class_docstr: ## Up-sampling layer
docstr: :param channels: is the number of channels
code: def __init__(self, channels: int):
      """
      :param channels: is the number of channels
      """
      super().__init__()
      # $3 \times 3$ convolution mapping
      self.conv = nn.Conv2d(channels, channels, 3, padding=1)
  
imports: from typing import List
  import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 1 to create a new UpSample object from inherited base classes: nn with example: obj = UpSample(channels)