



'''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 				__lowerCAmelCase(							unittest.TestCase      ):






			def 				_lowercase	(   self  :							Union[str, Any]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      '<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(' '	)
					SCREAMING_SNAKE_CASE_						:Tuple										=      dict(zip(SCREAMING_SNAKE_CASE      ,       range(len(SCREAMING_SNAKE_CASE	)	)	)	)

					SCREAMING_SNAKE_CASE_						:List[str]										=      {
					    'pad_token': '<pad>',
					    'unk_token': '<unk>',
					    'bos_token': '<s>',
					    'eos_token': '</s>',
					}
					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      {
					    'feature_size': 1,
					    'padding_value': 0.0,
					    'sampling_rate': 16_000,
					    'return_attention_mask': False,
					    'do_normalize': True,
					}

					SCREAMING_SNAKE_CASE_						:Optional[int]										=      tempfile.mkdtemp()
					SCREAMING_SNAKE_CASE_						:int										=      os.path.join(self.tmpdirname      ,       VOCAB_FILES_NAMES['vocab_file']	)
					SCREAMING_SNAKE_CASE_						:List[str]										=      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 				_lowercase	(   self  :							Tuple      ,       **SCREAMING_SNAKE_CASE  :							List[Any]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Optional[int]										=      self.add_kwargs_tokens_map.copy()
					kwargs.update(SCREAMING_SNAKE_CASE	)
					return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname      ,       **SCREAMING_SNAKE_CASE	)






			def 				_lowercase	(   self  :							List[Any]      ,       **SCREAMING_SNAKE_CASE  :							List[Any]	):




					"""simple docstring"""







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






			def 				_lowercase	(   self  :							Union[str, Any]	):




					"""simple docstring"""







					shutil.rmtree(self.tmpdirname	)






			def 				_lowercase	(   self  :							Tuple	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      self.get_tokenizer()
					SCREAMING_SNAKE_CASE_						:Dict										=      self.get_feature_extractor()

					SCREAMING_SNAKE_CASE_						:Optional[int]										=      WavaVecaProcessor(tokenizer=SCREAMING_SNAKE_CASE      ,       feature_extractor=SCREAMING_SNAKE_CASE	)

					processor.save_pretrained(self.tmpdirname	)
					SCREAMING_SNAKE_CASE_						:Any										=      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 				_lowercase	(   self  :							Optional[Any]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:List[str]										=      WavaVecaProcessor(tokenizer=self.get_tokenizer()      ,       feature_extractor=self.get_feature_extractor()	)
					processor.save_pretrained(self.tmpdirname	)

					SCREAMING_SNAKE_CASE_						:str										=      self.get_tokenizer(bos_token='(BOS)'      ,       eos_token='(EOS)'	)
					SCREAMING_SNAKE_CASE_						:Tuple										=      self.get_feature_extractor(do_normalize=SCREAMING_SNAKE_CASE      ,       padding_value=1.0	)

					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      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 				_lowercase	(   self  :							List[Any]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:List[str]										=      self.get_feature_extractor()
					SCREAMING_SNAKE_CASE_						:Any										=      self.get_tokenizer()

					SCREAMING_SNAKE_CASE_						:List[Any]										=      WavaVecaProcessor(tokenizer=SCREAMING_SNAKE_CASE      ,       feature_extractor=SCREAMING_SNAKE_CASE	)

					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      floats_list((3, 1_000)	)

					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      feature_extractor(SCREAMING_SNAKE_CASE      ,       return_tensors='np'	)
					SCREAMING_SNAKE_CASE_						:int										=      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 				_lowercase	(   self  :							Optional[Any]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Dict										=      self.get_feature_extractor()
					SCREAMING_SNAKE_CASE_						:Tuple										=      self.get_tokenizer()

					SCREAMING_SNAKE_CASE_						:Tuple										=      WavaVecaProcessor(tokenizer=SCREAMING_SNAKE_CASE      ,       feature_extractor=SCREAMING_SNAKE_CASE	)

					SCREAMING_SNAKE_CASE_						:str										=      'This is a test string'

					SCREAMING_SNAKE_CASE_						:int										=      processor(text=SCREAMING_SNAKE_CASE	)

					SCREAMING_SNAKE_CASE_						:Any										=      tokenizer(SCREAMING_SNAKE_CASE	)

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






			def 				_lowercase	(   self  :							Any	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Any										=      self.get_feature_extractor()
					SCREAMING_SNAKE_CASE_						:List[Any]										=      self.get_tokenizer()

					SCREAMING_SNAKE_CASE_						:int										=      WavaVecaProcessor(tokenizer=SCREAMING_SNAKE_CASE      ,       feature_extractor=SCREAMING_SNAKE_CASE	)

					SCREAMING_SNAKE_CASE_						:Dict										=      [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

					SCREAMING_SNAKE_CASE_						:int										=      processor.batch_decode(SCREAMING_SNAKE_CASE	)
					SCREAMING_SNAKE_CASE_						:Any										=      tokenizer.batch_decode(SCREAMING_SNAKE_CASE	)

					self.assertListEqual(SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE	)






			def 				_lowercase	(   self  :							Tuple	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Any										=      self.get_feature_extractor()
					SCREAMING_SNAKE_CASE_						:str										=      self.get_tokenizer()

					SCREAMING_SNAKE_CASE_						:Dict										=      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'''







def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE = 1000     ):
		return sum(i for i in range(SCREAMING_SNAKE_CASE     ) if i % 3 == 0 or i % 5 == 0     )


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