initializer=tf.random_normal_initializer(),
      trainable=True)
  z = tf.matmul(x, y)
  tensor_info_z = tf.compat.v1.saved_model.utils.build_tensor_info(z)

  return {
      'key': (tf.compat.v1.saved_model.signature_def_utils.build_signature_def(
          inputs=None,
          outputs={'z': tensor_info_z},
          method_name='some_function'))
  }, None, None


if __name__ == '__main__':

  @test_util.deprecated_graph_mode_only
  def test_create_feed_dict_from_input_data(self):
    signature_def = meta_graph_pb2.SignatureDef(
        inputs={'input_tensor': meta_graph_pb2.TensorInfo(name='input:0')}
    )
    rng = np.random.default_rng(seed=14)

    input_tensor_value = rng.random(size=(2, 2))
    sample = {'input_tensor': input_tensor_value}

  SavedModelBundle saved_model_bundle;
  SignatureDef signature_def;

  TensorInfo& in = (*signature_def.mutable_inputs())["input_arg"];
  in.mutable_composite_tensor()->add_components()->set_name("input1:0");
  in.mutable_composite_tensor()->add_components()->set_name("input2:0");

  TensorInfo& out = (*signature_def.mutable_outputs())["output_arg"];

    explicit Data(Int64 i64) : i64(i64) {}
    explicit Data(const char* s) : s(String(s)) {}
    explicit Data(Func fn) : func(fn) {}
    explicit Data(TaggedValueTensor tensor_in) {
      new (&tensor) TaggedValueTensor(std::move(tensor_in));
    }
    explicit Data(tensorflow::PartialTensorShape shape,
                  tensorflow::DataType dtype)
        : tensor_spec({shape, dtype}) {}
    ~Data() {}