code: def __init__(
      self,
      bottom_: int,
      horizontal_: int,
      out_: int,
      size: int = 5,
      setup: Any = None,
  ) -> None:
      super().__init__()
  
      self.bottom_ = bottom_
      self.horizontal_ = horizontal_
      self.cat_ = bottom_ + horizontal_
      self.out_ = out_
  
      self.upsample = TrivialUpsample()
      self.conv = Conv(self.cat_, self.out_, size)
  
imports: from __future__ import annotations
  from typing import Any
  import torch
  import torch.nn.functional
  from torch import nn
  from kornia.core import Module, Tensor
label_desc: Use image node_id 1 to create a new ThinUnetUpBlock object from inherited base classes: Module with example: obj = ThinUnetUpBlock(bottom_, horizontal_, out_, size, setup)