code: def output_shape(self):
      if self.block_type == "down":
          return (4, 32, 16, 16)
      elif self.block_type == "mid":
          return (4, 32, 32, 32)
      elif self.block_type == "up":
          return (4, 32, 64, 64)
  
      raise ValueError(
          f"'{self.block_type}' is not a supported block_type. Set it to 'up', 'mid', or 'down'."
      )
  
file_path: llmga/llmga/diffusers/tests/models/test_unet_blocks_common.py
imports: import unittest
  from typing import Tuple
  import torch
  from diffusers.utils.testing_utils import floats_tensor, require_torch, torch_all_close, torch_device
  from diffusers.utils.torch_utils import randn_tensor
label_desc: Use image node_id 2 for calling the UNetBlockTesterMixin obj's underlying member method code with example usage: obj.output_shape() and returns: int,  int,  int,  int, int,  int,  int,  int, int,  int,  int,  int