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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def vocab_token_counts(text_filepattern, max_lines):
 """Read a vocab file and return a dictionary of token counts. Reads a two-column CSV file of tokens and their frequency in a dataset. The tokens are presumed to be generated by encode() or the equivalent. Args: text_filepattern: A pattern matching one or more files. max_lines: An integer; maximum total lines to read. Returns: a dictionary mapping token to count. """

  ret = {}
  for i, line in enumerate(
      _read_filepattern(text_filepattern, max_lines=max_lines)):
    if "," not in line:
      tf.logging.warning("Malformed vocab line #%d '%s'", i, line)
      continue

    token, count = line.rsplit(",", 1)
    ret[_native_to_unicode(token)] = int(count)

  return ret