// .backing_device of shape is CPU since the tensor is backed by CPU
    backing_device_name =
        TFE_TensorHandleBackingDeviceName(retvals[0], status.get());
    ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
    ASSERT_TRUE(absl::StrContains(backing_device_name, "CPU:0"))
        << backing_device_name;

    TFE_DeleteOp(shape_op);

      stdout=subprocess.PIPE,
      env=maybe_encode_env(environ_cp))

  if proc.wait():
    # Errors from find_cuda_config.py were sent to stderr.
    print('Asking for detailed CUDA configuration...\n')
    return False

  config = dict(
      tuple(line.decode('ascii').rstrip().split(': ')) for line in proc.stdout)

  print('Found CUDA %s in:' % config['cuda_version'])

                                  const TF_ImportGraphDefOptions* options,
                                  TF_Status* status);

// Has the same behavior as TF_GraphImportGraphDefWithResults, but instead of
// taking in a serialized tensorflow::GraphDef, it takes in a *pointer* to the
// C++ *in memory representation* of the GraphDef, stored in `graph_def->data`
TF_CAPI_EXPORT extern TF_ImportGraphDefResults*