code: def __init__(self, n_in, n_out):
      super().__init__()
      self.conv = nn.Sequential(
          conv(n_in, n_out),
          nn.ReLU(),
          conv(n_out, n_out),
          nn.ReLU(),
          conv(n_out, n_out),
      )
      self.skip = (
          nn.Conv2d(n_in, n_out, 1, bias=False)
          if n_in != n_out
          else nn.Identity()
      )
      self.fuse = nn.ReLU()
  
imports: import os
  import torch
  import torch.nn
  from modules import devices, paths_internal, shared
label_desc: Use image node_id 1 to create a new Block object from inherited base classes: nn with example: obj = Block(n_in, n_out)