


"""simple docstring"""






import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin


class      __lowerCamelCase	(       a__	,       unittest.TestCase					):

     '''simple docstring'''
     A_							:						Union[str, Any]     =		SpeechaTextaTokenizer
     A_							:						int     =		False


     def 				_UpperCAmelCase   (   self				)							->				Union[str, Any]:
          super().setUp()

          _a     						=					'''<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab'''.split(''' '''				)
          _a     						=					['''he re</w> 123''', '''here a 1456''']
          _a     						=					dict(zip(__UpperCAmelCase     ,					range(len(__UpperCAmelCase				)				)				)				)

          _a     						=					{'''pad_token''': '''<pad>''', '''unk_token''': '''<unk>''', '''bos_token''': '''<s>''', '''eos_token''': '''</s>'''}

          _a     						=					tempfile.mkdtemp()
          _a     						=					os.path.join(self.tmpdirname     ,					VOCAB_FILES_NAMES['''vocab_file''']				)
          _a     						=					os.path.join(self.tmpdirname     ,					VOCAB_FILES_NAMES['''merges_file''']				)

          with open(self.vocab_file     ,					'''w'''     ,					encoding='''utf-8'''				) as fp:
               fp.write(json.dumps(__UpperCAmelCase				) + '''\n'''				)

          with open(self.merges_file     ,					'''w'''				) as fp:
               fp.write('''\n'''.join(__UpperCAmelCase				)				)


     def 				_UpperCAmelCase   (   self				)							->				Dict:
          _a     						=					list(self.get_tokenizer().get_vocab().keys()				)

          self.assertEqual(vocab_keys[0]     ,					'''<s>'''				)
          self.assertEqual(vocab_keys[1]     ,					'''<pad>'''				)
          self.assertEqual(vocab_keys[-1]     ,					'''vocab'''				)
          self.assertEqual(len(__UpperCAmelCase				)     ,					14				)


     def 				_UpperCAmelCase   (   self				)							->				Optional[int]:
          self.assertEqual(self.get_tokenizer().vocab_size     ,					14				)


     def 				_UpperCAmelCase   (   self				)							->				str:
          _a     						=					SpeechaTextaTokenizer.from_pretrained(self.tmpdirname				)

          # make sure @@ is correctly concatenated
          _a     						=					[4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
          _a     						=					tokenizer.decode(__UpperCAmelCase				)

          self.assertTrue(output_string == '''herecouple words ofthe'''				)


     def 				_UpperCAmelCase   (   self				)							->				int:
          _a     						=					SpeechaTextaTokenizer.from_pretrained(self.tmpdirname				)

          with tempfile.TemporaryDirectory() as tmp_dirname:
               tokenizer.save_pretrained(__UpperCAmelCase				)
               os.remove(os.path.join(__UpperCAmelCase     ,					'''merges.txt'''				)				)

               # load tokenizer without merges file should not throw an error
               _a     						=					SpeechaTextaTokenizer.from_pretrained(__UpperCAmelCase				)

          with tempfile.TemporaryDirectory() as tmp_dirname:
               # save tokenizer and load again
               tokenizer.save_pretrained(__UpperCAmelCase				)
               _a     						=					SpeechaTextaTokenizer.from_pretrained(__UpperCAmelCase				)

          self.assertIsNotNone(__UpperCAmelCase				)





     def 				_UpperCAmelCase   (   self				)							->				Any:
          if not self.test_slow_tokenizer:
               return

          _a     						=					inspect.signature(self.tokenizer_class.__init__				)
          _a     						=					self.get_tokenizer()

          for parameter_name, parameter in signature.parameters.items():
               if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
                    self.assertIn(__UpperCAmelCase     ,					tokenizer.init_kwargs				)



"""simple docstring"""






import math
import os

import cva
import numpy as np

__snake_case												=							255.0
def    A_ ( _lowerCAmelCase  :       float,  _lowerCAmelCase  :       float							):






     """simple docstring"""

     _a     						=					np.mean((original - contrast) ** 2							)
     if mse == 0:
          return 1_00

     return 20 * math.logaa(PIXEL_MAX / math.sqrt(_lowerCAmelCase							)							)
def    A_ ( ):






     """simple docstring"""

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

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