code: def efficientnet_init_weights(
      model: nn.Module, init_fn=None, zero_gamma=False
  ):
      last_bn = []
      if zero_gamma:
          prev_n = ""
          for n, m in model.named_modules():
              if isinstance(m, nn.BatchNorm2d):
                  if "".join(prev_n.split(".")[:-1]) != "".join(
                      n.split(".")[:-1]
                  ):
                      last_bn.append(prev_n)
                  prev_n = n
          last_bn.append(prev_n)
  
      init_fn = init_fn or init_weight_goog
      for n, m in model.named_modules():
          init_fn(m, n, last_bn=last_bn)
          init_fn(m, n, last_bn=last_bn)
  
file_path: nni/examples/nas/legacy/cream/lib/utils/builder_util.py
imports: import re
  import math
  import torch.nn
  from copy import deepcopy
  from timm.utils import *
  from timm.models.layers.activations import Swish
  from timm.models.layers import CondConv2d, get_condconv_initializer
label_desc: Use image node_id 7 for calling a global function with example usage: efficientnet_init_weights(model, init_fn, zero_gamma) without return types