class_docstr: Simple residual unit
class_docstr_tok: ["Simple","residual","unit"]
code: def __init__(self, N: int) -> None:
      super().__init__()
      self.conv = nn.Sequential(
          make_conv(N, N // 2, kernel_size=1),
          nn.ReLU(inplace=True),
          make_conv(N // 2, N // 2, kernel_size=3),
          nn.ReLU(inplace=True),
          make_conv(N // 2, N, kernel_size=1),
      )
      self.activation = nn.ReLU(inplace=True)
  
imports: from typing import List, Optional
  import torch
  import torch.nn
  from compressai.layers import GDN, AttentionBlock
  from neural.layers_utils import make_conv, make_deconv
  from torch import Tensor
label_desc: Use image node_id 1 to create a new ResidualUnit object from inherited base classes: nn with example: obj = ResidualUnit(N)