code: def efficientnet_params(model_name):
      """Get efficientnet params based on model name."""
      params_dict = {
          # (width_coefficient, depth_coefficient, resolution, dropout_rate)
          "efficientnet-b0": (1.0, 1.0, 224, 0.2),
          "efficientnet-b1": (1.0, 1.1, 240, 0.2),
          "efficientnet-b2": (1.1, 1.2, 260, 0.3),
          "efficientnet-b3": (1.2, 1.4, 300, 0.3),
          "efficientnet-b4": (1.4, 1.8, 380, 0.4),
          "efficientnet-b5": (1.6, 2.2, 456, 0.4),
          "efficientnet-b6": (1.8, 2.6, 528, 0.5),
          "efficientnet-b7": (2.0, 3.1, 600, 0.5),
          "efficientnet-b8": (2.2, 3.6, 672, 0.5),
          "efficientnet-l2": (4.3, 5.3, 800, 0.5),
      }
      return params_dict[model_name]
  
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 1 for calling a global function with example usage: efficientnet_params(model_name) and returns: params_dict