


from ...configuration_utils import PretrainedConfig
from ...utils import logging


_snake_case   = logging.get_logger(__name__)

_snake_case   = {
    "google/reformer-crime-and-punishment": (
        "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/config.json"
    ),
    "google/reformer-enwik8": "https://huggingface.co/google/reformer-enwik8/resolve/main/config.json",
}




class    A_   ( lowerCamelCase_     ):







	"""simple docstring"""





	_UpperCamelCase				: Dict      =					"""reformer"""
	_UpperCamelCase				: Tuple      =					["""past_buckets_states"""]
	_UpperCamelCase				: Optional[int]      =					{}
	def __init__(			self					: List[str]       ,    _a					: Any=6_4       ,    _a					: Any=["local", "lsh", "local", "lsh", "local", "lsh"]       ,    _a					: Dict=1.0       ,    _a					: Optional[Any]=True       ,    _a					: Optional[int]=[6_4, 6_4]       ,    _a					: List[str]=[6_4, 1_9_2]       ,    _a					: Dict=0       ,    _a					: Tuple=2       ,    _a					: Optional[int]=5_1_2       ,    _a					: List[Any]=None       ,    _a					: List[Any]="relu"       ,    _a					: str=0.0_5       ,    _a					: Any=2_5_6       ,    _a					: int=0.0_2       ,    _a					: Optional[int]=False       ,    _a					: Dict=1E-12       ,    _a					: Optional[Any]=1       ,    _a					: List[Any]=0       ,    _a					: Optional[Any]=0.0_5       ,    _a					: Optional[Any]=6_4       ,    _a					: Optional[int]=6_4       ,    _a					: Any=0.0       ,    _a					: Optional[int]=1       ,    _a					: List[Any]=0       ,    _a					: int=4_0_9_6       ,    _a					: Any=1_2       ,    _a					: str=None       ,    _a					: List[str]=1       ,    _a					: Dict=0       ,    _a					: Union[str, Any]=3_2_0       ,    _a					: List[Any]=False       ,    _a					: Optional[Any]=True       ,    _a					: Any=None       ,    **_a					: str       ,    )    ->			Union[str, Any]:
						UpperCAmelCase						:				List[str]		  =			hash_seed
						UpperCAmelCase						:				Union[str, Any]		  =			vocab_size
						UpperCAmelCase						:				Optional[Any]		  =			attention_head_size
						UpperCAmelCase						:				Optional[int]		  =			hidden_size
						UpperCAmelCase						:				Union[str, Any]		  =			num_attention_heads
						UpperCAmelCase						:				List[str]		  =			num_hashes
						UpperCAmelCase						:				str		  =			len(_a				)
						UpperCAmelCase						:				str		  =			tuple(_a				) if isinstance(_a       ,    _a				) else num_buckets
						UpperCAmelCase						:				int		  =			lsh_attn_chunk_length
						UpperCAmelCase						:				List[str]		  =			local_attn_chunk_length
						UpperCAmelCase						:				Any		  =			lsh_num_chunks_after
						UpperCAmelCase						:				Union[str, Any]		  =			lsh_num_chunks_before
						UpperCAmelCase						:				Tuple		  =			local_num_chunks_after
						UpperCAmelCase						:				Optional[int]		  =			local_num_chunks_before
						UpperCAmelCase						:				Tuple		  =			hidden_act
						UpperCAmelCase						:				List[str]		  =			feed_forward_size
						UpperCAmelCase						:				Tuple		  =			hidden_dropout_prob
						UpperCAmelCase						:				Optional[Any]		  =			lsh_attention_probs_dropout_prob
						UpperCAmelCase						:				Any		  =			local_attention_probs_dropout_prob
						UpperCAmelCase						:				List[Any]		  =			max_position_embeddings
						UpperCAmelCase						:				Tuple		  =			initializer_range
						UpperCAmelCase						:				Union[str, Any]		  =			layer_norm_eps
						UpperCAmelCase						:				str		  =			axial_pos_embds
						UpperCAmelCase						:				List[str]		  =			tuple(_a				)
						UpperCAmelCase						:				List[Any]		  =			tuple(_a				)
						UpperCAmelCase						:				int		  =			axial_norm_std
						UpperCAmelCase						:				List[Any]		  =			chunk_size_lm_head
						UpperCAmelCase						:				Optional[Any]		  =			attn_layers
						UpperCAmelCase						:				int		  =			use_cache
						UpperCAmelCase						:				Any		  =			classifier_dropout
						super().__init__(
						    pad_token_id=_a       ,    eos_token_id=_a       ,    is_decoder=_a       ,    tie_word_embeddings=_a       ,    **_a       ,    )







from cva import destroyAllWindows, imread, imshow, waitKey







def   A   (		A__		,		A__ ):
     UpperCAmelCase  , UpperCAmelCase						:				Optional[Any]		  =			img.shape[0], img.shape[1]

     def to_grayscale(A__		,		A__		,		A__ ):
          return 0.2126 * red + 0.587 * green + 0.114 * blue

     def normalize(A__ ):
          return min(A__		,		2_5_5 )

     for i in range(A__ ):
          for j in range(A__ ):
               UpperCAmelCase						:				Optional[Any]		  =			int(to_grayscale(*img[i][j] ) )
               UpperCAmelCase						:				List[str]		  =			[
                   normalize(A__ ),
                   normalize(greyscale + factor ),
                   normalize(greyscale + 2 * factor ),
               ]

     return img


if __name__ == "__main__":
      # read original image
      _snake_case   = {
          percentage: imread("image_data/lena.jpg", 1) for percentage in (1_0, 2_0, 3_0, 4_0)
      }

      for percentage, img in images.items():
            make_sepia(img, percentage)

      for percentage, img in images.items():
            imshow(f'''Original image with sepia (factor: {percentage})''', img)

      waitKey(0)
      destroyAllWindows()



