code: def get_model_params(model_name, override_params):
      """Get the block args and global params for a given model."""
      if model_name.startswith("efficientnet"):
          (
              width_coefficient,
              depth_coefficient,
              _,
              dropout_rate,
          ) = efficientnet_params(model_name)
          global_params = efficientnet(
              width_coefficient, depth_coefficient, dropout_rate
          )
      else:
          raise NotImplementedError(
              "model name is not pre-defined: %s" % model_name
          )
  
      if override_params:
          # ValueError will be raised here if override_params has fields not included
          # in global_params.
          global_params = global_params._replace(**override_params)
  
      decoder = BlockDecoder()
      blocks_args = decoder.decode(global_params.blocks_args)
  
      logging.info("global_params= %s", global_params)
      return blocks_args, global_params
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import os
  import re
  from absl import logging
  import numpy
  import six
  import tensorflow.compat.v1
  import efficientnet_model
  import utils
label_desc: Use image node_id 4 for calling a global function with example usage: get_model_params(model_name, override_params) and returns: blocks_args,  global_params