code: def main(_):
      # Generate schema of input data.
      raw_metadata = dataset_metadata.DatasetMetadata(
          schema_utils.schema_from_feature_spec(
              {
                  "text": tf.FixedLenFeature([], tf.string),
                  "language_code": tf.FixedLenFeature([], tf.string),
              }
          )
      )
  
      pipeline = word_count(
          FLAGS.input_path, FLAGS.output_path, raw_metadata
      )
      pipeline.run().wait_until_finish()
  
file_path: text/tensorflow_text/tools/wordpiece_vocab/generate_word_counts.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tempfile
  from absl import app
  from absl import flags
  import apache_beam
  import tensorflow.compat.v1
  import tensorflow_transform
  import tensorflow_transform.beam
  from tensorflow_transform.tf_metadata import dataset_metadata
  from tensorflow_transform.tf_metadata import schema_utils
  from tensorflow_text.tools.wordpiece_vocab import utils
label_desc: Use image node_id 2 for calling a global function with example usage: main(_) without return types