



import unittest
from dataclasses import dataclass
from typing import List, Union

import numpy as np
import PIL.Image

from diffusers.utils.outputs import BaseOutput
@dataclass
class  _snake_case	(    _UpperCamelCase):
				UpperCamelCase__ :    Union[List[PIL.Image.Image], np.ndarray]
class  _snake_case	(    unittest.TestCase):




				def 							A__					(  self    :  Union[str, Any]  ):
							lowercase__         = CustomOutput(images=np.random.rand(1,    3,    4,    4  )  )

							# check every way of getting the attribute
							assert isinstance(outputs.images,    np.ndarray  )
							assert outputs.images.shape == (1, 3, 4, 4)
							assert isinstance(outputs["images"],    np.ndarray  )
							assert outputs["images"].shape == (1, 3, 4, 4)
							assert isinstance(outputs[0],    np.ndarray  )
							assert outputs[0].shape == (1, 3, 4, 4)

							# test with a non-tensor attribute
							lowercase__         = CustomOutput(images=[PIL.Image.new("RGB",    (4, 4)  )]  )

							# check every way of getting the attribute
							assert isinstance(outputs.images,    __a  )
							assert isinstance(outputs.images[0],    PIL.Image.Image  )
							assert isinstance(outputs["images"],    __a  )
							assert isinstance(outputs["images"][0],    PIL.Image.Image  )
							assert isinstance(outputs[0],    __a  )
							assert isinstance(outputs[0][0],    PIL.Image.Image  )




				def 							A__					(  self    :  int  ):
							# test output reinitialization with a `dict` for compatibility with `accelerate`
							lowercase__         = CustomOutput({"images": np.random.rand(1,    3,    4,    4  )}  )

							# check every way of getting the attribute
							assert isinstance(outputs.images,    np.ndarray  )
							assert outputs.images.shape == (1, 3, 4, 4)
							assert isinstance(outputs["images"],    np.ndarray  )
							assert outputs["images"].shape == (1, 3, 4, 4)
							assert isinstance(outputs[0],    np.ndarray  )
							assert outputs[0].shape == (1, 3, 4, 4)

							# test with a non-tensor attribute
							lowercase__         = CustomOutput({"images": [PIL.Image.new("RGB",    (4, 4)  )]}  )

							# check every way of getting the attribute
							assert isinstance(outputs.images,    __a  )
							assert isinstance(outputs.images[0],    PIL.Image.Image  )
							assert isinstance(outputs["images"],    __a  )
							assert isinstance(outputs["images"][0],    PIL.Image.Image  )
							assert isinstance(outputs[0],    __a  )
							assert isinstance(outputs[0][0],    PIL.Image.Image  )











"""simple docstring"""


import glob
import os

from get_test_info import get_tester_classes


if __name__ == "__main__":
  lowerCamelCase__      =      []

  lowerCamelCase__      =      os.path.join("tests", "models", "**", "test_modeling_*.py")
  lowerCamelCase__      =      glob.glob(pattern)
  # TODO: deal with TF/Flax too
  lowerCamelCase__      =      [
      x for x in test_files if not (x.startswith("test_modeling_tf_") or x.startswith("test_modeling_flax_"))
  ]

  for test_file in test_files:
    lowerCamelCase__      =      get_tester_classes(test_file)
    for tester_class in tester_classes:
      # A few tester classes don't have `parent` parameter in `__init__`.
      # TODO: deal this better
      try:
        lowerCamelCase__      =      tester_class(parent=None)
      except Exception:
        continue
      if hasattr(tester, "get_config"):
        lowerCamelCase__      =      tester.get_config()
        for k, v in config.to_dict().items():
          if isinstance(v, int):
            lowerCamelCase__      =      None
            if k in ["vocab_size"]:
              lowerCamelCase__      =      100
            elif k in ["max_position_embeddings"]:
              lowerCamelCase__      =      128
            elif k in ["hidden_size", "d_model"]:
              lowerCamelCase__      =      40
            elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
              lowerCamelCase__      =      5
            if target is not None and v > target:
              failures.append(
                  f"""{tester_class.__name__} will produce a `config` of type `{config.__class__.__name__}`"""
                  f""" with config[\"{k}\"] = {v} which is too large for testing! Set its value to be smaller"""
                  f""" than {target}."""
              )

  if len(failures) > 0:
    raise Exception(f"""There were {len(failures)} failures:\n""" + "\n".join(failures))
