code: def _f_lcs(llcs, m, n):
      """Computes the LCS-based F-measure score.
  
      Source: https://www.microsoft.com/en-us/research/publication/
      rouge-a-package-for-automatic-evaluation-of-summaries/
  
      Args:
        llcs: Length of LCS
        m: number of words in reference summary
        n: number of words in candidate summary
  
      Returns:
        Float. LCS-based F-measure score
      """
      r_lcs = llcs / m
      p_lcs = llcs / n
      beta = p_lcs / (r_lcs + 1e-12)
      num = (1 + (beta**2)) * r_lcs * p_lcs
      denom = r_lcs + ((beta**2) * p_lcs)
      f_lcs = num / (denom + 1e-12)
      return f_lcs
  
file_path: tensor2tensor/tensor2tensor/utils/rouge.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling a global function with example usage: _f_lcs(llcs, m, n) and returns: f_lcs