code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      stride=1,
      padding=0,
      dilation=1,
      groups=1,
      bias=True,
      padding_mode="zeros",
  ):
      super(BiConv2d, self).__init__(
          in_channels,
          out_channels,
          kernel_size,
          stride,
          padding,
          dilation,
          groups,
          bias,
          padding_mode,
      )
  
imports: import dgl
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Function
  from torch.nn import Parameter
  from torch.nn.modules.utils import _single
label_desc: Use image node_id 1 to create a new BiConv2d object from inherited base classes: torch.nn with example: obj = BiConv2d(in_channels, out_channels, kernel_size, stride, padding, dilation, groups, bias, padding_mode)