code: def init_weights(self):
      n = self.in_channels
      for k in self.kernel_size:
          n *= k
      stdv = 1.0 / math.sqrt(n)
      self.weight.data.uniform_(-stdv, stdv)
      if self.bias is not None:
          self.bias.data.zero_()
  
imports: import math
  import torch
  import torch.nn
  from torch.autograd import Function
  from torch.autograd.function import once_differentiable
  from torch.nn.modules.utils import _pair, _single
  from annotator.uniformer.mmcv.utils import deprecated_api_warning
  from ..cnn import CONV_LAYERS
  from ..utils import ext_loader, print_log
label_desc: Use image node_id 2 for calling the ModulatedDeformConv2d obj's underlying member method code with example usage: obj.init_weights() without return types