char buffer[BUFFER_SIZE];
  std::strncpy(buffer, "VALID", BUFFER_SIZE);
  TFE_OpSetAttrString(op, "padding", buffer, std::strlen(buffer));
  // Overwriting value in "buffer", should be fine since TFE_Op
  // shouldn't be holding on to it.
  std::strncpy(buffer, "NHWC", BUFFER_SIZE);
  TFE_OpSetAttrString(op, "data_format", buffer, std::strlen(buffer));

  TFE_OpSetAttrType(op, "T", TF_FLOAT);

}

void NoOpDeallocator(void* data, size_t, void*) {}

TEST(CAPI, MalformedTensor) {
  // See https://github.com/tensorflow/tensorflow/issues/7394
  // num_dims = 0 implies a scalar, so should be backed by at least 4 bytes of
  // data.
  TF_Tensor* t =
      TF_NewTensor(TF_FLOAT, nullptr, 0, nullptr, 0, &NoOpDeallocator, nullptr);
  ASSERT_TRUE(t == nullptr);
}

TEST(CAPI, AllocateTensor) {

      // We have to join path for non-local filesystem manually to make sure
      // that this test will run on Windows since `tensorflow::io::JoinPath`
      // behaves differently on Windows. `tmp_dir` should be something like
      // `path/to/tmp/dir/`. After joining path, we will have
      // /path/to/tmp/dir/tf_fs_rng_name/`
      root_dir_ = tensorflow::strings::StrCat(
          "/", tmp_dir_,

///
/// Since filesystem plugins are outside of TensorFlow's code tree, they are not
/// tied with TensorFlow releases and should have their own versioning metadata
/// in addition with the data discussed in this section. Each plugin author can
/// use a custom scheme, but it should only relate to changes in plugin code.
/// This section only touches metadata related to the versioning of this

# Config setting that is satisfied when CUDA device code should be compiled
# with clang. It does not imply that CUDA support has been enabled.
alias(
    name = "is_cuda_compiler_clang",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_compiler_clang",
        "@local_config_cuda//cuda:TRUE",
    ),
)

# Config setting that is satisfied when CUDA device code should be compiled

    if environ_cp.get('TF_CUDA_CLANG') == '1':
      # Set up which clang we should use as the cuda / host compiler.
      clang_cuda_compiler_path = set_clang_cuda_compiler_path(environ_cp)
      clang_version = retrieve_clang_version(clang_cuda_compiler_path)
      disable_clang_offsetof_extension(clang_version)
    else:
      # Set up which gcc nvcc should use as the host compiler
      # No need to set this on Windows

build --incompatible_enforce_config_setting_visibility
# TODO: also enable this flag after fixing the visibility violations
# build --incompatible_config_setting_private_default_visibility

# Default options should come above this line.

# Android configs. Bazel needs to have --cpu and --fat_apk_cpu both set to the
# target CPU to build transient dependencies correctly. See

// Sets `output` based on `proto`, which should be a serialized
// CppShapeInferenceResult::HandleData proto. `output` should be a resource
// or variant tensor.
// NOTE(skyewm): `proto` is passed a void*/size_t pair instead of a std::string
// because I couldn't get SWIG to work otherwise.
TF_CAPI_EXPORT extern void TF_SetHandleShapeAndType(TF_Graph* graph,