GTEST_SKIP() << "NewWritableFile() not supported: " << status;

  const std::string test_data("asdf");
  status = file->Append(test_data);
  if (!status.ok()) GTEST_SKIP() << "Append() not supported: " << status;
  status = file->Flush();
  if (!status.ok()) GTEST_SKIP() << "Flush() not supported: " << status;
  status = file->Close();
  if (!status.ok()) GTEST_SKIP() << "Close() not supported: " << status;

/// that plugins provide (some are mandatory, some are optional, with or without
/// a default implementation).
///
/// Each plugin implements the operations that are supported and TensorFlow will
/// properly handle the cases when an operation is not supported (i.e., return
/// the corresponding `Status` value).
///
/// REQUIRED OPERATIONS: All required operations are marked as such, including

  if int(ndk_version) not in _SUPPORTED_ANDROID_NDK_VERSIONS:
    print('WARNING: The NDK version in %s is %s, which is not '
          'supported by Bazel (officially supported versions: %s). Please use '
          'another version. Compiling Android targets may result in confusing '
          'errors.\n' %
          (android_ndk_home_path, ndk_version, _SUPPORTED_ANDROID_NDK_VERSIONS))

#     v2: Build TF v2
#
# Feature and Third party library support options:
#     xla:          Build TF with XLA
#     tpu:          Build TF with TPU support
#     cuda:         Build with CUDA support.
#     cuda_clang    Build with CUDA Clang support.
#     rocm:         Build with AMD GPU support (rocm)
#     mkl:          Enable full mkl support.
#     tensorrt:     Enable Tensorrt support.
#     noaws:        Disable AWS S3 storage support

config_setting(
    name = "stackdriver_support",
    define_values = {"stackdriver_support": "true"},
    visibility = ["//visibility:public"],
)

config_setting(
    name = "with_xla_support",
    define_values = {"with_xla_support": "true"},
    visibility = ["//visibility:public"],
)

# By default, XLA GPU is compiled into tensorflow when building with
# --config=cuda even when `with_xla_support` is false. The config setting

// See TF_AddGradientsWithPrefix, which provides a means to specify a custom
// name prefix for operations added to a graph to compute the gradients.
//
// WARNING: This function does not yet support all the gradients that python
// supports. See
// https://www.tensorflow.org/code/tensorflow/cc/gradients/README.md
// for instructions on how to add C++ more gradients.
TF_CAPI_EXPORT void TF_AddGradients(TF_Graph* g, TF_Output* y, int ny,