for entry in vocabulary:
      f.write(entry + '\n')
  return vocabulary_file


def test():

  vocabulary_file = write_vocabulary_file(['cat', 'is', 'on', 'the', 'mat'])
  table_initializer = tf.lookup.TextFileInitializer(
      vocabulary_file, tf.string, tf.lookup.TextFileIndex.WHOLE_LINE, tf.int64,
      tf.lookup.TextFileIndex.LINE_NUMBER)
  # Incur another bound_input on the asset, but with a different sym_name, i.e.,

  def __init__(self):
    self.asset = asset.Asset(
        test.test_src_dir_path(
            "cc/saved_model/testdata/static_hashtable_asset.txt"))
    self.table = lookup_ops.StaticHashTable(
        lookup_ops.TextFileInitializer(self.asset, dtypes.string,
                                       lookup_ops.TextFileIndex.WHOLE_LINE,
                                       dtypes.int64,

    // Now, this pattern matching only supports the following case, which is
    // commonly used among inference use cases:
    //
    // tf.lookup.TextFileInitializer(
    //   "test.txt", tf.string, tf.lookup.TextFileIndex.WHOLE_LINE,
    //   tf.int64, tf.lookup.TextFileIndex.LINE_NUMBER, delimiter=" ")
    //

    # The resulting table looks like:
    # "static" -> 0
    # "range" -> 1
    # "quantization" -> 2
    # default -> -1
    init = lookup_ops.TextFileInitializer(
        filename=asset_file,
        key_dtype=dtypes.string,
        key_index=lookup_ops.TextFileIndex.WHOLE_LINE,
        value_dtype=dtypes.int64,
        value_index=lookup_ops.TextFileIndex.LINE_NUMBER,