code: def __init__(self, dim, blur=True):
      super().__init__()
      if blur:
          self.conv = nn.Sequential(
              nn.ConvTranspose2d(
                  dim, dim, kernel_size=4, stride=2, padding=1
              ),
              Blur(),
          )
      else:
          self.conv = nn.ConvTranspose2d(
              dim, dim, kernel_size=4, stride=2, padding=1
          )
  
imports: import math
  import kornia
  import torch
  import torch.nn.functional
  from einops import rearrange
  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(dim, blur)