






'''simple docstring'''





from collections import namedtuple

lowerCamelCase_		  =						namedtuple("""from_to""", """from_ to""")

lowerCamelCase_		  =						{
    """atm""": from_to(1, 1),
    """pascal""": from_to(0.0000098, 1_0_1_3_2_5),
    """bar""": from_to(0.986923, 1.01325),
    """kilopascal""": from_to(0.00986923, 101.325),
    """megapascal""": from_to(9.86923, 0.101325),
    """psi""": from_to(0.068046, 14.6959),
    """inHg""": from_to(0.0334211, 29.9213),
    """torr""": from_to(0.00131579, 7_6_0),
}
def   lowerCamelCase      (		a_				,		a_				,		a_			)			->    float:
							if from_type not in PRESSURE_CONVERSION:
														raise ValueError(
														    F'''Invalid \'from_type\' value: {from_type!r}  Supported values are:\n'''
														    + ', '.join(a_			)			)
							if to_type not in PRESSURE_CONVERSION:
														raise ValueError(
														    F'''Invalid \'to_type\' value: {to_type!r}.  Supported values are:\n'''
														    + ', '.join(a_			)			)
							return (
							    value * PRESSURE_CONVERSION[from_type].from_ * PRESSURE_CONVERSION[to_type].to
							)


if __name__ == "__main__":
		import doctest

		doctest.testmod()











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


lowerCamelCase_		  =						get_tests_dir("""fixtures/test_sentencepiece.model""")




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


							'''simple docstring'''






							def   _lowercase (	self     )      ->      Optional[int]:
														'''simple docstring'''

														lowerCAmelCase_       		=  tempfile.mkdtemp()

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

														lowerCAmelCase_       		=  SpeechaTextTokenizer.from_pretrained(self.tmpdirname     )
														tokenizer.save_pretrained(self.tmpdirname     )

														lowerCAmelCase_       		=  {
														    '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(lowercase_    ,    save_dir / FEATURE_EXTRACTOR_NAME     )

							def   _lowercase (	self    ,    **lowercase_     )      ->      List[Any]:
														'''simple docstring'''

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

							def   _lowercase (	self    ,    **lowercase_     )      ->      Optional[Any]:
														'''simple docstring'''

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

							def   _lowercase (	self     )      ->      List[Any]:
														'''simple docstring'''

														shutil.rmtree(self.tmpdirname     )

							def   _lowercase (	self     )      ->      List[Any]:
														'''simple docstring'''

														lowerCAmelCase_       		=  self.get_tokenizer()
														lowerCAmelCase_       		=  self.get_feature_extractor()

														lowerCAmelCase_       		=  SpeechaTextProcessor(tokenizer=lowercase_    ,    feature_extractor=lowercase_     )

														processor.save_pretrained(self.tmpdirname     )
														lowerCAmelCase_       		=  SpeechaTextProcessor.from_pretrained(self.tmpdirname     )

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

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

							def   _lowercase (	self     )      ->      Union[str, Any]:
														'''simple docstring'''

														lowerCAmelCase_       		=  SpeechaTextProcessor(
														    tokenizer=self.get_tokenizer()    ,    feature_extractor=self.get_feature_extractor()     )
														processor.save_pretrained(self.tmpdirname     )

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

														lowerCAmelCase_       		=  SpeechaTextProcessor.from_pretrained(
														    self.tmpdirname    ,    bos_token='(BOS)'    ,    eos_token='(EOS)'    ,    do_normalize=lowercase_    ,    padding_value=1.0     )

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

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

							def   _lowercase (	self     )      ->      Dict:
														'''simple docstring'''

														lowerCAmelCase_       		=  self.get_feature_extractor()
														lowerCAmelCase_       		=  self.get_tokenizer()

														lowerCAmelCase_       		=  SpeechaTextProcessor(tokenizer=lowercase_    ,    feature_extractor=lowercase_     )

														lowerCAmelCase_       		=  floats_list((3, 1_0_0_0)     )

														lowerCAmelCase_       		=  feature_extractor(lowercase_    ,    return_tensors='np'     )
														lowerCAmelCase_       		=  processor(lowercase_    ,    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     )      ->      Union[str, Any]:
														'''simple docstring'''

														lowerCAmelCase_       		=  self.get_feature_extractor()
														lowerCAmelCase_       		=  self.get_tokenizer()

														lowerCAmelCase_       		=  SpeechaTextProcessor(tokenizer=lowercase_    ,    feature_extractor=lowercase_     )

														lowerCAmelCase_       		=  'This is a test string'

														lowerCAmelCase_       		=  processor(text=lowercase_     )

														lowerCAmelCase_       		=  tokenizer(lowercase_     )

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

							def   _lowercase (	self     )      ->      Any:
														'''simple docstring'''

														lowerCAmelCase_       		=  self.get_feature_extractor()
														lowerCAmelCase_       		=  self.get_tokenizer()

														lowerCAmelCase_       		=  SpeechaTextProcessor(tokenizer=lowercase_    ,    feature_extractor=lowercase_     )

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

														lowerCAmelCase_       		=  processor.batch_decode(lowercase_     )
														lowerCAmelCase_       		=  tokenizer.batch_decode(lowercase_     )

														self.assertListEqual(lowercase_    ,    lowercase_     )






							def   _lowercase (	self     )      ->      Optional[Any]:
														'''simple docstring'''

														lowerCAmelCase_       		=  self.get_feature_extractor()
														lowerCAmelCase_       		=  self.get_tokenizer()

														lowerCAmelCase_       		=  SpeechaTextProcessor(tokenizer=lowercase_    ,    feature_extractor=lowercase_     )

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



