

"""simple docstring"""






import json
import os
import shutil
import tempfile
import unittest

from transformers import is_speech_available, is_torch_available
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_torch
from transformers.utils import FEATURE_EXTRACTOR_NAME


if is_speech_available() and is_torch_available():
							from transformers import SpeechTaFeatureExtractor, SpeechTaProcessor

							from .test_feature_extraction_speechta import floats_list


__lowerCAmelCase				      =   get_tests_dir('''fixtures/test_sentencepiece_bpe_char.model''')
@require_torch
class 	_lowerCAmelCase    (      unittest.TestCase       ):

							def 					_lowerCAmelCase  ( self       :    Union[str, Any]    )   ->    Union[str, Any]:

									"""simple docstring"""
									lowercase										=							tempfile.mkdtemp()

									lowercase										=							SpeechTaTokenizer(a    )
									tokenizer.save_pretrained(self.tmpdirname    )

									lowercase										=							{
									    '''feature_size''': 1,
									    '''padding_value''': 0.0,
									    '''sampling_rate''': 16000,
									    '''do_normalize''': False,
									    '''num_mel_bins''': 80,
									    '''hop_length''': 16,
									    '''win_length''': 64,
									    '''win_function''': '''hann_window''',
									    '''fmin''': 80,
									    '''fmax''': 7600,
									    '''mel_floor''': 1E-10,
									    '''reduction_factor''': 2,
									    '''return_attention_mask''': True,
									}

									lowercase										=							os.path.join(self.tmpdirname ,		a    )
									with open(self.feature_extraction_file ,		'''w''' ,		encoding='''utf-8'''    ) as fp:
											fp.write(json.dumps(a    ) + '''\n'''    )

							def 					_lowerCAmelCase  ( self       :    Union[str, Any] ,		**a       :    List[Any]    )   ->    Any:

									"""simple docstring"""
									return SpeechTaTokenizer.from_pretrained(self.tmpdirname ,		**a    )

							def 					_lowerCAmelCase  ( self       :    str ,		**a       :    Tuple    )   ->    Optional[Any]:

									"""simple docstring"""
									return SpeechTaFeatureExtractor.from_pretrained(self.tmpdirname ,		**a    )

							def 					_lowerCAmelCase  ( self       :    Union[str, Any]    )   ->    str:

									"""simple docstring"""
									shutil.rmtree(self.tmpdirname    )

							def 					_lowerCAmelCase  ( self       :    List[Any]    )   ->    Optional[int]:

									"""simple docstring"""
									lowercase										=							self.get_tokenizer()
									lowercase										=							self.get_feature_extractor()

									lowercase										=							SpeechTaProcessor(tokenizer=a ,		feature_extractor=a    )

									processor.save_pretrained(self.tmpdirname    )
									lowercase										=							SpeechTaProcessor.from_pretrained(self.tmpdirname    )

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

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

							def 					_lowerCAmelCase  ( self       :    Tuple    )   ->    Union[str, Any]:

									"""simple docstring"""
									lowercase										=							SpeechTaProcessor(tokenizer=self.get_tokenizer() ,		feature_extractor=self.get_feature_extractor()    )
									processor.save_pretrained(self.tmpdirname    )

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

									lowercase										=							SpeechTaProcessor.from_pretrained(
									    self.tmpdirname ,		bos_token='''(BOS)''' ,		eos_token='''(EOS)''' ,		do_normalize=a ,		padding_value=1.0    )

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

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

							def 					_lowerCAmelCase  ( self       :    List[Any]    )   ->    Dict:

									"""simple docstring"""
									lowercase										=							self.get_feature_extractor()
									lowercase										=							self.get_tokenizer()

									lowercase										=							SpeechTaProcessor(tokenizer=a ,		feature_extractor=a    )

									lowercase										=							floats_list((3, 1000)    )

									lowercase										=							feature_extractor(audio=a ,		return_tensors='''np'''    )
									lowercase										=							processor(audio=a ,		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 					_lowerCAmelCase  ( self       :    List[str]    )   ->    Optional[Any]:

									"""simple docstring"""
									lowercase										=							self.get_feature_extractor()
									lowercase										=							self.get_tokenizer()

									lowercase										=							SpeechTaProcessor(tokenizer=a ,		feature_extractor=a    )

									lowercase										=							floats_list((3, 1000)    )

									lowercase										=							feature_extractor(audio_target=a ,		return_tensors='''np'''    )
									lowercase										=							processor(audio_target=a ,		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 					_lowerCAmelCase  ( self       :    Optional[Any]    )   ->    Optional[Any]:

									"""simple docstring"""
									lowercase										=							self.get_feature_extractor()
									lowercase										=							self.get_tokenizer()

									lowercase										=							SpeechTaProcessor(tokenizer=a ,		feature_extractor=a    )

									lowercase										=							'''This is a test string'''

									lowercase										=							processor(text=a    )
									lowercase										=							tokenizer(a    )

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

							def 					_lowerCAmelCase  ( self       :    List[Any]    )   ->    int:

									"""simple docstring"""
									lowercase										=							self.get_feature_extractor()
									lowercase										=							self.get_tokenizer()

									lowercase										=							SpeechTaProcessor(tokenizer=a ,		feature_extractor=a    )

									lowercase										=							'''This is a test string'''

									lowercase										=							processor(text_target=a    )
									lowercase										=							tokenizer(a    )

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

							def 					_lowerCAmelCase  ( self       :    Any    )   ->    Tuple:

									"""simple docstring"""
									lowercase										=							self.get_feature_extractor()
									lowercase										=							self.get_tokenizer()

									lowercase										=							SpeechTaProcessor(tokenizer=a ,		feature_extractor=a    )

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

									lowercase										=							processor.batch_decode(a    )
									lowercase										=							tokenizer.batch_decode(a    )

									self.assertListEqual(a ,		a    )

							def 					_lowerCAmelCase  ( self       :    List[Any]    )   ->    List[str]:

									"""simple docstring"""
									lowercase										=							self.get_feature_extractor()
									lowercase										=							self.get_tokenizer()

									lowercase										=							SpeechTaProcessor(tokenizer=a ,		feature_extractor=a    )

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







'''simple docstring'''


lowerCamelCase_					:			List[Any]     						=				{0: [1, 2], 1: [0, 3], 2: [0], 3: [1], 4: [5, 6], 5: [4, 6], 6: [4, 5]}

lowerCamelCase_					:			Tuple     						=				{0: [1, 2, 3], 1: [0, 3], 2: [0], 3: [0, 1], 4: [], 5: []}







def 						__magic_name__(			_A    ,   _A    ,   _A       ):
						'''simple docstring'''





						UpperCamelCase__       =			True
						UpperCamelCase__       =			[]

						for neighbour in graph[vert]:
												if not visited[neighbour]:
																		connected_verts += dfs(_A    ,   _A    ,   _A       )

						return [vert, *connected_verts]







def 						__magic_name__(			_A       ):
						'''simple docstring'''





						UpperCamelCase__       =			len(_A       )
						UpperCamelCase__       =			graph_size * [False]
						UpperCamelCase__       =			[]

						for i in range(_A       ):
												if not visited[i]:
																		UpperCamelCase__       =			dfs(_A    ,   _A    ,   _A       )
																		components_list.append(_A       )

						return components_list


if __name__ == "__main__":
					import doctest

					doctest.testmod()
