






"""simple docstring"""



from typing import List, Union

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


__A		:	List[str]      =		logging.get_logger(__name__)

__A		:	Union[str, Any]      =		{
    '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/config.json''',
    # See all LED models at https://huggingface.co/models?filter=led
}





class  _UpperCAmelCase	(			_A							):
					SCREAMING_SNAKE_CASE_		:    Optional[int]							   =       "led"
					SCREAMING_SNAKE_CASE_		:    Any							   =       {
					    "num_attention_heads": "encoder_attention_heads",
					    "hidden_size": "d_model",
					    "attention_probs_dropout_prob": "attention_dropout",
					    "initializer_range": "init_std",
					}




					def __init__(    self					:						Any   ,						A					:						Dict=5_02_65   ,						A					:						Optional[Any]=1_63_84   ,						A					:						List[str]=10_24   ,						A					:						List[str]=12   ,						A					:						Tuple=40_96   ,						A					:						List[str]=16   ,						A					:						List[Any]=12   ,						A					:						List[Any]=40_96   ,						A					:						Dict=16   ,						A					:						str=0.0   ,						A					:						List[str]=0.0   ,						A					:						Optional[Any]=True   ,						A					:						Optional[Any]=True   ,						A					:						List[Any]="gelu"   ,						A					:						Any=10_24   ,						A					:						Optional[Any]=0.1   ,						A					:						Any=0.0   ,						A					:						Optional[int]=0.0   ,						A					:						int=0.02   ,						A					:						Union[str, Any]=2   ,						A					:						Union[str, Any]=0.0   ,						A					:						int=1   ,						A					:						str=0   ,						A					:						Dict=2   ,						A					:						Union[List[int], int] = 5_12   ,						**A					:						Optional[Any]   ,						)  ->  Optional[Any]:
							lowercase_			:			Tuple								=       vocab_size
							lowercase_			:			int								=       max_encoder_position_embeddings
							lowercase_			:			int								=       max_decoder_position_embeddings
							lowercase_			:			str								=       d_model
							lowercase_			:			Union[str, Any]								=       encoder_ffn_dim
							lowercase_			:			Dict								=       encoder_layers
							lowercase_			:			int								=       encoder_attention_heads
							lowercase_			:			List[str]								=       decoder_ffn_dim
							lowercase_			:			Union[str, Any]								=       decoder_layers
							lowercase_			:			int								=       decoder_attention_heads
							lowercase_			:			Dict								=       dropout
							lowercase_			:			Tuple								=       attention_dropout
							lowercase_			:			int								=       activation_dropout
							lowercase_			:			str								=       activation_function
							lowercase_			:			List[str]								=       init_std
							lowercase_			:			List[Any]								=       encoder_layerdrop
							lowercase_			:			Optional[int]								=       decoder_layerdrop
							lowercase_			:			List[Any]								=       classifier_dropout
							lowercase_			:			Dict								=       use_cache
							lowercase_			:			List[str]								=       encoder_layers
							lowercase_			:			Union[str, Any]								=       attention_window

							super().__init__(
							    pad_token_id=A   ,						bos_token_id=A   ,						eos_token_id=A   ,						is_encoder_decoder=A   ,						decoder_start_token_id=A   ,						**A   ,						)











"""simple docstring"""



import math
import os

import cva
import numpy as np

__A		:	int      =		255.0



def 						lowercase   (    __snake_case    :			float		, __snake_case    :			float     ):
		lowercase_			:			Any								=       np.mean((original - contrast) ** 2     )
		if mse == 0:
				return 1_0_0

		return 2_0 * math.logaa(PIXEL_MAX / math.sqrt(__snake_case     )     )



def 						lowercase   (    ):
		lowercase_			:			Any								=       os.path.dirname(os.path.realpath(__snake_case     )     )
		# Loading images (original image and compressed image)
		lowercase_			:			Union[str, Any]								=       cva.imread(os.path.join(__snake_case		, '''image_data/original_image.png'''     )     )
		lowercase_			:			List[Any]								=       cva.imread(os.path.join(__snake_case		, '''image_data/compressed_image.png'''     )		, 1     )

		lowercase_			:			Tuple								=       cva.imread(os.path.join(__snake_case		, '''image_data/PSNR-example-base.png'''     )     )
		lowercase_			:			List[str]								=       cva.imread(
		    os.path.join(__snake_case		, '''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(__snake_case		, __snake_case     )} dB'''     )

		# # Value expected: 31.53dB (Wikipedia Example)
		print('''\n-- Second Test --'''     )
		print(F'''PSNR value is {peak_signal_to_noise_ratio(__snake_case		, __snake_case     )} dB'''     )


if __name__ == "__main__":
						main()



