code: def forward(self, x: Tensor) -> Tensor:
      x = F.interpolate(x, scale_factor=2.0, mode="nearest")
      if self.with_conv:
          x = self.conv(x)
      return x
  
imports: import logging
  from typing import Optional, Sequence
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from neuralcompression.layers import XCA, ChannelNorm2D
  from .._outputs._vqvae_autoencoder_output import VqVaeAutoencoderOutput
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: x