class_docstr: ## Up-sampling layer
docstr: :param x: is the input feature map with shape `[batch_size, channels, height, width]`
code: def forward(self, x: torch.Tensor):
      """
      :param x: is the input feature map with shape `[batch_size, channels, height, width]`
      """
      # Up-sample by a factor of $2$
      x = F.interpolate(x, scale_factor=2.0, mode="nearest")
      # Apply convolution
      return self.conv(x)
  
imports: from typing import List
  import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 2 for calling the UpSample obj's underlying member method code with example usage: obj.forward(x) and returns: self