






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  __UpperCAmelCase						(unittest.TestCase       ):







			def 				UpperCamelCase (      self:    Any	):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE       =    """<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       =    dict(zip(lowercase__ ,      range(len(lowercase__	)	)	)	)

									_SCREAMING_SNAKE_CASE       =    {
									    """pad_token""": """<pad>""",
									    """unk_token""": """<unk>""",
									    """bos_token""": """<s>""",
									    """eos_token""": """</s>""",
									}
									_SCREAMING_SNAKE_CASE       =    {
									    """feature_size""": 1,
									    """padding_value""": 0.0,
									    """sampling_rate""": 16_000,
									    """return_attention_mask""": False,
									    """do_normalize""": True,
									}

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

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







			def 				UpperCamelCase (      self:    List[str] ,      **UpperCAmelCase_:    List[str]	):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE       =    self.add_kwargs_tokens_map.copy()
									kwargs.update(lowercase__	)
									return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname ,      **lowercase__	)







			def 				UpperCamelCase (      self:    Dict ,      **UpperCAmelCase_:    Tuple	):







									'''simple docstring'''




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







			def 				UpperCamelCase (      self:    Any	):







									'''simple docstring'''




									shutil.rmtree(self.tmpdirname	)







			def 				UpperCamelCase (      self:    Tuple	):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE       =    self.get_tokenizer()
									_SCREAMING_SNAKE_CASE       =    self.get_feature_extractor()

									_SCREAMING_SNAKE_CASE       =    WavaVecaProcessor(tokenizer=lowercase__ ,      feature_extractor=lowercase__	)

									processor.save_pretrained(self.tmpdirname	)
									_SCREAMING_SNAKE_CASE       =    WavaVecaProcessor.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 				UpperCamelCase (      self:    Optional[Any]	):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE       =    WavaVecaProcessor(tokenizer=self.get_tokenizer() ,      feature_extractor=self.get_feature_extractor()	)
									processor.save_pretrained(self.tmpdirname	)

									_SCREAMING_SNAKE_CASE       =    self.get_tokenizer(bos_token="""(BOS)""" ,      eos_token="""(EOS)"""	)
									_SCREAMING_SNAKE_CASE       =    self.get_feature_extractor(do_normalize=lowercase__ ,      padding_value=1.0	)

									_SCREAMING_SNAKE_CASE       =    WavaVecaProcessor.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 				UpperCamelCase (      self:    int	):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE       =    self.get_feature_extractor()
									_SCREAMING_SNAKE_CASE       =    self.get_tokenizer()

									_SCREAMING_SNAKE_CASE       =    WavaVecaProcessor(tokenizer=lowercase__ ,      feature_extractor=lowercase__	)

									_SCREAMING_SNAKE_CASE       =    floats_list((3, 1_000)	)

									_SCREAMING_SNAKE_CASE       =    feature_extractor(lowercase__ ,      return_tensors="""np"""	)
									_SCREAMING_SNAKE_CASE       =    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 				UpperCamelCase (      self:    Optional[int]	):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE       =    self.get_feature_extractor()
									_SCREAMING_SNAKE_CASE       =    self.get_tokenizer()

									_SCREAMING_SNAKE_CASE       =    WavaVecaProcessor(tokenizer=lowercase__ ,      feature_extractor=lowercase__	)

									_SCREAMING_SNAKE_CASE       =    """This is a test string"""

									_SCREAMING_SNAKE_CASE       =    processor(text=lowercase__	)

									_SCREAMING_SNAKE_CASE       =    tokenizer(lowercase__	)

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







			def 				UpperCamelCase (      self:    Optional[Any]	):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE       =    self.get_feature_extractor()
									_SCREAMING_SNAKE_CASE       =    self.get_tokenizer()

									_SCREAMING_SNAKE_CASE       =    WavaVecaProcessor(tokenizer=lowercase__ ,      feature_extractor=lowercase__	)

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

									_SCREAMING_SNAKE_CASE       =    processor.batch_decode(lowercase__	)
									_SCREAMING_SNAKE_CASE       =    tokenizer.batch_decode(lowercase__	)

									self.assertListEqual(lowercase__ ,      lowercase__	)







			def 				UpperCamelCase (      self:    Any	):







									'''simple docstring'''




									_SCREAMING_SNAKE_CASE       =    self.get_feature_extractor()
									_SCREAMING_SNAKE_CASE       =    self.get_tokenizer()

									_SCREAMING_SNAKE_CASE       =    WavaVecaProcessor(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""" ,      )









'''simple docstring'''







def     _UpperCamelCase				(  snake_case__				):
      if len(snake_case__				) <= 1:
            return data
      else:
            return [
                *quick_sort([e for e in data[1:] if e <= data[0]]				),
                data[0],
                *quick_sort([e for e in data[1:] if e > data[0]]				),
            ]


if __name__ == "__main__":
       import doctest

       doctest.testmod()


