code: def find_trainable(name, scope=None):
      """
      Find a single trainable variable in a function by name when the function has multiple parameters.
  
      Args:
          func: The function to search
          name (`str`): The name of the parameter
          scope (`str`): The scope of the search
  
      Returns:
          The trainable variable that is found
      """
      found = [
          tp
          for tp in tf.get_collection(
              tf.GraphKeys.TRAINABLE_VARIABLES, scope
          )
          if name in tp.name
      ]
      if len(found) == 0:
          raise Exception("not found")
      elif len(found) > 1:
          raise Exception("more than 1 found")
      return found[0]
  
imports: import tensorflow
  import numpy
  from cntk.contrib import crosstalk
label_desc: Use image node_id 1 for calling a global function with example usage: find_trainable(name, scope) and returns: found