EXPECT_TF_META("v", list.size(), TF_ATTR_STRING, list_total_size);
  std::unique_ptr<void*[]> values(new void*[list.size()]);
  std::unique_ptr<size_t[]> lens(new size_t[list.size()]);
  std::unique_ptr<char[]> storage(new char[list_total_size]);
  TF_OperationGetAttrStringList(oper, "v", values.get(), lens.get(),
                                list.size(), storage.get(), list_total_size,
                                s_);

_site_packages_dirs += [p for p in _sys.path if "site-packages" in p]
if "getsitepackages" in dir(_site):
  _site_packages_dirs += _site.getsitepackages()

if "sysconfig" in dir(_distutils):
  _site_packages_dirs += [_distutils.sysconfig.get_python_lib()]

_site_packages_dirs = list(set(_site_packages_dirs))

# Find the location of this exact file.
_current_file_location = _inspect.getfile(_inspect.currentframe())

        *   (since v2.7) `tf.math.segment_mean`
        *   (since v2.7) `tf.math.segment_prod`
        *   (since v2.7) `tf.math.segment_sum`
        *   (since v2.7) `tf.math.unsorted_segment_mean`
        *   (since v2.7) `tf.math.unsorted_segment_prod`
        *   (since v2.7) `tf.math.unsorted_segment_sum`
        *   (since v2.7) `tf.math.unsorted_segment_sqrt`

    std::vector<TF_Output> tf_outputs(inputs.size());
    for (int i = 0; i < inputs.size(); i++) {
      GraphTensor* t = dyn_cast<GraphTensor>(inputs[i]);
      if (!t) {
        return tensorflow::errors::InvalidArgument(
            "Unable to cast input to GraphTensor");
      }
      tf_outputs[i] = t->output_;
    }
    TF_AddInputList(op_.get(), tf_outputs.data(), tf_outputs.size());
    return absl::OkStatus();
  }

  void* data = tensorflow::port::Malloc(value.length());
  value.copy(static_cast<char*>(data), value.length(), 0);
  buf->data = data;
  buf->length = value.length();
  buf->data_deallocator = [](void* data, size_t length) {
    tensorflow::port::Free(data);
  };
}

TFE_MonitoringStringGauge0* TFE_MonitoringNewStringGauge0(
    const char* name, TF_Status* status, const char* description) {

# filesystem search takes place, since libtensorflow_framework.so has already
# been loaded by pywrap_tensorflow) and registers its ops and kernels via
# REGISTER_OP and REGISTER_KERNEL_BUILDER (which use symbols from
# libtensorflow_framework.so), and pywrap_tensorflow can then use these
# ops. Since other languages use the same libtensorflow_framework.so, op
# libraries are language agnostic.

        'details.')
  config_info_line('mkl', 'Build with MKL support.')
  config_info_line(
      'mkl_aarch64',
      'Build with oneDNN and Compute Library for the Arm Architecture (ACL).')
  config_info_line('monolithic', 'Config for mostly static monolithic build.')
  config_info_line('numa', 'Build with NUMA support.')
  config_info_line(
      'dynamic_kernels',

# Build everything statically for Android since all static libs are later
# bundled together into a single .so for deployment.
build:android --dynamic_mode=off

# Sets the default Apple platform to macOS.
build:macos --apple_platform_type=macos

# gRPC on MacOS requires this #define
build:macos --copt=-DGRPC_BAZEL_BUILD

# Avoid hitting command line argument limit
build:macos --features=archive_param_file

          # the end of the line.
          # See https://cloud.google.com/architecture/using-container-images#exploring_image_manifests_digests_and_tags
          echo -n "Trying to map name $1 to tag $2... "
          digest=$(curl -s --head "https://gcr.io/v2/tensorflow-sigs/build/manifests/$2" | egrep -o "sha256:[[:alnum:]]*")
          # Find the line matching the regex "sigbuild-r2.9" (with quotes) and