code: def __init__(
      self,
      in_dim,
      out_dim,
      kernel_size=3,
      stride=1,
      padding=1,
      **kwargs,
  ):
      super(ConvBNReluStack, self).__init__()
  
      in_dim = int(in_dim)
      out_dim = int(out_dim)
  
      self.conv = nn.Conv2d(
          in_dim, out_dim, kernel_size, stride=stride, padding=padding
      )
      # nn.init.xavier_normal(self.conv.weight.data)
  
      self.bn = nn.BatchNorm2d(out_dim)
      self.activation = nn.PReLU()
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new ConvBNReluStack object from inherited base classes: nn with example: obj = ConvBNReluStack(in_dim, out_dim, kernel_size, stride, padding)