backwards compatibility](#backwards_compatibility) -* [GPU support](#gpu_support) - * [Compiling the kernel for the GPU device](#compiling_the_kernel_for_the_gpu_device) -* [Implement the gradient in Python](#implement_the_gradient_in_python) -* [Shape functions in C++](#shape_functions_in_c) + * [Inputs and outputs](#inputs-and-outputs) + * [Backwards compatibility](#backwards-compatibility) +* [GPU support](#gpu-support) + * [Compiling the kernel for the GPU device](#compiling-the-kernel-for-the-gpu-device) +* [Implement the gradient in Python](#implement-the-gradient-in-python) +* [Shape functions in C++](#shape-functions-in-c) ### Conditional checks and validation @@ -1228,10 +1228,10 @@ into a single dynamically loadable library: ```bash nvcc -std=c++11 -c -o cuda_op_kernel.cu.o cuda_op_kernel.cu.cc \ --I $TF_INC -I$TF_INC/external/nsync/public -D GOOGLE_CUDA=1 -x cu -Xcompiler -fPIC + ${TF_CFLAGS[@]} -D GOOGLE_CUDA=1 -x cu -Xcompiler -fPIC g++ -std=c++11 -shared -o cuda_op_kernel.so cuda_op_kernel.cc \ -cuda_op_kernel.cu.o -I $TF_INC -I$TF_INC/external/nsync/public -fPIC -lcudart -L$TF_LIB -ltensorflow_framework + cuda_op_kernel.cu.o ${TF_CFLAGS[@]} -fPIC -lcudart ${TF_LFLAGS[@]} ``` `cuda_op_kernel.so` produced above can be loaded as usual in Python, using the diff --git a/tensorflow/docs_src/get_started/input_fn.md b/tensorflow/docs_src/get_started/input_fn.md index 0db5c6143af..f0dcdc47ff1 100644 --- a/tensorflow/docs_src/get_started/input_fn.md +++ b/tensorflow/docs_src/get_started/input_fn.md @@ -211,8 +211,8 @@ def get_input_fn_from_numpy(data_set, num_epochs=None, shuffle=True): ### A Neural Network Model for Boston House Values In the remainder of this tutorial, you'll write an input function for -preprocessing a subset of Boston housing data pulled from the [UCI Housing Data -Set](https://archive.ics.uci.edu/ml/datasets/Housing) and use it to feed data to +preprocessing a subset of Boston housing data pulled from the UCI Housing Data +Set and use it to feed data to a neural network regressor for predicting median house values. The [Boston CSV data sets](#setup) you'll use to train your neural network diff --git a/tensorflow/docs_src/install/install_windows.md b/tensorflow/docs_src/install/install_windows.md index 63742828b00..8d0eb7966fd 100644 --- a/tensorflow/docs_src/install/install_windows.md +++ b/tensorflow/docs_src/install/install_windows.md @@ -84,7 +84,7 @@ install it now: * [Python 3.5.x 64-bit from python.org](https://www.python.org/downloads/release/python-352/) * [Python 3.6.x 64-bit from python.org](https://www.python.org/downloads/release/python-362/) --TensorFlow supports Python 3.5.x and 3.6.x on Windows. +TensorFlow supports Python 3.5.x and 3.6.x on Windows. Note that Python 3 comes with the pip3 package manager, which is the program you'll use to install TensorFlow. @@ -98,7 +98,6 @@ To install the GPU version of TensorFlow, enter the following command: 
C:\> pip3 install --upgrade tensorflow-gpu
- ## Installing with Anaconda **The Anaconda installation is community supported, not officially supported.** @@ -219,6 +218,11 @@ ImportError: cannot import name 'descriptor' + + 38896424 + + 
Could not find a version that satisfies the requirement tensorflow
+ + - diff --git a/tensorflow/docs_src/mobile/ios_build.md b/tensorflow/docs_src/mobile/ios_build.md index a04655052fc..4c84a1214a2 100644 --- a/tensorflow/docs_src/mobile/ios_build.md +++ b/tensorflow/docs_src/mobile/ios_build.md @@ -98,7 +98,7 @@ There are three demo applications for iOS, all defined in Xcode projects inside ## Building the TensorFlow iOS libraries from source -While Cocapods is the quickest and easiest way of getting started, you sometimes +While Cocoapods is the quickest and easiest way of getting started, you sometimes need more flexibility to determine which parts of TensorFlow your app should be shipped with. For such cases, you can build the iOS libraries from the sources. [This diff --git a/tensorflow/docs_src/mobile/mobile_intro.md b/tensorflow/docs_src/mobile/mobile_intro.md index 3a002c4da2a..17dbf1c3e6a 100644 --- a/tensorflow/docs_src/mobile/mobile_intro.md +++ b/tensorflow/docs_src/mobile/mobile_intro.md @@ -156,7 +156,7 @@ easy cases on device. Doing on-device computation can also signal when it's time to switch to working on the cloud. A good example of this is hotword detection in speech. Since devices are able to constantly listen out for the keywords, this then triggers a -lot of traffic to cloud-based speech recognition once one is recognised. Without +lot of traffic to cloud-based speech recognition once one is recognized. Without the on-device component, the whole application wouldn’t be feasible, and this pattern exists across several other applications as well. Recognizing that some sensor input is interesting enough for further processing makes a lot of diff --git a/tensorflow/docs_src/mobile/optimizing.md b/tensorflow/docs_src/mobile/optimizing.md index d9e8875c385..44cacff5dbb 100644 --- a/tensorflow/docs_src/mobile/optimizing.md +++ b/tensorflow/docs_src/mobile/optimizing.md @@ -115,7 +115,7 @@ If you look at the resulting file size, you should see that it’s about a quart of the original at 23MB. Another transform is `round_weights`, which doesn't make the file smaller, but it -makes the file compressable to about the same size as when `quantize_weights` is +makes the file compressible to about the same size as when `quantize_weights` is used. This is particularly useful for mobile development, taking advantage of the fact that app bundles are compressed before they’re downloaded by consumers. diff --git a/tensorflow/docs_src/performance/xla/operation_semantics.md b/tensorflow/docs_src/performance/xla/operation_semantics.md index 4333f94486b..a49973d550b 100644 --- a/tensorflow/docs_src/performance/xla/operation_semantics.md +++ b/tensorflow/docs_src/performance/xla/operation_semantics.md @@ -776,7 +776,7 @@ The output type is a tuple of three ComputationDataHandles: | `batch_var` | `ComputationDataHandle` | 1 dimensional array (\\(\sigma^2\\)) | The `batch_mean` and `batch_var` are moments calculated across the batch and -spatial dimensions using the formulars above. +spatial dimensions using the formulas above. ## BatchNormInference diff --git a/tensorflow/docs_src/tutorials/image_recognition.md b/tensorflow/docs_src/tutorials/image_recognition.md index df13eabead8..32257f87d66 100644 --- a/tensorflow/docs_src/tutorials/image_recognition.md +++ b/tensorflow/docs_src/tutorials/image_recognition.md @@ -5,7 +5,7 @@ tell apart a lion and a jaguar, read a sign, or recognize a human's face. But these are actually hard problems to solve with a computer: they only seem easy because our brains are incredibly good at understanding images. -In the last few years the field of machine learning has made tremendous +In the last few years, the field of machine learning has made tremendous progress on addressing these difficult problems. In particular, we've found that a kind of model called a deep [convolutional neural network](https://colah.github.io/posts/2014-07-Conv-Nets-Modular/) diff --git a/tensorflow/examples/how_tos/reading_data/convert_to_records.py b/tensorflow/examples/how_tos/reading_data/convert_to_records.py index d14c1f7c86b..c89e8395632 100644 --- a/tensorflow/examples/how_tos/reading_data/convert_to_records.py +++ b/tensorflow/examples/how_tos/reading_data/convert_to_records.py @@ -52,17 +52,19 @@ def convert_to(data_set, name): filename = os.path.join(FLAGS.directory, name + '.tfrecords') print('Writing', filename) - writer = tf.python_io.TFRecordWriter(filename) - for index in range(num_examples): - image_raw = images[index].tostring() - example = tf.train.Example(features=tf.train.Features(feature={ - 'height': _int64_feature(rows), - 'width': _int64_feature(cols), - 'depth': _int64_feature(depth), - 'label': _int64_feature(int(labels[index])), - 'image_raw': _bytes_feature(image_raw)})) - writer.write(example.SerializeToString()) - writer.close() + with tf.python_io.TFRecordWriter(filename) as writer: + for index in range(num_examples): + image_raw = images[index].tostring() + example = tf.train.Example( + features=tf.train.Features( + feature={ + 'height': _int64_feature(rows), + 'width': _int64_feature(cols), + 'depth': _int64_feature(depth), + 'label': _int64_feature(int(labels[index])), + 'image_raw': _bytes_feature(image_raw) + })) + writer.write(example.SerializeToString()) def main(unused_argv): diff --git a/tensorflow/examples/speech_commands/input_data.py b/tensorflow/examples/speech_commands/input_data.py index 6d75fbb92b2..751652b330c 100644 --- a/tensorflow/examples/speech_commands/input_data.py +++ b/tensorflow/examples/speech_commands/input_data.py @@ -240,7 +240,8 @@ class AudioProcessor(object): # Look through all the subfolders to find audio samples search_path = os.path.join(self.data_dir, '*', '*.wav') for wav_path in gfile.Glob(search_path): - word = re.search('.*/([^/]+)/.*.wav', wav_path).group(1).lower() + _, word = os.path.split(os.path.dirname(wav_path)) + word = word.lower() # Treat the '_background_noise_' folder as a special case, since we expect # it to contain long audio samples we mix in to improve training. if word == BACKGROUND_NOISE_DIR_NAME: diff --git a/tensorflow/examples/speech_commands/train.py b/tensorflow/examples/speech_commands/train.py index a54bcbdb323..f5bf04305a7 100644 --- a/tensorflow/examples/speech_commands/train.py +++ b/tensorflow/examples/speech_commands/train.py @@ -156,7 +156,8 @@ def main(_): predicted_indices = tf.argmax(logits, 1) expected_indices = tf.argmax(ground_truth_input, 1) correct_prediction = tf.equal(predicted_indices, expected_indices) - confusion_matrix = tf.confusion_matrix(expected_indices, predicted_indices) + confusion_matrix = tf.confusion_matrix( + expected_indices, predicted_indices, num_classes=label_count) evaluation_step = tf.reduce_mean(tf.cast(correct_prediction, tf.float32)) tf.summary.scalar('accuracy', evaluation_step) diff --git a/tensorflow/examples/udacity/1_notmnist.ipynb b/tensorflow/examples/udacity/1_notmnist.ipynb index 39674e1aa49..dffe5d37c64 100644 --- a/tensorflow/examples/udacity/1_notmnist.ipynb +++ b/tensorflow/examples/udacity/1_notmnist.ipynb @@ -46,13 +46,13 @@ "# These are all the modules we'll be using later. Make sure you can import them\n", "# before proceeding further.\n", "from __future__ import print_function\n", + "import imageio\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import os\n", "import sys\n", "import tarfile\n", "from IPython.display import display, Image\n", - "from scipy import ndimage\n", "from sklearn.linear_model import LogisticRegression\n", "from six.moves.urllib.request import urlretrieve\n", "from six.moves import cPickle as pickle\n", @@ -325,13 +325,13 @@ " for image in image_files:\n", " image_file = os.path.join(folder, image)\n", " try:\n", - " image_data = (ndimage.imread(image_file).astype(float) - \n", + " image_data = (imageio.imread(image_file).astype(float) - \n", " pixel_depth / 2) / pixel_depth\n", " if image_data.shape != (image_size, image_size):\n", " raise Exception('Unexpected image shape: %s' % str(image_data.shape))\n", " dataset[num_images, :, :] = image_data\n", " num_images = num_images + 1\n", - " except IOError as e:\n", + " except (IOError, ValueError) as e:\n", " print('Could not read:', image_file, ':', e, '- it\\'s ok, skipping.')\n", " \n", " dataset = dataset[0:num_images, :, :]\n", diff --git a/tensorflow/java/src/main/java/org/tensorflow/OperationBuilder.java b/tensorflow/java/src/main/java/org/tensorflow/OperationBuilder.java index 9a1b7592b38..a24150484e8 100644 --- a/tensorflow/java/src/main/java/org/tensorflow/OperationBuilder.java +++ b/tensorflow/java/src/main/java/org/tensorflow/OperationBuilder.java @@ -265,6 +265,36 @@ public final class OperationBuilder { return this; } + public OperationBuilder setAttr(String name, Shape[] value) { + int[] numDimensions = new int[value.length]; + int totalNumDimensions = 0; + for (int idx = 0; idx < value.length; ++idx) { + int n = value[idx].numDimensions(); + numDimensions[idx] = n; + if (n > 0) { + totalNumDimensions += n; + } + } + // Flatten the shapes into a single array to avoid too much overhead in the + // native part + long[] shapes = new long[totalNumDimensions]; + int shapeIdx = 0; + for (Shape shape : value) { + if (shape.numDimensions() > 0) { + for (long dim : shape.asArray()) { + shapes[shapeIdx++] = dim; + } + } + } + Graph.Reference r = graph.ref(); + try { + setAttrShapeList(unsafeNativeHandle, name, shapes, numDimensions); + } finally { + r.close(); + } + return this; + } + public OperationBuilder setAttr(String name, String[] value) { Charset utf8 = Charset.forName("UTF-8"); Object[] objects = new Object[value.length]; @@ -297,8 +327,6 @@ public final class OperationBuilder { // The names of all the setAttr* family functions below correspond to the C library types, not the // Java library types. Roughly, setAttrFoo calls the TensorFlow C library function: TF_SetAttrFoo. - // TODO(ashankar): - // - setAttrShapeList: Which would take in a long[][] private static native void setAttrString(long handle, String name, byte[] value); @@ -324,5 +352,8 @@ public final class OperationBuilder { private static native void setAttrShape(long handle, String name, long[] shape, int numDims); + private static native void setAttrShapeList( + long handle, String name, long[] shapes, int[] numDims); + private static native void setAttrStringList(long handle, String name, Object[] value); } diff --git a/tensorflow/java/src/main/native/operation_builder_jni.cc b/tensorflow/java/src/main/native/operation_builder_jni.cc index e03be7b1103..55d214a7c4b 100644 --- a/tensorflow/java/src/main/native/operation_builder_jni.cc +++ b/tensorflow/java/src/main/native/operation_builder_jni.cc @@ -15,6 +15,7 @@ limitations under the License. #include "tensorflow/java/src/main/native/operation_builder_jni.h" +#include #include #include "tensorflow/c/c_api.h" #include "tensorflow/java/src/main/native/exception_jni.h" @@ -262,6 +263,41 @@ JNIEXPORT void JNICALL Java_org_tensorflow_OperationBuilder_setAttrShape( env->ReleaseStringUTFChars(name, cname); } +JNIEXPORT void JNICALL Java_org_tensorflow_OperationBuilder_setAttrShapeList( + JNIEnv* env, jclass clazz, jlong handle, jstring name, jlongArray shapes, + jintArray num_dims) { + TF_OperationDescription* d = requireHandle(env, handle); + if (d == nullptr) return; + std::unique_ptr cshapes; + std::unique_ptr cdims; + std::unique_ptr cnum_dims; + const int num_dims_length = env->GetArrayLength(num_dims); + if (num_dims_length > 0) { + const int shapes_length = env->GetArrayLength(shapes); + cshapes.reset(new int64_t[shapes_length]); + cdims.reset(new int64_t*[num_dims_length]); + cnum_dims.reset(new int[num_dims_length]); + jlong* shapes_elems = + static_cast(env->GetPrimitiveArrayCritical(shapes, nullptr)); + std::memcpy(cshapes.get(), shapes_elems, shapes_length << 3); + env->ReleasePrimitiveArrayCritical(shapes, shapes_elems, JNI_ABORT); + int64_t* cshapes_ptr = cshapes.get(); + jint* num_dims_elems = + static_cast(env->GetPrimitiveArrayCritical(num_dims, nullptr)); + for (int i = 0; i < num_dims_length; ++i) { + cnum_dims[i] = static_cast(num_dims_elems[i]); + cdims[i] = cshapes_ptr; + if (cnum_dims[i] > 0) { + cshapes_ptr += cnum_dims[i]; + } + } + env->ReleasePrimitiveArrayCritical(num_dims, num_dims_elems, JNI_ABORT); + } + const char* cname = env->GetStringUTFChars(name, nullptr); + TF_SetAttrShapeList(d, cname, cdims.get(), cnum_dims.get(), num_dims_length); + env->ReleaseStringUTFChars(name, cname); +} + JNIEXPORT void JNICALL Java_org_tensorflow_OperationBuilder_setAttrStringList( JNIEnv* env, jclass object, jlong handle, jstring name, jobjectArray values) { diff --git a/tensorflow/java/src/main/native/operation_builder_jni.h b/tensorflow/java/src/main/native/operation_builder_jni.h index 2e72bd68da5..cf0abe4829b 100644 --- a/tensorflow/java/src/main/native/operation_builder_jni.h +++ b/tensorflow/java/src/main/native/operation_builder_jni.h @@ -169,6 +169,14 @@ JNIEXPORT void JNICALL Java_org_tensorflow_OperationBuilder_setAttrTensorList( JNIEXPORT void JNICALL Java_org_tensorflow_OperationBuilder_setAttrShape( JNIEnv *, jclass, jlong, jstring, jlongArray, jint); +/* + * Class: org_tensorflow_OperationBuilder + * Method: setAttrShapeList + * Signature: (JLjava/lang/String;[J[I)V + */ +JNIEXPORT void JNICALL Java_org_tensorflow_OperationBuilder_setAttrShapeList( + JNIEnv *, jclass, jlong, jstring, jlongArray, jintArray); + /* * Class: org_tensorflow_OperationBuilder * Method: setAttrStringList diff --git a/tensorflow/java/src/test/java/org/tensorflow/OperationBuilderTest.java b/tensorflow/java/src/test/java/org/tensorflow/OperationBuilderTest.java index 6dc233987bb..0a4a8cf4e3f 100644 --- a/tensorflow/java/src/test/java/org/tensorflow/OperationBuilderTest.java +++ b/tensorflow/java/src/test/java/org/tensorflow/OperationBuilderTest.java @@ -148,6 +148,19 @@ public class OperationBuilderTest { } } + @Test + public void setAttrShapeList() { + // Those shapes match tensors ones, so no exception is thrown + testSetAttrShapeList(new Shape[] {Shape.make(2, 2), Shape.make(2, 2, 2)}); + try { + // Those shapes do not match tensors ones, exception is thrown + testSetAttrShapeList(new Shape[] {Shape.make(2, 2), Shape.make(2, 2, 2, 2)}); + fail("Shapes are incompatible and an exception was expected"); + } catch (IllegalArgumentException e) { + // expected + } + } + @Test public void addControlInput() { try (Graph g = new Graph(); @@ -175,6 +188,30 @@ public class OperationBuilderTest { } } + private static void testSetAttrShapeList(Shape[] shapes) { + try (Graph g = new Graph(); + Session s = new Session(g)) { + int[][] matrix = new int[][] {{0, 0}, {0, 0}}; + Output queue = + g.opBuilder("FIFOQueue", "queue") + .setAttr("component_types", new DataType[] {DataType.INT32, DataType.INT32}) + .setAttr("shapes", shapes) + .build() + .output(0); + assertTrue(hasNode(g, "queue")); + Output c1 = TestUtil.constant(g, "const1", matrix); + Output c2 = TestUtil.constant(g, "const2", new int[][][] {matrix, matrix}); + Operation enqueue = + g.opBuilder("QueueEnqueue", "enqueue") + .addInput(queue) + .addInputList(new Output[] {c1, c2}) + .build(); + assertTrue(hasNode(g, "enqueue")); + + s.runner().addTarget(enqueue).run(); + } + } + private static boolean hasNode(Graph g, String name) { return g.operation(name) != null; } diff --git a/tensorflow/python/BUILD b/tensorflow/python/BUILD index 5e7a6c0b596..12d81c43832 100644 --- a/tensorflow/python/BUILD +++ b/tensorflow/python/BUILD @@ -3341,6 +3341,7 @@ py_test( tags = [ "no_gpu", "no_oss", + "no_pip", "no_pip_gpu", "notap", ], @@ -3387,6 +3388,7 @@ py_test( srcs_version = "PY2AND3", tags = [ "no_gpu", + "no_windows", ], deps = [ ":array_ops", diff --git a/tensorflow/python/data/util/nest.py b/tensorflow/python/data/util/nest.py index 2f89c006d2f..2455395635c 100644 --- a/tensorflow/python/data/util/nest.py +++ b/tensorflow/python/data/util/nest.py @@ -376,6 +376,16 @@ def assert_shallow_structure(shallow_tree, input_tree, check_types=True): "structure has length %s, while shallow structure has length %s." % (len(input_tree), len(shallow_tree))) + if check_types and isinstance(shallow_tree, dict): + if set(input_tree) != set(shallow_tree): + raise ValueError( + "The two structures don't have the same keys. Input " + "structure has keys %s, while shallow structure has keys %s." % + (list(_six.iterkeys(input_tree)), + list(_six.iterkeys(shallow_tree)))) + input_tree = list(_six.iteritems(input_tree)) + shallow_tree = list(_six.iteritems(shallow_tree)) + for shallow_branch, input_branch in zip(shallow_tree, input_tree): assert_shallow_structure(shallow_branch, input_branch, check_types=check_types) diff --git a/tensorflow/python/data/util/nest_test.py b/tensorflow/python/data/util/nest_test.py index 0bd0a5f4439..90dd7dfe777 100644 --- a/tensorflow/python/data/util/nest_test.py +++ b/tensorflow/python/data/util/nest_test.py @@ -268,6 +268,15 @@ class NestTest(test.TestCase): nest.assert_shallow_structure(inp_ab2, inp_ab1) nest.assert_shallow_structure(inp_ab2, inp_ab1, check_types=False) + inp_ab1 = {"a": (1, 1), "b": {"c": (2, 2)}} + inp_ab2 = {"a": (1, 1), "b": {"d": (2, 2)}} + expected_message = ( + r"The two structures don't have the same keys. Input " + r"structure has keys \['c'\], while shallow structure has " + r"keys \['d'\].") + with self.assertRaisesRegexp(ValueError, expected_message): + nest.assert_shallow_structure(inp_ab2, inp_ab1) + def testFlattenUpTo(self): input_tree = (((2, 2), (3, 3)), ((4, 9), (5, 5))) shallow_tree = ((True, True), (False, True)) diff --git a/tensorflow/python/estimator/export/export.py b/tensorflow/python/estimator/export/export.py index 31e9933c6f7..3b295a7e35c 100644 --- a/tensorflow/python/estimator/export/export.py +++ b/tensorflow/python/estimator/export/export.py @@ -57,7 +57,7 @@ class ServingInputReceiver(collections.namedtuple( groups of receiver tensors, each of which may be a `Tensor` or a dict of string to `Tensor`. These named receiver tensor alternatives generate additional serving signatures, which may be used to feed inputs at - different points within the input reciever subgraph. A typical usage is + different points within the input receiver subgraph. A typical usage is to allow feeding raw feature `Tensor`s *downstream* of the tf.parse_example() op. Defaults to None. """ diff --git a/tensorflow/python/estimator/training_test.py b/tensorflow/python/estimator/training_test.py index 1862e325e2b..17d018aa880 100644 --- a/tensorflow/python/estimator/training_test.py +++ b/tensorflow/python/estimator/training_test.py @@ -1016,7 +1016,7 @@ class TrainingExecutorRunEvaluatorTest(test.TestCase): is_the_final_export): del export_path, checkpoint_path, eval_result estimator.times_export_was_called += 1 - # final_export is happend at the end. + # final_export is happened at the end. self.assertEqual(0, estimator.times_final_export_was_called) if is_the_final_export: estimator.times_final_export_was_called += 1 @@ -1361,7 +1361,7 @@ class TrainingExecutorRunLocalTest(test.TestCase): is_the_final_export): del export_path, checkpoint_path, eval_result estimator.times_export_was_called += 1 - # final_export is happend at the end. + # final_export is happened at the end. self.assertEqual(0, estimator.times_final_export_was_called) if is_the_final_export: estimator.times_final_export_was_called += 1 diff --git a/tensorflow/python/keras/BUILD b/tensorflow/python/keras/BUILD index e4992afbca7..d9391dd6c58 100644 --- a/tensorflow/python/keras/BUILD +++ b/tensorflow/python/keras/BUILD @@ -556,6 +556,7 @@ py_test( srcs = ["_impl/keras/utils/data_utils_test.py"], srcs_version = "PY2AND3", tags = [ + "no_windows", "noasan", # times out "notsan", ], diff --git a/tensorflow/python/keras/_impl/keras/backend.py b/tensorflow/python/keras/_impl/keras/backend.py index b029e5161f7..ec7a5dcffd0 100644 --- a/tensorflow/python/keras/_impl/keras/backend.py +++ b/tensorflow/python/keras/_impl/keras/backend.py @@ -2487,7 +2487,7 @@ class Function(object): """Runs a computation graph. It's possible to pass arguments to `tf.Session.run()` via `session_kwargs`. - In particular additonal operations via `fetches` argument and additional + In particular additional operations via `fetches` argument and additional tensor substitutions via `feed_dict` arguments. Note that given substitutions are merged with substitutions from `inputs`. Even though `feed_dict` is passed once in the constructor (called in `model.compile()`) diff --git a/tensorflow/python/keras/_impl/keras/callbacks.py b/tensorflow/python/keras/_impl/keras/callbacks.py index 40a996a03f7..16109b52b3a 100644 --- a/tensorflow/python/keras/_impl/keras/callbacks.py +++ b/tensorflow/python/keras/_impl/keras/callbacks.py @@ -768,7 +768,7 @@ class TensorBoard(Callback): self.writer.add_summary(summary, epoch) self.writer.flush() - def on_train_end(self, _): + def on_train_end(self, logs=None): self.writer.close() diff --git a/tensorflow/python/keras/_impl/keras/callbacks_test.py b/tensorflow/python/keras/_impl/keras/callbacks_test.py index 97a650a9920..79dfcd1bb66 100644 --- a/tensorflow/python/keras/_impl/keras/callbacks_test.py +++ b/tensorflow/python/keras/_impl/keras/callbacks_test.py @@ -19,16 +19,18 @@ from __future__ import division from __future__ import print_function import csv -import multiprocessing import os import re import shutil +import threading +import unittest import numpy as np from tensorflow.python.keras._impl import keras from tensorflow.python.keras._impl.keras import testing_utils from tensorflow.python.platform import test +from tensorflow.python.summary.writer import writer_cache try: import h5py # pylint:disable=g-import-not-at-top @@ -498,7 +500,10 @@ class KerasCallbacksTest(test.TestCase): values = [] with open(fp) as f: for x in csv.reader(f): - values.append(x) + # In windows, due to \r\n line ends we may end up reading empty lines + # after each line. Skip empty lines. + if x: + values.append(x) assert 'nan' in values[-1], 'The last epoch was not logged.' def test_TerminateOnNaN(self): @@ -678,23 +683,41 @@ class KerasCallbacksTest(test.TestCase): batch_size=5)] # fit w/o validation data should raise ValueError if histogram_freq > 0 + cbs = callbacks_factory(histogram_freq=1) with self.assertRaises(ValueError): - model.fit(x_train, y_train, batch_size=BATCH_SIZE, - callbacks=callbacks_factory(histogram_freq=1), epochs=3) + model.fit( + x_train, y_train, batch_size=BATCH_SIZE, callbacks=cbs, epochs=3) + + for cb in cbs: + cb.on_train_end() # fit generator without validation data should raise ValueError if # histogram_freq > 0 + cbs = callbacks_factory(histogram_freq=1) with self.assertRaises(ValueError): - model.fit_generator(data_generator(True), len(x_train), epochs=2, - callbacks=callbacks_factory(histogram_freq=1)) + model.fit_generator( + data_generator(True), len(x_train), epochs=2, callbacks=cbs) + + for cb in cbs: + cb.on_train_end() # fit generator with validation data generator should raise ValueError if # histogram_freq > 0 + cbs = callbacks_factory(histogram_freq=1) with self.assertRaises(ValueError): - model.fit_generator(data_generator(True), len(x_train), epochs=2, - validation_data=data_generator(False), - validation_steps=1, - callbacks=callbacks_factory(histogram_freq=1)) + model.fit_generator( + data_generator(True), + len(x_train), + epochs=2, + validation_data=data_generator(False), + validation_steps=1, + callbacks=cbs) + + for cb in cbs: + cb.on_train_end() + + # Make sure file writer cache is clear to avoid failures during cleanup. + writer_cache.FileWriterCache.clear() def test_TensorBoard_multi_input_output(self): np.random.seed(1337) @@ -767,6 +790,9 @@ class KerasCallbacksTest(test.TestCase): callbacks=callbacks_factory(histogram_freq=1)) assert os.path.isdir(filepath) + @unittest.skipIf( + os.name == 'nt', + 'use_multiprocessing=True does not work on windows properly.') def test_LambdaCallback(self): with self.test_session(): np.random.seed(1337) @@ -789,14 +815,15 @@ class KerasCallbacksTest(test.TestCase): # Start an arbitrary process that should run during model # training and be terminated after training has completed. - def target(): - while True: - pass + e = threading.Event() - p = multiprocessing.Process(target=target) - p.start() + def target(): + e.wait() + + t = threading.Thread(target=target) + t.start() cleanup_callback = keras.callbacks.LambdaCallback( - on_train_end=lambda logs: p.terminate()) + on_train_end=lambda logs: e.set()) cbks = [cleanup_callback] model.fit( @@ -807,8 +834,8 @@ class KerasCallbacksTest(test.TestCase): callbacks=cbks, epochs=5, verbose=0) - p.join() - assert not p.is_alive() + t.join() + assert not t.is_alive() def test_TensorBoard_with_ReduceLROnPlateau(self): with self.test_session(): diff --git a/tensorflow/python/keras/_impl/keras/engine/training_test.py b/tensorflow/python/keras/_impl/keras/engine/training_test.py index e2a06e8e778..17a26f978e2 100644 --- a/tensorflow/python/keras/_impl/keras/engine/training_test.py +++ b/tensorflow/python/keras/_impl/keras/engine/training_test.py @@ -18,6 +18,9 @@ from __future__ import absolute_import from __future__ import division from __future__ import print_function +import os +import unittest + import numpy as np from tensorflow.python.keras._impl import keras @@ -783,6 +786,9 @@ class TestDynamicTrainability(test.TestCase): class TestGeneratorMethods(test.TestCase): + @unittest.skipIf( + os.name == 'nt', + 'use_multiprocessing=True does not work on windows properly.') def test_generator_methods(self): arr_data = np.random.random((50, 2)) arr_labels = np.random.random((50,)) diff --git a/tensorflow/python/keras/_impl/keras/estimator_test.py b/tensorflow/python/keras/_impl/keras/estimator_test.py index 1144aa3152b..a7ea3b48a33 100644 --- a/tensorflow/python/keras/_impl/keras/estimator_test.py +++ b/tensorflow/python/keras/_impl/keras/estimator_test.py @@ -33,6 +33,7 @@ from tensorflow.python.keras._impl.keras import testing_utils from tensorflow.python.keras._impl.keras.applications import mobilenet from tensorflow.python.platform import gfile from tensorflow.python.platform import test +from tensorflow.python.summary.writer import writer_cache try: @@ -132,6 +133,8 @@ class TestKerasEstimator(test_util.TensorFlowTestCase): tf_random_seed=_RANDOM_SEED, model_dir=self._base_dir) def tearDown(self): + # Make sure nothing is stuck in limbo. + writer_cache.FileWriterCache.clear() if os.path.isdir(self._base_dir): gfile.DeleteRecursively(self._base_dir) @@ -153,6 +156,8 @@ class TestKerasEstimator(test_util.TensorFlowTestCase): est_keras.train(input_fn=train_input_fn, steps=_TRAIN_SIZE / 16) after_eval_results = est_keras.evaluate(input_fn=eval_input_fn, steps=1) self.assertLess(after_eval_results['loss'], before_eval_results['loss']) + + writer_cache.FileWriterCache.clear() gfile.DeleteRecursively(self._config.model_dir) def test_evaluate(self): diff --git a/tensorflow/python/keras/_impl/keras/models_test.py b/tensorflow/python/keras/_impl/keras/models_test.py index 86acac4604a..61938066b98 100644 --- a/tensorflow/python/keras/_impl/keras/models_test.py +++ b/tensorflow/python/keras/_impl/keras/models_test.py @@ -54,10 +54,11 @@ class TestModelSaving(test.TestCase): model.train_on_batch(x, y) out = model.predict(x) - _, fname = tempfile.mkstemp('.h5') + fd, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) new_model = keras.models.load_model(fname) + os.close(fd) os.remove(fname) out2 = new_model.predict(x) @@ -95,13 +96,14 @@ class TestModelSaving(test.TestCase): model.train_on_batch(x, y) out = model.predict(x) - _, fname = tempfile.mkstemp('.h5') + fd, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) model = keras.models.load_model( fname, custom_objects={'CustomOp': CustomOp, 'custom_loss': custom_loss}) + os.close(fd) os.remove(fname) out2 = model.predict(x) @@ -125,10 +127,11 @@ class TestModelSaving(test.TestCase): model.train_on_batch(x, y) out = model.predict(x) - _, fname = tempfile.mkstemp('.h5') + fd, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) model = keras.models.load_model(fname) + os.close(fd) os.remove(fname) out2 = model.predict(x) @@ -144,9 +147,10 @@ class TestModelSaving(test.TestCase): model.add(keras.layers.Dense(3)) model.compile(loss='mse', optimizer='sgd', metrics=['acc']) - _, fname = tempfile.mkstemp('.h5') + fd, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) model = keras.models.load_model(fname) + os.close(fd) os.remove(fname) def test_saving_with_tf_optimizer(self): @@ -161,9 +165,10 @@ class TestModelSaving(test.TestCase): optimizer=training_module.AdadeltaOptimizer(0.1), metrics=['acc']) - _, fname = tempfile.mkstemp('.h5') + fd, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) model = keras.models.load_model(fname) + os.close(fd) os.remove(fname) def test_saving_right_after_compilation(self): @@ -177,9 +182,10 @@ class TestModelSaving(test.TestCase): model.compile(loss='mse', optimizer='sgd', metrics=['acc']) model.model._make_train_function() - _, fname = tempfile.mkstemp('.h5') + fd, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) model = keras.models.load_model(fname) + os.close(fd) os.remove(fname) def test_saving_lambda_numpy_array_arguments(self): @@ -194,10 +200,11 @@ class TestModelSaving(test.TestCase): model = keras.models.Model(inputs, output) model.compile(loss='mse', optimizer='sgd', metrics=['acc']) - _, fname = tempfile.mkstemp('.h5') + fd, fname = tempfile.mkstemp('.h5') keras.models.save_model(model, fname) model = keras.models.load_model(fname) + os.close(fd) os.remove(fname) self.assertAllClose(mean, model.layers[1].arguments['mu']) diff --git a/tensorflow/python/keras/_impl/keras/utils/data_utils_test.py b/tensorflow/python/keras/_impl/keras/utils/data_utils_test.py index 14b2f084423..47c5b4cff06 100644 --- a/tensorflow/python/keras/_impl/keras/utils/data_utils_test.py +++ b/tensorflow/python/keras/_impl/keras/utils/data_utils_test.py @@ -22,6 +22,7 @@ from itertools import cycle import os import tarfile import threading +import unittest import zipfile import numpy as np @@ -164,6 +165,9 @@ class TestEnqueuers(test.TestCase): self.assertEqual(len(set(acc) - set(range(100))), 0) enqueuer.stop() + @unittest.skipIf( + os.name == 'nt', + 'use_multiprocessing=True does not work on windows properly.') def test_generator_enqueuer_processes(self): enqueuer = keras.utils.data_utils.GeneratorEnqueuer( create_generator_from_sequence_pcs(TestSequence([3, 200, 200, 3])), @@ -185,6 +189,9 @@ class TestEnqueuers(test.TestCase): with self.assertRaises(StopIteration): next(gen_output) + @unittest.skipIf( + os.name == 'nt', + 'use_multiprocessing=True does not work on windows properly.') def test_generator_enqueuer_fail_processes(self): enqueuer = keras.utils.data_utils.GeneratorEnqueuer( create_generator_from_sequence_pcs(FaultSequence()), diff --git a/tensorflow/python/keras/_impl/keras/utils/io_utils.py b/tensorflow/python/keras/_impl/keras/utils/io_utils.py index 1c8299c27d2..a8fc18c17ae 100644 --- a/tensorflow/python/keras/_impl/keras/utils/io_utils.py +++ b/tensorflow/python/keras/_impl/keras/utils/io_utils.py @@ -63,11 +63,11 @@ class HDF5Matrix(object): 'HDF5 and h5py installed.') if datapath not in list(self.refs.keys()): - f = h5py.File(datapath) - self.refs[datapath] = f + self._f = h5py.File(datapath) + self.refs[datapath] = self._f else: - f = self.refs[datapath] - self.data = f[dataset] + self._f = self.refs[datapath] + self.data = self._f[dataset] self.start = start if end is None: self.end = self.data.shape[0] @@ -78,6 +78,9 @@ class HDF5Matrix(object): def __len__(self): return self.end - self.start + def __del__(self): + self._f.close() + def __getitem__(self, key): if isinstance(key, slice): start, stop = key.start, key.stop diff --git a/tensorflow/python/keras/_impl/keras/utils/vis_utils.py b/tensorflow/python/keras/_impl/keras/utils/vis_utils.py index ce2faf2d968..d56c4484ce3 100644 --- a/tensorflow/python/keras/_impl/keras/utils/vis_utils.py +++ b/tensorflow/python/keras/_impl/keras/utils/vis_utils.py @@ -120,7 +120,7 @@ def model_to_dot(model, show_shapes=False, show_layer_names=True, rankdir='TB'): layer_id = str(id(layer)) for i, node in enumerate(layer._inbound_nodes): # pylint: disable=protected-access node_key = layer.name + '_ib-' + str(i) - if node_key in model.container_nodes: + if node_key in model._network_nodes: # pylint: disable=protected-access for inbound_layer in node.inbound_layers: inbound_layer_id = str(id(inbound_layer)) layer_id = str(id(layer)) diff --git a/tensorflow/python/kernel_tests/BUILD b/tensorflow/python/kernel_tests/BUILD index f15b3baabe1..f6721de32a2 100644 --- a/tensorflow/python/kernel_tests/BUILD +++ b/tensorflow/python/kernel_tests/BUILD @@ -2362,7 +2362,7 @@ cuda_py_test( cuda_py_test( name = "slice_op_test", - size = "medium", + size = "large", srcs = ["slice_op_test.py"], additional_deps = [ "//third_party/py/numpy", @@ -2942,6 +2942,20 @@ tf_py_test( ], ) +tf_py_test( + name = "prefetch_dataset_op_test", + size = "small", + srcs = ["prefetch_dataset_op_test.py"], + additional_deps = [ + "//tensorflow/python:array_ops", + "//tensorflow/python:client_testlib", + "//tensorflow/python:dataset_ops_gen", + "//tensorflow/python:dtypes", + "//tensorflow/python:errors", + "//tensorflow/python/data/ops:dataset_ops", + ], +) + tf_py_test( name = "range_dataset_op_test", size = "small", diff --git a/tensorflow/python/kernel_tests/decode_bmp_op_test.py b/tensorflow/python/kernel_tests/decode_bmp_op_test.py index 783492a6f25..35f8f76991a 100644 --- a/tensorflow/python/kernel_tests/decode_bmp_op_test.py +++ b/tensorflow/python/kernel_tests/decode_bmp_op_test.py @@ -64,6 +64,81 @@ class DecodeBmpOpTest(test.TestCase): decoded = decode.eval() self.assertAllEqual(decoded, img_bytes) + def testGrayscale(self): + img_bytes = [[[255], [0]], [[255], [0]]] + encoded_bytes = [ + 0x42, + 0x40, + 0x3d, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0x36, + 0, + 0, + 0, + 0x28, + 0, + 0, + 0, + 0x2, + 0, + 0, + 0, + 0x2, + 0, + 0, + 0, + 0x1, + 0, + 0x8, + 0, + 0, + 0, + 0, + 0, + 0x10, + 0, + 0, + 0, + 0x13, + 0xb, + 0, + 0, + 0x13, + 0xb, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0xff, + 0, + 0, + 0, + 0xff, + 0, + 0, + 0, + ] + + byte_string = bytes(bytearray(encoded_bytes)) + img_in = constant_op.constant(byte_string, dtype=dtypes.string) + decode = image_ops.decode_bmp(img_in) + + with self.test_session(): + decoded = decode.eval() + self.assertAllEqual(decoded, img_bytes) + if __name__ == "__main__": test.main() diff --git a/tensorflow/python/kernel_tests/prefetch_dataset_op_test.py b/tensorflow/python/kernel_tests/prefetch_dataset_op_test.py new file mode 100644 index 00000000000..646324cb95d --- /dev/null +++ b/tensorflow/python/kernel_tests/prefetch_dataset_op_test.py @@ -0,0 +1,59 @@ +# 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. +# ============================================================================== +"""Test PrefetchDataset.""" +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +from tensorflow.python.data.ops import dataset_ops +from tensorflow.python.framework import dtypes +from tensorflow.python.framework import errors +from tensorflow.python.ops import array_ops +from tensorflow.python.platform import test + + +class PrefetchDatasetTest(test.TestCase): + + def testBufferSize(self): + buffer_size = array_ops.placeholder(dtypes.int64, shape=[]) + iterator = dataset_ops.Dataset.range(10).prefetch( + buffer_size=buffer_size).make_initializable_iterator() + init_op = iterator.initializer + get_next = iterator.get_next() + + with self.test_session() as sess: + sess.run(init_op, feed_dict={buffer_size: 5}) + for m in range(10): + self.assertEqual(m, sess.run(get_next)) + with self.assertRaises(errors.OutOfRangeError): + sess.run(get_next) + + def testInvalidBufferSize(self): + buffer_size = array_ops.placeholder(dtypes.int64, shape=[]) + iterator = dataset_ops.Dataset.range(10).prefetch( + buffer_size=buffer_size).make_initializable_iterator() + init_op = iterator.initializer + + with self.assertRaisesRegexp(errors.InvalidArgumentError, "buffer_size"): + with self.test_session() as sess: + sess.run(init_op, feed_dict={buffer_size: 0}) + + with self.assertRaisesRegexp(errors.InvalidArgumentError, "buffer_size"): + with self.test_session() as sess: + sess.run(init_op, feed_dict={buffer_size: -5}) + + +if __name__ == "__main__": + test.main() diff --git a/tensorflow/python/layers/convolutional.py b/tensorflow/python/layers/convolutional.py index 8c327d7e270..fbb13bb72c4 100644 --- a/tensorflow/python/layers/convolutional.py +++ b/tensorflow/python/layers/convolutional.py @@ -920,6 +920,7 @@ class SeparableConv2D(Conv2D): trainable=trainable, name=name, **kwargs) + self.data_format = data_format self.depth_multiplier = depth_multiplier self.depthwise_initializer = depthwise_initializer self.pointwise_initializer = pointwise_initializer @@ -1231,9 +1232,8 @@ class Conv2DTranspose(Conv2D): def build(self, input_shape): if len(input_shape) != 4: - raise ValueError('Inputs should have rank ' + - str(4) + - 'Received input shape:', str(input_shape)) + raise ValueError('Inputs should have rank 4. Received input shape: ' + + str(input_shape)) if self.data_format == 'channels_first': channel_axis = 1 else: diff --git a/tensorflow/python/ops/math_ops_test.py b/tensorflow/python/ops/math_ops_test.py index 81a7cf28bbe..bd26ff66961 100644 --- a/tensorflow/python/ops/math_ops_test.py +++ b/tensorflow/python/ops/math_ops_test.py @@ -61,7 +61,7 @@ class ReduceTest(test_util.TensorFlowTestCase): @test_util.run_in_graph_and_eager_modes() def testReduceInvalidAxis(self): if context.in_eager_mode(): - # The shape check is in run a graph contruction time. In eager mode, + # The shape check is in run a graph construction time. In eager mode, # it misses the check, magically return result given wrong shape. return x = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32) diff --git a/tensorflow/python/ops/variable_scope.py b/tensorflow/python/ops/variable_scope.py index ae2d46a2b71..3643861a16d 100644 --- a/tensorflow/python/ops/variable_scope.py +++ b/tensorflow/python/ops/variable_scope.py @@ -1697,7 +1697,7 @@ class variable_scope(object): # pylint: disable=invalid-name v1 = foo() # Creates v. v2 = foo() # Gets the same, existing v. assert v1 == v2 - + ``` Basic example of sharing a variable with reuse=True: diff --git a/tensorflow/python/ops/variables.py b/tensorflow/python/ops/variables.py index a1e4305de13..e0748d87e2d 100644 --- a/tensorflow/python/ops/variables.py +++ b/tensorflow/python/ops/variables.py @@ -200,7 +200,7 @@ class Variable(object): @compatibility(eager) `tf.Variable` is not compatible with eager execution. Use - `tfe.Variable` instead which is compatable with both eager execution + `tfe.Variable` instead which is compatible with both eager execution and graph construction. See [the TensorFlow Eager Execution guide](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/eager/python/g3doc/guide.md#variables-and-optimizers) for details on how variables work in eager execution. @@ -1064,7 +1064,7 @@ class PartitionedVariable(object): """A container for partitioned `Variable` objects. @compatibility(eager) `tf.PartitionedVariable` is not compatible with - eager execution. Use `tfe.Variable` instead which is compatable + eager execution. Use `tfe.Variable` instead which is compatible with both eager execution and graph construction. See [the TensorFlow Eager Execution guide](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/eager/python/g3doc/guide.md#variables-and-optimizers) diff --git a/tensorflow/python/profiler/model_analyzer_test.py b/tensorflow/python/profiler/model_analyzer_test.py index c39d0fa5b1a..ccfb9aac537 100644 --- a/tensorflow/python/profiler/model_analyzer_test.py +++ b/tensorflow/python/profiler/model_analyzer_test.py @@ -65,7 +65,7 @@ class PrintModelAnalysisTest(test.TestCase): ' ScalarW (1, 1/1 params)\n', f.read()) - def testSelectEverthingDetail(self): + def testSelectEverythingDetail(self): ops.reset_default_graph() dev = '/device:GPU:0' if test.is_gpu_available() else '/device:CPU:0' outfile = os.path.join(test.get_temp_dir(), 'dump') diff --git a/tensorflow/python/training/saver_test.py b/tensorflow/python/training/saver_test.py index 98ac1972046..74ee1e5fa8d 100644 --- a/tensorflow/python/training/saver_test.py +++ b/tensorflow/python/training/saver_test.py @@ -726,6 +726,8 @@ class SaverTest(test.TestCase): class SaveRestoreShardedTest(test.TestCase): + _WRITE_VERSION = saver_pb2.SaverDef.V1 + def _get_test_dir(self, dirname): test_dir = os.path.join(self.get_temp_dir(), dirname) gfile.MakeDirs(test_dir) @@ -751,6 +753,7 @@ class SaveRestoreShardedTest(test.TestCase): "t0": t0.saveable, "t1": t1.saveable }, + write_version=self._WRITE_VERSION, sharded=True) variables.global_variables_initializer().run() t0.insert("k1", 30.0).run() @@ -771,7 +774,13 @@ class SaveRestoreShardedTest(test.TestCase): with sess.graph.device("/cpu:0"): v0 = variables.Variable(111, name="v0") t0 = saver_test_utils.CheckpointedOp(name="t0") - save = saver_module.Saver({"v0": v0, "t0": t0.saveable}, sharded=True) + save = saver_module.Saver( + { + "v0": v0, + "t0": t0.saveable + }, + write_version=self._WRITE_VERSION, + sharded=True) variables.global_variables_initializer().run() t0.insert("k11", 33.0).run() self.assertEqual(111, v0.eval()) @@ -789,7 +798,13 @@ class SaveRestoreShardedTest(test.TestCase): with sess.graph.device("/cpu:0"): v1 = variables.Variable(222) t1 = saver_test_utils.CheckpointedOp(name="t1") - save = saver_module.Saver({"v1": v1, "t1": t1.saveable}, sharded=True) + save = saver_module.Saver( + { + "v1": v1, + "t1": t1.saveable + }, + write_version=self._WRITE_VERSION, + sharded=True) variables.global_variables_initializer().run() t1.insert("k22", 44.0).run() self.assertEqual(222, v1.eval()) @@ -817,6 +832,7 @@ class SaveRestoreShardedTest(test.TestCase): "t0": t0.saveable, "t1": t1.saveable }, + write_version=self._WRITE_VERSION, sharded=True) variables.global_variables_initializer().run() t0.insert("k11", 33.0).run() @@ -982,6 +998,10 @@ class SaveRestoreShardedTest(test.TestCase): self._testPartitionedVariables(use_resource=True) +class SaveRestoreShardedTestV2(SaveRestoreShardedTest): + _WRITE_VERSION = saver_pb2.SaverDef.V2 + + class MaxToKeepTest(test.TestCase): def _get_test_dir(self, dirname): diff --git a/tensorflow/python/training/sync_replicas_optimizer.py b/tensorflow/python/training/sync_replicas_optimizer.py index 2a97d45daa9..b52d101a215 100644 --- a/tensorflow/python/training/sync_replicas_optimizer.py +++ b/tensorflow/python/training/sync_replicas_optimizer.py @@ -99,7 +99,7 @@ class SyncReplicasOptimizer(optimizer.Optimizer): # Note that if you want to have 2 backup replicas, you can change # total_num_replicas=52 and make sure this number matches how many physical # replicas you started in your job. - opt = tf.SyncReplicasOptimizer(opt, replicas_to_aggregate=50, + opt = tf.train.SyncReplicasOptimizer(opt, replicas_to_aggregate=50, total_num_replicas=50) # Some models have startup_delays to help stabilize the model but when using diff --git a/tensorflow/python/util/nest.py b/tensorflow/python/util/nest.py index 75f482e5a8d..5c066e2bef1 100644 --- a/tensorflow/python/util/nest.py +++ b/tensorflow/python/util/nest.py @@ -116,7 +116,7 @@ def flatten(nest): used instead. The same convention is followed in `pack_sequence_as`. This correctly repacks dicts and `OrderedDict`s after they have been flattened, and also allows flattening an `OrderedDict` and then repacking it back using - a correponding plain dict, or vice-versa. + a corresponding plain dict, or vice-versa. Dictionaries with non-sortable keys cannot be flattened. Users must not modify any collections used in `nest` while this function is @@ -296,7 +296,7 @@ def pack_sequence_as(structure, flat_sequence): keys is used instead. The same convention is followed in `flatten`. This correctly repacks dicts and `OrderedDict`s after they have been flattened, and also allows flattening an `OrderedDict` and then repacking it - back using a correponding plain dict, or vice-versa. + back using a corresponding plain dict, or vice-versa. Dictionaries with non-sortable keys cannot be flattened. Args: @@ -452,6 +452,17 @@ def assert_shallow_structure(shallow_tree, input_tree, check_types=True): "structure has length %s, while shallow structure has length %s." % (len(input_tree), len(shallow_tree))) + if check_types and isinstance(shallow_tree, dict): + if set(input_tree) != set(shallow_tree): + raise ValueError( + "The two structures don't have the same keys. Input " + "structure has keys %s, while shallow structure has keys %s." % + (list(_six.iterkeys(input_tree)), + list(_six.iterkeys(shallow_tree)))) + + input_tree = list(_six.iteritems(input_tree)) + shallow_tree = list(_six.iteritems(shallow_tree)) + for shallow_branch, input_branch in zip(shallow_tree, input_tree): assert_shallow_structure(shallow_branch, input_branch, check_types=check_types) diff --git a/tensorflow/python/util/nest_test.py b/tensorflow/python/util/nest_test.py index c4020f4f3ce..3d9e9f96849 100644 --- a/tensorflow/python/util/nest_test.py +++ b/tensorflow/python/util/nest_test.py @@ -385,6 +385,16 @@ class NestTest(test.TestCase): nest.assert_shallow_structure(inp_ab2, inp_ab1) nest.assert_shallow_structure(inp_ab2, inp_ab1, check_types=False) + inp_ab1 = {"a": (1, 1), "b": {"c": (2, 2)}} + inp_ab2 = {"a": (1, 1), "b": {"d": (2, 2)}} + expected_message = ( + r"The two structures don't have the same keys. Input " + r"structure has keys \['c'\], while shallow structure has " + r"keys \['d'\].") + + with self.assertRaisesRegexp(ValueError, expected_message): + nest.assert_shallow_structure(inp_ab2, inp_ab1) + def testFlattenUpTo(self): # Shallow tree ends at scalar. input_tree = [[[2, 2], [3, 3]], [[4, 9], [5, 5]]] @@ -429,8 +439,7 @@ class NestTest(test.TestCase): input_tree_flattened_as_shallow_tree = nest.flatten_up_to(shallow_tree, input_tree) self.assertEqual(input_tree_flattened_as_shallow_tree, [0, 1, 2, 3, 4]) - shallow_tree = collections.OrderedDict([("a", 0), - ("b", {"d": 3, "e": 1})]) + shallow_tree = collections.OrderedDict([("a", 0), ("c", {"d": 3, "e": 1})]) input_tree_flattened_as_shallow_tree = nest.flatten_up_to(shallow_tree, input_tree) self.assertEqual(input_tree_flattened_as_shallow_tree, diff --git a/tensorflow/tools/api/golden/tensorflow.keras.callbacks.-tensor-board.pbtxt b/tensorflow/tools/api/golden/tensorflow.keras.callbacks.-tensor-board.pbtxt index 6620a9d308f..7de4008c454 100644 --- a/tensorflow/tools/api/golden/tensorflow.keras.callbacks.-tensor-board.pbtxt +++ b/tensorflow/tools/api/golden/tensorflow.keras.callbacks.-tensor-board.pbtxt @@ -29,7 +29,7 @@ tf_class { } member_method { name: "on_train_end" - argspec: "args=[\'self\', \'_\'], varargs=None, keywords=None, defaults=None" + argspec: "args=[\'self\', \'logs\'], varargs=None, keywords=None, defaults=[\'None\'], " } member_method { name: "set_model" diff --git a/tensorflow/tools/benchmark/benchmark_model.cc b/tensorflow/tools/benchmark/benchmark_model.cc index 2d59299da4d..9809ad52de1 100644 --- a/tensorflow/tools/benchmark/benchmark_model.cc +++ b/tensorflow/tools/benchmark/benchmark_model.cc @@ -622,7 +622,7 @@ int Main(int argc, char** argv) { RecordBenchmarkEntry(output_prefix, benchmark_name, "meta-first-inference", warmup_runs, warmup_time_us / 1000000.0); - // Time from starting to intialize TF to getting the first result back. + // Time from starting to initialize TF to getting the first result back. // This also assumes that only one warmup run is performed. RecordBenchmarkEntry( output_prefix, benchmark_name, "meta-init-plus-first-inference", 1, diff --git a/tensorflow/tools/ci_build/builds/test_user_ops.sh b/tensorflow/tools/ci_build/builds/test_user_ops.sh index 4f1c61b8e9a..358f82ac5da 100755 --- a/tensorflow/tools/ci_build/builds/test_user_ops.sh +++ b/tensorflow/tools/ci_build/builds/test_user_ops.sh @@ -76,17 +76,17 @@ echo "PYTHON_BIN_PATH: ${PYTHON_BIN_PATH}" pushd "${TMP_DIR}" -# Obtain paths include and lib paths to the TensorFlow installation -TF_INC=$("${PYTHON_BIN_PATH}" \ - -c 'import tensorflow as tf; print(tf.sysconfig.get_include())') -TF_LIB=$("${PYTHON_BIN_PATH}" \ - -c 'import tensorflow as tf; print(tf.sysconfig.get_lib())') +# Obtain compilation and linking flags +TF_CFLAGS=( $("${PYTHON_BIN_PATH}" \ + -c 'import tensorflow as tf; print(" ".join(tf.sysconfig.get_compile_flags()))') ) +TF_LFLAGS=( $("${PYTHON_BIN_PATH}" \ + -c 'import tensorflow as tf; print(" ".join(tf.sysconfig.get_link_flags()))') ) -if [[ -z "${TF_INC}" ]]; then - die "FAILED to determine TensorFlow include path" +if [[ -z "${TF_CFLAGS}" || -z "${TF_LFLAGS}" ]]; then + die "FAILED to determine TensorFlow compilation or linking flags" else - echo "TensorFlow include path: ${TF_INC}" - TF_INCLUDE_PATH="-I${TF_INC} -I${TF_INC}/external/nsync/public" + echo "TensorFlow compile flags: ${TF_CFLAGS[@]}" + echo "TensorFlow link flags: ${TF_LFLAGS[@]}" fi # Check g++ availability @@ -145,7 +145,7 @@ if [[ ${IS_GPU} == "0" ]]; then "${GPP_BIN}" -std=c++11 ${EXTRA_GPP_FLAGS} \ -shared "${SRC_FILE}" -o "${USER_OP_SO}" \ - -fPIC ${TF_INCLUDE_PATH} -L "${TF_LIB}" -ltensorflow_framework || \ + -fPIC ${TF_CFLAGS[@]} ${TF_LFLAGS[@]} || \ die "g++ compilation of ${SRC_FILE} FAILED" else @@ -184,7 +184,7 @@ else OP_KERNEL_O=$(echo "${OP_KERNEL_CC}" | sed -e 's/\.cc/\.o/') "${NVCC_BIN}" -std=c++11 \ -c -o "${OP_KERNEL_O}" "${OP_KERNEL_CU}" \ - ${TF_INCLUDE_PATH} -D GOOGLE_CUDA=1 -x cu -Xcompiler -fPIC || \ + ${TF_CFLAGS[@]} -D GOOGLE_CUDA=1 -x cu -Xcompiler -fPIC || \ die "nvcc compilation of ${OP_KERNEL_CC} FAILED" CUDA_LIB_DIR="/usr/local/cuda/lib64" @@ -203,8 +203,8 @@ else USER_OP_SO="add_one.so" "${GPP_BIN}" -std=c++11 ${EXTRA_GPP_FLAGS} \ -shared -o "${USER_OP_SO}" "${OP_KERNEL_CC}" \ - "${OP_KERNEL_O}" ${TF_INCLUDE_PATH} -L "${CUDA_LIB_DIR}" -L "${TF_LIB}" \ - -fPIC -lcudart -ltensorflow_framework || \ + "${OP_KERNEL_O}" ${TF_CFLAGS[@]} -L "${CUDA_LIB_DIR}" ${TF_LFLAGS[@]} \ + -fPIC -lcudart || \ die "g++ compilation of ${OP_KERNEL_CC}" FAILED fi diff --git a/tensorflow/tools/ci_build/ci_parameterized_build.sh b/tensorflow/tools/ci_build/ci_parameterized_build.sh index c27f4953e3d..2217b110e3f 100755 --- a/tensorflow/tools/ci_build/ci_parameterized_build.sh +++ b/tensorflow/tools/ci_build/ci_parameterized_build.sh @@ -546,8 +546,8 @@ echo "" TMP_DIR="" DOCKERFILE_FLAG="" -if [[ "${TF_BUILD_PYTHON_VERSION}" == "python3.5" ] || - ["${TF_BUILD_PYTHON_VERSION}" == "python3.6" ]]; then +if [[ "${TF_BUILD_PYTHON_VERSION}" == "python3.5" ]] || + [[ "${TF_BUILD_PYTHON_VERSION}" == "python3.6" ]]; then # Modify Dockerfile for Python3.5 | Python3.6 build TMP_DIR=$(mktemp -d) echo "Docker build will occur in temporary directory: ${TMP_DIR}" diff --git a/tensorflow/tools/ci_build/windows/cpu/cmake/run_build.bat b/tensorflow/tools/ci_build/windows/cpu/cmake/run_build.bat index 6e600e2dcfb..56bff077746 100644 --- a/tensorflow/tools/ci_build/windows/cpu/cmake/run_build.bat +++ b/tensorflow/tools/ci_build/windows/cpu/cmake/run_build.bat @@ -37,4 +37,4 @@ SET MSBUILD_EXE="C:\Program Files (x86)\MSBuild\14.0\Bin\msbuild.exe" %CMAKE_EXE% %CMAKE_DIR% -A x64 -DSWIG_EXECUTABLE=%SWIG_EXE% -DPYTHON_EXECUTABLE=%PY_EXE% -DCMAKE_BUILD_TYPE=Release -DPYTHON_LIBRARIES=%PY_LIB% -Dtensorflow_BUILD_PYTHON_TESTS=%BUILD_PYTHON_TESTS% -Dtensorflow_BUILD_CC_TESTS=%BUILD_CC_TESTS% -Dtensorflow_TF_NIGHTLY=%TF_NIGHTLY% :: Run msbuild in the resulting VS project files to build a pip package. -%MSBUILD_EXE% /p:Configuration=Release /maxcpucount:32 /verbosity:minimal tf_python_build_pip_package.vcxproj \ No newline at end of file +%MSBUILD_EXE% /p:Configuration=Release /maxcpucount:32 tf_python_build_pip_package.vcxproj diff --git a/tensorflow/tools/ci_build/windows/cpu/pip/build_tf_windows.sh b/tensorflow/tools/ci_build/windows/cpu/pip/build_tf_windows.sh index f6e3d2e6c71..8520ca898f8 100644 --- a/tensorflow/tools/ci_build/windows/cpu/pip/build_tf_windows.sh +++ b/tensorflow/tools/ci_build/windows/cpu/pip/build_tf_windows.sh @@ -64,7 +64,7 @@ reinstall_tensorflow_pip ${PIP_NAME} # https://github.com/tensorflow/tensorflow/issues/12844 is fixed. bazel test -c opt $BUILD_OPTS -k --test_output=errors \ --define=no_tensorflow_py_deps=true --test_lang_filters=py \ - --test_tag_filters=-no_pip,-no_windows \ - --build_tag_filters=-no_pip,-no_windows --build_tests_only \ + --test_tag_filters=-no_pip,-no_windows,-no_oss \ + --build_tag_filters=-no_pip,-no_windows,-no_oss --build_tests_only \ --test_env=TF_SAVER_LENIENT_NAMES=True \ //${PY_TEST_DIR}/tensorflow/python/... diff --git a/tensorflow/tools/ci_build/windows/gpu/cmake/run_build.bat b/tensorflow/tools/ci_build/windows/gpu/cmake/run_build.bat index 44d8252a7a9..832943ad6c8 100644 --- a/tensorflow/tools/ci_build/windows/gpu/cmake/run_build.bat +++ b/tensorflow/tools/ci_build/windows/gpu/cmake/run_build.bat @@ -38,4 +38,4 @@ SET MSBUILD_EXE="C:\Program Files (x86)\MSBuild\14.0\Bin\msbuild.exe" %CMAKE_EXE% %CMAKE_DIR% -A x64 -DSWIG_EXECUTABLE=%SWIG_EXE% -DPYTHON_EXECUTABLE=%PY_EXE% -DCMAKE_BUILD_TYPE=Release -DPYTHON_LIBRARIES=%PY_LIB% -Dtensorflow_BUILD_PYTHON_TESTS=%BUILD_PYTHON_TESTS% -Dtensorflow_BUILD_CC_TESTS=%BUILD_CC_TESTS% -Dtensorflow_ENABLE_GPU=ON -DCUDNN_HOME=%CUDNN_HOME% -Dtensorflow_TF_NIGHTLY=%TF_NIGHTLY% :: Run msbuild in the resulting VS project files to build a pip package. -%MSBUILD_EXE% /p:Configuration=Release /maxcpucount:32 /verbosity:minimal tf_python_build_pip_package.vcxproj +%MSBUILD_EXE% /p:Configuration=Release /maxcpucount:32 tf_python_build_pip_package.vcxproj diff --git a/tensorflow/tools/ci_build/windows/gpu/pip/build_tf_windows.sh b/tensorflow/tools/ci_build/windows/gpu/pip/build_tf_windows.sh index 25d327c8188..47ca42d6422 100644 --- a/tensorflow/tools/ci_build/windows/gpu/pip/build_tf_windows.sh +++ b/tensorflow/tools/ci_build/windows/gpu/pip/build_tf_windows.sh @@ -65,7 +65,7 @@ reinstall_tensorflow_pip ${PIP_NAME} # https://github.com/tensorflow/tensorflow/issues/12844 is fixed. bazel test -c opt $BUILD_OPTS -k --test_output=errors \ --define=no_tensorflow_py_deps=true --test_lang_filters=py \ - --test_tag_filters=-no_pip,-no_windows,-no_windows_gpu,-no_gpu,-no_pip_gpu \ - --build_tag_filters=-no_pip,-no_windows,-no_windows_gpu,-no_gpu,-no_pip_gpu \ + --test_tag_filters=-no_pip,-no_windows,-no_windows_gpu,-no_gpu,-no_pip_gpu,no_oss \ + --build_tag_filters=-no_pip,-no_windows,-no_windows_gpu,-no_gpu,-no_pip_gpu,no_oss \ --test_env=TF_SAVER_LENIENT_NAMES=True \ --local_test_jobs=1 --build_tests_only //${PY_TEST_DIR}/tensorflow/python/... diff --git a/tensorflow/tools/dist_test/python/census_widendeep.py b/tensorflow/tools/dist_test/python/census_widendeep.py index 3a557814960..8feb5386e98 100644 --- a/tensorflow/tools/dist_test/python/census_widendeep.py +++ b/tensorflow/tools/dist_test/python/census_widendeep.py @@ -263,8 +263,7 @@ if __name__ == "__main__": "--data_dir", type=str, default="/tmp/census-data", - help="Directory for storing the cesnsus data" - ) + help="Directory for storing the census data") parser.add_argument( "--model_dir", type=str, diff --git a/tensorflow/tools/docker/Dockerfile.devel b/tensorflow/tools/docker/Dockerfile.devel index 1a0145b0785..3525c7524f3 100644 --- a/tensorflow/tools/docker/Dockerfile.devel +++ b/tensorflow/tools/docker/Dockerfile.devel @@ -101,4 +101,3 @@ EXPOSE 6006 EXPOSE 8888 WORKDIR /root -CMD ["/bin/bash"] diff --git a/tensorflow/tools/docker/Dockerfile.devel-cpu-mkl b/tensorflow/tools/docker/Dockerfile.devel-cpu-mkl new file mode 100644 index 00000000000..8180e5e7fb6 --- /dev/null +++ b/tensorflow/tools/docker/Dockerfile.devel-cpu-mkl @@ -0,0 +1,85 @@ +FROM tensorflow/tensorflow:latest-devel + +LABEL maintainer="Clayne Robison" + +# These arguments are parameterized. Use --build-args to override. +ARG TF_BRANCH=r1.4 +ARG WHL_DIR=/whl + +RUN apt-get update && apt-get install -y --no-install-recommends \ + golang \ + vim \ + emacs \ + && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* + +RUN pip --no-cache-dir install --upgrade \ + pip setuptools + +RUN pip --no-cache-dir install wheel + +# Download and build TensorFlow. +WORKDIR / +RUN rm -rf tensorflow && \ + git clone https://github.com/tensorflow/tensorflow.git && \ + cd tensorflow && \ + git checkout ${TF_BRANCH} +WORKDIR /tensorflow + +# Configure the build for CPU with MKL by accepting default build options and +# setting library locations +ENV CI_BUILD_PYTHON=python \ + LD_LIBRARY_PATH=${LD_LIBRARY_PATH} \ + PYTHON_BIN_PATH=/usr/bin/python \ + PYTHON_LIB_PATH=/usr/local/lib/python2.7/dist-packages \ + CC_OPT_FLAGS='-march=native' \ + TF_NEED_JEMALLOC=0 \ + TF_NEED_GCP=0 \ + TF_NEED_CUDA=0 \ + TF_NEED_HDFS=0 \ + TF_NEED_S3=0 \ + TF_NEED_OPENCL=0 \ + TF_NEED_GDR=0 \ + TF_ENABLE_XLA=0 \ + TF_NEED_VERBS=0 \ + TF_NEED_MPI=0 +RUN ./configure + +# Build and Install TensorFlow. +# The 'mkl' option builds with Intel(R) Math Kernel Library (MKL), which detects +# the platform it is currently running on and takes appropriately optimized +# paths. The -march=native option is for code that is not in MKL, and assumes +# this container will be run on the same architecture on which it is built. +RUN LD_LIBRARY_PATH=${LD_LIBRARY_PATH} \ + bazel build --config=mkl \ + --config="opt" \ + --copt="-march=native" \ + --copt="-O3" \ + //tensorflow/tools/pip_package:build_pip_package && \ + mkdir ${WHL_DIR} && \ + bazel-bin/tensorflow/tools/pip_package/build_pip_package ${WHL_DIR} + +# Clean up Bazel cache when done, but leave the whl. +# This will upgrade the default Tensorflow version with the Intel MKL version +RUN pip --no-cache-dir install --upgrade ${WHL_DIR}/tensorflow-*.whl && \ + rm -rf /root/.cache + +WORKDIR /root + +#add welcome message with instructions + +RUN echo '[ ! -z "$TERM" -a -r /etc/motd ] && cat /etc/issue && cat /etc/motd' \ + >> /etc/bash.bashrc \ + ; echo "\ +||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n\ +| \n\ +| Docker container running Ubuntu \n\ +| with TensorFlow ${TF_BRANCH} optimized for CPU \n\ +| with Intel(R) MKL \n\ +| \n\ +||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n\ +\n "\ + > /etc/motd + +CMD ["/bin/bash"] diff --git a/tensorflow/tools/docker/Dockerfile.devel-gpu b/tensorflow/tools/docker/Dockerfile.devel-gpu index 21a44ee4044..041f45971bc 100644 --- a/tensorflow/tools/docker/Dockerfile.devel-gpu +++ b/tensorflow/tools/docker/Dockerfile.devel-gpu @@ -102,5 +102,3 @@ WORKDIR /root EXPOSE 6006 # IPython EXPOSE 8888 - -RUN ["/bin/bash"] diff --git a/tensorflow/tools/docker/Dockerfile.devel-gpu-cuda9-cudnn7 b/tensorflow/tools/docker/Dockerfile.devel-gpu-cuda9-cudnn7 index 9bcc3925a8a..3bedc8cf346 100644 --- a/tensorflow/tools/docker/Dockerfile.devel-gpu-cuda9-cudnn7 +++ b/tensorflow/tools/docker/Dockerfile.devel-gpu-cuda9-cudnn7 @@ -113,5 +113,3 @@ WORKDIR /root EXPOSE 6006 # IPython EXPOSE 8888 - -RUN ["/bin/bash"] diff --git a/tensorflow/tools/docker/notebooks/2_getting_started.ipynb b/tensorflow/tools/docker/notebooks/2_getting_started.ipynb index e171b439fee..b0963ebc3f7 100644 --- a/tensorflow/tools/docker/notebooks/2_getting_started.ipynb +++ b/tensorflow/tools/docker/notebooks/2_getting_started.ipynb @@ -159,7 +159,7 @@ "X = np.array([np.linspace(-2, 4, num_examples), np.linspace(-6, 6, num_examples)])\n", "X += np.random.randn(2, num_examples)\n", "x, y = X\n", - "x_with_bias = np.array([(1., a) for a in x]).astype(np.float32)\n", + "bias_with_x = np.array([(1., a) for a in x]).astype(np.float32)\n", "\n", "losses = []\n", "training_steps = 50\n", @@ -167,7 +167,7 @@ "\n", "with tf.Session() as sess:\n", " # Set up all the tensors, variables, and operations.\n", - " input = tf.constant(x_with_bias)\n", + " input = tf.constant(bias_with_x)\n", " target = tf.constant(np.transpose([y]).astype(np.float32))\n", " weights = tf.Variable(tf.random_normal([2, 1], 0, 0.1))\n", "\n", @@ -583,7 +583,7 @@ "# Split into x and y\n", "x, y = X\n", "# Add the bias node which always has a value of 1\n", - "x_with_bias = np.array([(1., a) for a in x]).astype(np.float32)\n", + "bias_with_x = np.array([(1., a) for a in x]).astype(np.float32)\n", "\n", "# Keep track of the loss at each iteration so we can chart it later\n", "losses = []\n", @@ -598,7 +598,7 @@ "with tf.Session() as sess:\n", " # Set up all the tensors.\n", " # Our input layer is the x value and the bias node.\n", - " input = tf.constant(x_with_bias)\n", + " input = tf.constant(bias_with_x)\n", " # Our target is the y values. They need to be massaged to the right shape.\n", " target = tf.constant(np.transpose([y]).astype(np.float32))\n", " # Weights are a variable. They change every time through the loop.\n", @@ -621,7 +621,7 @@ " loss = tf.nn.l2_loss(yerror)\n", "\n", " # Perform gradient descent. \n", - " # This essentially just updates weights, like weights += grads * learning_rate\n", + " # This essentially just updates weights, like weights -= grads * learning_rate\n", " # using the partial derivative of the loss with respect to the\n", " # weights. It's the direction we want to go to move toward lower error.\n", " update_weights = tf.train.GradientDescentOptimizer(learning_rate).minimize(loss)\n", @@ -743,7 +743,7 @@ "with tf.Session() as sess:\n", " # Set up all the tensors.\n", " # The input is the x values with the bias appended on to each x.\n", - " input = tf.constant(x_with_bias)\n", + " input = tf.constant(bias_with_x)\n", " # We're trying to find the best fit for the target y values.\n", " target = tf.constant(np.transpose([y]).astype(np.float32))\n", " # Let's set up the weights randomly\n", diff --git a/tensorflow/tools/docker/notebooks/3_mnist_from_scratch.ipynb b/tensorflow/tools/docker/notebooks/3_mnist_from_scratch.ipynb index 614a19c178d..5585ebdcd36 100644 --- a/tensorflow/tools/docker/notebooks/3_mnist_from_scratch.ipynb +++ b/tensorflow/tools/docker/notebooks/3_mnist_from_scratch.ipynb @@ -135,6 +135,8 @@ "from six.moves.urllib.request import urlretrieve\n", "\n", "SOURCE_URL = 'https://storage.googleapis.com/cvdf-datasets/mnist/'\n", + "#SOURCE_URL = 'http://yann.lecun.com/exdb/mnist/'\n", + "# for those who have no access to google storage, use lecun's repo please\n", "WORK_DIRECTORY = \"/tmp/mnist-data\"\n", "\n", "def maybe_download(filename):\n", diff --git a/tensorflow/tools/pip_package/pip_smoke_test.py b/tensorflow/tools/pip_package/pip_smoke_test.py index 3677aaa886f..cc46dd5162b 100644 --- a/tensorflow/tools/pip_package/pip_smoke_test.py +++ b/tensorflow/tools/pip_package/pip_smoke_test.py @@ -66,9 +66,6 @@ BLACKLIST = [ "//tensorflow/contrib/timeseries/examples:data/period_trend.csv", # pylint:disable=line-too-long "//tensorflow/contrib/timeseries/python/timeseries:test_utils", "//tensorflow/contrib/timeseries/python/timeseries/state_space_models:test_utils", # pylint:disable=line-too-long - - # TODO(yifeif): Remove when py_library(testonly=1) is ignored. - "//tensorflow/contrib/summary:summary_test_internal", ] diff --git a/tensorflow/tools/pip_package/setup.py b/tensorflow/tools/pip_package/setup.py index a493c6f2aae..3852b251d95 100644 --- a/tensorflow/tools/pip_package/setup.py +++ b/tensorflow/tools/pip_package/setup.py @@ -33,11 +33,16 @@ _VERSION = '1.4.0' REQUIRED_PACKAGES = [ 'absl-py', - 'enum34 >= 1.1.6', + # weakref.finalize introduced in Python 3.4 + 'backports.weakref >= 1.0rc1; python_version < "3.4"', + # enum module introduced in Python 3.4 + 'enum34 >= 1.1.6; python_version < "3.4"', + # Needed for unittest.mock in Python 2 + 'mock >= 2.0.0; python_version < "3.0"', 'numpy >= 1.12.1', 'six >= 1.10.0', 'protobuf >= 3.4.0', - 'tensorflow-tensorboard >= 0.4.0rc1, < 0.5.0', + 'tensorflow-tensorboard', ] project_name = 'tensorflow' @@ -52,20 +57,14 @@ if sys.version_info.major == 3: REQUIRED_PACKAGES.append('wheel >= 0.26') else: REQUIRED_PACKAGES.append('wheel') - # mock comes with unittest.mock for python3, need to install for python2 - REQUIRED_PACKAGES.append('mock >= 2.0.0') -# remove tensorboard from tf-nightly packages +# tf-nightly should depend on tb-nightly if 'tf_nightly' in project_name: - for package in REQUIRED_PACKAGES: - if 'tensorflow-tensorboard' in package: - REQUIRED_PACKAGES.remove(package) + for i, pkg in enumerate(REQUIRED_PACKAGES): + if 'tensorboard' in pkg: + REQUIRED_PACKAGES[i] = 'tb-nightly >= 1.5.0a0, < 1.6.0a0' break -# weakref.finalize was introduced in Python 3.4 -if sys.version_info < (3, 4): - REQUIRED_PACKAGES.append('backports.weakref >= 1.0rc1') - # pylint: disable=line-too-long CONSOLE_SCRIPTS = [ 'freeze_graph = tensorflow.python.tools.freeze_graph:main', @@ -76,13 +75,13 @@ CONSOLE_SCRIPTS = [ # is now declared by the tensorboard pip package. If we remove the # TensorBoard command, pip will inappropriately remove it during install, # even though the command is not removed, just moved to a different wheel. - 'tensorboard = tensorboard.main:main', + 'tensorboard = tensorboard.main:run_main', ] # pylint: enable=line-too-long # remove the tensorboard console script if building tf_nightly if 'tf_nightly' in project_name: - CONSOLE_SCRIPTS.remove('tensorboard = tensorboard.main:main') + CONSOLE_SCRIPTS.remove('tensorboard = tensorboard.main:run_main') TEST_PACKAGES = [ 'scipy >= 0.15.1', diff --git a/tensorflow/workspace.bzl b/tensorflow/workspace.bzl index 68d663acfc5..b61012f71e3 100644 --- a/tensorflow/workspace.bzl +++ b/tensorflow/workspace.bzl @@ -80,7 +80,7 @@ def _apply_patch(repo_ctx, patch_file): bazel_sh = _get_env_var(repo_ctx, "BAZEL_SH") if not bazel_sh: fail("BAZEL_SH environment variable is not set") - cmd = [bazel_sh, "-c", " ".join(cmd)] + cmd = [bazel_sh, "-l", "-c", " ".join(cmd)] _execute_and_check_ret_code(repo_ctx, cmd) # Download the repository and apply a patch to its root diff --git a/third_party/flatbuffers/flatbuffers.BUILD b/third_party/flatbuffers/flatbuffers.BUILD index e1563103c86..0a76adcf918 100644 --- a/third_party/flatbuffers/flatbuffers.BUILD +++ b/third_party/flatbuffers/flatbuffers.BUILD @@ -6,8 +6,11 @@ licenses(["notice"]) # Apache 2.0 FLATBUFFERS_COPTS = [ "-fexceptions", - "-Wno-implicit-fallthrough", -] +] + select({ + "@bazel_tools//src:windows": [], + "@bazel_tools//src:windows_msvc": [], + "//conditions:default": ["-Wno-implicit-fallthrough"], +}) # Public flatc library to compile flatbuffer files at runtime. cc_library( diff --git a/third_party/mkl/build_defs.bzl b/third_party/mkl/build_defs.bzl index f637873f147..8b73ddabdd7 100644 --- a/third_party/mkl/build_defs.bzl +++ b/third_party/mkl/build_defs.bzl @@ -20,7 +20,7 @@ def if_mkl(if_true, if_false = []): """ return select({ - "//third_party/mkl:using_mkl": if_true, + str(Label("//third_party/mkl:using_mkl")): if_true, "//conditions:default": if_false }) diff --git a/third_party/nccl.BUILD b/third_party/nccl.BUILD index 3a2a3afe461..b2b8e188248 100644 --- a/third_party/nccl.BUILD +++ b/third_party/nccl.BUILD @@ -55,7 +55,7 @@ cc_library( ], "@org_tensorflow//tensorflow:ios": [], "@org_tensorflow//tensorflow:windows": [ - "ws2_32.lib", + "-DEFAULTLIB:ws2_32.lib", ], "//conditions:default": [ "-lrt", diff --git a/third_party/py/python_configure.bzl b/third_party/py/python_configure.bzl index bbc07905fc7..c16eb3a12a8 100644 --- a/third_party/py/python_configure.bzl +++ b/third_party/py/python_configure.bzl @@ -1,11 +1,8 @@ -# -*- Python -*- """Repository rule for Python autoconfiguration. `python_configure` depends on the following environment variables: - * `NUMPY_INCLUDE_PATH`: Location of Numpy libraries. * `PYTHON_BIN_PATH`: location of python binary. - * `PYTHON_INCLUDE_PATH`: Location of python binaries. * `PYTHON_LIB_PATH`: Location of python libraries. """ @@ -23,32 +20,13 @@ def _tpl(repository_ctx, tpl, substitutions={}, out=None): substitutions) -def _python_configure_warning(msg): - """Output warning message during auto configuration.""" - yellow = "\033[1;33m" - no_color = "\033[0m" - print("%sPython Configuration Warning:%s %s" % (yellow, no_color, msg)) - - -def _python_configure_fail(msg): +def _fail(msg): """Output failure message when auto configuration fails.""" red = "\033[0;31m" no_color = "\033[0m" fail("%sPython Configuration Error:%s %s\n" % (red, no_color, msg)) -def _get_env_var(repository_ctx, name, default = None, enable_warning = True): - """Find an environment variable in system path.""" - if name in repository_ctx.os.environ: - return repository_ctx.os.environ[name] - if default != None: - if enable_warning: - _python_configure_warning( - "'%s' environment variable is not set, using '%s' as default" % (name, default)) - return default - _python_configure_fail("'%s' environment variable is not set" % name) - - def _is_windows(repository_ctx): """Returns true if the host operating system is windows.""" os_name = repository_ctx.os.name.lower() @@ -73,11 +51,10 @@ def _execute(repository_ctx, cmdline, error_msg=None, error_details=None, """ result = repository_ctx.execute(cmdline) if result.stderr or not (empty_stdout_fine or result.stdout): - _python_configure_fail( - "\n".join([ - error_msg.strip() if error_msg else "Repository command failed", - result.stderr.strip(), - error_details if error_details else ""])) + _fail("\n".join([ + error_msg.strip() if error_msg else "Repository command failed", + result.stderr.strip(), + error_details if error_details else ""])) return result @@ -163,21 +140,23 @@ def _symlink_genrule_for_dir(repository_ctx, src_dir, dest_dir, genrule_name, def _get_python_bin(repository_ctx): """Gets the python bin path.""" - python_bin = _get_env_var(repository_ctx, _PYTHON_BIN_PATH, - None, False) + python_bin = repository_ctx.os.environ.get(_PYTHON_BIN_PATH) if python_bin != None: return python_bin python_bin_path = repository_ctx.which("python") if python_bin_path != None: return str(python_bin_path) - path = _get_env_var(repository_ctx, "PATH") - _python_configure_fail("Cannot find python in PATH, please make sure " + - "python is installed and add its directory in PATH, or set the " + - "environment variable PYTHON_BIN_PATH.\nPATH=%s" % (path)) + _fail("Cannot find python in PATH, please make sure " + + "python is installed and add its directory in PATH, or --define " + + "%s='/something/else'.\nPATH=%s" % ( + _PYTHON_BIN_PATH, repository_ctx.os.environ.get("PATH", ""))) def _get_python_lib(repository_ctx, python_bin): """Gets the python lib path.""" + python_lib = repository_ctx.os.environ.get(_PYTHON_LIB_PATH) + if python_lib != None: + return python_lib print_lib = ("<