



"""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    A_    (  unittest.TestCase       ):



						"""simple docstring"""






						def 			UpperCAmelCase__  (      self				:List[Any]      )       ->    Dict:
												UpperCAmelCase    =				'''<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(' '      )
												UpperCAmelCase    =				dict(zip(_snake_case     ,						range(len(_snake_case      )      )      )      )

												UpperCAmelCase    =				{
												    '''pad_token''': '''<pad>''',
												    '''unk_token''': '''<unk>''',
												    '''bos_token''': '''<s>''',
												    '''eos_token''': '''</s>''',
												}
												UpperCAmelCase    =				{
												    '''feature_size''': 1,
												    '''padding_value''': 0.0,
												    '''sampling_rate''': 1_60_00,
												    '''return_attention_mask''': False,
												    '''do_normalize''': True,
												}

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

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






						def 			UpperCAmelCase__  (      self				:Optional[int]     ,						**lowercase_				:Optional[Any]      )       ->    Optional[int]:
												UpperCAmelCase    =				self.add_kwargs_tokens_map.copy()
												kwargs.update(_snake_case      )
												return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname     ,						**_snake_case      )






						def 			UpperCAmelCase__  (      self				:Optional[int]     ,						**lowercase_				:Union[str, Any]      )       ->    List[str]:
												return WavaVecaFeatureExtractor.from_pretrained(self.tmpdirname     ,						**_snake_case      )






						def 			UpperCAmelCase__  (      self				:Union[str, Any]      )       ->    Optional[Any]:
												shutil.rmtree(self.tmpdirname      )






						def 			UpperCAmelCase__  (      self				:Optional[Any]      )       ->    List[str]:
												UpperCAmelCase    =				self.get_tokenizer()
												UpperCAmelCase    =				self.get_feature_extractor()

												UpperCAmelCase    =				WavaVecaProcessor(tokenizer=_snake_case     ,						feature_extractor=_snake_case      )

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

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

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






						def 			UpperCAmelCase__  (      self				:Optional[int]      )       ->    Optional[int]:
												UpperCAmelCase    =				WavaVecaProcessor(tokenizer=self.get_tokenizer()     ,						feature_extractor=self.get_feature_extractor()      )
												processor.save_pretrained(self.tmpdirname      )

												UpperCAmelCase    =				self.get_tokenizer(bos_token='(BOS)'     ,						eos_token='(EOS)'      )
												UpperCAmelCase    =				self.get_feature_extractor(do_normalize=_snake_case     ,						padding_value=1.0      )

												UpperCAmelCase    =				WavaVecaProcessor.from_pretrained(
												    self.tmpdirname     ,						bos_token='(BOS)'     ,						eos_token='(EOS)'     ,						do_normalize=_snake_case     ,						padding_value=1.0      )

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

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






						def 			UpperCAmelCase__  (      self				:str      )       ->    List[Any]:
												UpperCAmelCase    =				self.get_feature_extractor()
												UpperCAmelCase    =				self.get_tokenizer()

												UpperCAmelCase    =				WavaVecaProcessor(tokenizer=_snake_case     ,						feature_extractor=_snake_case      )

												UpperCAmelCase    =				floats_list((3, 10_00)      )

												UpperCAmelCase    =				feature_extractor(_snake_case     ,						return_tensors='np'      )
												UpperCAmelCase    =				processor(_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 			UpperCAmelCase__  (      self				:List[Any]      )       ->    Optional[int]:
												UpperCAmelCase    =				self.get_feature_extractor()
												UpperCAmelCase    =				self.get_tokenizer()

												UpperCAmelCase    =				WavaVecaProcessor(tokenizer=_snake_case     ,						feature_extractor=_snake_case      )

												UpperCAmelCase    =				'''This is a test string'''

												UpperCAmelCase    =				processor(text=_snake_case      )

												UpperCAmelCase    =				tokenizer(_snake_case      )

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






						def 			UpperCAmelCase__  (      self				:Dict      )       ->    Optional[Any]:
												UpperCAmelCase    =				self.get_feature_extractor()
												UpperCAmelCase    =				self.get_tokenizer()

												UpperCAmelCase    =				WavaVecaProcessor(tokenizer=_snake_case     ,						feature_extractor=_snake_case      )

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

												UpperCAmelCase    =				processor.batch_decode(_snake_case      )
												UpperCAmelCase    =				tokenizer.batch_decode(_snake_case      )

												self.assertListEqual(_snake_case     ,						_snake_case      )






						def 			UpperCAmelCase__  (      self				:List[str]      )       ->    Tuple:
												UpperCAmelCase    =				self.get_feature_extractor()
												UpperCAmelCase    =				self.get_tokenizer()

												UpperCAmelCase    =				WavaVecaProcessor(tokenizer=_snake_case     ,						feature_extractor=_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"""


def 				_lowerCAmelCase   (     lowercase_	,			lowercase_		):
						UpperCAmelCase    =				1.0
						for i in range(1	,			r + 1		):
												ret *= (n + 1 - i) / i
						return round(lowercase_		)

def 				_lowerCAmelCase   (     lowercase_		):
						return choose(8 + n	,			lowercase_		) + choose(9 + n	,			lowercase_		) - 10

def 				_lowerCAmelCase   (     lowercase_		):
						return sum(non_bouncy_exact(lowercase_		) for i in range(1	,			n + 1		)		)

def 				_lowerCAmelCase   (     lowercase_ = 100		):
						return non_bouncy_upto(lowercase_		)


if __name__ == "__main__":
				print(f'''{solution() = }''')





