





"""simple docstring"""


import json
import os
import shutil
import tempfile
import unittest

from transformers.models.wavaveca import WavaVecaCTCTokenizer, WavaVecaFeatureExtractor, WavaVecaProcessor
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.utils import FEATURE_EXTRACTOR_NAME

from .test_feature_extraction_wavaveca import floats_list



class   lowercase_					(  unittest.TestCase				):

       def 		_SCREAMING_SNAKE_CASE(      self  ):






        '''simple docstring'''

        snake_case__     				=					"<pad> <s> </s> <unk> | E T A O N I H S R D L U M W C F G Y P B V K ' X J Q Z".split(" "  )
        snake_case__     				=					dict(zip(__SCREAMING_SNAKE_CASE ,       range(len(__SCREAMING_SNAKE_CASE  )  )  )  )

        snake_case__     				=					{
            "pad_token": "<pad>",
            "unk_token": "<unk>",
            "bos_token": "<s>",
            "eos_token": "</s>",
        }
        snake_case__     				=					{
            "feature_size": 1,
            "padding_value": 0.0,
            "sampling_rate": 1_6000,
            "return_attention_mask": False,
            "do_normalize": True,
        }

        snake_case__     				=					tempfile.mkdtemp()
        snake_case__     				=					os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES["vocab_file"]  )
        snake_case__     				=					os.path.join(self.tmpdirname ,       __SCREAMING_SNAKE_CASE  )
        with open(self.vocab_file ,       "w" ,       encoding="utf-8"  ) as fp:
         fp.write(json.dumps(__SCREAMING_SNAKE_CASE  ) + "\n"  )

        with open(self.feature_extraction_file ,       "w" ,       encoding="utf-8"  ) as fp:
         fp.write(json.dumps(__SCREAMING_SNAKE_CASE  ) + "\n"  )

       def 		_SCREAMING_SNAKE_CASE(      self ,       **__SCREAMING_SNAKE_CASE  ):






        '''simple docstring'''

        snake_case__     				=					self.add_kwargs_tokens_map.copy()
        kwargs.update(__SCREAMING_SNAKE_CASE  )
        return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname ,       **__SCREAMING_SNAKE_CASE  )

       def 		_SCREAMING_SNAKE_CASE(      self ,       **__SCREAMING_SNAKE_CASE  ):






        '''simple docstring'''

        return WavaVecaFeatureExtractor.from_pretrained(self.tmpdirname ,       **__SCREAMING_SNAKE_CASE  )

       def 		_SCREAMING_SNAKE_CASE(      self  ):






        '''simple docstring'''

        shutil.rmtree(self.tmpdirname  )

       def 		_SCREAMING_SNAKE_CASE(      self  ):






        '''simple docstring'''

        snake_case__     				=					self.get_tokenizer()
        snake_case__     				=					self.get_feature_extractor()

        snake_case__     				=					WavaVecaProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,       feature_extractor=__SCREAMING_SNAKE_CASE  )

        processor.save_pretrained(self.tmpdirname  )
        snake_case__     				=					WavaVecaProcessor.from_pretrained(self.tmpdirname  )

        self.assertEqual(processor.tokenizer.get_vocab() ,       tokenizer.get_vocab()  )
        self.assertIsInstance(processor.tokenizer ,       __SCREAMING_SNAKE_CASE  )

        self.assertEqual(processor.feature_extractor.to_json_string() ,       feature_extractor.to_json_string()  )
        self.assertIsInstance(processor.feature_extractor ,       __SCREAMING_SNAKE_CASE  )

       def 		_SCREAMING_SNAKE_CASE(      self  ):






        '''simple docstring'''

        snake_case__     				=					WavaVecaProcessor(tokenizer=self.get_tokenizer() ,       feature_extractor=self.get_feature_extractor()  )
        processor.save_pretrained(self.tmpdirname  )

        snake_case__     				=					self.get_tokenizer(bos_token="(BOS)" ,       eos_token="(EOS)"  )
        snake_case__     				=					self.get_feature_extractor(do_normalize=__SCREAMING_SNAKE_CASE ,       padding_value=1.0  )

        snake_case__     				=					WavaVecaProcessor.from_pretrained(
            self.tmpdirname ,       bos_token="(BOS)" ,       eos_token="(EOS)" ,       do_normalize=__SCREAMING_SNAKE_CASE ,       padding_value=1.0  )

        self.assertEqual(processor.tokenizer.get_vocab() ,       tokenizer_add_kwargs.get_vocab()  )
        self.assertIsInstance(processor.tokenizer ,       __SCREAMING_SNAKE_CASE  )

        self.assertEqual(processor.feature_extractor.to_json_string() ,       feature_extractor_add_kwargs.to_json_string()  )
        self.assertIsInstance(processor.feature_extractor ,       __SCREAMING_SNAKE_CASE  )

       def 		_SCREAMING_SNAKE_CASE(      self  ):






        '''simple docstring'''

        snake_case__     				=					self.get_feature_extractor()
        snake_case__     				=					self.get_tokenizer()

        snake_case__     				=					WavaVecaProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,       feature_extractor=__SCREAMING_SNAKE_CASE  )

        snake_case__     				=					floats_list((3, 1000)  )

        snake_case__     				=					feature_extractor(__SCREAMING_SNAKE_CASE ,       return_tensors="np"  )
        snake_case__     				=					processor(__SCREAMING_SNAKE_CASE ,       return_tensors="np"  )

        for key in input_feat_extract.keys():
         self.assertAlmostEqual(input_feat_extract[key].sum() ,       input_processor[key].sum() ,       delta=1e-2  )

       def 		_SCREAMING_SNAKE_CASE(      self  ):






        '''simple docstring'''

        snake_case__     				=					self.get_feature_extractor()
        snake_case__     				=					self.get_tokenizer()

        snake_case__     				=					WavaVecaProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,       feature_extractor=__SCREAMING_SNAKE_CASE  )

        snake_case__     				=					"This is a test string"

        snake_case__     				=					processor(text=__SCREAMING_SNAKE_CASE  )

        snake_case__     				=					tokenizer(__SCREAMING_SNAKE_CASE  )

        for key in encoded_tok.keys():
         self.assertListEqual(encoded_tok[key] ,       encoded_processor[key]  )

       def 		_SCREAMING_SNAKE_CASE(      self  ):






        '''simple docstring'''

        snake_case__     				=					self.get_feature_extractor()
        snake_case__     				=					self.get_tokenizer()

        snake_case__     				=					WavaVecaProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,       feature_extractor=__SCREAMING_SNAKE_CASE  )

        snake_case__     				=					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        snake_case__     				=					processor.batch_decode(__SCREAMING_SNAKE_CASE  )
        snake_case__     				=					tokenizer.batch_decode(__SCREAMING_SNAKE_CASE  )

        self.assertListEqual(__SCREAMING_SNAKE_CASE ,       __SCREAMING_SNAKE_CASE  )

       def 		_SCREAMING_SNAKE_CASE(      self  ):






        '''simple docstring'''

        snake_case__     				=					self.get_feature_extractor()
        snake_case__     				=					self.get_tokenizer()

        snake_case__     				=					WavaVecaProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,       feature_extractor=__SCREAMING_SNAKE_CASE  )

        self.assertListEqual(
            processor.model_input_names ,       feature_extractor.model_input_names ,       msg="`processor` and `feature_extractor` model input names do not match" ,       )








"""simple docstring"""


a__       :  Optional[Any]       		=					{
    """A""": ("""ABCDEFGHIJKLM""", """NOPQRSTUVWXYZ"""),
    """B""": ("""ABCDEFGHIJKLM""", """NOPQRSTUVWXYZ"""),
    """C""": ("""ABCDEFGHIJKLM""", """ZNOPQRSTUVWXY"""),
    """D""": ("""ABCDEFGHIJKLM""", """ZNOPQRSTUVWXY"""),
    """E""": ("""ABCDEFGHIJKLM""", """YZNOPQRSTUVWX"""),
    """F""": ("""ABCDEFGHIJKLM""", """YZNOPQRSTUVWX"""),
    """G""": ("""ABCDEFGHIJKLM""", """XYZNOPQRSTUVW"""),
    """H""": ("""ABCDEFGHIJKLM""", """XYZNOPQRSTUVW"""),
    """I""": ("""ABCDEFGHIJKLM""", """WXYZNOPQRSTUV"""),
    """J""": ("""ABCDEFGHIJKLM""", """WXYZNOPQRSTUV"""),
    """K""": ("""ABCDEFGHIJKLM""", """VWXYZNOPQRSTU"""),
    """L""": ("""ABCDEFGHIJKLM""", """VWXYZNOPQRSTU"""),
    """M""": ("""ABCDEFGHIJKLM""", """UVWXYZNOPQRST"""),
    """N""": ("""ABCDEFGHIJKLM""", """UVWXYZNOPQRST"""),
    """O""": ("""ABCDEFGHIJKLM""", """TUVWXYZNOPQRS"""),
    """P""": ("""ABCDEFGHIJKLM""", """TUVWXYZNOPQRS"""),
    """Q""": ("""ABCDEFGHIJKLM""", """STUVWXYZNOPQR"""),
    """R""": ("""ABCDEFGHIJKLM""", """STUVWXYZNOPQR"""),
    """S""": ("""ABCDEFGHIJKLM""", """RSTUVWXYZNOPQ"""),
    """T""": ("""ABCDEFGHIJKLM""", """RSTUVWXYZNOPQ"""),
    """U""": ("""ABCDEFGHIJKLM""", """QRSTUVWXYZNOP"""),
    """V""": ("""ABCDEFGHIJKLM""", """QRSTUVWXYZNOP"""),
    """W""": ("""ABCDEFGHIJKLM""", """PQRSTUVWXYZNO"""),
    """X""": ("""ABCDEFGHIJKLM""", """PQRSTUVWXYZNO"""),
    """Y""": ("""ABCDEFGHIJKLM""", """OPQRSTUVWXYZN"""),
    """Z""": ("""ABCDEFGHIJKLM""", """OPQRSTUVWXYZN"""),
}





def 				a__      (	_UpperCAmelCase						)     ->	list[tuple[str, str]]:

 '''simple docstring'''






 return [alphabet[char] for char in key.upper()]





def 				a__      (	_UpperCAmelCase						,  _UpperCAmelCase						)     ->	str:

 '''simple docstring'''






 snake_case__     				=					""
 snake_case__     				=					0
 snake_case__     				=					generate_table(_UpperCAmelCase						)
 for char in words.upper():
  cipher += get_opponent(table[count]						,  _UpperCAmelCase						)
  snake_case__     				=					(count + 1) % len(_UpperCAmelCase						)
 return cipher





def 				a__      (	_UpperCAmelCase						,  _UpperCAmelCase						)     ->	str:

 '''simple docstring'''






 return encrypt(_UpperCAmelCase						,  _UpperCAmelCase						)





def 				a__      (	_UpperCAmelCase						,  _UpperCAmelCase						)     ->	tuple[int, int]:

 '''simple docstring'''






 snake_case__     				=					0 if char in table[0] else 1
 snake_case__     				=					table[row].index(_UpperCAmelCase						)
 return row, col





def 				a__      (	_UpperCAmelCase						,  _UpperCAmelCase						)     ->	str:

 '''simple docstring'''






 snake_case__				, snake_case__     				=					get_position(_UpperCAmelCase						,  char.upper()						)
 if row == 1:
  return table[0][col]
 else:
  return table[1][col] if row == 0 else char


if __name__ == "__main__":
   import doctest

   doctest.testmod()  # Fist ensure that all our tests are passing...
   a__       :  int       		=					input("""Enter key: """).strip()
   a__       :  Optional[int]       		=					input("""Enter text to encrypt: """).strip()
   a__       :  Dict       		=					encrypt(key, text)

   print(f'''Encrypted: {cipher_text}''')
   print(f'''Decrypted with key: {decrypt(key, cipher_text)}''')

