code: def set_parameter(tower_name, parameter_name, value, dtype=tf.int32):
      """Saves a tower's parameter in the checkpoint as a tensor.
  
      Args:
        tower_name: string - the name of the tower.
        parameter_name: string - the name of the parameter.
        value: the value you wish to store.
        dtype: the type of the value. E.g., tf.int32.
      """
      tf.compat.v1.get_variable(
          name="params/{}/{}".format(tower_name, parameter_name),
          shape=[],
          trainable=False,
          initializer=tf.compat.v1.constant_initializer(value),
          dtype=dtype,
      )
  
imports: import collections
  import os
  import string
  import time
  from absl import flags
  from absl import logging
  from model_search import block
  from model_search import block_builder
  from model_search import hparam
  from model_search import utils
  from model_search.proto import hparam_pb2
  from model_search.proto import phoenix_spec_pb2
  from model_search.proto import transfer_learning_spec_pb2
  import numpy
  import tensorflow.compat.v2
  import tf_slim
  from google.protobuf import text_format
label_desc: Use image node_id 11 for calling a global function with example usage: set_parameter(tower_name, parameter_name, value, dtype) without return types