code: def convert_tf_name(tf_name):
      """Convert certain patterns in TF layer names to Torch patterns"""
      tf_name_tmp = tf_name
      tf_name_tmp = tf_name_tmp.replace(":0", "")
      tf_name_tmp = tf_name_tmp.replace(
          "/forward_lstm/lstm_cell_1/recurrent_kernel", "/weight_hh_l0"
      )
      tf_name_tmp = tf_name_tmp.replace(
          "/forward_lstm/lstm_cell_2/kernel", "/weight_ih_l1"
      )
      tf_name_tmp = tf_name_tmp.replace(
          "/recurrent_kernel", "/weight_hh"
      )
      tf_name_tmp = tf_name_tmp.replace("/kernel", "/weight")
      tf_name_tmp = tf_name_tmp.replace("/gamma", "/weight")
      tf_name_tmp = tf_name_tmp.replace("/beta", "/bias")
      tf_name_tmp = tf_name_tmp.replace("/", ".")
      return tf_name_tmp
  
imports: import numpy
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: convert_tf_name(tf_name) and returns: tf_name_tmp