





"""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"""


import math





def 							a__     (					_UpperCAmelCase		)      ->					list:

 '''simple docstring'''






 if n <= 0:
  raise ValueError("Only positive integers have prime factors"		)
 snake_case__      							=			[]
 while n % 2 == 0:
  pf.append(2		)
  snake_case__      							=			int(n / 2		)
 for i in range(3		,       int(math.sqrt(_UpperCAmelCase		)		) + 1		,       2		):
  while n % i == 0:
   pf.append(_UpperCAmelCase		)
   snake_case__      							=			int(n / i		)
 if n > 2:
  pf.append(_UpperCAmelCase		)
 return pf





def 							a__     (					_UpperCAmelCase		)      ->					int:

 '''simple docstring'''






 if n <= 0:
  raise ValueError("Only positive numbers are accepted"		)
 snake_case__      							=			1
 snake_case__      							=			1
 while n % 2 == 0:
  temp += 1
  snake_case__      							=			int(n / 2		)
 div *= temp
 for i in range(3		,       int(math.sqrt(_UpperCAmelCase		)		) + 1		,       2		):
  snake_case__      							=			1
  while n % i == 0:
   temp += 1
   snake_case__      							=			int(n / i		)
  div *= temp
 if n > 1:
  div *= 2
 return div





def 							a__     (					_UpperCAmelCase		)      ->					int:

 '''simple docstring'''






 if n <= 0:
  raise ValueError("Only positive numbers are accepted"		)
 snake_case__      							=			1
 snake_case__      							=			1
 while n % 2 == 0:
  temp += 1
  snake_case__      							=			int(n / 2		)
 if temp > 1:
  s *= (2**temp - 1) / (2 - 1)
 for i in range(3		,       int(math.sqrt(_UpperCAmelCase		)		) + 1		,       2		):
  snake_case__      							=			1
  while n % i == 0:
   temp += 1
   snake_case__      							=			int(n / i		)
  if temp > 1:
   s *= (i**temp - 1) / (i - 1)
 return int(_UpperCAmelCase		)





def 							a__     (					_UpperCAmelCase		)      ->					int:

 '''simple docstring'''






 snake_case__      							=			n
 for x in set(prime_factors(_UpperCAmelCase		)		):
  s *= (x - 1) / x
 return int(_UpperCAmelCase		)


if __name__ == "__main__":
   import doctest

   doctest.testmod()

