'''simple docstring'''


import shutil
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import SpeechaTextTokenizer, is_speech_available
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, require_torchaudio
from transformers.utils import FEATURE_EXTRACTOR_NAME

from .test_feature_extraction_speech_to_text import floats_list


if is_speech_available():
 from transformers import SpeechaTextFeatureExtractor, SpeechaTextProcessor


snake_case__	:     str      =    get_tests_dir('''fixtures/test_sentencepiece.model''')






@require_torch
@require_torchaudio
@require_sentencepiece
class 	__SCREAMING_SNAKE_CASE		(			unittest.TestCase			):







  '''simple docstring'''






  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  Optional[int]  = tempfile.mkdtemp()

       UpperCAmelCase_				:  Union[str, Any]  = ['<s>', '<pad>', '</s>', '<unk>', '▁This', '▁is', '▁a', '▁t', 'est']
       UpperCAmelCase_				:  Tuple  = dict(zip(snake_case_ ,						range(len(snake_case_		)		)		)		)
       UpperCAmelCase_				:  Tuple  = Path(self.tmpdirname		)
       save_json(snake_case_ ,						save_dir / VOCAB_FILES_NAMES['vocab_file']		)
       if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
            copyfile(snake_case_ ,						save_dir / VOCAB_FILES_NAMES['spm_file']		)

       UpperCAmelCase_				:  List[str]  = SpeechaTextTokenizer.from_pretrained(self.tmpdirname		)
       tokenizer.save_pretrained(self.tmpdirname		)

       UpperCAmelCase_				:  str  = {
           'feature_size': 2_4,
           'num_mel_bins': 2_4,
           'padding_value': 0.0,
           'sampling_rate': 1_6_0_0_0,
           'return_attention_mask': False,
           'do_normalize': True,
       }
       save_json(snake_case_ ,						save_dir / FEATURE_EXTRACTOR_NAME		)


  def _UpperCamelCase	(					self ,						**snake_case_		):




       '''simple docstring'''

       return SpeechaTextTokenizer.from_pretrained(self.tmpdirname ,						**snake_case_		)


  def _UpperCamelCase	(					self ,						**snake_case_		):




       '''simple docstring'''

       return SpeechaTextFeatureExtractor.from_pretrained(self.tmpdirname ,						**snake_case_		)


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       shutil.rmtree(self.tmpdirname		)


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  int  = self.get_tokenizer()
       UpperCAmelCase_				:  int  = self.get_feature_extractor()

       UpperCAmelCase_				:  List[str]  = SpeechaTextProcessor(tokenizer=snake_case_ ,						feature_extractor=snake_case_		)

       processor.save_pretrained(self.tmpdirname		)
       UpperCAmelCase_				:  Dict  = SpeechaTextProcessor.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		):




       '''simple docstring'''

       UpperCAmelCase_				:  Tuple  = SpeechaTextProcessor(
           tokenizer=self.get_tokenizer() ,						feature_extractor=self.get_feature_extractor()		)
       processor.save_pretrained(self.tmpdirname		)

       UpperCAmelCase_				:  Optional[Any]  = self.get_tokenizer(bos_token='(BOS)' ,						eos_token='(EOS)'		)
       UpperCAmelCase_				:  Union[str, Any]  = self.get_feature_extractor(do_normalize=snake_case_ ,						padding_value=1.0		)

       UpperCAmelCase_				:  Any  = SpeechaTextProcessor.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		):




       '''simple docstring'''

       UpperCAmelCase_				:  List[Any]  = self.get_feature_extractor()
       UpperCAmelCase_				:  Union[str, Any]  = self.get_tokenizer()

       UpperCAmelCase_				:  Union[str, Any]  = SpeechaTextProcessor(tokenizer=snake_case_ ,						feature_extractor=snake_case_		)

       UpperCAmelCase_				:  List[Any]  = floats_list((3, 1_0_0_0)		)

       UpperCAmelCase_				:  Union[str, Any]  = feature_extractor(snake_case_ ,						return_tensors='np'		)
       UpperCAmelCase_				:  Any  = 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		):




       '''simple docstring'''

       UpperCAmelCase_				:  Union[str, Any]  = self.get_feature_extractor()
       UpperCAmelCase_				:  Tuple  = self.get_tokenizer()

       UpperCAmelCase_				:  Tuple  = SpeechaTextProcessor(tokenizer=snake_case_ ,						feature_extractor=snake_case_		)

       UpperCAmelCase_				:  Tuple  = 'This is a test string'

       UpperCAmelCase_				:  List[str]  = processor(text=snake_case_		)

       UpperCAmelCase_				:  Optional[int]  = tokenizer(snake_case_		)

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


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  Optional[Any]  = self.get_feature_extractor()
       UpperCAmelCase_				:  Dict  = self.get_tokenizer()

       UpperCAmelCase_				:  Any  = SpeechaTextProcessor(tokenizer=snake_case_ ,						feature_extractor=snake_case_		)

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

       UpperCAmelCase_				:  str  = processor.batch_decode(snake_case_		)
       UpperCAmelCase_				:  Union[str, Any]  = tokenizer.batch_decode(snake_case_		)

       self.assertListEqual(snake_case_ ,						snake_case_		)






  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  Optional[Any]  = self.get_feature_extractor()
       UpperCAmelCase_				:  Union[str, Any]  = self.get_tokenizer()

       UpperCAmelCase_				:  int  = SpeechaTextProcessor(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' ,						)







from hashlib import mda, shaaaa

__snake_case         =     (shaaaa, mda)







class       __snake_case :
 def __init__(	self		, snake_case__ = 8    )						->				None:
       '''simple docstring'''





       UpperCAmelCase     :			str     	=0b0
       UpperCAmelCase     :			str     	=size
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				None:
       '''simple docstring'''





       UpperCAmelCase     :			Union[str, Any]     	=self.hash_(snake_case__    )
       self.bitarray |= h
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				bool:
       '''simple docstring'''





       UpperCAmelCase     :			List[Any]     	=self.hash_(snake_case__    )
       return (h & self.bitarray) == h
 def __contains__(	self		, snake_case__    )						->				bool:
       '''simple docstring'''





       return self.exists(snake_case__    )
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				str:
       '''simple docstring'''





       UpperCAmelCase     :			Dict     	=bin(snake_case__    )[2:]
       return res.zfill(self.size    )
 @property
 def 						UpperCAmelCase__							(	self    )						->				str:
       '''simple docstring'''





       return self.format_bin(self.bitarray    )
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				int:
       '''simple docstring'''





       UpperCAmelCase     :			Union[str, Any]     	=0b0
       for func in HASH_FUNCTIONS:
             UpperCAmelCase     :			Optional[Any]     	=(
                 int.from_bytes(func(value.encode()    ).digest()		, '''little'''    ) % self.size
             )
             res |= 2**position
       return res
 def 						UpperCAmelCase__							(	self		, snake_case__    )						->				str:
       '''simple docstring'''





       return self.format_bin(self.hash_(snake_case__    )    )






 @property
 def 						UpperCAmelCase__							(	self    )						->				float:
       '''simple docstring'''





       UpperCAmelCase     :			int     	=bin(self.bitarray    ).count('''1'''    )
       return (n_ones / self.size) ** len(snake_case__    )
