






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__A          = {
    'configuration_splinter': ['SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SplinterConfig'],
    'tokenization_splinter': ['SplinterTokenizer'],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A          = ['SplinterTokenizerFast']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A          = [
				    'SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'SplinterForQuestionAnswering',
				    'SplinterForPreTraining',
				    'SplinterLayer',
				    'SplinterModel',
				    'SplinterPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
				from .tokenization_splinter import SplinterTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_splinter_fast import SplinterTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_splinter import (
								    SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SplinterForPreTraining,
								    SplinterForQuestionAnswering,
								    SplinterLayer,
								    SplinterModel,
								    SplinterPreTrainedModel,
								)


else:
				import sys

				__A          = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






import math
import os

import cva
import numpy as np

__UpperCAmelCase      = 255.0





def 	snake_case_      (__A     :						float					,   __A     :						float     )			->	float:
   __lowerCAmelCase  :			Any					    =						np.mean((original - contrast) ** 2     )
   if mse == 0:
      return 1_0_0

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





def 	snake_case_      ()			->	None:
   __lowerCAmelCase  :			int					    =						os.path.dirname(os.path.realpath(__A     )     )
   # Loading images (original image and compressed image)
   __lowerCAmelCase  :			Tuple					    =						cva.imread(os.path.join(__A					,   """image_data/original_image.png"""     )     )
   __lowerCAmelCase  :			Dict					    =						cva.imread(os.path.join(__A					,   """image_data/compressed_image.png"""     )					,   1     )

   __lowerCAmelCase  :			Optional[int]					    =						cva.imread(os.path.join(__A					,   """image_data/PSNR-example-base.png"""     )     )
   __lowerCAmelCase  :			Optional[int]					    =						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()


