






import glob
import os

from get_test_info import get_tester_classes


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

  SCREAMING_SNAKE_CASE														=  os.path.join('tests', 'models', '**', 'test_modeling_*.py')
  SCREAMING_SNAKE_CASE														=  glob.glob(pattern)
  # TODO: deal with TF/Flax too
  SCREAMING_SNAKE_CASE														=  [
      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:
    SCREAMING_SNAKE_CASE														=  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:
        SCREAMING_SNAKE_CASE														=  tester_class(parent=None)
      except Exception:
        continue
      if hasattr(tester, 'get_config'):
        SCREAMING_SNAKE_CASE														=  tester.get_config()
        for k, v in config.to_dict().items():
          if isinstance(v, int):
            SCREAMING_SNAKE_CASE														=  None
            if k in ["vocab_size"]:
              SCREAMING_SNAKE_CASE														=  100
            elif k in ["max_position_embeddings"]:
              SCREAMING_SNAKE_CASE														=  128
            elif k in ["hidden_size", "d_model"]:
              SCREAMING_SNAKE_CASE														=  40
            elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
              SCREAMING_SNAKE_CASE														=  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))












from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import divide, inta, multiply, ravel, sort, zeros_like

def        _lowerCamelCase		(  __A      :							str						,						__A      :							List[str]=3	) ->   List[Any]:
    _UpperCAmelCase			: Tuple     					=			int(mask / 2	)
    # copy image size
    _UpperCAmelCase			: Any     					=			zeros_like(__A	)
    for i in range(__A						,						gray_img.shape[0] - bd	):
        for j in range(__A						,						gray_img.shape[1] - bd	):
            # get mask according with mask
            _UpperCAmelCase			: Any     					=			ravel(gray_img[i - bd : i + bd + 1, j - bd : j + bd + 1]	)
            # calculate mask median
            _UpperCAmelCase			: List[str]     					=			sort(__A	)[inta(divide((multiply(__A						,						__A	))						,						2	) + 1	)]
            _UpperCAmelCase			: int     					=			median
    return median_img


if __name__ == "__main__":
  # read original image
  SCREAMING_SNAKE_CASE								=  imread('../image_data/lena.jpg')
  # turn image in gray scale value
  SCREAMING_SNAKE_CASE								=  cvtColor(img, COLOR_BGR2GRAY)

  # get values with two different mask size
  SCREAMING_SNAKE_CASE								=  median_filter(gray, 3)
  SCREAMING_SNAKE_CASE								=  median_filter(gray, 5)

  # show result images
  imshow('median filter with 3x3 mask', medianaxa)
  imshow('median filter with 5x5 mask', medianaxa)
  waitKey(0)




