code: def efficientnet_b7(
      num_classes=1000, include_top=True, input_shape=(600, 600, 3)
  ):
      # https://storage.googleapis.com/keras-applications/efficientnetb7.h5
      return efficient_net(
          width_coefficient=2.0,
          depth_coefficient=3.1,
          input_shape=input_shape,
          dropout_rate=0.5,
          model_name="efficientnetb7",
          include_top=include_top,
          num_classes=num_classes,
      )
  
file_path: deep-learning-for-image-processing/tensorflow_classification/Test9_efficientNet/model.py
imports: import math
  from typing import Union
  from tensorflow.keras import layers, Model
label_desc: Use image node_id 11 for calling a global function with example usage: efficientnet_b7(num_classes, include_top, input_shape) and returns: efficient_net