code: def __init__(self, in_channels, out_channels, mid_channels=None):
      if mid_channels is None:
          mid_channels = out_channels
      super(DoubleConv, self).__init__(
          nn.Conv2d(
              in_channels,
              mid_channels,
              kernel_size=3,
              padding=1,
              bias=False,
          ),
          nn.BatchNorm2d(mid_channels),
          nn.ReLU(inplace=True),
          nn.Conv2d(
              mid_channels,
              out_channels,
              kernel_size=3,
              padding=1,
              bias=False,
          ),
          nn.BatchNorm2d(out_channels),
          nn.ReLU(inplace=True),
      )
  
imports: from typing import Dict
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new DoubleConv object from inherited base classes: nn with example: obj = DoubleConv(in_channels, out_channels, mid_channels)