


'''simple docstring'''

import copy
from typing import Dict

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
from ..bit import BitConfig


lowerCamelCase							:       Dict  						=     logging.get_logger(__name__)

lowerCamelCase							:       Union[str, Any]  						=     {
    'google/vit-hybrid-base-bit-384': 'https://huggingface.co/vit-hybrid-base-bit-384/resolve/main/config.json',
    # See all ViT hybrid models at https://huggingface.co/models?filter=vit
}
class   __lowerCAmelCase						(lowercase_					):





      '''simple docstring'''






      lowerCAmelCase__ :					Optional[int]   =							"""vit-hybrid"""



      def __init__(self   :   Tuple       ,						UpperCamelCase   :   Tuple=None       ,						UpperCamelCase   :   Optional[Any]=768       ,						UpperCamelCase   :   List[Any]=12       ,						UpperCamelCase   :   Any=12       ,						UpperCamelCase   :   List[str]=3072       ,						UpperCamelCase   :   Dict="gelu"       ,						UpperCamelCase   :   List[Any]=0.0       ,						UpperCamelCase   :   List[str]=0.0       ,						UpperCamelCase   :   int=0.02       ,						UpperCamelCase   :   Any=1E-12       ,						UpperCamelCase   :   str=224       ,						UpperCamelCase   :   List[str]=1       ,						UpperCamelCase   :   int=3       ,						UpperCamelCase   :   Tuple=[1, 1024, 24, 24]       ,						UpperCamelCase   :   str=True       ,						**UpperCamelCase   :   Tuple       ,						):

             '''simple docstring'''







             super().__init__(**UpperCamelCase			)

             if backbone_config is None:
                    logger.info('''`backbone_config` is `None`. Initializing the config with a `BiT` backbone.'''			)
                    lowercase__				      =			{
                        '''global_padding''': '''same''',
                        '''layer_type''': '''bottleneck''',
                        '''depths''': [3, 4, 9],
                        '''out_features''': ['''stage3'''],
                        '''embedding_dynamic_padding''': True,
                    }

             if isinstance(UpperCamelCase       ,						UpperCamelCase			):
                    if "model_type" in backbone_config:
                           lowercase__				      =			CONFIG_MAPPING[backbone_config['''model_type''']]
                    else:
                           logger.info(
                               '''`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class.'''			)
                           lowercase__				      =			BitConfig
                    lowercase__				      =			backbone_config_class(**UpperCamelCase			)

             lowercase__				      =			backbone_featmap_shape
             lowercase__				      =			backbone_config
             lowercase__				      =			hidden_size
             lowercase__				      =			num_hidden_layers
             lowercase__				      =			num_attention_heads
             lowercase__				      =			intermediate_size
             lowercase__				      =			hidden_act
             lowercase__				      =			hidden_dropout_prob
             lowercase__				      =			attention_probs_dropout_prob
             lowercase__				      =			initializer_range
             lowercase__				      =			layer_norm_eps
             lowercase__				      =			image_size
             lowercase__				      =			patch_size
             lowercase__				      =			num_channels
             lowercase__				      =			qkv_bias






      def 				UpperCamelCase__		(self   :   int			):

             '''simple docstring'''







             lowercase__				      =			copy.deepcopy(self.__dict__			)
             lowercase__				      =			self.backbone_config.to_dict()
             lowercase__				      =			self.__class__.model_type
             return output








'''simple docstring'''

import math
import os

import cva
import numpy as np

lowerCamelCase							:       Optional[Any]  						=     2_5_5.0

def _SCREAMING_SNAKE_CASE				(A  ,			A	)	->	float:






       """simple docstring"""







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

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

def _SCREAMING_SNAKE_CASE				()	->	None:






       """simple docstring"""







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

       lowercase__				      =			cva.imread(os.path.join(A  ,			'''image_data/PSNR-example-base.png'''	)	)
       lowercase__				      =			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()




