code: def initialize_weight_default(m, n=""):
      if isinstance(m, CondConv2d):
          init_fn = get_condconv_initializer(
              partial(
                  nn.init.kaiming_normal_,
                  mode="fan_out",
                  nonlinearity="relu",
              ),
              m.num_experts,
              m.weight_shape,
          )
          init_fn(m.weight)
      elif isinstance(m, nn.Conv2d):
          nn.init.kaiming_normal_(
              m.weight, mode="fan_out", nonlinearity="relu"
          )
      elif isinstance(m, nn.BatchNorm2d):
          m.weight.data.fill_(1.0)
          m.bias.data.zero_()
      elif isinstance(m, nn.Linear):
          nn.init.kaiming_uniform_(
              m.weight, mode="fan_in", nonlinearity="linear"
          )
  
imports: import re
  from copy import deepcopy
  from .conv2d_layers import *
  from geffnet.activations import *
label_desc: Use image node_id 13 for calling a global function with example usage: initialize_weight_default(m, n) without return types