code: def efficientnet_b0(num_classes=1000):
      # input image size 224x224
      return EfficientNet(
          width_coefficient=1.0,
          depth_coefficient=1.0,
          dropout_rate=0.2,
          num_classes=num_classes,
      )
  
imports: import math
  import copy
  from functools import partial
  from collections import OrderedDict
  from typing import Optional, Callable
  import torch
  import torch.nn
  from torch import Tensor
  from torch.nn import functional
label_desc: Use image node_id 3 for calling a global function with example usage: efficientnet_b0(num_classes) and returns: EfficientNet