const char* device_name =
      tensorflow::unwrap(h)->BackingDeviceName(&status->status);
  DeviceNameUtils::ParsedName parsed_name;
  tensorflow::DeviceNameUtils::ParseFullName(device_name, &parsed_name);
  std::string device_type = parsed_name.type;
  int device_id = 0;
  if (parsed_name.has_id) {
    device_id = parsed_name.id;
  }

  ctx.device_id = device_id;
  if (device_type == "CPU") {

  parser.add_argument('-v', '--verbose',
                      action='store_true', dest='verbose', default=False,
                      help='Prints out lines helpful for debugging.')
  parsed_args = parser.parse_args()
  if not parsed_args.print and not parsed_args.xml_out_path:
    raise TypeError('`--print` or `--xml-out-path` must be specified')

  return parsed_args


def parse_log(file_path: str,

    }
  }
  std::vector<std::string> local_names;
  local_names.reserve(underlying_devices_.size());
  for (const DeviceNameUtils::ParsedName& parsed_component :
       parsed_components) {
    local_names.push_back(
        absl::StrCat(parsed_component.type, ":", parsed_component.id));
  }
  return local_names;
}

std::unique_ptr<ParallelTensor> ParallelTensor::FromTensorHandles(

        git diff --diff-filter ACMRT --name-only origin/master > $BATS_FILE_TMPDIR/changed_files
    fi
}

# Note: this is excluded on the full code base, since any submitted code must
# have passed Google's internal style guidelines.
@test "Check buildifier formatting on BUILD files" {
    echo "buildifier formatting is recommended. Here are the suggested fixes:"
    echo "============================="

  // make sure there is no information loss.
  if (proto_len > std::numeric_limits<int>::max()) {
    status->status = InvalidArgument(
        "proto_len (", proto_len,
        " bytes) is too large to be parsed by the protocol buffer library");
    return;
  }
  TensorShapeProto shape;
  if (shape.ParseFromArray(proto, static_cast<int>(proto_len))) {
    desc->node_builder.Attr(attr_name, shape);

TFCI_ARTIFACT_FINAL_PYPI_ENABLE=1
TFCI_ARTIFACT_LATEST_GCS_URI="gs://tensorflow/versions/latest/"
TFCI_ARTIFACT_STAGING_GCS_ENABLE=1
TFCI_ARTIFACT_STAGING_GCS_URI="gs://tensorflow-ci-artifact-staging/staging/versions/${_LOUHI_EXECUTION_ID:-$(git rev-parse HEAD)}/"

python_register_toolchains(
    name = "python",
    ignore_root_user_error = True,
    python_version = TF_PYTHON_VERSION,
)

load("@python//:defs.bzl", "interpreter")
load("@rules_python//python:pip.bzl", "package_annotation", "pip_parse")

NUMPY_ANNOTATIONS = {
    "numpy": package_annotation(
        additive_build_content = """\
filegroup(
    name = "includes",
    srcs = glob(["site-packages/numpy/core/include/**/*.h"]),
)
cc_library(

  // here. This is the default behavior if `pack` is null when passed to
  // TFE_RegisterCustomDevice.
  TFE_TensorHandle* (*pack)(TFE_Context* context, TFE_TensorHandle** handles,
                            int num_handles, TF_Status* s,
                            void* device_info) = nullptr;

  // Pins the op to `device` based on inputs to `op`. Returns true

  // a tensor with the result.
  AbstractTensorHandle* AggregateGradients(
      gtl::ArraySlice<AbstractTensorHandle*> gradient_tensors) const override;

  // Calls the passed-in backward function.
  // op_type is the op's name provided in RecordOperation.
  Status CallBackwardFunction(
      const string& op_type, GradientFunction* gradient_function,

    [tensorflow/core](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core)
    and
    [tensorflow/python](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/python).
    TensorFlow has passed version 1.0 and hence cannot make
    non-backward-compatible API changes without a major release. Reviewers of
    your pull request will comment on any API compatibility issues