class_docstr: ### Scale down the feature map by $rac{1}{2}       imes$
class_docstr_tok: ["#","#","#","Scale","down","the","feature","map","by","$","rac","{","1","}","{","2","}","imes","$"]
code: def __init__(self, n_channels):
      super().__init__()
      self.conv = nn.Conv2d(
          n_channels, n_channels, (3, 3), (2, 2), (1, 1)
      )
  
imports: import math
  from typing import Optional, Tuple, Union, List
  import torch
  from torch import nn
  from labml_helpers.module import Module
label_desc: Use image node_id 1 to create a new Downsample object from inherited base classes: nn with example: obj = Downsample(n_channels)