if (input_arg.number_attr().empty()) {
    status->status = tensorflow::errors::NotFound(
        op_name, " does not have number_attr() defined.");
    return nullptr;
  }

  // The returned string is owned by OpRegistry, so liveness is not a concern.
  return input_arg.number_attr().c_str();
}

int TF_OpIsStateful(const char* op_type, TF_Status* status) {

// into python now.
template <typename Gradient, typename BackwardFunction, typename TapeTensor>
class VSpace {
 public:
  virtual ~VSpace() {}

  // Returns the number of elements in the gradient tensor.
  virtual int64_t NumElements(Gradient* tensor) const = 0;

  // Consumes references to the tensors in the gradient_tensors list and returns
  // a tensor with the result.

  elif var:
    write_to_bazelrc('build --config=%s' % bazel_config_name)
  environ_cp[var_name] = str(var)


def convert_version_to_int(version):
  """Convert a version number to a integer that can be used to compare.

  Version strings of the form X.YZ and X.Y.Z-xxxxx are supported. The
  'xxxxx' part, for instance 'homebrew' on OS/X, is ignored.

  Args:

// modification of the graph can increase the number of inputs of
// an operation.
TF_CAPI_EXPORT extern void TF_OperationAllInputs(TF_Operation* oper,
                                                 TF_Output* inputs,
                                                 int max_inputs);

// Get the number of current consumers of a specific output of an
// operation.  Note that this number can change when new operations

      # WindowOpsTest.test_tflite_convert0 (<function hann_window at
      #     0x7fc61728dd40>, 10, False, tf.float32)
      # Where 0x... is a thread ID (or something) that is not important for
      # debugging, but breaks this "number of failures" counter because it's
      # different for repetitions of the same test. We use re.sub(r"0x\w+")
      # to remove it.
      key = re.sub(r"0x\w+", "", p.getparent().get("name", "")) + p.text
      if key in seen:

  TAG="latest-multi-python"
else
  # If it is a change, grab a good tag for iterative builds
  if [[ -z "${KOKORO_GITHUB_PULL_REQUEST_NUMBER}" ]]; then
    TAG=$(head -n 1 "$KOKORO_PIPER_DIR/presubmit_request.txt" | cut -d" " -f2)
  else
    TAG="pr-${KOKORO_GITHUB_PULL_REQUEST_NUMBER}"
  fi
fi

# Build for both JAX and TF usage.  We do these in one place because they share
# almost all of the same cache layers

# This script uploads all staged artifacts from all previous builds in the same
# job chain to GCS and PyPI.
source "${BASH_SOURCE%/*}/utilities/setup.sh"

# Update the version numbers for Nightly only, then fetch the version numbers
# for choosing the final directory name. This adds "-devYYYYMMDD" to the end of
# the version string (.devYYYYMMDD for Python; see pypi.org/project/tf-nightly)

TFCI_ARTIFACT_LATEST_GCS_URI="gs://tensorflow/nightly/latest/"
TFCI_ARTIFACT_STAGING_GCS_ENABLE=1
TFCI_ARTIFACT_STAGING_GCS_URI="gs://tensorflow-ci-artifact-staging/staging/nightly/$(git rev-parse HEAD)/"

# 2. The internal version numbers get changed
TFCI_NIGHTLY_UPDATE_VERSION_ENABLE=1

# 3. Push results to public build cache (unique cache for MacOS)
if [[ $(uname -s) == "Darwin" ]]; then

      theta_inputs[input_index];  // parameter we are grad checking

  // Convert from AbstractTensor to TF_Tensor.
  TF_Tensor* theta_tensor;
  TF_RETURN_IF_ERROR(GetValue(theta, &theta_tensor));

  // Get number of elements and fill data.
  int num_elems = TF_TensorElementCount(theta_tensor);
  vector<float> theta_data(num_elems);
  memcpy(theta_data.data(), TF_TensorData(theta_tensor),
         TF_TensorByteSize(theta_tensor));

        first_bad_status.reset(TF_NewStatus());
        TF_SetStatus(first_bad_status.get(), TF_INTERNAL,
                     "Parallel ops produced different numbers of tensors.");
      }
    }
  }
  if (first_bad_status != nullptr) {
    TF_SetStatus(status, TF_GetCode(first_bad_status.get()),
                 TF_Message(first_bad_status.get()));
    return result;