code: def __init__(
      self,
      in_channels: int,
      out_channels: int,
      kernel_size: int,
      bias: bool = True,
  ):
      super().__init__()
  
      left_top_pad = right_bottom_pad = kernel_size // 2
      if kernel_size % 2 == 0:
          right_bottom_pad -= 1
  
      self.layer = nn.Sequential(
          nn.ReflectionPad2d(
              (
                  left_top_pad,
                  right_bottom_pad,
                  left_top_pad,
                  right_bottom_pad,
              )
          ),
          nn.Conv2d(
              in_channels=in_channels,
              out_channels=out_channels,
              kernel_size=kernel_size,
              bias=bias,
          ),
      )
  
file_path: pywick/pywick/models/segmentation/testnets/unet_plus_plus.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new ConvSamePad2d object from inherited base classes: nn with example: obj = ConvSamePad2d(in_channels, out_channels, kernel_size, bias)