Add rpi4ub-armv8 build configuration

This reverts commit 9b67f161e5.

.bazelrc

@@ -94,6 +94,9 @@ build:libc++ --linkopt -fuse-ld=lld
 # https://docs.bazel.build/versions/master/user-manual.html#flag--fat_apk_cpu
 build:android --crosstool_top=//external:android/crosstool
 build:android --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
+build:android --copt=-D_GLIBCXX_USE_C99
+build:android --cxxopt=-std=c++14
+build:android --action_env ANDROID_NDK_API_LEVEL=21
 build:android_arm --config=android
 build:android_arm --cpu=armeabi-v7a
 build:android_arm --fat_apk_cpu=armeabi-v7a
@@ -202,6 +205,29 @@ build:sycl_asan --copt -fno-omit-frame-pointer --copt -fsanitize-coverage=3 --co
 build:sycl_nodouble --config=sycl
 build:sycl_trisycl --define=using_trisycl=true
 
+build --copt=-DTFLITE_WITH_RUY_GEMV
+
+build:rpi3 --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
+build:rpi3 --crosstool_top=//third_party/toolchains/embedded/linaro-gcc72-armeabi:toolchain
+build:rpi3 --cpu=armv7a --define=target_system=rpi3
+build:rpi3 --copt=-march=armv7-a --copt=-mtune=cortex-a53 --copt=-mfloat-abi=hard --copt=-mfpu=neon-fp-armv8 --copt=-DRASPBERRY_PI --copt=-D_GLIBCXX_USE_CXX11_ABI=0 --copt=-std=gnu99 --copt=-mno-unaligned-access
+build:rpi3 --define=tensorflow_mkldnn_contraction_kernel=0
+build:rpi3_opt -c opt --config=rpi3 --copt=-funsafe-math-optimizations --copt=-ftree-vectorize --copt=-pipe
+
+build:rpi3-armv8 --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
+build:rpi3-armv8 --crosstool_top=//third_party/toolchains/embedded/linaro-gcc72-aarch64:toolchain
+build:rpi3-armv8 --cpu=aarch64 --define=target_system=rpi3-armv8
+build:rpi3-armv8 --copt=-march=armv8-a --copt=-mtune=cortex-a53 --copt=-DRASPBERRY_PI --copt=-D_GLIBCXX_USE_CXX11_ABI=0 --copt=-std=gnu99
+build:rpi3-armv8 --define=tensorflow_mkldnn_contraction_kernel=0
+build:rpi3-armv8_opt -c opt --config=rpi3-armv8 --copt=-funsafe-math-optimizations --copt=-ftree-vectorize --copt=-pipe
+
+build:rpi4ub-armv8 --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
+build:rpi4ub-armv8 --crosstool_top=//third_party/toolchains/embedded/linaro-gcc72-aarch64:toolchain
+build:rpi4ub-armv8 --cpu=aarch64 --define=target_system=rpi4ub-armv8
+build:rpi4ub-armv8 --copt=-march=armv8-a --copt=-mtune=cortex-a72 --copt=-DRASPBERRY_PI --copt=-D_GLIBCXX_USE_CXX11_ABI=0 --copt=-std=gnu99
+build:rpi4ub-armv8 --define=tensorflow_mkldnn_contraction_kernel=0
+build:rpi4ub-armv8_opt -c opt --config=rpi4ub-armv8 --copt=-funsafe-math-optimizations --copt=-ftree-vectorize --copt=-pipe
+
 # Options extracted from configure script
 build:ngraph --define=with_ngraph_support=true
 build:numa --define=with_numa_support=true

.github/pull_request_template.md

@@ -0,0 +1,15 @@
+# Pull request guidelines
+
+Welcome to the 🐸tensorflow project! We are excited to see your interest, and appreciate your support!
+
+This repository is governed by the Contributor Covenant Code of Conduct. For more details, see the [CODE_OF_CONDUCT.md](CODE_OF_CONDUCT.md) file.
+
+In order to make a good pull request, please see our [CONTRIBUTING.md](CONTRIBUTING.md) file.
+
+Before accepting your pull request, you will be asked to sign a [Contributor License Agreement](https://cla-assistant.io/coqui-ai/tensorflow).
+
+This [Contributor License Agreement](https://cla-assistant.io/coqui-ai/tensorflow):
+
+- Protects you, Coqui, and the users of the code.
+- Does not change your rights to use your contributions for any purpose.
+- Does not change the license of the 🐸tensorflow project. It just makes the terms of your contribution clearer and lets us know you are OK to contribute.

RELEASE.md

@@ -1,78 +1,3 @@
-# Release 2.3.2
-
-## Bug Fixes and Other Changes
-* Fixes an access to unitialized memory in Eigen code
-  ([CVE-2020-26266](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-26266))
-* Fixes a security vulnerability caused by lack of validation in
-  `tf.raw_ops.DataFormatVecPermute` and `tf.raw_ops.DataFormatDimMap`
-  ([CVE-2020-26267](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-26267))
-* Fixes a vulnerability caused by attempting to write to immutable memory region in
-  `tf.raw_ops.ImmutableConst`
-  ([CVE-2020-26268](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-26268)
-* Fixes a `CHECK`-fail in LSTM with zero-length input
-  ([CVE-2020-26270](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-26270))
-* Fixes a security vulnerability caused by accessing heap data outside of bounds
-  when loading a specially crafted `SavedModel`
-  ([CVE-2020-26271](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-26271))
-* Solves an OOM issue on TPUs when XLA contexts use fused average updates
-* Updates `libjpeg-turbo` to `2.0.5` to handle
-  [CVE-2020-13790](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-13790).
-* Updates `junit` to `4.13.1` to handle
-  [CVE-2020-15250](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15250).
-* Updates `PCRE` to `8.44` to handle
-  [CVE-2019-20838](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-20838)
-  and
-  [CVE-2020-14155](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-14155).
-* Updates `sqlite3` to `3.44.0` to keep in sync with master branch.
-
-# Release 2.3.1
-
-## Bug Fixes and Other Changes
-* Fixes an undefined behavior causing a segfault in `tf.raw_ops.Switch`
-  ([CVE-2020-15190](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15190))
-* Fixes three vulnerabilities in conversion to DLPack format
-  ([CVE-2020-15191](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15191),
-  [CVE-2020-15192](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15192),
-  [CVE-2020-15193](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15193))
-* Fixes two vulnerabilities in `SparseFillEmptyRowsGrad`
-  ([CVE-2020-15194](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15194),
-  [CVE-2020-15195](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15195))
-* Fixes several vulnerabilities in `RaggedCountSparseOutput` and
-  `SparseCountSparseOutput` operations
-  ([CVE-2020-15196](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15196),
-  [CVE-2020-15197](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15197),
-  [CVE-2020-15198](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15198),
-  [CVE-2020-15199](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15199),
-  [CVE-2020-15200](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15200),
-  [CVE-2020-15201](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15201))
-* Fixes an integer truncation vulnerability in code using the work sharder API
-  ([CVE-2020-15202](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15202))
-* Fixes a format string vulnerability in `tf.strings.as_string`
-  ([CVE-2020-15203](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15203))
-* Fixes segfault raised by calling session-only ops in eager mode
-  ([CVE-2020-15204](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15204))
-* Fixes data leak and potential ASLR violation from `tf.raw_ops.StringNGrams`
-  ([CVE-2020-15205](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15205))
-* Fixes segfaults caused by incomplete `SavedModel` validation
-  ([CVE-2020-15206](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15206))
-* Fixes a data corruption due to a bug in negative indexing support in TFLite
-  ([CVE-2020-15207](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15207))
-* Fixes a data corruption due to dimension mismatch in TFLite
-  ([CVE-2020-15208](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15208))
-* Fixes several vulnerabilities in TFLite saved model format
-  ([CVE-2020-15209](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15209),
-  [CVE-2020-15210](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15210),
-  [CVE-2020-15211](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15211))
-* Fixes several vulnerabilities in TFLite implementation of segment sum
-  ([CVE-2020-15212](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15212),
-  [CVE-2020-15213](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15213),
-  [CVE-2020-15214](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15214))
-* Updates `sqlite3` to `3.33.00` to handle
-  [CVE-2020-15358](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15358).
-* Fixes deprecated usage of `collections` API
-* Removes `scipy` dependency from `setup.py` since TensorFlow does not need it
-  to install the pip package
-
 # Release 2.3.0
 
 ## Major Features and Improvements

WORKSPACE

@@ -18,6 +18,18 @@ load("//tensorflow:workspace.bzl", "tf_repositories")
 # Please add all new TensorFlow dependencies in workspace.bzl.
 tf_repositories()
 
+load("@bazel_tools//tools/build_defs/repo:git.bzl", "git_repository")
+
+git_repository(
+    name = "com_github_nelhage_rules_boost",
+    commit = "1e3a69bf2d5cd10c34b74f066054cd335d033d71",
+    remote = "https://github.com/nelhage/rules_boost",
+    shallow_since = "1591047380 -0700",
+)
+
+load("@com_github_nelhage_rules_boost//:boost/boost.bzl", "boost_deps")
+boost_deps()
+
 register_toolchains("@local_config_python//:py_toolchain")
 
 load("@io_bazel_rules_closure//closure:defs.bzl", "closure_repositories")

native_client

@@ -0,0 +1 @@
+../native_client

tensorflow/c/eager/dlpack.cc

@@ -248,36 +248,21 @@ void TFE_CallDLManagedTensorDeleter(void* dlm_ptr) {
 }
 
 void* TFE_HandleToDLPack(TFE_TensorHandle* h, TF_Status* status) {
-  auto tf_dlm_context = GetDlContext(h, status);
-  if (!status->status.ok()) {
-    return nullptr;
-  }
-
-  auto* tf_dlm_data = TFE_TensorHandleDevicePointer(h, status);
-  if (!status->status.ok()) {
-    return nullptr;
-  }
-
   const Tensor* tensor = GetTensorFromHandle(h, status);
   TF_DataType data_type = static_cast<TF_DataType>(tensor->dtype());
-
-  auto tf_dlm_type = GetDlDataType(data_type, status);
-  if (!status->status.ok()) {
-    return nullptr;
-  }
-
   TensorReference tensor_ref(*tensor);  // This will call buf_->Ref()
+
   auto* tf_dlm_tensor_ctx = new TfDlManagedTensorCtx(tensor_ref);
   tf_dlm_tensor_ctx->reference = tensor_ref;
 
   DLManagedTensor* dlm_tensor = &tf_dlm_tensor_ctx->tensor;
   dlm_tensor->manager_ctx = tf_dlm_tensor_ctx;
   dlm_tensor->deleter = &DLManagedTensorDeleter;
-  dlm_tensor->dl_tensor.ctx = tf_dlm_context;
+  dlm_tensor->dl_tensor.ctx = GetDlContext(h, status);
   int ndim = tensor->dims();
   dlm_tensor->dl_tensor.ndim = ndim;
-  dlm_tensor->dl_tensor.data = tf_dlm_data;
-  dlm_tensor->dl_tensor.dtype = tf_dlm_type;
+  dlm_tensor->dl_tensor.data = TFE_TensorHandleDevicePointer(h, status);
+  dlm_tensor->dl_tensor.dtype = GetDlDataType(data_type, status);
 
   std::vector<int64_t>* shape_arr = &tf_dlm_tensor_ctx->shape;
   std::vector<int64_t>* stride_arr = &tf_dlm_tensor_ctx->strides;
@@ -290,14 +275,13 @@ void* TFE_HandleToDLPack(TFE_TensorHandle* h, TF_Status* status) {
     (*stride_arr)[i] = (*shape_arr)[i + 1] * (*stride_arr)[i + 1];
   }
 
-  dlm_tensor->dl_tensor.shape = shape_arr->data();
+  dlm_tensor->dl_tensor.shape = &(*shape_arr)[0];
   // There are two ways to represent compact row-major data
   // 1) nullptr indicates tensor is compact and row-majored.
   // 2) fill in the strides array as the real case for compact row-major data.
   // Here we choose option 2, since some frameworks didn't handle the strides
   // argument properly.
-  dlm_tensor->dl_tensor.strides = stride_arr->data();
-
+  dlm_tensor->dl_tensor.strides = &(*stride_arr)[0];
   dlm_tensor->dl_tensor.byte_offset =
       0;  // TF doesn't handle the strides and byte_offsets here
   return static_cast<void*>(dlm_tensor);

tensorflow/cc/saved_model/loader.cc

@@ -21,7 +21,6 @@ limitations under the License.
 #include "tensorflow/cc/saved_model/loader_util.h"
 #include "tensorflow/cc/saved_model/reader.h"
 #include "tensorflow/core/framework/attr_value.pb.h"
-#include "tensorflow/core/framework/function.pb.h"
 #include "tensorflow/core/framework/node_def.pb.h"
 #include "tensorflow/core/framework/tensor.pb.h"
 #include "tensorflow/core/lib/io/path.h"
@@ -73,41 +72,26 @@ uint64 GetLatencyMicroseconds(const uint64 start_microseconds) {
 // Ensure that constant tensors loaded from the saved model have valid shape.
 // Also ensure that constant nodes have a value assigned to them.
 // TODO(b/154763635): this is temporary and will be replaced with a better audit
-static Status ValidateNode(const NodeDef& node) {
-  const auto node_iterator = node.attr().find("value");
-  if (node_iterator != node.attr().end()) {
-    AttrValue node_value = node_iterator->second;
-    if (node_value.has_tensor()) {
-      const PartialTensorShape node_shape(node_value.tensor().tensor_shape());
-      if (node_shape.num_elements() < 0) {
-        return errors::FailedPrecondition(
-            "Saved model contains node \"", node.name(), "\" (op \"", node.op(),
-            "\") which initializes from a tensor with ",
-            node_shape.num_elements(), " elements");
-      }
-    }
-  } else if (node.op() == "Const") {
-    return errors::FailedPrecondition(
-        "Saved model contains node \"", node.name(),
-        "\" which is a constant tensor but no value has been provided");
-  }
-  return Status::OK();
-}
-
 static Status ValidateSavedTensors(const GraphDef& graph_def) {
   for (const auto& node : graph_def.node()) {
-    TF_RETURN_IF_ERROR(ValidateNode(node));
-  }
-
-  if (graph_def.has_library()) {
-    const FunctionDefLibrary& library = graph_def.library();
-    for (const auto& function : library.function()) {
-      for (const auto& node : function.node_def()) {
-	TF_RETURN_IF_ERROR(ValidateNode(node));
+    const auto node_iterator = node.attr().find("value");
+    if (node_iterator != node.attr().end()) {
+      AttrValue node_value = node_iterator->second;
+      if (node_value.has_tensor()) {
+        const PartialTensorShape node_shape(node_value.tensor().tensor_shape());
+        if (node_shape.num_elements() < 0) {
+          return errors::FailedPrecondition(
+              "Saved model contains node \"", node.name(), "\" (op \"",
+              node.op(), "\") which initializes from a tensor with ",
+              node_shape.num_elements(), " elements");
+        }
       }
+    } else if (node.op() == "Const") {
+      return errors::FailedPrecondition(
+          "Saved model contains node \"", node.name(),
+          "\" which is a constant tensor but no value has been provided");
     }
   }
-
   return Status::OK();
 }
 

tensorflow/core/common_runtime/eager/kernel_and_device.cc

@@ -307,12 +307,7 @@ Status KernelAndDeviceOp::Run(
   if (outputs != nullptr) {
     outputs->clear();
     for (int i = 0; i < context.num_outputs(); ++i) {
-      const auto* output_tensor = context.mutable_output(i);
-      if (output_tensor != nullptr) {
-        outputs->push_back(Tensor(*output_tensor));
-      } else {
-        outputs->push_back(Tensor());
-      }
+      outputs->push_back(Tensor(*context.mutable_output(i)));
     }
   }
   return Status::OK();

tensorflow/core/common_runtime/graph_constructor.cc

@@ -44,7 +44,6 @@ limitations under the License.
 #include "tensorflow/core/lib/gtl/inlined_vector.h"
 #include "tensorflow/core/lib/strings/scanner.h"
 #include "tensorflow/core/lib/strings/str_util.h"
-#include "tensorflow/core/platform/errors.h"
 #include "tensorflow/core/platform/logging.h"
 #include "tensorflow/core/platform/macros.h"
 #include "tensorflow/core/public/version.h"
@@ -1426,17 +1425,6 @@ void GraphConstructor::Undo() {
 
 Status GraphConstructor::MakeEdge(Node* src, int output_index, Node* dst,
                                   int input_index) {
-  if (output_index >= src->num_outputs()) {
-    return errors::InvalidArgument(
-        "Output ", output_index, " of node ", src->name(),
-        " does not exist. Node only has ", src->num_outputs(), " outputs.");
-  }
-  if (input_index >= dst->num_inputs()) {
-    return errors::InvalidArgument(
-        "Input ", input_index, " of node ", dst->name(),
-        " does not exist. Node only has ", dst->num_inputs(), " inputs.");
-  }
-
   DataType src_out = src->output_type(output_index);
   DataType dst_in = dst->input_type(input_index);
   if (!TypesCompatible(dst_in, src_out)) {

tensorflow/core/kernels/BUILD

@@ -5864,15 +5864,15 @@ cc_library(
         ":string_format_op",
         ":string_join_op",
         ":string_length_op",
-        ":string_lower_op",
+        # ":string_lower_op",
         ":string_ngrams_op",
         ":string_split_op",
         ":string_strip_op",
         ":string_to_hash_bucket_op",
-        ":string_upper_op",
+        # ":string_upper_op",
         ":substr_op",
-        ":unicode_ops",
-        ":unicode_script_op",
+        # ":unicode_ops",
+        # ":unicode_script_op",
         ":unsorted_segment_join_op",
     ],
 )
@@ -5885,7 +5885,7 @@ cc_library(
         "//tensorflow/core:framework",
         "//tensorflow/core:lib",
         "//tensorflow/core:protos_all_cc",
-        "@icu//:common",
+        # "@icu//:common",
     ],
 )
 
@@ -6041,7 +6041,7 @@ tf_kernel_library(
     prefix = "string_lower_op",
     deps = STRING_DEPS + [
         "@com_google_absl//absl/strings",
-        "@icu//:common",
+        # "@icu//:common",
     ],
 )
 
@@ -6050,7 +6050,7 @@ tf_kernel_library(
     prefix = "string_upper_op",
     deps = STRING_DEPS + [
         "@com_google_absl//absl/strings",
-        "@icu//:common",
+        # "@icu//:common",
     ],
 )
 
@@ -6085,24 +6085,6 @@ tf_kernel_library(
     deps = STRING_DEPS,
 )
 
-tf_cc_test(
-    name = "as_string_op_test",
-    size = "small",
-    srcs = ["as_string_op_test.cc"],
-    deps = [
-        ":as_string_op",
-        ":ops_testutil",
-        ":ops_util",
-        "//tensorflow/core:core_cpu",
-        "//tensorflow/core:framework",
-        "//tensorflow/core:lib",
-        "//tensorflow/core:protos_all_cc",
-        "//tensorflow/core:test",
-        "//tensorflow/core:test_main",
-        "//tensorflow/core:testlib",
-    ],
-)
-
 tf_kernel_library(
     name = "unicode_ops",
     prefix = "unicode_ops",
@@ -6114,7 +6096,7 @@ tf_kernel_library(
         "//tensorflow/core:lib_internal",
         "//third_party/eigen3",
         "//third_party/icu/data:conversion_data",
-        "@icu//:common",
+        # "@icu//:common",
     ],
 )
 
@@ -7143,10 +7125,10 @@ filegroup(
             "mutex_ops.*",
             "batch_kernels.*",
             "regex_replace_op.cc",
-            "string_lower_op.cc",  # Requires ICU for unicode.
-            "string_upper_op.cc",  # Requires ICU for unicode.
+            # "string_lower_op.cc",  # Requires ICU for unicode.
+            # "string_upper_op.cc",  # Requires ICU for unicode.
             "unicode_ops.cc",
-            "unicode_script_op.cc",
+            # "unicode_script_op.cc",
             # Ops that are inherently incompatible with Android (e.g. tied to x86 platform).
             "mkl_*",
             "xsmm_*",
@@ -8638,7 +8620,7 @@ tf_kernel_library(
     srcs = ["unicode_script_op.cc"],
     deps = [
         "//tensorflow/core:framework",
-        "@icu//:common",
+        # "@icu//:common",
     ],
 )
 
@@ -8670,6 +8652,39 @@ cc_library(
     ],
 )
 
+tf_kernel_library(
+    name = "deepspeech_cwise_ops",
+    srcs = [
+        "cwise_op_add_1.cc",
+        "cwise_op_add_2.cc",
+        "cwise_op_less.cc",
+        "cwise_op_minimum.cc",
+        "cwise_op_mul_1.cc",
+        "cwise_op_rsqrt.cc",
+        "cwise_op_squared_difference.cc",
+        "cwise_op_sub.cc",
+        "cwise_op_sigmoid.cc",
+        "cwise_op_tanh.cc",
+    ],
+    gpu_srcs = [
+        "cwise_op_gpu_add.cu.cc",
+        "cwise_op_gpu_less.cu.cc",
+        "cwise_op_gpu_minimum.cu.cc",
+        "cwise_op_gpu_mul.cu.cc",
+        "cwise_op_gpu_rsqrt.cu.cc",
+        "cwise_op_gpu_squared_difference.cu.cc",
+        "cwise_op_gpu_sub.cu.cc",
+        "cwise_op_gpu_sigmoid.cu.cc",
+        "cwise_op_gpu_tanh.cu.cc",
+    ],
+    deps = [
+        ":cwise_lib",
+        "//tensorflow/core:framework",
+        "//tensorflow/core:lib",
+        "//third_party/eigen3",
+    ],
+)
+
 # Header-only version of cwise_lib for clients that want to use the cwise_ops
 # functionality in their own custom ops.
 cc_header_only_library(

tensorflow/core/kernels/as_string_op.cc

@@ -65,26 +65,9 @@ class AsStringOp : public OpKernel {
     OP_REQUIRES(ctx, !(scientific && shortest),
                 errors::InvalidArgument(
                     "Cannot select both scientific and shortest notation"));
-
     format_ = "%";
-    if (!fill_string.empty()) {
-      switch (fill_string[0]) {
-        case ' ':
-        case '+':
-        case '-':
-        case '0':
-        case '#':
-          strings::Appendf(&format_, "%s", fill_string.c_str());
-          break;
-        default:
-          bool fill_not_supported = true;
-          OP_REQUIRES(ctx, !fill_not_supported,
-                      errors::InvalidArgument("Fill argument not supported: \"",
-                                              fill_string, "\""));
-      }
-    }
     if (width > -1) {
-      strings::Appendf(&format_, "%d", width);
+      strings::Appendf(&format_, "%s%d", fill_string.c_str(), width);
     }
     if (precision > -1) {
       strings::Appendf(&format_, ".%d", precision);

tensorflow/core/kernels/as_string_op_test.cc

@@ -1,245 +0,0 @@
-/* Copyright 2020 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 "tensorflow/core/framework/fake_input.h"
-#include "tensorflow/core/framework/node_def_builder.h"
-#include "tensorflow/core/framework/tensor.h"
-#include "tensorflow/core/framework/tensor_testutil.h"
-#include "tensorflow/core/framework/types.h"
-#include "tensorflow/core/kernels/ops_testutil.h"
-#include "tensorflow/core/kernels/ops_util.h"
-#include "tensorflow/core/lib/core/status_test_util.h"
-
-namespace tensorflow {
-namespace {
-
-class AsStringGraphTest : public OpsTestBase {
- protected:
-  Status Init(DataType input_type, const string& fill = "", int width = -1,
-              int precision = -1, bool scientific = false,
-              bool shortest = false) {
-    TF_CHECK_OK(NodeDefBuilder("op", "AsString")
-                    .Input(FakeInput(input_type))
-                    .Attr("fill", fill)
-                    .Attr("precision", precision)
-                    .Attr("scientific", scientific)
-                    .Attr("shortest", shortest)
-                    .Attr("width", width)
-                    .Finalize(node_def()));
-    return InitOp();
-  }
-};
-
-TEST_F(AsStringGraphTest, Int8) {
-  TF_ASSERT_OK(Init(DT_INT8));
-
-  AddInputFromArray<int8>(TensorShape({3}), {-42, 0, 42});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({3}));
-  test::FillValues<tstring>(&expected, {"-42", "0", "42"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, Int64) {
-  TF_ASSERT_OK(Init(DT_INT64));
-
-  AddInputFromArray<int64>(TensorShape({3}), {-42, 0, 42});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({3}));
-  test::FillValues<tstring>(&expected, {"-42", "0", "42"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, FloatDefault) {
-  TF_ASSERT_OK(Init(DT_FLOAT));
-
-  AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({4}));
-  test::FillValues<tstring>(
-      &expected, {"-42.000000", "0.000000", "3.141590", "42.000000"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, FloatScientific) {
-  TF_ASSERT_OK(Init(DT_FLOAT, /*fill=*/"", /*width=*/-1, /*precision=*/-1,
-                    /*scientific=*/true));
-
-  AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({4}));
-  test::FillValues<tstring>(&expected, {"-4.200000e+01", "0.000000e+00",
-                                        "3.141590e+00", "4.200000e+01"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, FloatShortest) {
-  TF_ASSERT_OK(Init(DT_FLOAT, /*fill=*/"", /*width=*/-1, /*precision=*/-1,
-                    /*scientific=*/false, /*shortest=*/true));
-
-  AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({4}));
-  test::FillValues<tstring>(&expected, {"-42", "0", "3.14159", "42"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, FloatPrecisionOnly) {
-  TF_ASSERT_OK(Init(DT_FLOAT, /*fill=*/"", /*width=*/-1, /*precision=*/2));
-
-  AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({4}));
-  test::FillValues<tstring>(&expected, {"-42.00", "0.00", "3.14", "42.00"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, FloatWidthOnly) {
-  TF_ASSERT_OK(Init(DT_FLOAT, /*fill=*/"", /*width=*/5));
-
-  AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({4}));
-  test::FillValues<tstring>(
-      &expected, {"-42.000000", "0.000000", "3.141590", "42.000000"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, Float_5_2_Format) {
-  TF_ASSERT_OK(Init(DT_FLOAT, /*fill=*/"", /*width=*/5, /*precision=*/2));
-
-  AddInputFromArray<float>(TensorShape({4}), {-42, 0, 3.14159, 42});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({4}));
-  test::FillValues<tstring>(&expected, {"-42.00", " 0.00", " 3.14", "42.00"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, Complex) {
-  TF_ASSERT_OK(Init(DT_COMPLEX64, /*fill=*/"", /*width=*/5, /*precision=*/2));
-
-  AddInputFromArray<complex64>(TensorShape({3}), {{-4, 2}, {0}, {3.14159, -1}});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({3}));
-  test::FillValues<tstring>(
-      &expected, {"(-4.00, 2.00)", "( 0.00, 0.00)", "( 3.14,-1.00)"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, Bool) {
-  TF_ASSERT_OK(Init(DT_BOOL));
-
-  AddInputFromArray<bool>(TensorShape({2}), {true, false});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({2}));
-  test::FillValues<tstring>(&expected, {"true", "false"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, String) {
-  Status s = Init(DT_STRING);
-  ASSERT_EQ(error::INVALID_ARGUMENT, s.code());
-  ASSERT_TRUE(absl::StrContains(
-      s.error_message(),
-      "Value for attr 'T' of string is not in the list of allowed values"));
-}
-
-TEST_F(AsStringGraphTest, OnlyOneOfScientificAndShortest) {
-  Status s = Init(DT_FLOAT, /*fill=*/"", /*width=*/-1, /*precision=*/-1,
-                  /*scientific=*/true, /*shortest=*/true);
-  ASSERT_EQ(error::INVALID_ARGUMENT, s.code());
-  ASSERT_TRUE(
-      absl::StrContains(s.error_message(),
-                        "Cannot select both scientific and shortest notation"));
-}
-
-TEST_F(AsStringGraphTest, NoShortestForNonFloat) {
-  Status s = Init(DT_INT32, /*fill=*/"", /*width=*/-1, /*precision=*/-1,
-                  /*scientific=*/false, /*shortest=*/true);
-  ASSERT_EQ(error::INVALID_ARGUMENT, s.code());
-  ASSERT_TRUE(absl::StrContains(
-      s.error_message(),
-      "scientific and shortest format not supported for datatype"));
-}
-
-TEST_F(AsStringGraphTest, NoScientificForNonFloat) {
-  Status s = Init(DT_INT32, /*fill=*/"", /*width=*/-1, /*precision=*/-1,
-                  /*scientific=*/true);
-  ASSERT_EQ(error::INVALID_ARGUMENT, s.code());
-  ASSERT_TRUE(absl::StrContains(
-      s.error_message(),
-      "scientific and shortest format not supported for datatype"));
-}
-
-TEST_F(AsStringGraphTest, NoPrecisionForNonFloat) {
-  Status s = Init(DT_INT32, /*fill=*/"", /*width=*/-1, /*precision=*/5);
-  ASSERT_EQ(error::INVALID_ARGUMENT, s.code());
-  ASSERT_TRUE(absl::StrContains(s.error_message(),
-                                "precision not supported for datatype"));
-}
-
-TEST_F(AsStringGraphTest, LongFill) {
-  Status s = Init(DT_INT32, /*fill=*/"asdf");
-  ASSERT_EQ(error::INVALID_ARGUMENT, s.code());
-  ASSERT_TRUE(absl::StrContains(s.error_message(),
-                                "Fill string must be one or fewer characters"));
-}
-
-TEST_F(AsStringGraphTest, FillWithZero) {
-  TF_ASSERT_OK(Init(DT_INT64, /*fill=*/"0", /*width=*/4));
-
-  AddInputFromArray<int64>(TensorShape({3}), {-42, 0, 42});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({3}));
-  test::FillValues<tstring>(&expected, {"-042", "0000", "0042"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, FillWithSpace) {
-  TF_ASSERT_OK(Init(DT_INT64, /*fill=*/" ", /*width=*/4));
-
-  AddInputFromArray<int64>(TensorShape({3}), {-42, 0, 42});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({3}));
-  test::FillValues<tstring>(&expected, {" -42", "   0", "  42"});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, FillWithChar1) {
-  TF_ASSERT_OK(Init(DT_INT64, /*fill=*/"-", /*width=*/4));
-
-  AddInputFromArray<int64>(TensorShape({3}), {-42, 0, 42});
-  TF_ASSERT_OK(RunOpKernel());
-  Tensor expected(allocator(), DT_STRING, TensorShape({3}));
-  test::FillValues<tstring>(&expected, {"-42 ", "0   ", "42  "});
-  test::ExpectTensorEqual<tstring>(expected, *GetOutput(0));
-}
-
-TEST_F(AsStringGraphTest, FillWithChar3) {
-  Status s = Init(DT_INT32, /*fill=*/"s");
-  ASSERT_EQ(error::INVALID_ARGUMENT, s.code());
-  ASSERT_TRUE(
-      absl::StrContains(s.error_message(), "Fill argument not supported"));
-}
-
-TEST_F(AsStringGraphTest, FillWithChar4) {
-  Status s = Init(DT_INT32, /*fill=*/"n");
-  ASSERT_EQ(error::INVALID_ARGUMENT, s.code());
-  ASSERT_TRUE(
-      absl::StrContains(s.error_message(), "Fill argument not supported"));
-}
-
-}  // end namespace
-}  // end namespace tensorflow

tensorflow/core/kernels/banded_triangular_solve_op.cc

@@ -193,8 +193,7 @@ struct LaunchBatchBandedTriangularSolve {
 
     Shard(worker_threads.num_threads, worker_threads.workers, batch_size,
           cost_per_unit,
-          [&in_x, &in_y, adjoint, lower, &bcast, out](int64 start,
-                                                      int64 limit) {
+          [&in_x, &in_y, adjoint, lower, &bcast, out](int start, int limit) {
             SequentialBandedTriangularSolveKernel<Scalar>::Run(
                 in_x, in_y, lower, adjoint, bcast, out, start, limit);
           });

tensorflow/core/kernels/boosted_trees/prediction_ops.cc

@@ -121,7 +121,7 @@ class BoostedTreesTrainingPredictOp : public OpKernel {
       auto do_work = [&resource, &bucketized_features, &cached_tree_ids,
                       &cached_node_ids, &output_partial_logits,
                       &output_node_ids, latest_tree,
-                      this](int64 start, int64 end) {
+                      this](int32 start, int32 end) {
         for (int32 i = start; i < end; ++i) {
           int32 tree_id = cached_tree_ids(i);
           int32 node_id = cached_node_ids(i);
@@ -237,7 +237,7 @@ class BoostedTreesPredictOp : public OpKernel {
 
     const int32 last_tree = resource->num_trees() - 1;
     auto do_work = [&resource, &bucketized_features, &output_logits, last_tree,
-                    this](int64 start, int64 end) {
+                    this](int32 start, int32 end) {
       for (int32 i = start; i < end; ++i) {
         std::vector<float> tree_logits(logits_dimension_, 0.0);
         int32 tree_id = 0;
@@ -340,7 +340,7 @@ class BoostedTreesExampleDebugOutputsOp : public OpKernel {
     // path. Note: feature_ids has one less value than logits_path because the
     // first value of each logit path will be the bias.
     auto do_work = [&resource, &bucketized_features, &output_debug_info,
-                    last_tree](int64 start, int64 end) {
+                    last_tree](int32 start, int32 end) {
       for (int32 i = start; i < end; ++i) {
         // Proto to store debug outputs, per example.
         boosted_trees::DebugOutput example_debug_info;

tensorflow/core/kernels/constant_op.cc

@@ -116,6 +116,7 @@ REGISTER_KERNEL(GPU, int16);
 REGISTER_KERNEL(GPU, qint16);
 REGISTER_KERNEL(GPU, quint16);
 REGISTER_KERNEL(GPU, uint32);
+REGISTER_KERNEL(GPU, int32);
 REGISTER_KERNEL(GPU, qint32);
 REGISTER_KERNEL(GPU, int64);
 REGISTER_KERNEL(GPU, uint64);

tensorflow/core/kernels/count_ops.cc

@@ -178,30 +178,10 @@ class SparseCount : public OpKernel {
     const Tensor& weights = context->input(3);
     bool use_weights = weights.NumElements() > 0;
 
-    OP_REQUIRES(context, TensorShapeUtils::IsMatrix(indices.shape()),
-                errors::InvalidArgument(
-                    "Input indices must be a 2-dimensional tensor. Got: ",
-                    indices.shape().DebugString()));
-
-    if (use_weights) {
-      OP_REQUIRES(
-          context, weights.shape() == values.shape(),
-          errors::InvalidArgument(
-              "Weights and values must have the same shape. Weight shape: ",
-              weights.shape().DebugString(),
-              "; values shape: ", values.shape().DebugString()));
-    }
-
     bool is_1d = shape.NumElements() == 1;
     int num_batches = is_1d ? 1 : shape.flat<int64>()(0);
     int num_values = values.NumElements();
 
-    OP_REQUIRES(context, num_values == indices.shape().dim_size(0),
-                errors::InvalidArgument(
-                    "Number of values must match first dimension of indices.",
-                    "Got ", num_values,
-                    " values, indices shape: ", indices.shape().DebugString()));
-
     const auto indices_values = indices.matrix<int64>();
     const auto values_values = values.flat<T>();
     const auto weight_values = weights.flat<W>();
@@ -255,33 +235,12 @@ class RaggedCount : public OpKernel {
     bool use_weights = weights.NumElements() > 0;
     bool is_1d = false;
 
-    if (use_weights) {
-      OP_REQUIRES(
-          context, weights.shape() == values.shape(),
-          errors::InvalidArgument(
-              "Weights and values must have the same shape. Weight shape: ",
-              weights.shape().DebugString(),
-              "; values shape: ", values.shape().DebugString()));
-    }
-
     const auto splits_values = splits.flat<int64>();
     const auto values_values = values.flat<T>();
     const auto weight_values = weights.flat<W>();
     int num_batches = splits.NumElements() - 1;
     int num_values = values.NumElements();
 
-    OP_REQUIRES(
-        context, num_batches > 0,
-        errors::InvalidArgument(
-            "Must provide at least 2 elements for the splits argument"));
-    OP_REQUIRES(context, splits_values(0) == 0,
-                errors::InvalidArgument("Splits must start with 0, not with ",
-                                        splits_values(0)));
-    OP_REQUIRES(context, splits_values(num_batches) == num_values,
-                errors::InvalidArgument(
-                    "Splits must end with the number of values, got ",
-                    splits_values(num_batches), " instead of ", num_values));
-
     auto per_batch_counts = BatchedMap<W>(num_batches);
     T max_value = 0;
     int batch_idx = 0;

tensorflow/core/kernels/crop_and_resize_op.cc

@@ -223,7 +223,7 @@ struct CropAndResize<CPUDevice, T> {
     const int depth = crops.dimension(3);
 
     // Sharding across boxes.
-    auto CropAndResizePerBox = [&](int64 start_box, int64 limit_box) {
+    auto CropAndResizePerBox = [&](int start_box, int limit_box) {
       for (int b = start_box; b < limit_box; ++b) {
         const float y1 = boxes(b, 0);
         const float x1 = boxes(b, 1);
@@ -449,7 +449,7 @@ struct CropAndResizeBackpropImage<CPUDevice, T> {
 
     grads_image.setZero();
 
-    auto CropAndResizeBackImgPerBox = [&](int64 start_box, int64 limit_box) {
+    auto CropAndResizeBackImgPerBox = [&](int start_box, int limit_box) {
       for (int b = start_box; b < limit_box; ++b) {
         const float y1 = boxes(b, 0);
         const float x1 = boxes(b, 1);

tensorflow/core/kernels/data_format_ops.cc

@@ -18,52 +18,16 @@ limitations under the License.
 #define EIGEN_USE_THREADS
 
 #include "tensorflow/core/kernels/data_format_ops.h"
-
-#include <map>
-
 #include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
 #include "tensorflow/core/framework/op_kernel.h"
 #include "tensorflow/core/framework/register_types.h"
 #include "tensorflow/core/framework/tensor.h"
-#include "tensorflow/core/platform/errors.h"
 
 namespace tensorflow {
 
 typedef Eigen::ThreadPoolDevice CPUDevice;
 typedef Eigen::GpuDevice GPUDevice;
 
-// Ensure that `src` and `dst` define a valid permutation.
-// Ops defined in this file assume that user specifies a permutation via two
-// string attributes. This check validates that these attributes properly define
-// it to prevent security vulnerabilities.
-static bool IsValidPermutation(const std::string& src, const std::string& dst) {
-  if (src.size() != dst.size()) {
-    return false;
-  }
-
-  std::map<char, bool> characters;
-
-  // Every character in `src` must be present only once
-  for (const auto c : src) {
-    if (characters[c]) {
-      return false;
-    }
-    characters[c] = true;
-  }
-
-  // Every character in `dst` must show up in `src` exactly once
-  for (const auto c : dst) {
-    if (!characters[c]) {
-      return false;
-    }
-    characters[c] = false;
-  }
-
-  // At this point, characters[] has been switched to true and false exactly
-  // once for all character in `src` (and `dst`) so we have a valid permutation
-  return true;
-}
-
 template <typename Device, typename T>
 class DataFormatDimMapOp : public OpKernel {
  public:
@@ -73,20 +37,15 @@ class DataFormatDimMapOp : public OpKernel {
     OP_REQUIRES_OK(context, context->GetAttr("src_format", &src_format));
     string dst_format;
     OP_REQUIRES_OK(context, context->GetAttr("dst_format", &dst_format));
-    OP_REQUIRES(context, src_format.size() == 4 || src_format.size() == 5,
-                errors::InvalidArgument(
-                    "Source format must be of length 4 or 5, received "
-                    "src_format = ",
-                    src_format));
-    OP_REQUIRES(context, dst_format.size() == 4 || dst_format.size() == 5,
-                errors::InvalidArgument("Destination format must be of length "
-                                        "4 or 5, received dst_format = ",
-                                        dst_format));
+    OP_REQUIRES(context, src_format.size() == 4,
+                errors::InvalidArgument(strings::StrCat(
+                    "Source format must of length 4, received src_format = ",
+                    src_format)));
     OP_REQUIRES(
-        context, IsValidPermutation(src_format, dst_format),
-        errors::InvalidArgument(
-            "Destination and source format must determine a permutation, got ",
-            src_format, " and ", dst_format));
+        context, dst_format.size() == 4,
+        errors::InvalidArgument(strings::StrCat(
+            "Destination format must of length 4, received dst_format = ",
+            dst_format)));
     dst_idx_ = Tensor(DT_INT32, {static_cast<int64>(src_format.size())});
     for (int i = 0; i < src_format.size(); ++i) {
       for (int j = 0; j < dst_format.size(); ++j) {
@@ -118,22 +77,8 @@ class DataFormatVecPermuteOp : public OpKernel {
       : OpKernel(context) {
     string src_format;
     OP_REQUIRES_OK(context, context->GetAttr("src_format", &src_format));
-    OP_REQUIRES(context, src_format.size() == 4 || src_format.size() == 5,
-                errors::InvalidArgument(
-                    "Source format must be of length 4 or 5, received "
-                    "src_format = ",
-                    src_format));
     string dst_format;
     OP_REQUIRES_OK(context, context->GetAttr("dst_format", &dst_format));
-    OP_REQUIRES(context, dst_format.size() == 4 || dst_format.size() == 5,
-                errors::InvalidArgument("Destination format must be of length "
-                                        "4 or 5, received dst_format = ",
-                                        dst_format));
-    OP_REQUIRES(
-        context, IsValidPermutation(src_format, dst_format),
-        errors::InvalidArgument(
-            "Destination and source format must determine a permutation, got ",
-            src_format, " and ", dst_format));
     src_format_ = src_format;
     dst_format_ = dst_format;
   }
@@ -179,10 +124,6 @@ class DataFormatVecPermuteOp : public OpKernel {
       };
       keep_only_spatial_dimensions(&src_format_str);
       keep_only_spatial_dimensions(&dst_format_str);
-      OP_REQUIRES(context,
-                  src_format_str.size() == 2 && dst_format_str.size() == 2,
-                  errors::InvalidArgument(
-                      "Format specifier must contain H and W for 2D case"));
     }
     ComputeDstIndex(src_format_str, dst_format_str, input.dims(), &dst_idx);
 

tensorflow/core/kernels/immutable_constant_op.cc

@@ -62,12 +62,6 @@ class MemmappedTensorAllocator : public Allocator {
 
   void set_delete_on_deallocate() { delete_on_deallocate_ = true; }
 
-  // Make sure tensors or complex types (strings, variants, resources) don't get
-  // their constructor called via a placement new since that would require
-  // writing to immutable data.
-  // See also: tensorflow/core/framework/typed_allocator.h
-  bool AllocatesOpaqueHandle() const override { return true; }
-
  private:
   std::unique_ptr<ReadOnlyMemoryRegion> memory_region_;
   // If there is an error during allocation we keep it in this status.

tensorflow/core/kernels/nth_element_op.cc

@@ -95,8 +95,7 @@ struct NthElementFunctor<CPUDevice, T> {
     const int last_dim = input_tensor.dim_size(input_tensor.dims() - 1);
 
     // Allocate each row to different shard.
-    auto SubNthElement = [&, input, output, last_dim, n](int64 start,
-                                                         int64 limit) {
+    auto SubNthElement = [&, input, output, last_dim, n](int start, int limit) {
       // std::nth_element would rearrange the array, so we need a new buffer.
       std::vector<T> buf(last_dim);
 

tensorflow/core/kernels/parameterized_truncated_normal_op.cc

@@ -70,8 +70,8 @@ struct TruncatedNormalFunctor<CPUDevice, T> {
 
     auto do_work = [samples_per_batch, num_elements, &ctx, &means, &stddevs,
                     &minvals, &maxvals, &gen, &output,
-                    kStdDevsInsideBoundsToUseRandnSampler](int64 start_batch,
-                                                           int64 limit_batch) {
+                    kStdDevsInsideBoundsToUseRandnSampler](int start_batch,
+                                                           int limit_batch) {
       // Capturing "gen" by-value would only make a copy for the _shared_
       // lambda.  Since we want to let each worker have its own copy, we pass
       // "gen" by reference and explicitly do a copy assignment here.
@@ -333,8 +333,8 @@ struct TruncatedNormalFunctorV2<CPUDevice, T> {
 
     auto do_work = [num_batches, samples_per_batch, &ctx, &bcast, &means,
                     &stddevs, &minvals, &maxvals, &gen, &output,
-                    kStdDevsInsideBoundsToUseRandnSampler](int64 start_output,
-                                                           int64 limit_output) {
+                    kStdDevsInsideBoundsToUseRandnSampler](int start_output,
+                                                           int limit_output) {
       // Capturing "gen" by-value would only make a copy for the _shared_
       // lambda.  Since we want to let each worker have its own copy, we pass
       // "gen" by reference and explicitly do a copy assignment here.

tensorflow/core/kernels/random_binomial_op.cc

@@ -182,7 +182,7 @@ struct RandomBinomialFunctor<CPUDevice, T, U> {
     // the sample shape and [H1, ... Hm] for the batch shape of the samples.
     // We have B1 * ... * Bk samples per batch member we need.
     auto DoWork = [num_batches, samples_per_batch, &bcast, &counts, &probs,
-                   &gen, &output](int64 start_output, int64 limit_output) {
+                   &gen, &output](int start_output, int limit_output) {
       // Vectorized intermediate calculations for uniform rejection sampling.
       // We always generate at most 4 samples.
       Eigen::array<T, 4> z;

tensorflow/core/kernels/random_op.cc

@@ -205,7 +205,7 @@ class RandomGammaOp : public OpKernel {
     // avoid a couple flops which can be done on a per-alpha basis.
 
     auto DoWork = [samples_per_alpha, num_alphas, &rng, samples_flat,
-                   alpha_flat](int64 start_output, int64 limit_output) {
+                   alpha_flat](int start_output, int limit_output) {
       using Eigen::numext::exp;
       using Eigen::numext::log;
       using Eigen::numext::log1p;

tensorflow/core/kernels/random_poisson_op.cc

@@ -97,7 +97,7 @@ struct PoissonFunctor<CPUDevice, T, U> {
     typedef random::UniformDistribution<random::PhiloxRandom, CT> Uniform;
 
     auto DoWork = [num_samples, num_rate, &rng, samples_flat, rate_flat](
-                      int64 start_output, int64 limit_output) {
+                      int start_output, int limit_output) {
       // Capturing "rng" by value would only make a copy for the _shared_
       // lambda.  Since we want to let each worker have its own copy, we pass
       // "rng" by reference and explicitly do a copy assignment.

tensorflow/core/kernels/session_ops.cc

@@ -16,7 +16,6 @@ limitations under the License.
 // See docs in ../ops/data_flow_ops.cc.
 
 #include <limits.h>
-
 #include <vector>
 
 #include "tensorflow/core/common_runtime/device.h"
@@ -28,7 +27,6 @@ limitations under the License.
 #include "tensorflow/core/framework/types.h"
 #include "tensorflow/core/lib/core/errors.h"
 #include "tensorflow/core/lib/gtl/map_util.h"
-#include "tensorflow/core/platform/errors.h"
 #include "tensorflow/core/platform/logging.h"
 #include "tensorflow/core/platform/macros.h"
 #include "tensorflow/core/platform/mutex.h"
@@ -44,11 +42,7 @@ class GetSessionHandleOp : public OpKernel {
 
   void Compute(OpKernelContext* ctx) override {
     const Tensor& val = ctx->input(0);
-    auto session_state = ctx->session_state();
-    OP_REQUIRES(ctx, session_state != nullptr,
-                errors::FailedPrecondition(
-                    "GetSessionHandle called on null session state"));
-    int64 id = session_state->GetNewId();
+    int64 id = ctx->session_state()->GetNewId();
     TensorStore::TensorAndKey tk{val, id, requested_device()};
     OP_REQUIRES_OK(ctx, ctx->tensor_store()->AddTensor(name(), tk));
 

tensorflow/core/kernels/sparse_fill_empty_rows_op.cc

@@ -232,9 +232,6 @@ class SparseFillEmptyRowsGradOp : public OpKernel {
         context, TensorShapeUtils::IsVector(reverse_index_map_t->shape()),
         errors::InvalidArgument("reverse_index_map must be a vector, saw: ",
                                 reverse_index_map_t->shape().DebugString()));
-    OP_REQUIRES(context, TensorShapeUtils::IsVector(grad_values_t->shape()),
-                errors::InvalidArgument("grad_values must be a vector, saw: ",
-                                        grad_values_t->shape().DebugString()));
 
     const auto reverse_index_map = reverse_index_map_t->vec<int64>();
     const auto grad_values = grad_values_t->vec<T>();
@@ -263,13 +260,8 @@ class SparseFillEmptyRowsGradOp : public OpKernel {
       // Locate the index of the output of the forward prop associated
       // with this location in the input of the forward prop.  Copy
       // the gradient into it.  Mark it as visited.
-      int64 reverse_index = reverse_index_map(i);
-      OP_REQUIRES(
-          context, 0 <= reverse_index && reverse_index < N_full,
-          errors::InvalidArgument("Elements in reverse index must be in [0, ",
-                                  N_full, ") but got ", reverse_index));
-      d_values(i) = grad_values(reverse_index);
-      visited(reverse_index) = true;
+      d_values(i) = grad_values(reverse_index_map(i));
+      visited(reverse_index_map(i)) = true;
     }
     for (int j = 0; j < N_full; ++j) {
       // The default value gradient gets the accumulated remainder of

tensorflow/core/kernels/stateless_random_ops.cc

@@ -252,7 +252,7 @@ class StatelessRandomGammaOp : public StatelessRandomOpBase {
     // avoid a couple flops which can be done on a per-alpha basis.
 
     auto DoWork = [samples_per_alpha, num_alphas, &random, samples_flat,
-                   alpha_flat](int64 start_output, int64 limit_output) {
+                   alpha_flat](int start_output, int limit_output) {
       // Capturing "random" by-value would only make a copy for the _shared_
       // lambda.  Since we want to let each worker have its own copy, we pass
       // "random" by reference and explicitly do a copy assignment.

tensorflow/core/kernels/string_ngrams_op.cc

@@ -19,7 +19,6 @@ limitations under the License.
 #include "absl/strings/ascii.h"
 #include "absl/strings/str_cat.h"
 #include "tensorflow/core/framework/op_kernel.h"
-#include "tensorflow/core/platform/errors.h"
 
 namespace tensorflow {
 namespace text {
@@ -61,18 +60,6 @@ class StringNGramsOp : public tensorflow::OpKernel {
     OP_REQUIRES_OK(context, context->input("data_splits", &splits));
     const auto& splits_vec = splits->flat<SPLITS_TYPE>();
 
-    // Validate that the splits are valid indices into data
-    const int input_data_size = data->flat<tstring>().size();
-    const int splits_vec_size = splits_vec.size();
-    for (int i = 0; i < splits_vec_size; ++i) {
-      bool valid_splits = splits_vec(i) >= 0;
-      valid_splits = valid_splits && (splits_vec(i) <= input_data_size);
-      OP_REQUIRES(
-          context, valid_splits,
-          errors::InvalidArgument("Invalid split value ", splits_vec(i),
-                                  ", must be in [0,", input_data_size, "]"));
-    }
-
     int num_batch_items = splits_vec.size() - 1;
     tensorflow::Tensor* ngrams_splits;
     OP_REQUIRES_OK(

tensorflow/core/kernels/topk_op.cc

@@ -136,7 +136,7 @@ struct TopKFunctor<CPUDevice, T> {
       return Status::OK();
     }
 
-    auto SortIndices = [&](int64 start_batch, int64 limit_batch) {
+    auto SortIndices = [&](int start_batch, int limit_batch) {
       for (int32 b = start_batch; b < limit_batch; ++b) {
         const T* input_data = &input(b, 0);
         const auto stable_comp = [input_data](const int32 a, const int32 b) {

tensorflow/core/public/version.h

@@ -22,7 +22,7 @@ limitations under the License.
 // tensorflow/tools/pip_package/setup.py
 #define TF_MAJOR_VERSION 2
 #define TF_MINOR_VERSION 3
-#define TF_PATCH_VERSION 2
+#define TF_PATCH_VERSION 0
 
 // TF_VERSION_SUFFIX is non-empty for pre-releases (e.g. "-alpha", "-alpha.1",
 // "-beta", "-rc", "-rc.1")

tensorflow/java/maven/spark-tensorflow-connector/pom.xml

@@ -35,7 +35,7 @@
         <java.version>1.8</java.version>
         <spark.version>2.4.5</spark.version>
         <yarn.api.version>2.7.3</yarn.api.version>
-        <junit.version>4.13.1</junit.version>
+        <junit.version>4.11</junit.version>
     </properties>
 
     <build>

tensorflow/java/maven/tensorflow-hadoop/pom.xml

@@ -16,7 +16,7 @@
         <maven.compiler.target>1.6</maven.compiler.target>
         <hadoop.version>2.6.0</hadoop.version>
         <protobuf.version>3.5.1</protobuf.version>
-        <junit.version>4.13.1</junit.version>
+        <junit.version>4.11</junit.version>
     </properties>
 
     <licenses>

tensorflow/lite/core/subgraph.cc

@@ -18,7 +18,6 @@ limitations under the License.
 #include <algorithm>
 
 #include "tensorflow/lite/arena_planner.h"
-#include "tensorflow/lite/builtin_ops.h"
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow/lite/context_util.h"
 #include "tensorflow/lite/core/api/tensor_utils.h"
@@ -568,33 +567,6 @@ TfLiteStatus Subgraph::CheckTensorIndices(const char* label, const int* indices,
   return kTfLiteOk;
 }
 
-// We have two arrays and we need to check that elements from one array don't
-// show up in the other. We could sort both arrays and then iterate with two
-// pointers from start to finish always increasing the smaller one but since
-// these arrays are usually short (<25 elements for inputs, usually <3 for
-// outputs), this might be slower than the naive approach (if arrays have size n
-// and m, with n >> m ~ O(1), first approach is O(nlogn) whereas the other is
-// O(n)). Plus, sorting the input and output arrays might not be something we
-// want as it destroys ordering of elements.
-//
-// If it turns out that this is an issue, we can switch to the other algorithm.
-TfLiteStatus Subgraph::CheckInputAndOutputForOverlap(const int* input_indices,
-                                                     int num_inputs,
-                                                     const int* output_indices,
-                                                     int num_outputs) {
-  for (int i = 0; i < num_inputs; i++) {
-    for (int j = 0; j < num_outputs; j++) {
-      if (input_indices[i] == output_indices[j]) {
-        ReportError("Tensor %d is both input %d and output %d\n",
-                    input_indices[i], i, j);
-        consistent_ = false;
-        return kTfLiteError;
-      }
-    }
-  }
-  return kTfLiteOk;
-}
-
 namespace {
 // Multiply two sizes and return true if overflow occurred;
 // This is based off tensorflow/overflow.h but is simpler as we already
@@ -716,16 +688,6 @@ TfLiteStatus Subgraph::AddNodeWithParameters(
       &context_,
       CheckTensorIndices("node outputs", outputs.data(), outputs.size()));
 
-  // For builtin ops, inputs and outputs must not overlap. Custom ops must do
-  // this check by themselves if they don't support overlapping tensors. This
-  // distinction is to allow custom ops to just forward a tensor, reusing it as
-  // both input and output.
-  if (builtin_data != nullptr) {
-    TF_LITE_ENSURE_OK(&context_, CheckInputAndOutputForOverlap(
-                                     inputs.data(), inputs.size(),
-                                     outputs.data(), outputs.size()));
-  }
-
   int new_node_index = nodes_and_registration_.size();
   if (node_index) *node_index = new_node_index;
   nodes_and_registration_.resize(nodes_and_registration_.size() + 1);
@@ -972,19 +934,6 @@ TfLiteStatus Subgraph::Invoke() {
           tensor->data_is_stale) {
         TF_LITE_ENSURE_STATUS(EnsureTensorDataIsReadable(tensor_index));
       }
-      if (tensor->data.raw == nullptr && tensor->bytes > 0) {
-        if (registration.builtin_code == kTfLiteBuiltinReshape && i == 1) {
-          // In general, having a tensor here with no buffer will be an error.
-          // However, for the reshape operator, the second input tensor is only
-          // used for the shape, not for the data. Thus, null buffer is ok.
-          continue;
-        } else {
-          // In all other cases, we need to return an error as otherwise we will
-          // trigger a null pointer dereference (likely).
-          ReportError("Input tensor %d lacks data", tensor_index);
-          return kTfLiteError;
-        }
-      }
     }
 
     if (check_cancelled_func_ != nullptr &&

tensorflow/lite/core/subgraph.h

@@ -433,15 +433,6 @@ class Subgraph {
   TfLiteStatus CheckTensorIndices(const char* label, const int* indices,
                                   int length);
 
-  // Check that the input indices and the output indices don't overlap.
-  // This is needed because same tensor must not be used both as input and
-  // output for an operator.
-  // NOTE: this changes consistent_ to be false if indices are out of bounds.
-  TfLiteStatus CheckInputAndOutputForOverlap(const int* input_indices,
-                                             int num_inputs,
-                                             const int* output_indices,
-                                             int num_outputs);
-
   // Compute the number of bytes required to represent a tensor with dimensions
   // specified by the array dims (of length dims_size). Returns the status code
   // and bytes.

tensorflow/lite/interpreter_builder.cc

@@ -609,12 +609,7 @@ TfLiteStatus InterpreterBuilder::operator()(
   auto* buffers = model_->buffers();
 
   if (subgraphs->size() == 0) {
-    TF_LITE_REPORT_ERROR(error_reporter_, "No subgraph in the model.\n");
-    return cleanup_and_error();
-  }
-
-  if (!buffers) {
-    TF_LITE_REPORT_ERROR(error_reporter_, "No buffers in the model.\n");
+    error_reporter_->Report("No subgraph in the model.\n");
     return cleanup_and_error();
   }
 
@@ -635,10 +630,10 @@ TfLiteStatus InterpreterBuilder::operator()(
         (*interpreter)->subgraph(subgraph_index);
     auto operators = subgraph->operators();
     auto tensors = subgraph->tensors();
-    if (!operators || !tensors) {
-      TF_LITE_REPORT_ERROR(error_reporter_,
-                           "Did not get operators or tensors in subgraph %d.\n",
-                           subgraph_index);
+    if (!operators || !tensors || !buffers) {
+      error_reporter_->Report(
+          "Did not get operators, tensors, or buffers in subgraph %d.\n",
+          subgraph_index);
       return cleanup_and_error();
     }
     if (modified_subgraph->AddTensors(tensors->size()) != kTfLiteOk) {

tensorflow/lite/kernels/internal/reference/reduce.h

@@ -70,9 +70,6 @@ inline bool ResolveAxis(const int num_dims, const int* axis,
     // eg: For num_dims=3, [0, 1, 2] is the same as [-3, -2, -1]  */
     int current = axis[idx] < 0 ? (axis[idx] + num_dims) : axis[idx];
     TFLITE_DCHECK(current >= 0 && current < num_dims);
-    if (current < 0 || current >= num_dims) {
-      return false;
-    }
     bool is_dup = false;
     for (int j = 0; j < *out_num_axis; ++j) {
       if (out_axis[j] == current) {

tensorflow/lite/kernels/internal/types.h

@@ -432,7 +432,7 @@ int MatchingArraySize(const ArrayType1& array1, int index1,
 inline int MatchingDim(const RuntimeShape& shape1, int index1,
                        const RuntimeShape& shape2, int index2) {
   TFLITE_DCHECK_EQ(shape1.Dims(index1), shape2.Dims(index2));
-  return std::min(shape1.Dims(index1), shape2.Dims(index2));
+  return shape1.Dims(index1);
 }
 
 template <typename... Args>

tensorflow/lite/kernels/kernel_util.h

@@ -30,48 +30,27 @@ inline int SizeOfDimension(const TfLiteTensor* t, int dim) {
 }
 inline const TfLiteTensor* GetInput(const TfLiteContext* context,
                                     const TfLiteNode* node, int index) {
-  const int tensor_index = node->inputs->data[index];
-  if (tensor_index < 0) {
-    return nullptr;
-  }
-  return &context->tensors[tensor_index];
+  return &context->tensors[node->inputs->data[index]];
 }
 // Note: You must check if result is not null:
 // TfLiteTensor* my_tensor = GetVariableInput(context, node, kMyTensorIdx);
 // TF_LITE_ENSURE(context, my_tensor != nullptr);
 inline TfLiteTensor* GetVariableInput(TfLiteContext* context,
                                       const TfLiteNode* node, int index) {
-  const int tensor_index = node->inputs->data[index];
-  if (tensor_index < 0) {
-    return nullptr;
-  }
-  TfLiteTensor* tensor = &context->tensors[tensor_index];
+  TfLiteTensor* tensor = &context->tensors[node->inputs->data[index]];
   return (tensor->is_variable) ? tensor : nullptr;
 }
 inline TfLiteTensor* GetOutput(TfLiteContext* context, const TfLiteNode* node,
                                int index) {
-  const int tensor_index = node->outputs->data[index];
-  if (tensor_index < 0) {
-    return nullptr;
-  }
-  return &context->tensors[tensor_index];
+  return &context->tensors[node->outputs->data[index]];
 }
 inline TfLiteTensor* GetTemporary(TfLiteContext* context,
                                   const TfLiteNode* node, int index) {
-  const int tensor_index = node->temporaries->data[index];
-  if (tensor_index < 0) {
-    return nullptr;
-  }
-  return &context->tensors[tensor_index];
+  return &context->tensors[node->temporaries->data[index]];
 }
-
 inline const TfLiteTensor* GetIntermediates(TfLiteContext* context,
                                             const TfLiteNode* node, int index) {
-  const int tensor_index = node->intermediates->data[index];
-  if (tensor_index < 0) {
-    return nullptr;
-  }
-  return &context->tensors[tensor_index];
+  return &context->tensors[node->intermediates->data[index]];
 }
 inline int NumInputs(const TfLiteNode* node) { return node->inputs->size; }
 inline int NumOutputs(const TfLiteNode* node) { return node->outputs->size; }
@@ -94,7 +73,12 @@ inline int64_t NumElements(const TfLiteTensor* t) {
 inline const TfLiteTensor* GetOptionalInputTensor(TfLiteContext* context,
                                                   const TfLiteNode* node,
                                                   int index) {
-  return GetInput(context, node, index);
+  const bool use_tensor = index < node->inputs->size &&
+                          node->inputs->data[index] != kTfLiteOptionalTensor;
+  if (use_tensor) {
+    return &context->tensors[node->inputs->data[index]];
+  }
+  return nullptr;
 }
 
 // Determines whether tensor is constant.

tensorflow/lite/kernels/segment_sum.cc

@@ -34,24 +34,11 @@ TfLiteStatus ResizeOutputTensor(TfLiteContext* context,
                                 const TfLiteTensor* data,
                                 const TfLiteTensor* segment_ids,
                                 TfLiteTensor* output) {
-  // Segment ids should be of same cardinality as first input dimension and they
-  // should be increasing by at most 1, from 0 (e.g., [0, 0, 1, 2, 3] is valid)
+  int max_index = -1;
   const int segment_id_size = segment_ids->dims->data[0];
-  TF_LITE_ENSURE_EQ(context, segment_id_size, data->dims->data[0]);
-  int previous_segment_id = -1;
-  for (int i = 0; i < segment_id_size; i++) {
-    const int current_segment_id = GetTensorData<int32_t>(segment_ids)[i];
-    if (i == 0) {
-      TF_LITE_ENSURE_EQ(context, current_segment_id, 0);
-    } else {
-      int delta = current_segment_id - previous_segment_id;
-      TF_LITE_ENSURE(context, delta == 0 || delta == 1);
-    }
-    previous_segment_id = current_segment_id;
+  if (segment_id_size > 0) {
+    max_index = segment_ids->data.i32[segment_id_size - 1];
   }
-
-  const int max_index = previous_segment_id;
-
   const int data_rank = NumDimensions(data);
   TfLiteIntArray* output_shape = TfLiteIntArrayCreate(NumDimensions(data));
   output_shape->data[0] = max_index + 1;

tensorflow/lite/kernels/segment_sum_test.cc

@@ -110,37 +110,5 @@ TEST(SegmentSumOpModelTest, Float32Test_ThreeDimensions) {
   EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({2, 2, 1}));
 }
 
-TEST(SegmentSumOpModelTest, TestFailIfSegmentsAreNotSorted) {
-  SegmentSumOpModel<int32_t> model({TensorType_INT32, {3, 2}},
-                                   {TensorType_INT32, {3}});
-  model.PopulateTensor<int32_t>(model.data(), {1, 2, 3, 4, 5, 6});
-  model.PopulateTensor<int32_t>(model.segment_ids(), {0, 3, 1});
-  ASSERT_EQ(model.InvokeUnchecked(), kTfLiteError);
-}
-
-TEST(SegmentSumOpModelTest, TestFailIfSegmentsAreNotConsecutive) {
-  SegmentSumOpModel<int32_t> model({TensorType_INT32, {3, 2}},
-                                   {TensorType_INT32, {3}});
-  model.PopulateTensor<int32_t>(model.data(), {1, 2, 3, 4, 5, 6});
-  model.PopulateTensor<int32_t>(model.segment_ids(), {0, 3, 5});
-  ASSERT_EQ(model.InvokeUnchecked(), kTfLiteError);
-}
-
-TEST(SegmentSumOpModelTest, TestFailIfSegmentsAreNegative) {
-  SegmentSumOpModel<int32_t> model({TensorType_INT32, {3, 2}},
-                                   {TensorType_INT32, {3}});
-  model.PopulateTensor<int32_t>(model.data(), {1, 2, 3, 4, 5, 6});
-  model.PopulateTensor<int32_t>(model.segment_ids(), {-1, 0, 1});
-  ASSERT_EQ(model.InvokeUnchecked(), kTfLiteError);
-}
-
-TEST(SegmentSumOpModelTest, TestFailIfSegmentsAreNotTheRightCardinality) {
-  SegmentSumOpModel<int32_t> model({TensorType_INT32, {3, 2}},
-                                   {TensorType_INT32, {2}});
-  model.PopulateTensor<int32_t>(model.data(), {1, 2, 3, 4, 5, 6});
-  model.PopulateTensor<int32_t>(model.segment_ids(), {0, 1});
-  ASSERT_EQ(model.InvokeUnchecked(), kTfLiteError);
-}
-
 }  // namespace
 }  // namespace tflite

tensorflow/lite/tools/evaluation/BUILD

@@ -57,7 +57,6 @@ cc_library(
         "//conditions:default": [],
     }) + select({
         "//tensorflow:fuchsia": [],
-        "//tensorflow:windows": [],
         "//conditions:default": [
             "//tensorflow/lite/delegates/xnnpack:xnnpack_delegate",
         ],

tensorflow/python/compiler/xla/xla.py

@@ -18,6 +18,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import collections
 import contextlib
 
 from six.moves import xrange  # pylint: disable=redefined-builtin
@@ -36,7 +37,6 @@ from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.util import compat
 from tensorflow.python.util import nest
 from tensorflow.python.util import tf_inspect
-from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 _XLA_COMPILE_ATTR = '_xla_compile_id'
@@ -329,7 +329,7 @@ def _compile_internal(computation, inputs=None):
   if inputs is None:
     inputs = []
 
-  if not isinstance(inputs, collections_abc.Sequence):
+  if not isinstance(inputs, collections.Sequence):
     raise TypeError('inputs must be a list')
 
   # Flatten inputs.
@@ -428,15 +428,15 @@ def is_flat(outputs):
   """
   # If outputs is a list or tuple, check if it has any nested structure. If
   # there is, then outputs is non-flat.
-  if isinstance(outputs, collections_abc.Sequence):
+  if isinstance(outputs, collections.Sequence):
     for o in outputs:
-      if (isinstance(o, collections_abc.Sequence) or
-          isinstance(o, collections_abc.Mapping) or
+      if (isinstance(o, collections.Sequence) or
+          isinstance(o, collections.Mapping) or
           hasattr(o.__class__, '__attrs_attrs__')):
         return False
 
   # If outputs is a dict, it is non-flat.
-  if isinstance(outputs, collections_abc.Mapping):
+  if isinstance(outputs, collections.Mapping):
     return False
 
   # If outputs is from the attrs library, it is non-flat.
@@ -467,7 +467,7 @@ def _postprocess_flat_outputs(outputs):
   if outputs is None:
     outputs = tuple()
   # If the computation only returned one value, make it a tuple.
-  if not isinstance(outputs, collections_abc.Sequence):
+  if not isinstance(outputs, collections.Sequence):
     outputs = (outputs,)
 
   # Append `no_op` here so that return value of this function always contains

tensorflow/python/data/ops/dataset_ops.py

@@ -18,6 +18,7 @@ from __future__ import division
 from __future__ import print_function
 
 import abc
+import collections
 import functools
 import sys
 import threading
@@ -71,7 +72,6 @@ from tensorflow.python.util import deprecation
 from tensorflow.python.util import function_utils
 from tensorflow.python.util import lazy_loader
 from tensorflow.python.util import nest as tf_nest
-from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 # Loaded lazily due to a circular dependency (roughly
@@ -103,7 +103,7 @@ tf_export("data.UNKNOWN_CARDINALITY").export_constant(__name__, "UNKNOWN")
 
 @tf_export("data.Dataset", v1=[])
 @six.add_metaclass(abc.ABCMeta)
-class DatasetV2(collections_abc.Iterable, tracking_base.Trackable,
+class DatasetV2(collections.Iterable, tracking_base.Trackable,
                 composite_tensor.CompositeTensor):
   """Represents a potentially large set of elements.
 

tensorflow/python/data/ops/iterator_ops.py

@@ -18,6 +18,7 @@ from __future__ import division
 from __future__ import print_function
 
 import abc
+import collections
 import threading
 import warnings
 
@@ -40,7 +41,6 @@ from tensorflow.python.ops import gen_experimental_dataset_ops
 from tensorflow.python.training.saver import BaseSaverBuilder
 from tensorflow.python.training.tracking import base as trackable
 from tensorflow.python.util import deprecation
-from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 
@@ -543,7 +543,7 @@ class IteratorResourceDeleter(object):
 
 @tf_export("data.Iterator", v1=[])
 @six.add_metaclass(abc.ABCMeta)
-class IteratorBase(collections_abc.Iterator, trackable.Trackable,
+class IteratorBase(collections.Iterator, trackable.Trackable,
                    composite_tensor.CompositeTensor):
   """Represents an iterator of a `tf.data.Dataset`.
 

tensorflow/python/data/util/structure.py

@@ -440,7 +440,7 @@ def type_spec_from_value(element, use_fallback=True):
 
   if isinstance(element, tuple):
     if hasattr(element, "_fields") and isinstance(
-        element._fields, collections_abc.Sequence) and all(
+        element._fields, collections.Sequence) and all(
             isinstance(f, six.string_types) for f in element._fields):
       if isinstance(element, wrapt.ObjectProxy):
         element_type = type(element.__wrapped__)

tensorflow/python/debug/wrappers/framework.py

@@ -99,6 +99,7 @@ from __future__ import division
 from __future__ import print_function
 
 import abc
+import collections
 import re
 import threading
 
@@ -112,7 +113,6 @@ from tensorflow.python.framework import ops
 from tensorflow.python.platform import tf_logging
 from tensorflow.python.training import monitored_session
 from tensorflow.python.util import nest
-from tensorflow.python.util.compat import collections_abc
 
 
 # Helper function.
@@ -445,7 +445,7 @@ class BaseDebugWrapperSession(session.SessionInterface):
       """Check whether a possibly nested structure is empty."""
       if not nest.is_nested(x):
         return False
-      if isinstance(x, collections_abc.Mapping):
+      if isinstance(x, collections.Mapping):
         return is_empty(list(x.values()))
       for item in x:
         if not is_empty(item):

tensorflow/python/distribute/input_lib.py

@@ -18,6 +18,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import collections
 import functools
 import sys
 
@@ -52,7 +53,6 @@ from tensorflow.python.ops import math_ops
 from tensorflow.python.ops.ragged import ragged_tensor
 from tensorflow.python.types import distribute as distribute_types
 from tensorflow.python.util import nest
-from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.deprecation import deprecated
 from tensorflow.python.util.tf_export import tf_export
 from tensorflow.tools.docs import doc_controls
@@ -143,7 +143,7 @@ def get_distributed_datasets_from_function(dataset_fn,
 
 
 @tf_export("distribute.DistributedIterator", v1=[])
-class DistributedIteratorInterface(collections_abc.Iterator,
+class DistributedIteratorInterface(collections.Iterator,
                                    distribute_types.Iterator):
   """An iterator over `tf.distribute.DistributedDataset`.
 
@@ -272,7 +272,7 @@ class DistributedIteratorInterface(collections_abc.Iterator,
 
 
 @tf_export("distribute.DistributedDataset", v1=[])
-class DistributedDatasetInterface(collections_abc.Iterable,
+class DistributedDatasetInterface(collections.Iterable,
                                   distribute_types.Iterable):
   # pylint: disable=line-too-long
   """Represents a dataset distributed among devices and machines.

tensorflow/python/dlpack/dlpack_test.py

@@ -20,11 +20,9 @@ from __future__ import print_function
 from absl.testing import parameterized
 import numpy as np
 
-
 from tensorflow.python.dlpack import dlpack
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
-from tensorflow.python.framework import errors
 from tensorflow.python.framework import ops
 from tensorflow.python.platform import test
 
@@ -97,12 +95,6 @@ class DLPackTest(parameterized.TestCase, test.TestCase):
     self.assertRaisesRegex(Exception, ".* is not supported by dlpack",
                            UnsupportedComplex64)
 
-  def testMustPassTensorArgumentToDLPack(self):
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        "The argument to `to_dlpack` must be a TF tensor, not Python object"):
-      dlpack.to_dlpack([1])
-
 
 if __name__ == "__main__":
   ops.enable_eager_execution()

tensorflow/python/feature_column/BUILD

@@ -231,10 +231,7 @@ py_test(
     srcs = ["sequence_feature_column_integration_test.py"],
     python_version = "PY3",
     srcs_version = "PY2AND3",
-    tags = [
-        "no_mac",
-        "no_pip",
-    ],
+    tags = ["no_pip"],
     deps = [
         ":feature_column_v2",
         "//tensorflow/python:client_testlib",

tensorflow/python/framework/indexed_slices.py

@@ -32,7 +32,6 @@ from tensorflow.python.framework import tensor_conversion_registry
 from tensorflow.python.framework import tensor_shape
 from tensorflow.python.framework import type_spec
 from tensorflow.python.types import internal
-from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.lazy_loader import LazyLoader
 from tensorflow.python.util.tf_export import tf_export
 
@@ -345,7 +344,7 @@ def internal_convert_n_to_tensor_or_indexed_slices(values,
     RuntimeError: If a registered conversion function returns an invalid
       value.
   """
-  if not isinstance(values, collections_abc.Iterable):
+  if not isinstance(values, collections.Iterable):
     raise TypeError("values must be iterable.")
   ret = []
   for i, value in enumerate(values):

tensorflow/python/keras/engine/training_utils.py

@@ -19,6 +19,7 @@ from __future__ import print_function
 
 import abc
 import atexit
+import collections
 from collections import OrderedDict
 import functools
 import multiprocessing.pool
@@ -616,7 +617,7 @@ def standardize_sample_or_class_weights(x_weight, output_names, weight_type):
                        'You should provide one `' + weight_type + '`'
                        'array per model output.')
     return x_weight
-  if isinstance(x_weight, collections_abc.Mapping):
+  if isinstance(x_weight, collections.Mapping):
     generic_utils.check_for_unexpected_keys(weight_type, x_weight, output_names)
     x_weights = []
     for name in output_names:
@@ -863,7 +864,7 @@ def collect_per_output_metric_info(metrics,
               [metrics_module.clone_metric(m) for m in metrics])
       else:
         nested_metrics = [metrics]
-  elif isinstance(metrics, collections_abc.Mapping):
+  elif isinstance(metrics, collections.Mapping):
     generic_utils.check_for_unexpected_keys('metrics', metrics, output_names)
     nested_metrics = []
     for name in output_names:
@@ -1442,7 +1443,7 @@ def prepare_sample_weight_modes(training_endpoints, sample_weight_mode):
     ValueError: In case of invalid `sample_weight_mode` input.
   """
 
-  if isinstance(sample_weight_mode, collections_abc.Mapping):
+  if isinstance(sample_weight_mode, collections.Mapping):
     generic_utils.check_for_unexpected_keys(
         'sample_weight_mode', sample_weight_mode,
         [e.output_name for e in training_endpoints])
@@ -1535,7 +1536,7 @@ def prepare_loss_weights(training_endpoints, loss_weights=None):
   if loss_weights is None:
     for e in training_endpoints:
       e.loss_weight = 1.
-  elif isinstance(loss_weights, collections_abc.Mapping):
+  elif isinstance(loss_weights, collections.Mapping):
     generic_utils.check_for_unexpected_keys(
         'loss_weights', loss_weights,
         [e.output_name for e in training_endpoints])

tensorflow/python/keras/layers/normalization.py

@@ -30,12 +30,12 @@ from tensorflow.python.keras.engine.base_layer import Layer
 from tensorflow.python.keras.engine.input_spec import InputSpec
 from tensorflow.python.keras.utils import tf_utils
 from tensorflow.python.ops import array_ops
-from tensorflow.python.ops import control_flow_ops
 from tensorflow.python.ops import init_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import nn
 from tensorflow.python.ops import state_ops
 from tensorflow.python.ops import variables as tf_variables
+from tensorflow.python.platform import device_context
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.util.tf_export import keras_export
 
@@ -514,7 +514,7 @@ class BatchNormalizationBase(Layer):
     use_fused_avg_updates = (
         ops.executing_eagerly_outside_functions() and
         isinstance(self.momentum, (float, int)) and
-        enclosing_xla_context() is None)
+        device_context.enclosing_tpu_context() is None)
     if use_fused_avg_updates:
       exponential_avg_factor = 1.0 - self.momentum
     else:
@@ -930,23 +930,6 @@ def replace_in_base_docstring(replacements):
   return string
 
 
-def enclosing_xla_context():
-  """Recursively find and return the XLAControlFlowContext."""
-  graph = ops.get_default_graph()
-  while graph is not None:
-    # pylint: disable=protected-access
-    context_ = graph._get_control_flow_context()
-    # pylint: enable=protected-access
-    while context_ is not None:
-      if isinstance(context_, control_flow_ops.XLAControlFlowContext):
-        return context_
-      context_ = context_.outer_context
-    # This may be a FuncGraph due to defuns or v2 control flow. We need to
-    # find the original graph with the XLAControlFlowContext.
-    graph = getattr(graph, 'outer_graph', None)
-  return None
-
-
 @keras_export(v1=['keras.layers.BatchNormalization'])  # pylint: disable=missing-docstring
 class BatchNormalization(BatchNormalizationBase):
 

tensorflow/python/keras/layers/preprocessing/preprocessing_test_utils.py

@@ -18,10 +18,11 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import collections
+
 import numpy as np
 
 from tensorflow.python.platform import test
-from tensorflow.python.util.compat import collections_abc
 
 
 class PreprocessingLayerTest(test.TestCase):
@@ -37,7 +38,7 @@ class PreprocessingLayerTest(test.TestCase):
       self.assertEqual(len(a), len(b))
       for a_value, b_value in zip(a, b):
         self.assertAllCloseOrEqual(a_value, b_value, msg=msg)
-    elif isinstance(a, collections_abc.Mapping):
+    elif isinstance(a, collections.Mapping):
       self.assertEqual(len(a), len(b))
       for key, a_value in a.items():
         b_value = b[key]

tensorflow/python/keras/layers/recurrent.py

@@ -44,10 +44,14 @@ from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.training.tracking import base as trackable
 from tensorflow.python.training.tracking import data_structures
 from tensorflow.python.util import nest
-from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import keras_export
 from tensorflow.tools.docs import doc_controls
 
+try:
+  from collections import abc as collections_abc  # pylint: disable=g-import-not-at-top
+except ImportError:  # For Python 2
+  import collections as collections_abc  # pylint: disable=g-import-not-at-top
+
 
 RECURRENT_DROPOUT_WARNING_MSG = (
     'RNN `implementation=2` is not supported when `recurrent_dropout` is set. '

tensorflow/python/kernel_tests/BUILD

@@ -727,7 +727,6 @@ cuda_py_test(
     name = "matrix_solve_ls_op_test",
     size = "medium",
     srcs = ["matrix_solve_ls_op_test.py"],
-    tags = ["no_mac"],
     deps = [
         "//tensorflow/python:array_ops",
         "//tensorflow/python:client_testlib",
@@ -790,7 +789,6 @@ tf_py_test(
     name = "parsing_ops_test",
     size = "medium",
     srcs = ["parsing_ops_test.py"],
-    tags = ["no_mac"],
     deps = [
         "//tensorflow/core:protos_all_py",
         "//tensorflow/python:array_ops",

tensorflow/python/kernel_tests/boosted_trees/BUILD

@@ -24,7 +24,6 @@ tf_py_test(
     name = "resource_ops_test",
     size = "small",
     srcs = ["resource_ops_test.py"],
-    tags = ["no_mac"],
     deps = [
         "//tensorflow/core/kernels/boosted_trees:boosted_trees_proto_py",
         "//tensorflow/python:boosted_trees_ops",
@@ -40,7 +39,6 @@ tf_py_test(
     name = "prediction_ops_test",
     size = "small",
     srcs = ["prediction_ops_test.py"],
-    tags = ["no_mac"],
     deps = [
         "//tensorflow/core/kernels/boosted_trees:boosted_trees_proto_py",
         "//tensorflow/python:array_ops",
@@ -71,7 +69,6 @@ tf_py_test(
     name = "training_ops_test",
     size = "small",
     srcs = ["training_ops_test.py"],
-    tags = ["no_mac"],
     deps = [
         "//tensorflow/core/kernels/boosted_trees:boosted_trees_proto_py",
         "//tensorflow/python:array_ops",

tensorflow/python/kernel_tests/control_flow_ops_py_test.py

@@ -4581,14 +4581,6 @@ class ControlFlowTest(test.TestCase, parameterized.TestCase):
       result = control_flow_ops.merge([v_f, v_t])
       self.evaluate(result)
 
-  def testSwitchEagerMode(self):
-    if not context.executing_eagerly():
-      return
-    input_data = [1, 2, 3, 4]
-    vf, vt = control_flow_ops.switch(input_data, False)
-    self.assertAllEqual(vf, input_data)
-    self.assertAllEqual(vt, [])
-
   @test_util.run_deprecated_v1
   def testQIntArgAndRet(self):
 

tensorflow/python/ops/bincount_ops_test.py

@@ -25,9 +25,7 @@ from tensorflow.python.eager import context
 from tensorflow.python.framework import errors
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import sparse_tensor
-from tensorflow.python.framework import test_util
 from tensorflow.python.ops import bincount_ops
-from tensorflow.python.ops import gen_count_ops
 from tensorflow.python.ops import sparse_ops
 from tensorflow.python.ops.ragged import ragged_factory_ops
 from tensorflow.python.ops.ragged import ragged_tensor
@@ -836,121 +834,5 @@ class TestSparseCountFailureModes(test.TestCase):
       self.evaluate(bincount_ops.sparse_bincount(x, weights=weights, axis=-1))
 
 
-@test_util.run_all_in_graph_and_eager_modes
-@test_util.disable_tfrt
-class RawOpsTest(test.TestCase, parameterized.TestCase):
-
-  def testSparseCountSparseOutputBadIndicesShape(self):
-    indices = [[[0], [0]], [[0], [1]], [[1], [0]], [[1], [2]]]
-    values = [1, 1, 1, 10]
-    weights = [1, 2, 4, 6]
-    dense_shape = [2, 3]
-    with self.assertRaisesRegex(errors.InvalidArgumentError,
-                                "Input indices must be a 2-dimensional tensor"):
-      self.evaluate(
-          gen_count_ops.SparseCountSparseOutput(
-              indices=indices,
-              values=values,
-              dense_shape=dense_shape,
-              weights=weights,
-              binary_output=False))
-
-  def testSparseCountSparseOutputBadWeightsShape(self):
-    indices = [[0, 0], [0, 1], [1, 0], [1, 2]]
-    values = [1, 1, 1, 10]
-    weights = [1, 2, 4]
-    dense_shape = [2, 3]
-    with self.assertRaisesRegex(errors.InvalidArgumentError,
-                                "Weights and values must have the same shape"):
-      self.evaluate(
-          gen_count_ops.SparseCountSparseOutput(
-              indices=indices,
-              values=values,
-              dense_shape=dense_shape,
-              weights=weights,
-              binary_output=False))
-
-  def testSparseCountSparseOutputBadNumberOfValues(self):
-    indices = [[0, 0], [0, 1], [1, 0]]
-    values = [1, 1, 1, 10]
-    weights = [1, 2, 4, 6]
-    dense_shape = [2, 3]
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        "Number of values must match first dimension of indices"):
-      self.evaluate(
-          gen_count_ops.SparseCountSparseOutput(
-              indices=indices,
-              values=values,
-              dense_shape=dense_shape,
-              weights=weights,
-              binary_output=False))
-
-  def testRaggedCountSparseOutput(self):
-    splits = [0, 4, 7]
-    values = [1, 1, 2, 1, 2, 10, 5]
-    weights = [1, 2, 3, 4, 5, 6, 7]
-    output_indices, output_values, output_shape = self.evaluate(
-        gen_count_ops.RaggedCountSparseOutput(
-            splits=splits, values=values, weights=weights, binary_output=False))
-    self.assertAllEqual([[0, 1], [0, 2], [1, 2], [1, 5], [1, 10]],
-                        output_indices)
-    self.assertAllEqual([7, 3, 5, 7, 6], output_values)
-    self.assertAllEqual([2, 11], output_shape)
-
-  def testRaggedCountSparseOutputBadWeightsShape(self):
-    splits = [0, 4, 7]
-    values = [1, 1, 2, 1, 2, 10, 5]
-    weights = [1, 2, 3, 4, 5, 6]
-    with self.assertRaisesRegex(errors.InvalidArgumentError,
-                                "Weights and values must have the same shape"):
-      self.evaluate(
-          gen_count_ops.RaggedCountSparseOutput(
-              splits=splits,
-              values=values,
-              weights=weights,
-              binary_output=False))
-
-  def testRaggedCountSparseOutputEmptySplits(self):
-    splits = []
-    values = [1, 1, 2, 1, 2, 10, 5]
-    weights = [1, 2, 3, 4, 5, 6, 7]
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        "Must provide at least 2 elements for the splits argument"):
-      self.evaluate(
-          gen_count_ops.RaggedCountSparseOutput(
-              splits=splits,
-              values=values,
-              weights=weights,
-              binary_output=False))
-
-  def testRaggedCountSparseOutputBadSplitsStart(self):
-    splits = [1, 7]
-    values = [1, 1, 2, 1, 2, 10, 5]
-    weights = [1, 2, 3, 4, 5, 6, 7]
-    with self.assertRaisesRegex(errors.InvalidArgumentError,
-                                "Splits must start with 0"):
-      self.evaluate(
-          gen_count_ops.RaggedCountSparseOutput(
-              splits=splits,
-              values=values,
-              weights=weights,
-              binary_output=False))
-
-  def testRaggedCountSparseOutputBadSplitsEnd(self):
-    splits = [0, 5]
-    values = [1, 1, 2, 1, 2, 10, 5]
-    weights = [1, 2, 3, 4, 5, 6, 7]
-    with self.assertRaisesRegex(errors.InvalidArgumentError,
-                                "Splits must end with the number of values"):
-      self.evaluate(
-          gen_count_ops.RaggedCountSparseOutput(
-              splits=splits,
-              values=values,
-              weights=weights,
-              binary_output=False))
-
-
 if __name__ == "__main__":
   test.main()

tensorflow/python/ops/math_ops.py

@@ -70,6 +70,8 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import collections
+
 import numpy as np
 import six
 from six.moves import builtins
@@ -98,7 +100,6 @@ from tensorflow.python.util import compat
 from tensorflow.python.util import deprecation
 from tensorflow.python.util import dispatch
 from tensorflow.python.util import nest
-from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 # Aliases for some automatically-generated names.
@@ -3492,7 +3493,7 @@ def add_n(inputs, name=None):
     ValueError: If `inputs` don't all have same shape and dtype or the shape
     cannot be inferred.
   """
-  if not inputs or not isinstance(inputs, collections_abc.Iterable):
+  if not inputs or not isinstance(inputs, collections.Iterable):
     raise ValueError("inputs must be an iterable of at least one "
                      "Tensor/IndexedSlices with the same dtype and shape")
   inputs = ops.convert_n_to_tensor_or_indexed_slices(inputs)
@@ -3625,9 +3626,9 @@ def sigmoid(x, name=None):
 
   Returns:
     A Tensor with the same type as `x`.
-
+  
   Usage Example:
-
+  
   >>> x = tf.constant([-128.0, 0.0, 128.0], dtype=tf.float32)
   >>> tf.sigmoid(x)
   <tf.Tensor: shape=(3,), dtype=float32,

tensorflow/python/ops/nn_ops.py

@@ -18,6 +18,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import collections
 import functools
 import numbers
 import os
@@ -3269,7 +3270,7 @@ def conv_transpose(input,  # pylint: disable=redefined-builtin
                       [input, filter, output_shape]) as name:
     if tensor_util.is_tensor(output_shape):
       n = output_shape.shape[0] - 2
-    elif isinstance(output_shape, collections_abc.Sized):
+    elif isinstance(output_shape, collections.Sized):
       n = len(output_shape) - 2
     else:
       raise ValueError("output_shape must be a tensor or sized collection.")

tensorflow/python/ops/nn_test.py

@@ -27,7 +27,6 @@ from six.moves import xrange  # pylint: disable=redefined-builtin
 from tensorflow.python.eager import def_function
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
-from tensorflow.python.framework import errors
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import tensor_spec
 from tensorflow.python.framework import test_util
@@ -1217,46 +1216,6 @@ class DataFormatDimMapTest(test_lib.TestCase):
       y_val = self.evaluate(y)
       self.assertAllEqual(y_val, y_val_expected)
 
-  @test_util.disable_xla("XLA catches the error and rethrows as different one")
-  def testInvalidLength(self):
-    x = [-4, -3, -2, -1, 0, 1, 2, 3]
-    with self.assertRaisesRegex(errors.InvalidArgumentError,
-                                "Source format must be of length 4 or 5"):
-      op = nn_ops.data_format_dim_map(
-          x, src_format="12345678", dst_format="87654321")
-      with test_util.use_gpu():
-        self.evaluate(op)
-
-  @test_util.disable_xla("XLA catches the error and rethrows as different one")
-  def testDuplicateSrc(self):
-    x = [-4, -3, -2, -1, 0, 1, 2, 3]
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        "Destination and source format must determine a permutation"):
-      op = nn_ops.data_format_dim_map(x, src_format="1233", dst_format="4321")
-      with test_util.use_gpu():
-        self.evaluate(op)
-
-  @test_util.disable_xla("XLA catches the error and rethrows as different one")
-  def testDuplicateDst(self):
-    x = [-4, -3, -2, -1, 0, 1, 2, 3]
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        "Destination and source format must determine a permutation"):
-      op = nn_ops.data_format_dim_map(x, src_format="1234", dst_format="3321")
-      with test_util.use_gpu():
-        self.evaluate(op)
-
-  @test_util.disable_xla("XLA catches the error and rethrows as different one")
-  def testExtraSpecifiers(self):
-    x = [-4, -3, -2, -1, 0, 1, 2, 3]
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        "Destination and source format must determine a permutation"):
-      op = nn_ops.data_format_dim_map(x, src_format="1234", dst_format="5321")
-      with test_util.use_gpu():
-        self.evaluate(op)
-
 
 class DataFormatVectorPermuteTest(test_lib.TestCase):
 
@@ -1358,60 +1317,6 @@ class DataFormatVectorPermuteTest(test_lib.TestCase):
       y_val = self.evaluate(y)
       self.assertAllEqual(y_val, [[7, 4], [4, 5], [5, 1], [9, 3]])
 
-  @test_util.disable_xla("XLA catches the error and rethrows as different one")
-  def testInvalidLength(self):
-    x = [0, 1, 2, 3]
-    with self.assertRaisesRegex(errors.InvalidArgumentError,
-                                "Source format must be of length 4 or 5"):
-      op = nn_ops.data_format_vec_permute(
-          x, src_format="12345678", dst_format="87654321")
-      with test_util.use_gpu():
-        self.evaluate(op)
-
-  @test_util.disable_xla("XLA catches the error and rethrows as different one")
-  def testDuplicateSrc(self):
-    x = [0, 1, 2, 3]
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        "Destination and source format must determine a permutation"):
-      op = nn_ops.data_format_vec_permute(
-          x, src_format="1233", dst_format="4321")
-      with test_util.use_gpu():
-        self.evaluate(op)
-
-  @test_util.disable_xla("XLA catches the error and rethrows as different one")
-  def testDuplicateDst(self):
-    x = [0, 1, 2, 3]
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        "Destination and source format must determine a permutation"):
-      op = nn_ops.data_format_vec_permute(
-          x, src_format="1234", dst_format="3321")
-      with test_util.use_gpu():
-        self.evaluate(op)
-
-  @test_util.disable_xla("XLA catches the error and rethrows as different one")
-  def testExtraSpecifiers(self):
-    x = [0, 1, 2, 3]
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        "Destination and source format must determine a permutation"):
-      op = nn_ops.data_format_vec_permute(
-          x, src_format="1234", dst_format="5321")
-      with test_util.use_gpu():
-        self.evaluate(op)
-
-  @test_util.disable_xla("XLA catches the error and rethrows as different one")
-  def test2DNoWH(self):
-    x = [[0, 1], [2, 3]]
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        "Format specifier must contain H and W for 2D case"):
-      op = nn_ops.data_format_vec_permute(
-          x, src_format="1234", dst_format="4321")
-      with test_util.use_gpu():
-        self.evaluate(op)
-
 
 @test_util.run_all_in_graph_and_eager_modes
 class AvgPoolTest(test_lib.TestCase):

tensorflow/python/ops/raw_ops_test.py

@@ -18,22 +18,16 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-from absl.testing import parameterized
-
 from tensorflow.python.eager import context
 from tensorflow.python.framework import constant_op
-from tensorflow.python.framework import errors
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import test_util
-from tensorflow.python.ops import gen_data_flow_ops
 from tensorflow.python.ops import gen_math_ops
-from tensorflow.python.ops import gen_string_ops
 from tensorflow.python.platform import test
 
 
 @test_util.run_all_in_graph_and_eager_modes
-@test_util.disable_tfrt
-class RawOpsTest(test.TestCase, parameterized.TestCase):
+class RawOpsTest(test.TestCase):
 
   def testSimple(self):
     x = constant_op.constant(1)
@@ -64,29 +58,6 @@ class RawOpsTest(test.TestCase, parameterized.TestCase):
         gen_math_ops.Any(input=x, axis=0),
         gen_math_ops.Any(input=x, axis=0, keep_dims=False))
 
-  @parameterized.parameters([[0, 8]], [[-1, 6]])
-  def testStringNGramsBadDataSplits(self, splits):
-    data = ["aa", "bb", "cc", "dd", "ee", "ff"]
-    with self.assertRaisesRegex(errors.InvalidArgumentError,
-                                "Invalid split value"):
-      self.evaluate(
-          gen_string_ops.string_n_grams(
-              data=data,
-              data_splits=splits,
-              separator="",
-              ngram_widths=[2],
-              left_pad="",
-              right_pad="",
-              pad_width=0,
-              preserve_short_sequences=False))
-
-  def testGetSessionHandle(self):
-    if context.executing_eagerly():
-      with self.assertRaisesRegex(
-          errors.FailedPreconditionError,
-          "GetSessionHandle called on null session state"):
-        gen_data_flow_ops.GetSessionHandle(value=[1])
-
 
 if __name__ == "__main__":
   ops.enable_eager_execution()

tensorflow/python/ops/sparse_ops_test.py

@@ -21,17 +21,14 @@ from __future__ import print_function
 from absl.testing import parameterized
 import numpy as np
 
-from tensorflow.python.eager import context
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
-from tensorflow.python.framework import errors
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import sparse_tensor
 from tensorflow.python.framework import test_util
 # Need array_grad to register gradient for Identity.
 from tensorflow.python.ops import array_grad  # pylint: disable=unused-import
 from tensorflow.python.ops import array_ops
-from tensorflow.python.ops import gen_sparse_ops
 from tensorflow.python.ops import gradient_checker_v2 as gradient_checker
 from tensorflow.python.ops import math_ops
 # Need sparse_grad to register gradient for SparseToDense.
@@ -184,57 +181,5 @@ class SparseOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
     self.assertAllEqual(expected, result)
 
 
-@test_util.run_all_in_graph_and_eager_modes
-class RawOpsTest(test_util.TensorFlowTestCase, parameterized.TestCase):
-
-  def testSparseFillEmptyRowsGrad(self):
-    reverse_index_map = [2, 1]
-    grad_values = [0, 1, 2, 3]
-    d_values, d_default_value = self.evaluate(
-        gen_sparse_ops.SparseFillEmptyRowsGrad(
-            reverse_index_map=reverse_index_map, grad_values=grad_values))
-    self.assertAllEqual([2, 1], d_values)
-    self.assertEqual(3, d_default_value)
-
-  def testSparseFillEmptyRowsGradNegativeIndexMapValue(self):
-    reverse_index_map = [2, -1]
-    grad_values = [0, 1, 2, 3]
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        r'Elements in reverse index must be in \[0, 4\)'):
-      self.evaluate(
-          gen_sparse_ops.SparseFillEmptyRowsGrad(
-              reverse_index_map=reverse_index_map, grad_values=grad_values))
-
-  def testSparseFillEmptyRowsGradLargeIndexMapValue(self):
-    reverse_index_map = [2, 10]
-    grad_values = [0, 1, 2, 3]
-    with self.assertRaisesRegex(
-        errors.InvalidArgumentError,
-        r'Elements in reverse index must be in \[0, 4\)'):
-      self.evaluate(
-          gen_sparse_ops.SparseFillEmptyRowsGrad(
-              reverse_index_map=reverse_index_map, grad_values=grad_values))
-
-  def testSparseFillEmptyRowsGradMatrix(self):
-    reverse_index_map = [0, 1]
-    grad_values = [[0, 1], [2, 3]]
-    # Note: Eager mode and graph mode throw different errors here. Graph mode
-    # will fail with a ValueError from the shape checking logic, while Eager
-    # will fail with an InvalidArgumentError from the kernel itself.
-    if context.executing_eagerly():
-      with self.assertRaisesRegex(errors.InvalidArgumentError,
-                                  r'grad_values must be a vector'):
-        self.evaluate(
-            gen_sparse_ops.SparseFillEmptyRowsGrad(
-                reverse_index_map=reverse_index_map, grad_values=grad_values))
-    else:
-      with self.assertRaisesRegex(ValueError,
-                                  r'Shape must be rank 1 but is rank 2'):
-        self.evaluate(
-            gen_sparse_ops.SparseFillEmptyRowsGrad(
-                reverse_index_map=reverse_index_map, grad_values=grad_values))
-
-
 if __name__ == '__main__':
   googletest.main()

tensorflow/python/ops/variable_scope.py

@@ -18,6 +18,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import collections as collections_lib
 import copy
 import enum  # pylint: disable=g-bad-import-order
 import functools
@@ -46,7 +47,6 @@ from tensorflow.python.util import deprecation
 from tensorflow.python.util import function_utils
 from tensorflow.python.util import tf_contextlib
 from tensorflow.python.util import tf_inspect
-from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 __all__ = [
@@ -77,13 +77,13 @@ class _PartitionInfo(object):
       ValueError: If `full_shape` or `var_offset` differ in length. If
         `var_offset` exceeds `full_shape` in any dimension.
     """
-    if not isinstance(full_shape, collections_abc.Sequence) or isinstance(
+    if not isinstance(full_shape, collections_lib.Sequence) or isinstance(
         full_shape, six.string_types):
       raise TypeError(
           "`full_shape` must be a sequence (like tuple or list) instead of " +
           type(full_shape).__name__)
 
-    if not isinstance(var_offset, collections_abc.Sequence) or isinstance(
+    if not isinstance(var_offset, collections_lib.Sequence) or isinstance(
         var_offset, six.string_types):
       raise TypeError(
           "`var_offset` must be a sequence (like tuple or list) instead of " +
@@ -151,7 +151,7 @@ class _PartitionInfo(object):
       ValueError: If `shape` is not the same length as `self.full_shape`. If
         the variable is partitioned in more than one dimension.
     """
-    if not isinstance(shape, collections_abc.Sequence) or isinstance(
+    if not isinstance(shape, collections_lib.Sequence) or isinstance(
         shape, six.string_types):
       raise TypeError(
           "`shape` must be a sequence (like tuple or list) instead of " +
@@ -451,7 +451,7 @@ class _VariableStore(object):
         synchronization=VariableSynchronization.AUTO,
         aggregation=VariableAggregation.NONE):
       is_scalar = (
-          shape is not None and isinstance(shape, collections_abc.Sequence) and
+          shape is not None and isinstance(shape, collections_lib.Sequence) and
           not shape)
       # Partitioned variable case
       if partitioner is not None and not is_scalar:
@@ -2511,7 +2511,7 @@ def _call_partitioner(partitioner, shape, dtype):
                      "shape: %s" % shape)
 
   slicing = partitioner(shape=shape, dtype=dtype)
-  if not isinstance(slicing, collections_abc.Sequence):
+  if not isinstance(slicing, collections_lib.Sequence):
     raise ValueError("Partitioner must return a sequence, but saw: %s" %
                      slicing)
   if len(slicing) != shape.ndims:

tensorflow/python/tfe_wrapper.cc

@@ -1129,16 +1129,9 @@ PYBIND11_MODULE(_pywrap_tfe, m) {
   // DLPack functions
   m.def("TFE_ToDlpackCapsule", [](py::handle& o) {
     PyObject* eager_tensor_pyobject_ptr = o.ptr();
+    TFE_TensorHandle* thandle = EagerTensor_Handle(eager_tensor_pyobject_ptr);
     tensorflow::Safe_TF_StatusPtr status =
         tensorflow::make_safe(TF_NewStatus());
-
-    if (!EagerTensor_CheckExact(eager_tensor_pyobject_ptr)) {
-      status->status = tensorflow::errors::InvalidArgument(
-          "The argument to `to_dlpack` must be a TF tensor, not Python object");
-      tensorflow::MaybeRaiseRegisteredFromTFStatus(status.get());
-    }
-
-    TFE_TensorHandle* thandle = EagerTensor_Handle(eager_tensor_pyobject_ptr);
     void* dlm_ptr = tensorflow::TFE_HandleToDLPack(thandle, status.get());
     tensorflow::MaybeRaiseRegisteredFromTFStatus(status.get());
 

tensorflow/python/tools/saved_model_cli.py

@@ -24,6 +24,7 @@ from __future__ import division
 from __future__ import print_function
 
 import argparse
+import collections
 import os
 import re
 import sys
@@ -50,7 +51,6 @@ from tensorflow.python.saved_model import signature_constants
 from tensorflow.python.tools import saved_model_aot_compile
 from tensorflow.python.tools import saved_model_utils
 from tensorflow.python.tpu import tpu
-from tensorflow.python.util.compat import collections_abc
 
 
 _XLA_DEBUG_OPTIONS_URL = (
@@ -241,7 +241,7 @@ def _print_args(arguments, argument_type='Argument', indent=0):
       in_print('  %s' % element)
     elif isinstance(element, tensor_spec.TensorSpec):
       print((indent + 1) * '  ' + '%s: %s' % (element.name, repr(element)))
-    elif (isinstance(element, collections_abc.Iterable) and
+    elif (isinstance(element, collections.Iterable) and
           not isinstance(element, dict)):
       in_print('  DType: %s' % type(element).__name__)
       in_print('  Value: [', end='')

tensorflow/stream_executor/cuda/cuda_dnn.cc

@@ -1474,9 +1474,7 @@ class CudnnRnnSequenceTensorDescriptor
   static port::StatusOr<CudnnRnnSequenceTensorDescriptor> Create(
       GpuExecutor* parent, int max_seq_length, int batch_size, int data_size,
       cudnnDataType_t data_type) {
-    if (max_seq_length <= 0) {
-      return port::Status(port::error::INVALID_ARGUMENT, "max_seq_length <= 0");
-    }
+    CHECK_GT(max_seq_length, 0);
     int dims[] = {batch_size, data_size, 1};
     int strides[] = {dims[1] * dims[2], dims[2], 1};
     TensorDescriptor tensor_desc = CreateTensorDescriptor();
@@ -1497,9 +1495,7 @@ class CudnnRnnSequenceTensorDescriptor
       const absl::Span<const int>& seq_lengths, bool time_major,
       cudnnDataType_t data_type) {
 #if CUDNN_VERSION >= 7201
-    if (max_seq_length <= 0) {
-      return port::Status(port::error::INVALID_ARGUMENT, "max_seq_length <= 0");
-    }
+    CHECK_GT(max_seq_length, 0);
     int dims[] = {batch_size, data_size, 1};
     int strides[] = {dims[1] * dims[2], dims[2], 1};
     TensorDescriptor tensor_desc = CreateTensorDescriptor();

tensorflow/tensorflow.bzl

@@ -59,7 +59,7 @@ load(
 # not contain rc or alpha, only numbers.
 # Also update tensorflow/core/public/version.h
 # and tensorflow/tools/pip_package/setup.py
-VERSION = "2.3.2"
+VERSION = "2.3.0"
 VERSION_MAJOR = VERSION.split(".")[0]
 
 # Sanitize a dependency so that it works correctly from code that includes

tensorflow/tools/ci_build/builds/libtensorflow.sh

@@ -56,7 +56,6 @@ function build_libtensorflow_tarball() {
   if [ "${TF_NEED_CUDA}" == "1" ]; then
     BAZEL_OPTS="${BAZEL_OPTS} --config=cuda --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain"
     export TF_NEED_ROCM=0
-    export TF_CUDA_COMPUTE_CAPABILITIES="sm_35,sm_50,sm_60,sm_70,sm_75"
   fi
   bazel clean --expunge
   yes "" | ./configure

tensorflow/tools/ci_build/linux/libtensorflow_docker.sh

@@ -58,7 +58,6 @@ ${DOCKER_BINARY} run \
   -e "TF_NEED_HDFS=0" \
   -e "TF_NEED_CUDA=${TF_NEED_CUDA}" \
   -e "TF_NEED_TENSORRT=${TF_NEED_CUDA}" \
-  -e "TF_CUDA_COMPUTE_CAPABILITIES=${TF_CUDA_COMPUTE_CAPABILITIES}" \
   -e "TF_NEED_ROCM=${TF_NEED_ROCM}" \
   -e "TF_NEED_OPENCL_SYCL=0" \
   "${DOCKER_IMAGE}" \

tensorflow/tools/ci_build/rel/macos/cpu_libtensorflow.sh

@@ -1,27 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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.
-# ==============================================================================
-echo "chmod go+w lib_package/*" >> tensorflow/tools/ci_build/linux/libtensorflow.sh
-echo "bazel clean --expunge" >> tensorflow/tools/ci_build/linux/libtensorflow.sh
-
-# Install latest bazel
-source tensorflow/tools/ci_build/release/common.sh
-install_bazelisk
-
-# Pick a version of xcode
-export DEVELOPER_DIR=/Applications/Xcode_10.3.app/Contents/Developer
-sudo xcode-select -s "${DEVELOPER_DIR}"
-
-tensorflow/tools/ci_build/osx/libtensorflow_cpu.sh

tensorflow/tools/ci_build/rel/macos/cpu_py35_nonpip.sh

@@ -1,51 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-install_bazelisk
-
-# Pick a more recent version of xcode
-export DEVELOPER_DIR=/Applications/Xcode_10.3.app/Contents/Developer
-sudo xcode-select -s "${DEVELOPER_DIR}"
-python3.5 -m virtualenv tf_build_env --system-site-packages
-source tf_build_env/bin/activate
-
-# Install macos pip dependencies
-install_macos_pip_deps sudo pip3.5
-
-# Run configure.
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export TF2_BEHAVIOR=1
-export PYTHON_BIN_PATH=$(which python3.5)
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-tag_filters="-no_oss,-oss_serial,-nomac,-no_mac,-no_oss_py35,-v1only,-gpu,-tpu,-benchmark-test"
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Run tests
-set +e
-bazel test --test_output=errors --config=opt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --build_tag_filters="${tag_filters}" \
-  --test_tag_filters="${tag_filters}" -- \
-  ${DEFAULT_BAZEL_TARGETS} \
-  -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/macos/cpu_py35_pip.sh

@@ -1,51 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-install_bazelisk
-
-# Pick a more recent version of xcode
-export DEVELOPER_DIR=/Applications/Xcode_10.3.app/Contents/Developer
-sudo xcode-select -s "${DEVELOPER_DIR}"
-
-# Install macos pip dependencies
-install_macos_pip_deps sudo pip3.5
-
-# Export required variables for running pip_new.sh
-export OS_TYPE="MACOS"
-export CONTAINER_TYPE="CPU"
-export TF_PYTHON_VERSION='python3.5'
-export TF_BUILD_BOTH_CPU_PACKAGES=1
-
-# Run configure.
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Export optional variables for running pip.sh
-export TF_BUILD_FLAGS="--config=opt --config=v2"
-export TF_TEST_FLAGS="--define=no_tensorflow_py_deps=true --test_lang_filters=py --test_output=errors --verbose_failures=true --keep_going --test_env=TF2_BEHAVIOR=1"
-export TF_TEST_TARGETS="//tensorflow/python/..."
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-export TF_TEST_FILTER_TAGS='-nomac,-no_mac,-no_oss,-oss_serial,-no_oss_py35,-gpu,-tpu,-benchmark-test'
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME="tensorflow"
-export TF_PIP_TEST_ROOT="pip_test"
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/macos/cpu_py36_nonpip.sh

@@ -1,51 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-install_bazelisk
-
-# Pick a more recent version of xcode
-export DEVELOPER_DIR=/Applications/Xcode_10.3.app/Contents/Developer
-sudo xcode-select -s "${DEVELOPER_DIR}"
-python3.6 -m virtualenv tf_build_env --system-site-packages
-source tf_build_env/bin/activate
-
-# Install macos pip dependencies
-install_macos_pip_deps sudo pip3.6
-
-# Run configure.
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export TF2_BEHAVIOR=1
-export PYTHON_BIN_PATH=$(which python3.6)
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-tag_filters="-no_oss,-oss_serial,-nomac,-no_mac,-no_oss_py36,-v1only,-gpu,-tpu,-benchmark-test"
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Run tests
-set +e
-bazel test --test_output=errors --config=opt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --build_tag_filters="${tag_filters}" \
-  --test_tag_filters="${tag_filters}" -- \
-  ${DEFAULT_BAZEL_TARGETS} \
-  -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/macos/cpu_py36_pip.sh

@@ -1,51 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-install_bazelisk
-
-# Pick a more recent version of xcode
-export DEVELOPER_DIR=/Applications/Xcode_10.3.app/Contents/Developer
-sudo xcode-select -s "${DEVELOPER_DIR}"
-
-# Install macos pip dependencies
-install_macos_pip_deps sudo pip3.6
-
-# Export required variables for running pip_new.sh
-export OS_TYPE="MACOS"
-export CONTAINER_TYPE="CPU"
-export TF_PYTHON_VERSION='python3.6'
-export TF_BUILD_BOTH_CPU_PACKAGES=1
-
-# Run configure.
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Export optional variables for running pip.sh
-export TF_BUILD_FLAGS="--config=opt --config=v2"
-export TF_TEST_FLAGS="--define=no_tensorflow_py_deps=true --test_lang_filters=py --test_output=errors --verbose_failures=true --keep_going --test_env=TF2_BEHAVIOR=1"
-export TF_TEST_TARGETS="//tensorflow/python/..."
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-export TF_TEST_FILTER_TAGS='-nomac,-no_mac,-no_oss,-oss_serial,-no_oss_py35,-v1only,-gpu,-tpu,-benchmark-test'
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME="tensorflow"
-export TF_PIP_TEST_ROOT="pip_test"
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/macos/cpu_py37_nonpip.sh

@@ -1,51 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-install_bazelisk
-
-# Pick a more recent version of xcode
-export DEVELOPER_DIR=/Applications/Xcode_10.3.app/Contents/Developer
-sudo xcode-select -s "${DEVELOPER_DIR}"
-python -m virtualenv tf_build_env --system-site-packages
-source tf_build_env/bin/activate
-
-# Install macos pip dependencies
-install_macos_pip_deps sudo pip3.7
-
-# Run configure.
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export TF2_BEHAVIOR=1
-export PYTHON_BIN_PATH=$(which python3.7)
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-tag_filters="-no_oss,-oss_serial,-nomac,-no_mac$(maybe_skip_v1),-gpu,-tpu,-benchmark-test"
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Run tests
-set +e
-bazel test --test_output=errors --config=opt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --build_tag_filters="${tag_filters}" \
-  --test_tag_filters="${tag_filters}" -- \
-  ${DEFAULT_BAZEL_TARGETS} \
-  -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/macos/cpu_py37_pip.sh

@@ -1,51 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-install_bazelisk
-
-# Pick a more recent version of xcode
-export DEVELOPER_DIR=/Applications/Xcode_10.3.app/Contents/Developer
-sudo xcode-select -s "${DEVELOPER_DIR}"
-
-# Install macos pip dependencies
-install_macos_pip_deps sudo pip3.7
-
-# Export required variables for running pip_new.sh
-export OS_TYPE="MACOS"
-export CONTAINER_TYPE="CPU"
-export TF_PYTHON_VERSION='python3.7'
-export TF_BUILD_BOTH_CPU_PACKAGES=1
-
-# Run configure.
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Export optional variables for running pip.sh
-export TF_BUILD_FLAGS="--config=opt --config=v2"
-export TF_TEST_FLAGS="--define=no_tensorflow_py_deps=true --test_lang_filters=py --test_output=errors --verbose_failures=true --keep_going --test_env=TF2_BEHAVIOR=1"
-export TF_TEST_TARGETS="//tensorflow/python/..."
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-export TF_TEST_FILTER_TAGS='-nomac,-no_mac,-no_oss,-oss_serial,-no_oss_py37,-v1only,-gpu,-tpu,-benchmark-test'
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME="tensorflow"
-export TF_PIP_TEST_ROOT="pip_test"
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/macos/cpu_py38_nonpip.sh

@@ -1,51 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-install_bazelisk
-
-# Pick a more recent version of xcode
-export DEVELOPER_DIR=/Applications/Xcode_10.3.app/Contents/Developer
-sudo xcode-select -s "${DEVELOPER_DIR}"
-python -m virtualenv tf_build_env --system-site-packages
-source tf_build_env/bin/activate
-
-# Install macos pip dependencies
-install_macos_pip_deps sudo pip3.8
-
-# Run configure.
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export TF2_BEHAVIOR=1
-export PYTHON_BIN_PATH=$(which python3.8)
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-tag_filters="-no_oss,-oss_serial,-nomac,-no_mac$(maybe_skip_v1),-gpu,-tpu,-benchmark-test"
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Run tests
-set +e
-bazel test --test_output=errors --config=opt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --build_tag_filters="${tag_filters}" \
-  --test_tag_filters="${tag_filters}" -- \
-  ${DEFAULT_BAZEL_TARGETS} \
-  -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/macos/cpu_py38_pip.sh

@@ -1,51 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-install_bazelisk
-
-# Pick a more recent version of xcode
-export DEVELOPER_DIR=/Applications/Xcode_10.3.app/Contents/Developer
-sudo xcode-select -s "${DEVELOPER_DIR}"
-
-# Install macos pip dependencies
-install_macos_pip_deps sudo pip3.8
-
-# Export required variables for running pip_new.sh
-export OS_TYPE="MACOS"
-export CONTAINER_TYPE="CPU"
-export TF_PYTHON_VERSION='python3.8'
-export TF_BUILD_BOTH_CPU_PACKAGES=1
-
-# Run configure.
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Export optional variables for running pip.sh
-export TF_BUILD_FLAGS="--config=opt --config=v2"
-export TF_TEST_FLAGS="--define=no_tensorflow_py_deps=true --test_lang_filters=py --test_output=errors --verbose_failures=true --keep_going --test_env=TF2_BEHAVIOR=1"
-export TF_TEST_TARGETS="//tensorflow/python/..."
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-export TF_TEST_FILTER_TAGS='-nomac,-no_mac,-no_oss,-oss_serial,-no_oss_py38,-v1only,-gpu,-tpu,-benchmark-test'
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME="tensorflow"
-export TF_PIP_TEST_ROOT="pip_test"
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/ubuntu/cpu_libtensorflow.sh

@@ -1,40 +0,0 @@
-#!/bin/bash
-# Copyright 2020 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
-
-# Source the external common scripts.
-source tensorflow/tools/ci_build/release/common.sh
-
-
-# Install latest bazel
-install_bazelisk
-which bazel
-
-# Install realpath
-sudo apt-get install realpath
-
-# Update the version string to nightly
-if [ -n "${IS_NIGHTLY_BUILD}" ]; then
-  ./tensorflow/tools/ci_build/update_version.py --nightly
-fi
-
-./tensorflow/tools/ci_build/linux/libtensorflow.sh
-
-# Copy the nightly version update script
-if [ -n "${IS_NIGHTLY_BUILD}" ]; then
-  cp tensorflow/tools/ci_build/builds/libtensorflow_nightly_symlink.sh lib_package
-fi
-

tensorflow/tools/ci_build/rel/ubuntu/cpu_py35_nonpip.sh

@@ -1,48 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.5
-# Update bazel
-install_bazelisk
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which python3.5)
-export TF2_BEHAVIOR=1
-yes "" | "$PYTHON_BIN_PATH" configure.py
-tag_filters="-no_oss,-oss_serial,-gpu,-tpu,-benchmark-test,-no_oss_py35,-v1only"
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Run tests
-set +e
-bazel test --test_output=errors --config=opt --test_lang_filters=py \
-  --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain \
-  --linkopt=-lrt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --build_tag_filters="${tag_filters}" \
-  --test_tag_filters="${tag_filters}" -- \
-  ${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/ubuntu/cpu_py35_pip.sh

@@ -1,52 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.5
-# Update bazel
-install_bazelisk
-
-# Export required variables for running pip.sh
-export OS_TYPE="UBUNTU"
-export CONTAINER_TYPE="CPU"
-export TF_PYTHON_VERSION='python3.5'
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Export optional variables for running pip.sh
-export TF_BUILD_FLAGS="--config=opt --config=v2 --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain"
-export TF_TEST_FLAGS="--define=no_tensorflow_py_deps=true --test_lang_filters=py --test_output=errors --verbose_failures=true --keep_going --test_env=TF2_BEHAVIOR=1"
-export TF_TEST_TARGETS="${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/... "
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-export TF_TEST_FILTER_TAGS='-no_oss,-oss_serial,-no_oss_py35,-v1only'
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME="tensorflow_cpu"
-export TF_PIP_TEST_ROOT="pip_test"
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/ubuntu/cpu_py36_nonpip.sh

@@ -1,48 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.6
-# Update bazel
-install_bazelisk
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which python3.6)
-export TF2_BEHAVIOR=1
-yes "" | "$PYTHON_BIN_PATH" configure.py
-tag_filters="-no_oss,-oss_serial,-gpu,-tpu,-benchmark-test,-no_oss_py36,-v1only"
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Run tests
-set +e
-bazel test --test_output=errors --config=opt --test_lang_filters=py \
-  --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain \
-  --linkopt=-lrt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --build_tag_filters="${tag_filters}" \
-  --test_tag_filters="${tag_filters}" -- \
-  ${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/ubuntu/cpu_py36_pip.sh

@@ -1,52 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.6
-# Update bazel
-install_bazelisk
-
-# Export required variables for running pip.sh
-export OS_TYPE="UBUNTU"
-export CONTAINER_TYPE="CPU"
-export TF_PYTHON_VERSION='python3.6'
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Export optional variables for running pip.sh
-export TF_BUILD_FLAGS="--config=opt --config=v2 --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain"
-export TF_TEST_FLAGS="--define=no_tensorflow_py_deps=true --test_lang_filters=py --test_output=errors --verbose_failures=true --keep_going --test_env=TF2_BEHAVIOR=1"
-export TF_TEST_TARGETS="${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/... "
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-export TF_TEST_FILTER_TAGS='-no_oss,-oss_serial,-no_oss_py36,-v1only'
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME="tensorflow_cpu"
-export TF_PIP_TEST_ROOT="pip_test"
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/ubuntu/cpu_py37_nonpip.sh

@@ -1,48 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.7
-# Update bazel
-install_bazelisk
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which python3.7)
-export TF2_BEHAVIOR=1
-yes "" | "$PYTHON_BIN_PATH" configure.py
-tag_filters="-no_oss,-oss_serial,-gpu,-tpu,-benchmark-test,-no_oss_py37,-v1only"
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Run tests
-set +e
-bazel test --test_output=errors --config=opt --test_lang_filters=py \
-  --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain \
-  --linkopt=-lrt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --build_tag_filters="${tag_filters}" \
-  --test_tag_filters="${tag_filters}" -- \
-  ${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/ubuntu/cpu_py37_pip.sh

@@ -1,52 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.7
-# Update bazel
-install_bazelisk
-
-# Export required variables for running pip.sh
-export OS_TYPE="UBUNTU"
-export CONTAINER_TYPE="CPU"
-export TF_PYTHON_VERSION='python3.7'
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Export optional variables for running pip.sh
-export TF_BUILD_FLAGS="--config=opt --config=v2 --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain"
-export TF_TEST_FLAGS="--define=no_tensorflow_py_deps=true --test_lang_filters=py --test_output=errors --verbose_failures=true --keep_going --test_env=TF2_BEHAVIOR=1"
-export TF_TEST_TARGETS="${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/... "
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-export TF_TEST_FILTER_TAGS='-no_oss,-oss_serial,-no_oss_py37,-v1only'
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME="tensorflow_cpu"
-export TF_PIP_TEST_ROOT="pip_test"
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/ubuntu/cpu_py38_nonpip.sh

@@ -1,48 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.8
-# Update bazel
-install_bazelisk
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which python3.8)
-export TF2_BEHAVIOR=1
-yes "" | "$PYTHON_BIN_PATH" configure.py
-tag_filters="-no_oss,-oss_serial,-gpu,-tpu,-benchmark-test,-no_oss_py38,-v1only"
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Run tests
-set +e
-bazel test --test_output=errors --config=opt --test_lang_filters=py \
-  --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain \
-  --linkopt=-lrt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --build_tag_filters="${tag_filters}" \
-  --test_tag_filters="${tag_filters}" -- \
-  ${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/ubuntu/cpu_py38_pip.sh

@@ -1,52 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.8
-# Update bazel
-install_bazelisk
-
-# Export required variables for running pip.sh
-export OS_TYPE="UBUNTU"
-export CONTAINER_TYPE="CPU"
-export TF_PYTHON_VERSION='python3.8'
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=0
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Export optional variables for running pip.sh
-export TF_BUILD_FLAGS="--config=opt --config=v2 --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain"
-export TF_TEST_FLAGS="--define=no_tensorflow_py_deps=true --test_lang_filters=py --test_output=errors --verbose_failures=true --keep_going --test_env=TF2_BEHAVIOR=1"
-export TF_TEST_TARGETS="${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/... "
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-export TF_TEST_FILTER_TAGS='-no_oss,-oss_serial,-no_oss_py38,-v1only'
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME="tensorflow_cpu"
-export TF_PIP_TEST_ROOT="pip_test"
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/ubuntu/gpu_libtensorflow.sh

@@ -1,40 +0,0 @@
-# Copyright 2020 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
-
-# Source the external common scripts.
-source tensorflow/tools/ci_build/release/common.sh
-
-
-# Install latest bazel
-install_bazelisk
-which bazel
-
-# Install realpath
-sudo apt-get install realpath
-
-export TF_NEED_CUDA=1
-
-# Update the version string to nightly
-if [ -n "${IS_NIGHTLY_BUILD}" ]; then
-  ./tensorflow/tools/ci_build/update_version.py --nightly
-fi
-
-./tensorflow/tools/ci_build/linux/libtensorflow.sh
-
-# Copy the nightly version update script
-if [ -n "${IS_NIGHTLY_BUILD}" ]; then
-  cp tensorflow/tools/ci_build/builds/libtensorflow_nightly_symlink.sh lib_package
-fi

tensorflow/tools/ci_build/rel/ubuntu/gpu_pip_on_cpu.sh

@@ -1,61 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.6
-# Update Bazel to the desired version
-install_bazelisk
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=1
-export TF_CUDA_VERSION=10
-export TF_CUDNN_VERSION=7
-export TF_NEED_TENSORRT=1
-export TENSORRT_INSTALL_PATH=/usr/local/tensorrt
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which python3.6)
-export LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$TENSORRT_INSTALL_PATH/lib"
-export TF_CUDA_COMPUTE_CAPABILITIES=sm_35,sm_37,sm_52,sm_60,sm_61,compute_70
-
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-########################
-## Build GPU pip package
-########################
-bazel build --config=opt \
-  --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain \
-  tensorflow/tools/pip_package:build_pip_package
-
-# Set TF nightly flag so we get the proper version of estimator
-if [[ "$IS_NIGHTLY" == 1 ]]; then
-  NIGHTLY_FLAG="--nightly_flag"
-fi
-
-PIP_WHL_DIR=whl
-mkdir -p ${PIP_WHL_DIR}
-PIP_WHL_DIR=$(readlink -f ${PIP_WHL_DIR})  # Get absolute path
-bazel-bin/tensorflow/tools/pip_package/build_pip_package "${PIP_WHL_DIR}" "${NIGHTLY_FLAG}"
-WHL_PATH=$(ls "${PIP_WHL_DIR}"/*.whl)
-
-cp "${WHL_PATH}" "$(pwd)"/.
-chmod +x tensorflow/tools/ci_build/builds/docker_cpu_pip.sh
-docker run -e "BAZEL_VERSION=${BAZEL_VERSION}" -e "CI_BUILD_USER=$(id -u -n)" -e "CI_BUILD_UID=$(id -u)"  -e "CI_BUILD_GROUP=$(id -g -n)" -e "CI_BUILD_GID=$(id -g)"  -e "CI_BUILD_HOME=/bazel_pip" -v "$(pwd)":/bazel_pip tensorflow/tensorflow:devel "./bazel_pip/tensorflow/tools/ci_build/builds/with_the_same_user" "./bazel_pip/tensorflow/tools/ci_build/builds/docker_cpu_pip.sh"

tensorflow/tools/ci_build/rel/ubuntu/gpu_py35_nonpip.sh

@@ -1,60 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.5
-# Update bazel
-install_bazelisk
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=1
-export TF_CUDA_VERSION=10
-export TF_CUDNN_VERSION=7
-export TF_NEED_TENSORRT=1
-export TENSORRT_INSTALL_PATH=/usr/local/tensorrt
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which python3.5)
-export TF2_BEHAVIOR=1
-export PROJECT_NAME="tensorflow_gpu"
-export LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$TENSORRT_INSTALL_PATH/lib"
-export TF_CUDA_COMPUTE_CAPABILITIES=sm_35,sm_37,sm_52,sm_60,sm_61,compute_70
-
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-tag_filters="gpu,requires-gpu,-no_gpu,-no_oss,-oss_serial,-no_oss_py35"
-
-set +e
-bazel test --config=cuda --config=opt \
-  --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain \
-  --linkopt=-lrt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --test_lang_filters=py \
-  --test_tag_filters=${tag_filters} \
-  --build_tag_filters=${tag_filters} \
-  --test_timeout="300,450,1200,3600" --local_test_jobs=4 \
-  --test_output=errors --verbose_failures=true --keep_going \
-  --run_under=//tensorflow/tools/ci_build/gpu_build:parallel_gpu_execute \
-  -- ${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/ubuntu/gpu_py35_pip.sh

@@ -1,69 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.5
-# Update bazel
-install_bazelisk
-
-# Export required variables for running pip.sh
-export OS_TYPE="UBUNTU"
-export CONTAINER_TYPE="GPU"
-export TF_PYTHON_VERSION='python3.5'
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=1
-export TF_CUDA_VERSION=10
-export TF_CUDNN_VERSION=7
-export TF_NEED_TENSORRT=1
-export TENSORRT_INSTALL_PATH=/usr/local/tensorrt
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-export PROJECT_NAME="tensorflow_gpu"
-export LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$TENSORRT_INSTALL_PATH/lib"
-export TF_CUDA_COMPUTE_CAPABILITIES=sm_35,sm_37,sm_52,sm_60,sm_61,compute_70
-
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Export optional variables for running pip.sh
-export TF_TEST_FILTER_TAGS='gpu,requires-gpu,-no_gpu,-no_oss,-oss_serial,-no_oss_py35'
-export TF_BUILD_FLAGS="--config=opt --config=v2 --config=cuda --distinct_host_configuration=false \
---action_env=TF_CUDA_VERSION --action_env=TF_CUDNN_VERSION --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain "
-export TF_TEST_FLAGS="--test_tag_filters=${TF_TEST_FILTER_TAGS} --build_tag_filters=${TF_TEST_FILTER_TAGS} \
---distinct_host_configuration=false \
---action_env=TF_CUDA_VERSION --action_env=TF_CUDNN_VERSION --test_env=TF2_BEHAVIOR=1 \
---config=cuda --test_output=errors --local_test_jobs=4 --test_lang_filters=py \
---verbose_failures=true --keep_going --define=no_tensorflow_py_deps=true \
---run_under=//tensorflow/tools/ci_build/gpu_build:parallel_gpu_execute "
-export TF_TEST_TARGETS="${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/... "
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME=${PROJECT_NAME}
-export TF_PIP_TEST_ROOT="pip_test"
-
-# To build both tensorflow and tensorflow-gpu pip packages
-export TF_BUILD_BOTH_GPU_PACKAGES=1
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/ubuntu/gpu_py36_nonpip.sh

@@ -1,60 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.6
-# Update bazel
-install_bazelisk
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=1
-export TF_CUDA_VERSION=10
-export TF_CUDNN_VERSION=7
-export TF_NEED_TENSORRT=1
-export TENSORRT_INSTALL_PATH=/usr/local/tensorrt
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which python3.6)
-export TF2_BEHAVIOR=1
-export PROJECT_NAME="tensorflow_gpu"
-export LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$TENSORRT_INSTALL_PATH/lib"
-export TF_CUDA_COMPUTE_CAPABILITIES=sm_35,sm_37,sm_52,sm_60,sm_61,compute_70
-
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-tag_filters="gpu,requires-gpu,-no_gpu,-no_oss,-oss_serial,-no_oss_py36"
-
-set +e
-bazel test --config=cuda --config=opt \
-  --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain \
-  --linkopt=-lrt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --test_lang_filters=py \
-  --test_tag_filters=${tag_filters} \
-  --build_tag_filters=${tag_filters} \
-  --test_timeout="300,450,1200,3600" --local_test_jobs=4 \
-  --test_output=errors --verbose_failures=true --keep_going \
-  --run_under=//tensorflow/tools/ci_build/gpu_build:parallel_gpu_execute \
-  -- ${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/ubuntu/gpu_py36_pip.sh

@@ -1,69 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.6
-# Update bazel
-install_bazelisk
-
-# Export required variables for running pip.sh
-export OS_TYPE="UBUNTU"
-export CONTAINER_TYPE="GPU"
-export TF_PYTHON_VERSION='python3.6'
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=1
-export TF_CUDA_VERSION=10
-export TF_CUDNN_VERSION=7
-export TF_NEED_TENSORRT=1
-export TENSORRT_INSTALL_PATH=/usr/local/tensorrt
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-export PROJECT_NAME="tensorflow_gpu"
-export LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$TENSORRT_INSTALL_PATH/lib"
-export TF_CUDA_COMPUTE_CAPABILITIES=sm_35,sm_37,sm_52,sm_60,sm_61,compute_70
-
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Export optional variables for running pip.sh
-export TF_TEST_FILTER_TAGS='gpu,requires-gpu,-no_gpu,-no_oss,-oss_serial,-no_oss_py36'
-export TF_BUILD_FLAGS="--config=opt --config=v2 --config=cuda --distinct_host_configuration=false \
---action_env=TF_CUDA_VERSION --action_env=TF_CUDNN_VERSION --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain "
-export TF_TEST_FLAGS="--test_tag_filters=${TF_TEST_FILTER_TAGS} --build_tag_filters=${TF_TEST_FILTER_TAGS} \
---distinct_host_configuration=false \
---action_env=TF_CUDA_VERSION --action_env=TF_CUDNN_VERSION --test_env=TF2_BEHAVIOR=1 \
---config=cuda --test_output=errors --local_test_jobs=4 --test_lang_filters=py \
---verbose_failures=true --keep_going --define=no_tensorflow_py_deps=true \
---run_under=//tensorflow/tools/ci_build/gpu_build:parallel_gpu_execute "
-export TF_TEST_TARGETS="${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/... "
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME=${PROJECT_NAME}
-export TF_PIP_TEST_ROOT="pip_test"
-
-# To build both tensorflow and tensorflow-gpu pip packages
-export TF_BUILD_BOTH_GPU_PACKAGES=1
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/ubuntu/gpu_py37_nonpip.sh

@@ -1,60 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.7
-# Update bazel
-install_bazelisk
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=1
-export TF_CUDA_VERSION=10
-export TF_CUDNN_VERSION=7
-export TF_NEED_TENSORRT=1
-export TENSORRT_INSTALL_PATH=/usr/local/tensorrt
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which python3.7)
-export TF2_BEHAVIOR=1
-export PROJECT_NAME="tensorflow_gpu"
-export LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$TENSORRT_INSTALL_PATH/lib"
-export TF_CUDA_COMPUTE_CAPABILITIES=sm_35,sm_37,sm_52,sm_60,sm_61,compute_70
-
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-tag_filters="gpu,requires-gpu,-no_gpu,-no_oss,-oss_serial,-no_oss_py37"
-
-set +e
-bazel test --config=cuda --config=opt \
-  --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain \
-  --linkopt=-lrt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --test_lang_filters=py \
-  --build_tag_filters=${tag_filters} \
-  --test_tag_filters=${tag_filters} \
-  --test_timeout="300,450,1200,3600" --local_test_jobs=4 \
-  --test_output=errors --verbose_failures=true --keep_going \
-  --run_under=//tensorflow/tools/ci_build/gpu_build:parallel_gpu_execute \
-  -- ${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/ubuntu/gpu_py37_pip.sh

@@ -1,69 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.7
-# Update bazel
-install_bazelisk
-
-# Export required variables for running pip.sh
-export OS_TYPE="UBUNTU"
-export CONTAINER_TYPE="GPU"
-export TF_PYTHON_VERSION='python3.7'
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=1
-export TF_CUDA_VERSION=10
-export TF_CUDNN_VERSION=7
-export TF_NEED_TENSORRT=1
-export TENSORRT_INSTALL_PATH=/usr/local/tensorrt
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-export PROJECT_NAME="tensorflow_gpu"
-export LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$TENSORRT_INSTALL_PATH/lib"
-export TF_CUDA_COMPUTE_CAPABILITIES=sm_35,sm_37,sm_52,sm_60,sm_61,compute_70
-
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Export optional variables for running pip.sh
-export TF_TEST_FILTER_TAGS='gpu,requires-gpu,-no_gpu,-no_oss,-oss_serial,-no_oss_py37'
-export TF_BUILD_FLAGS="--config=opt --config=v2 --config=cuda --distinct_host_configuration=false \
---action_env=TF_CUDA_VERSION --action_env=TF_CUDNN_VERSION --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain "
-export TF_TEST_FLAGS="--test_tag_filters=${TF_TEST_FILTER_TAGS} --build_tag_filters=${TF_TEST_FILTER_TAGS} \
---distinct_host_configuration=false \
---action_env=TF_CUDA_VERSION --action_env=TF_CUDNN_VERSION --test_env=TF2_BEHAVIOR=1 \
---config=cuda --test_output=errors --local_test_jobs=4 --test_lang_filters=py \
---verbose_failures=true --keep_going --define=no_tensorflow_py_deps=true \
---run_under=//tensorflow/tools/ci_build/gpu_build:parallel_gpu_execute "
-export TF_TEST_TARGETS="${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/... "
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME=${PROJECT_NAME}
-export TF_PIP_TEST_ROOT="pip_test"
-
-# To build both tensorflow and tensorflow-gpu pip packages
-export TF_BUILD_BOTH_GPU_PACKAGES=1
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/ubuntu/gpu_py38_nonpip.sh

@@ -1,60 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.8
-# Update bazel
-update_bazel_linux
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=1
-export TF_CUDA_VERSION=10
-export TF_CUDNN_VERSION=7
-export TF_NEED_TENSORRT=1
-export TENSORRT_INSTALL_PATH=/usr/local/tensorrt
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which python3.8)
-export TF2_BEHAVIOR=1
-export PROJECT_NAME="tensorflow_gpu"
-export LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$TENSORRT_INSTALL_PATH/lib"
-export TF_CUDA_COMPUTE_CAPABILITIES=sm_35,sm_37,sm_52,sm_60,sm_61,compute_70
-
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-tag_filters="gpu,requires-gpu,-no_gpu,-no_oss,-oss_serial,-no_oss_py38"
-
-test +e
-bazel test --config=cuda --config=opt \
-  --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain \
-  --linkopt=-lrt \
-  --action_env=TF2_BEHAVIOR="${TF2_BEHAVIOR}" \
-  --test_lang_filters=py \
-  --build_tag_filters=${tag_filters} \
-  --test_tag_filters=${tag_filters} \
-  --test_timeout="300,450,1200,3600" --local_test_jobs=4 \
-  --test_output=errors --verbose_failures=true --keep_going \
-  --run_under=//tensorflow/tools/ci_build/gpu_build:parallel_gpu_execute \
-  -- ${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/...
-test_xml_summary_exit

tensorflow/tools/ci_build/rel/ubuntu/gpu_py38_pip.sh

@@ -1,69 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-set -x
-
-source tensorflow/tools/ci_build/release/common.sh
-
-install_ubuntu_16_pip_deps pip3.8
-# Update bazel
-update_bazel_linux
-
-# Export required variables for running pip.sh
-export OS_TYPE="UBUNTU"
-export CONTAINER_TYPE="GPU"
-export TF_PYTHON_VERSION='python3.8'
-
-# Run configure.
-export TF_NEED_GCP=1
-export TF_NEED_HDFS=1
-export TF_NEED_S3=1
-export TF_NEED_CUDA=1
-export TF_CUDA_VERSION=10
-export TF_CUDNN_VERSION=7
-export TF_NEED_TENSORRT=1
-export TENSORRT_INSTALL_PATH=/usr/local/tensorrt
-export CC_OPT_FLAGS='-mavx'
-export PYTHON_BIN_PATH=$(which ${TF_PYTHON_VERSION})
-export PROJECT_NAME="tensorflow_gpu"
-export LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$TENSORRT_INSTALL_PATH/lib"
-export TF_CUDA_COMPUTE_CAPABILITIES=sm_35,sm_37,sm_52,sm_60,sm_61,compute_70
-
-yes "" | "$PYTHON_BIN_PATH" configure.py
-
-# Get the default test targets for bazel.
-source tensorflow/tools/ci_build/build_scripts/PRESUBMIT_BUILD_TARGETS.sh
-
-# Export optional variables for running pip.sh
-export TF_TEST_FILTER_TAGS='gpu,requires-gpu,-no_gpu,-no_oss,-oss_serial,-no_oss_py38'
-export TF_BUILD_FLAGS="--config=opt --config=v2 --config=cuda --distinct_host_configuration=false \
---action_env=TF_CUDA_VERSION --action_env=TF_CUDNN_VERSION --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain "
-export TF_TEST_FLAGS="--test_tag_filters=${TF_TEST_FILTER_TAGS} --build_tag_filters=${TF_TEST_FILTER_TAGS} \
---distinct_host_configuration=false \
---action_env=TF_CUDA_VERSION --action_env=TF_CUDNN_VERSION --test_env=TF2_BEHAVIOR=1 \
---config=cuda --test_output=errors --local_test_jobs=4 --test_lang_filters=py \
---verbose_failures=true --keep_going --define=no_tensorflow_py_deps=true \
---run_under=//tensorflow/tools/ci_build/gpu_build:parallel_gpu_execute "
-export TF_TEST_TARGETS="${DEFAULT_BAZEL_TARGETS} -//tensorflow/lite/... "
-export TF_PIP_TESTS="test_pip_virtualenv_non_clean test_pip_virtualenv_clean"
-#export IS_NIGHTLY=0 # Not nightly; uncomment if building from tf repo.
-export TF_PROJECT_NAME=${PROJECT_NAME}
-export TF_PIP_TEST_ROOT="pip_test"
-
-# To build both tensorflow and tensorflow-gpu pip packages
-export TF_BUILD_BOTH_GPU_PACKAGES=1
-
-./tensorflow/tools/ci_build/builds/pip_new.sh

tensorflow/tools/ci_build/rel/ubuntu/sanity.sh

@@ -1,36 +0,0 @@
-#!/bin/bash
-# Copyright 2019 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
-
-# Install latest bazel
-source tensorflow/tools/ci_build/release/common.sh
-install_bazelisk
-which bazel
-
-# We need py3 lint
-sudo pip3 install pep8
-
-# TODO(gunan): figure out why we get stuck with later versions of pylint.
-# Install pylint.
-sudo python3 -m pip install setuptools --upgrade
-sudo python2 -m pip install pylint==1.6.4
-sudo python3 -m pip install pylint==1.6.4
-
-# TODO(yifeif): print pylint version for debug. remove later.
-python3 -m pylint --version
-
-# Run tensorflow sanity checks.
-tensorflow/tools/ci_build/ci_sanity.sh

tensorflow/tools/ci_build/rel/windows/cpu_libtensorflow.bat

@@ -1,20 +0,0 @@
-:: Copyright 2019 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.
-:: =============================================================================
-
-CALL tensorflow\tools\ci_build\release\common_win.bat
-
-call tensorflow\tools\ci_build\windows\cpu\bazel\run_libtensorflow.bat || exit /b 1
-
-copy lib_package %TF_ARTIFACTS_DIR%\lib_package