table = tf.lookup.StaticVocabularyTable(table_initializer, num_oov_buckets=10)
  vocab_file_tensor = tf.convert_to_tensor(
      vocabulary_file, tf.string, name='asset_filepath')
  tf.add_to_collection(tf.GraphKeys.ASSET_FILEPATHS, vocab_file_tensor)

  x = tf.placeholder(tf.string, shape=(), name='input')
  r = table.lookup(x)

  tensor_info_x = tf.compat.v1.saved_model.utils.build_tensor_info(x)

          signature_def_key,
          tags,
          inputs=inputs,
          outputs=outputs,
          init_op=lookup_ops.tables_initializer(),
          assets_collection=ops.get_collection(ops.GraphKeys.ASSET_FILEPATHS),
      )

    return inputs, outputs

  def _create_and_save_file_init_hash_table_model_tf1(
      self,
      output_path: str,
      tags: Collection[str],
      signature_def_key: str,

    restore_op_name: "save/restore_all"
    max_to_keep: 5
    sharded: true
    keep_checkpoint_every_n_hours: 10000.0
    version: V2
  }
  collection_def {
    key: "asset_filepaths"
    value {
      node_list {
        value: "Const:0"
      }
    }
  }
  collection_def {
    key: "legacy_init_op"
    value {
      node_list {

    const string asset_directory =
        io::JoinPath(export_dir, kSavedModelAssetsDirectory);
    const string asset_filename = "foo.txt";
    const string asset_filepath = io::JoinPath(asset_directory, asset_filename);
    TF_EXPECT_OK(Env::Default()->FileExists(asset_filepath));

    std::vector<Tensor> path_outputs;
    TF_ASSERT_OK(
        bundle.GetSession()->Run({}, {"filename_tensor:0"}, {}, &path_outputs));

    const string asset_directory =
        io::JoinPath(export_dir, kSavedModelAssetsDirectory);
    const string asset_filename = "foo.txt";
    const string asset_filepath = io::JoinPath(asset_directory, asset_filename);
    TF_EXPECT_OK(Env::Default()->FileExists(asset_filepath));

    std::vector<Tensor> path_outputs;
    TF_ASSERT_OK(
        bundle.session->Run({}, {"filename_tensor:0"}, {}, &path_outputs));