namespace gradients {
namespace internal {

// Helper functions which delegate to `AbstractOperation`, update
// the state of the ForwardOperation and call the tape as appropriate.
// These APIs are mainly to facilitate testing and are subject to change.

// Records the op name in the `ForwardOperation`.
Status Reset(AbstractOperation*, const char* op, const char* raw_device_name,
             ForwardOperation*);

  EXPECT_EQ(assign, 1);
  int id = TF_OpIsStateful("Identity", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  EXPECT_EQ(id, 0);
}

class ShapeInferenceTest : public ::testing::Test {
 protected:
  ShapeInferenceTest()
      : status_(TF_NewStatus()), tfe_context_options_(TFE_NewContextOptions()) {
    tfe_context_ = TFE_NewContext(tfe_context_options_, status_);

  tensorflow::ClusterDef* cluster_def = server_def.mutable_cluster();
  tensorflow::JobDef* job_def = cluster_def->add_job();
  job_def->set_name(job_name);
  for (int i = 0; i < num_tasks; i++) {
    int port = tensorflow::testing::PickUnusedPortOrDie();
    job_def->mutable_tasks()->insert(
        {i, tensorflow::strings::StrCat("localhost:", port)});
    LOG(INFO) << "Picked test port: " << port << " for job: " << job_name

Compiling models via the recommended entry points described in
[XLA](https://www.tensorflow.org/xla) and
[JAX](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html)
documentation should be safe, while some of the testing and debugging tools that
come with the compiler are not designed to be used with untrusted data and
should be used with caution when working with untrusted models.

### Saved graphs and checkpoints

  typedef std::pair<string, string> Base;

  // Inherit the set of constructors
  using Base::pair;

  string ToString() const { return strings::StrCat(first, "->", second); }
};

class CApiFunctionTest : public ::testing::Test {
 protected:
  CApiFunctionTest()
      : s_(TF_NewStatus()),
        func_graph_(TF_NewGraph()),
        host_graph_(TF_NewGraph()),
        func_(nullptr) {}

  void SetUp() override {}

#     visibility = ["//visibility:public"],
# )
#
# filegroup(
#     name = "copybara_config",
#     srcs = ["copy.bara.sky"],
#     data = [
#         ":copybara_library",
#         "//learning/brain/testing/copybara:all_bara_sky",
#         "//third_party/tsl:copybara_library",
#         "//third_party/xla:copybara_library",
#     ],
#     visibility = ["//visibility:public"],
# )
#
# copybara_config_test(

If you experience any snags when using TF 2.0, please let us know at the
[TF 2.0 Testing User Group](https://groups.google.com/a/tensorflow.org/forum/?utm_medium=email&utm_source=footer#!forum/testing).
We have a support mailing list as well as weekly testing meetings, and would
love to hear your migration feedback and questions.

## Bug Fixes and Other Changes

*   `tf.contrib`:

  result_tensor = nullptr;
}

INSTANTIATE_TEST_SUITE_P(
    CustomGradientTest, CustomGradientTest,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),
                       /*executing_eagerly*/ ::testing::Values(true, false)));

}  // namespace
}  // namespace internal
}  // namespace gradients

    UnifiedCAPI, CppGradients,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),
                       /*use_function*/ ::testing::Values(true, false)));
#else
INSTANTIATE_TEST_SUITE_P(
    UnifiedCAPI, CppGradients,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),

common:rbe_linux_cpu_old --remote_instance_name=projects/tensorflow-testing/instances/default_instance

build:rbe_linux_cuda --config=cuda_clang_official
build:rbe_linux_cuda --config=rbe_linux_cpu
# For Remote build execution -- GPU configuration
build:rbe_linux_cuda --repo_env=REMOTE_GPU_TESTING=1
build:rbe_linux_cuda --repo_env=TF_CUDA_CONFIG_REPO="@sigbuild-r2.17-clang_config_cuda"