code: def __init__(self, in_channels: int, with_conv: bool):
      super().__init__()
      if not with_conv:
          self.conv = None
      else:
          self.conv = HijackConv2d(in_channels, in_channels, 3, 1, 1)
  
file_path: carefree-learn/cflearn/models/cv/decoder/attn.py
imports: import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from typing import Tuple
  from typing import Optional
  from .schema import DecoderMixin
  from ....modules.blocks import make_attention
  from ....modules.blocks import HijackConv2d
  from ....modules.blocks import ApplyTanhMixin
  from ....modules.blocks import ResidualBlockWithTimeEmbedding
label_desc: Use image node_id 1 to create a new Upsample object from inherited base classes: nn with example: obj = Upsample(in_channels, with_conv)