

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


a_         =      logging.get_logger(__name__)

a_         =      {
    '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 _UpperCamelCase							(							__A				):
			'''simple docstring'''







			lowerCamelCase__          ='reformer'
			lowerCamelCase__          =['past_buckets_states']
			lowerCamelCase__          ={}
			def __init__(     self							:	Dict , a							:	Any=64 , a							:	Union[str, Any]=["local", "lsh", "local", "lsh", "local", "lsh"] , a							:	Any=1.0 , a							:	Tuple=True , a							:	Union[str, Any]=[64, 64] , a							:	Any=[64, 192] , a							:	List[str]=0 , a							:	Dict=2 , a							:	Any=512 , a							:	Any=None , a							:	List[Any]="relu" , a							:	Optional[int]=0.05 , a							:	List[str]=256 , a							:	List[str]=0.02 , a							:	int=False , a							:	Union[str, Any]=1e-12 , a							:	str=1 , a							:	Optional[Any]=0 , a							:	Optional[Any]=0.05 , a							:	List[str]=64 , a							:	Dict=64 , a							:	Tuple=0.0 , a							:	Any=1 , a							:	Optional[Any]=0 , a							:	Optional[Any]=4096 , a							:	Tuple=12 , a							:	Union[str, Any]=None , a							:	Tuple=1 , a							:	List[Any]=0 , a							:	Dict=320 , a							:	List[Any]=False , a							:	Any=True , a							:	Optional[Any]=None , **a							:	Optional[Any] , )							->    Union[str, Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE				: int			       =    hash_seed
				SCREAMING_SNAKE_CASE				: Dict			       =    vocab_size
				SCREAMING_SNAKE_CASE				: str			       =    attention_head_size
				SCREAMING_SNAKE_CASE				: Optional[int]			       =    hidden_size
				SCREAMING_SNAKE_CASE				: Any			       =    num_attention_heads
				SCREAMING_SNAKE_CASE				: Tuple			       =    num_hashes
				SCREAMING_SNAKE_CASE				: Optional[int]			       =    len(a		)
				SCREAMING_SNAKE_CASE				: Any			       =    tuple(a		) if isinstance(a , a		) else num_buckets
				SCREAMING_SNAKE_CASE				: Dict			       =    lsh_attn_chunk_length
				SCREAMING_SNAKE_CASE				: Optional[int]			       =    local_attn_chunk_length
				SCREAMING_SNAKE_CASE				: List[Any]			       =    lsh_num_chunks_after
				SCREAMING_SNAKE_CASE				: List[Any]			       =    lsh_num_chunks_before
				SCREAMING_SNAKE_CASE				: Any			       =    local_num_chunks_after
				SCREAMING_SNAKE_CASE				: Dict			       =    local_num_chunks_before
				SCREAMING_SNAKE_CASE				: List[Any]			       =    hidden_act
				SCREAMING_SNAKE_CASE				: Any			       =    feed_forward_size
				SCREAMING_SNAKE_CASE				: Any			       =    hidden_dropout_prob
				SCREAMING_SNAKE_CASE				: Tuple			       =    lsh_attention_probs_dropout_prob
				SCREAMING_SNAKE_CASE				: str			       =    local_attention_probs_dropout_prob
				SCREAMING_SNAKE_CASE				: Optional[Any]			       =    max_position_embeddings
				SCREAMING_SNAKE_CASE				: str			       =    initializer_range
				SCREAMING_SNAKE_CASE				: str			       =    layer_norm_eps
				SCREAMING_SNAKE_CASE				: List[str]			       =    axial_pos_embds
				SCREAMING_SNAKE_CASE				: Tuple			       =    tuple(a		)
				SCREAMING_SNAKE_CASE				: Optional[int]			       =    tuple(a		)
				SCREAMING_SNAKE_CASE				: List[Any]			       =    axial_norm_std
				SCREAMING_SNAKE_CASE				: int			       =    chunk_size_lm_head
				SCREAMING_SNAKE_CASE				: Optional[Any]			       =    attn_layers
				SCREAMING_SNAKE_CASE				: str			       =    use_cache
				SCREAMING_SNAKE_CASE				: Tuple			       =    classifier_dropout
				super().__init__(
				    pad_token_id=a , eos_token_id=a , is_decoder=a , tie_word_embeddings=a , **a , )


import math
import os

import cva
import numpy as np

a_         =      255.0

def 	lowerCamelCase__	(   _a							,     _a):
	SCREAMING_SNAKE_CASE				: Optional[int]			       =    np.mean((original - contrast) ** 2)
	if mse == 0:
		return 100

	return 20 * math.logaa(PIXEL_MAX / math.sqrt(_a))

def 	lowerCamelCase__	(   ):
	SCREAMING_SNAKE_CASE				: List[Any]			       =    os.path.dirname(os.path.realpath(_a))
	# Loading images (original image and compressed image)
	SCREAMING_SNAKE_CASE				: Any			       =    cva.imread(os.path.join(_a							,     "image_data/original_image.png"))
	SCREAMING_SNAKE_CASE				: List[str]			       =    cva.imread(os.path.join(_a							,     "image_data/compressed_image.png")							,     1)

	SCREAMING_SNAKE_CASE				: List[Any]			       =    cva.imread(os.path.join(_a							,     "image_data/PSNR-example-base.png"))
	SCREAMING_SNAKE_CASE				: List[str]			       =    cva.imread(
	    os.path.join(_a							,     "image_data/PSNR-example-comp-10.jpg")							,     1)

	# Value expected: 29.73dB
	print("-- First Test --")
	print(f"PSNR value is {peak_signal_to_noise_ratio(_a							,     _a)} dB")

	# # Value expected: 31.53dB (Wikipedia Example)
	print("\n-- Second Test --")
	print(f"PSNR value is {peak_signal_to_noise_ratio(_a							,     _a)} dB")


if __name__ == "__main__":
			main()