code: def create_sentence_with_root(attributes, vocabs):
      """Create a sentence containing a root.
  
      Args:
        attributes: attributes extracted from token.
        vocabs: dictionary of vocabs.
  
      Returns:
        A list representing a sentence containing the root only,
        e.g., [[2, 1, 0]] for root word, unknown xpos, and head 0.
      """
      # Create the token properties of an artificial root node.
      token_properties = [
          ROOT for _ in range(12)
      ]  # CoNLL 09 has 12 columns.
      token_properties[CoNLLAttributes.ID.value] = "0"
      token_properties[CoNLLAttributes.HEAD.value] = "0"
      token = create_token(token_properties, attributes, vocabs)
      if len(token) == 1:
          token = token[0]
      return [token]
  
file_path: flax/examples/nlp_seq/input_pipeline.py
imports: import codecs
  import collections
  import enum
  import tensorflow
label_desc: Use image node_id 3 for calling a global function with example usage: create_sentence_with_root(attributes, vocabs) and returns: list