




"""simple docstring"""





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


_lowercase						   =     logging.get_logger(__name__)

_lowercase						   =     {
    """microsoft/mpnet-base""": """https://huggingface.co/microsoft/mpnet-base/resolve/main/config.json""",
}

class    __lowercase							(      snake_case_						):


				'''simple docstring'''


				_lowerCAmelCase						      ="mpnet"

				def __init__( self :  Union[str, Any]   ,SCREAMING_SNAKE_CASE_ :  Dict=3_0_5_2_7   ,SCREAMING_SNAKE_CASE_ :  Any=7_6_8   ,SCREAMING_SNAKE_CASE_ :  str=1_2   ,SCREAMING_SNAKE_CASE_ :  Optional[int]=1_2   ,SCREAMING_SNAKE_CASE_ :  Union[str, Any]=3_0_7_2   ,SCREAMING_SNAKE_CASE_ :  int="gelu"   ,SCREAMING_SNAKE_CASE_ :  Union[str, Any]=0.1   ,SCREAMING_SNAKE_CASE_ :  List[str]=0.1   ,SCREAMING_SNAKE_CASE_ :  Tuple=5_1_2   ,SCREAMING_SNAKE_CASE_ :  Optional[int]=0.02   ,SCREAMING_SNAKE_CASE_ :  str=1E-12   ,SCREAMING_SNAKE_CASE_ :  Tuple=3_2   ,SCREAMING_SNAKE_CASE_ :  Dict=1   ,SCREAMING_SNAKE_CASE_ :  Union[str, Any]=0   ,SCREAMING_SNAKE_CASE_ :  List[Any]=2   ,**SCREAMING_SNAKE_CASE_ :  int   ,):
										super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_   ,bos_token_id=SCREAMING_SNAKE_CASE_   ,eos_token_id=SCREAMING_SNAKE_CASE_   ,**SCREAMING_SNAKE_CASE_   )

										snake_case__							:       Optional[int]				      =       vocab_size
										snake_case__							:       str				      =       hidden_size
										snake_case__							:       Dict				      =       num_hidden_layers
										snake_case__							:       List[str]				      =       num_attention_heads
										snake_case__							:       Dict				      =       hidden_act
										snake_case__							:       List[str]				      =       intermediate_size
										snake_case__							:       List[Any]				      =       hidden_dropout_prob
										snake_case__							:       Optional[int]				      =       attention_probs_dropout_prob
										snake_case__							:       int				      =       max_position_embeddings
										snake_case__							:       Tuple				      =       initializer_range
										snake_case__							:       Tuple				      =       layer_norm_eps
										snake_case__							:       int				      =       relative_attention_num_buckets








"""simple docstring"""





import math
import os

import cva
import numpy as np

_lowercase						   =     2_55.0

def 		lowerCAmelCase				(			lowerCamelCase   ,      lowerCamelCase		):
						'''simple docstring'''


						snake_case__							:       Tuple				      =       np.mean((original - contrast) ** 2		)
						if mse == 0:
												return 100

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

def 		lowerCAmelCase				(			):
						'''simple docstring'''


						snake_case__							:       Any				      =       os.path.dirname(os.path.realpath(lowerCamelCase		)		)
						# Loading images (original image and compressed image)
						snake_case__							:       Any				      =       cva.imread(os.path.join(lowerCamelCase   ,      '''image_data/original_image.png'''		)		)
						snake_case__							:       Any				      =       cva.imread(os.path.join(lowerCamelCase   ,      '''image_data/compressed_image.png'''		)   ,      1		)

						snake_case__							:       Optional[Any]				      =       cva.imread(os.path.join(lowerCamelCase   ,      '''image_data/PSNR-example-base.png'''		)		)
						snake_case__							:       Tuple				      =       cva.imread(
						    os.path.join(lowerCamelCase   ,      '''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(lowerCamelCase   ,      lowerCamelCase		)} dB'''		)

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


if __name__ == "__main__":
							main()


