
import unittest

from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase__		:     Optional[int]     			=      get_tests_dir('fixtures/test_sentencepiece_bpe_char.model')






@require_sentencepiece
@require_tokenizers
class UpperCAmelCase   (						SCREAMING_SNAKE_CASE__							,							unittest.TestCase   ):





   '''simple docstring'''
   __UpperCamelCase		:    Optional[Any] 				=    SpeechTaTokenizer
   __UpperCamelCase		:    Union[str, Any] 				=    False
   __UpperCamelCase		:    List[str] 				=    True


   def  __magic_name__				(					self     :							Dict     ):

      """simple docstring"""
      super().setUp()

      # We have a SentencePiece fixture for testing
      _A:  str					=       SpeechTaTokenizer(lowerCAmelCase_     )

      _A:  Dict					=       AddedToken('''<mask>'''			,			lstrip=lowerCAmelCase_			,			rstrip=lowerCAmelCase_     )
      _A:  Tuple					=       mask_token
      tokenizer.add_special_tokens({'''mask_token''': mask_token}     )
      tokenizer.add_tokens(['''<ctc_blank>''']     )

      tokenizer.save_pretrained(self.tmpdirname     )


   def  __magic_name__				(					self     :							int			,			lowerCAmelCase_     :							List[str]     ):

      """simple docstring"""
      _A:  List[str]					=       '''this is a test'''
      _A:  str					=       '''this is a test'''
      return input_text, output_text


   def  __magic_name__				(					self     :							int			,			lowerCAmelCase_     :							List[str]			,			lowerCAmelCase_     :							List[Any]=False			,			lowerCAmelCase_     :							Union[str, Any]=2_0			,			lowerCAmelCase_     :							Optional[Any]=5     ):

      """simple docstring"""
      _A			,  _A:  Dict					=       self.get_input_output_texts(lowerCAmelCase_     )
      _A:  Tuple					=       tokenizer.encode(lowerCAmelCase_			,			add_special_tokens=lowerCAmelCase_     )
      _A:  Union[str, Any]					=       tokenizer.decode(lowerCAmelCase_			,			clean_up_tokenization_spaces=lowerCAmelCase_     )
      return text, ids


   def  __magic_name__				(					self     :							List[Any]     ):

      """simple docstring"""
      _A:  Any					=       '''<pad>'''
      _A:  List[Any]					=       1

      self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase_     )			,			lowerCAmelCase_     )
      self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase_     )			,			lowerCAmelCase_     )


   def  __magic_name__				(					self     :							List[str]     ):

      """simple docstring"""
      _A:  List[Any]					=       list(self.get_tokenizer().get_vocab().keys()     )

      self.assertEqual(vocab_keys[0]			,			'''<s>'''     )
      self.assertEqual(vocab_keys[1]			,			'''<pad>'''     )
      self.assertEqual(vocab_keys[-4]			,			'''œ'''     )
      self.assertEqual(vocab_keys[-2]			,			'''<mask>'''     )
      self.assertEqual(vocab_keys[-1]			,			'''<ctc_blank>'''     )
      self.assertEqual(len(lowerCAmelCase_     )			,			8_1     )


   def  __magic_name__				(					self     :							List[Any]     ):

      """simple docstring"""
      self.assertEqual(self.get_tokenizer().vocab_size			,			7_9     )


   def  __magic_name__				(					self     :							List[str]     ):

      """simple docstring"""
      _A:  List[Any]					=       self.get_tokenizers(do_lower_case=lowerCAmelCase_     )
      for tokenizer in tokenizers:
         with self.subTest(F"""{tokenizer.__class__.__name__}"""     ):
            _A:  Any					=       tokenizer.vocab_size
            _A:  List[Any]					=       len(lowerCAmelCase_     )

            self.assertNotEqual(lowerCAmelCase_			,			0     )

            # We usually have added tokens from the start in tests because our vocab fixtures are
            # smaller than the original vocabs - let's not assert this
            # self.assertEqual(vocab_size, all_size)

            _A:  Tuple					=       ['''aaaaa bbbbbb''', '''cccccccccdddddddd''']
            _A:  Tuple					=       tokenizer.add_tokens(lowerCAmelCase_     )
            _A:  Any					=       tokenizer.vocab_size
            _A:  Tuple					=       len(lowerCAmelCase_     )

            self.assertNotEqual(lowerCAmelCase_			,			0     )
            self.assertEqual(lowerCAmelCase_			,			lowerCAmelCase_     )
            self.assertEqual(lowerCAmelCase_			,			len(lowerCAmelCase_     )     )
            self.assertEqual(lowerCAmelCase_			,			all_size + len(lowerCAmelCase_     )     )

            _A:  str					=       tokenizer.encode('''aaaaa bbbbbb low cccccccccdddddddd l'''			,			add_special_tokens=lowerCAmelCase_     )

            self.assertGreaterEqual(len(lowerCAmelCase_     )			,			4     )
            self.assertGreater(tokens[0]			,			tokenizer.vocab_size - 1     )
            self.assertGreater(tokens[-3]			,			tokenizer.vocab_size - 1     )

            _A:  Union[str, Any]					=       {'''eos_token''': '''>>>>|||<||<<|<<''', '''pad_token''': '''<<<<<|||>|>>>>|>'''}
            _A:  Union[str, Any]					=       tokenizer.add_special_tokens(lowerCAmelCase_     )
            _A:  Dict					=       tokenizer.vocab_size
            _A:  str					=       len(lowerCAmelCase_     )

            self.assertNotEqual(lowerCAmelCase_			,			0     )
            self.assertEqual(lowerCAmelCase_			,			lowerCAmelCase_     )
            self.assertEqual(lowerCAmelCase_			,			len(lowerCAmelCase_     )     )
            self.assertEqual(lowerCAmelCase_			,			all_size_a + len(lowerCAmelCase_     )     )

            _A:  str					=       tokenizer.encode(
                '''>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l'''			,			add_special_tokens=lowerCAmelCase_     )

            self.assertGreaterEqual(len(lowerCAmelCase_     )			,			6     )
            self.assertGreater(tokens[0]			,			tokenizer.vocab_size - 1     )
            self.assertGreater(tokens[0]			,			tokens[1]     )
            self.assertGreater(tokens[-3]			,			tokenizer.vocab_size - 1     )
            self.assertGreater(tokens[-3]			,			tokens[-4]     )
            self.assertEqual(tokens[0]			,			tokenizer.eos_token_id     )
            self.assertEqual(tokens[-3]			,			tokenizer.pad_token_id     )


   def  __magic_name__				(					self     :							Any     ):

      """simple docstring"""
      pass


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

      """simple docstring"""
      pass


   def  __magic_name__				(					self     :							List[str]     ):

      """simple docstring"""
      _A:  Union[str, Any]					=       self.get_tokenizer()

      _A:  List[str]					=       tokenizer.tokenize('''This is a test'''     )
      # fmt: off
      self.assertListEqual(lowerCAmelCase_			,			[SPIECE_UNDERLINE, '''T''', '''h''', '''i''', '''s''', SPIECE_UNDERLINE, '''i''', '''s''', SPIECE_UNDERLINE, '''a''', SPIECE_UNDERLINE, '''t''', '''e''', '''s''', '''t''']     )
      # fmt: on

      self.assertListEqual(
          tokenizer.convert_tokens_to_ids(lowerCAmelCase_     )			,			[4, 3_2, 1_1, 1_0, 1_2, 4, 1_0, 1_2, 4, 7, 4, 6, 5, 1_2, 6]			,			)

      _A:  Tuple					=       tokenizer.tokenize('''I was born in 92000, and this is falsé.'''     )
      self.assertListEqual(
          lowerCAmelCase_			,			[SPIECE_UNDERLINE, '''I''', SPIECE_UNDERLINE, '''w''', '''a''', '''s''', SPIECE_UNDERLINE, '''b''', '''o''', '''r''', '''n''', SPIECE_UNDERLINE, '''i''', '''n''', SPIECE_UNDERLINE, '''92000''', ''',''', SPIECE_UNDERLINE, '''a''', '''n''', '''d''', SPIECE_UNDERLINE, '''t''', '''h''', '''i''', '''s''', SPIECE_UNDERLINE, '''i''', '''s''', SPIECE_UNDERLINE, '''f''', '''a''', '''l''', '''s''', '''é''', '''.''']     )

      _A:  List[Any]					=       tokenizer.convert_tokens_to_ids(lowerCAmelCase_     )
      # fmt: off
      self.assertListEqual(lowerCAmelCase_			,			[4, 3_0, 4, 2_0, 7, 1_2, 4, 2_5, 8, 1_3, 9, 4, 1_0, 9, 4, 3, 2_3, 4, 7, 9, 1_4, 4, 6, 1_1, 1_0, 1_2, 4, 1_0, 1_2, 4, 1_9, 7, 1_5, 1_2, 7_3, 2_6]     )
      # fmt: on

      _A:  Optional[int]					=       tokenizer.convert_ids_to_tokens(lowerCAmelCase_     )
      self.assertListEqual(
          lowerCAmelCase_			,			[SPIECE_UNDERLINE, '''I''', SPIECE_UNDERLINE, '''w''', '''a''', '''s''', SPIECE_UNDERLINE, '''b''', '''o''', '''r''', '''n''', SPIECE_UNDERLINE, '''i''', '''n''', SPIECE_UNDERLINE, '''<unk>''', ''',''', SPIECE_UNDERLINE, '''a''', '''n''', '''d''', SPIECE_UNDERLINE, '''t''', '''h''', '''i''', '''s''', SPIECE_UNDERLINE, '''i''', '''s''', SPIECE_UNDERLINE, '''f''', '''a''', '''l''', '''s''', '''é''', '''.''']     )


   @slow
   def  __magic_name__				(					self     :							Dict     ):

      """simple docstring"""
      # Use custom sequence because this tokenizer does not handle numbers.
      _A:  List[str]					=       [
          '''Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides '''
          '''general-purpose architectures (BERT, GPT, RoBERTa, XLM, DistilBert, XLNet...) for Natural '''
          '''Language Understanding (NLU) and Natural Language Generation (NLG) with over thirty-two pretrained '''
          '''models in one hundred plus languages and deep interoperability between Jax, PyTorch and TensorFlow.''',
          '''BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly '''
          '''conditioning on both left and right context in all layers.''',
          '''The quick brown fox jumps over the lazy dog.''',
      ]

      # fmt: off
      _A:  List[str]					=       {
          '''input_ids''': [
              [4, 3_2, 1_3, 7, 9, 1_2, 1_9, 8, 1_3, 1_8, 5, 1_3, 1_2, 4, 6_4, 1_9, 8, 1_3, 1_8, 5, 1_3, 1_5, 2_2, 4, 2_8, 9, 8, 2_0, 9, 4, 7, 1_2, 4, 2_4, 2_2, 6, 8, 1_3, 1_7, 1_1, 3_9, 6, 1_3, 7, 9, 1_2, 1_9, 8, 1_3, 1_8, 5, 1_3, 1_2, 4, 7, 9, 1_4, 4, 2_4, 2_2, 6, 8, 1_3, 1_7, 1_1, 3_9, 2_4, 1_3, 5, 6, 1_3, 7, 1_0, 9, 5, 1_4, 3_9, 2_5, 5, 1_3, 6, 6_3, 4, 2_4, 1_3, 8, 2_7, 1_0, 1_4, 5, 1_2, 4, 2_1, 5, 9, 5, 1_3, 7, 1_5, 3_9, 2_4, 1_6, 1_3, 2_4, 8, 1_2, 5, 4, 7, 1_3, 1_7, 1_1, 1_0, 6, 5, 1_7, 6, 1_6, 1_3, 5, 1_2, 4, 6_4, 4_0, 4_7, 5_4, 3_2, 2_3, 4, 5_3, 4_9, 3_2, 2_3, 4, 5_4, 8, 4_0, 4_7, 5_4, 3_2, 7, 2_3, 4, 6_9, 5_2, 4_3, 2_3, 4, 5_1, 1_0, 1_2, 6, 1_0, 1_5, 4_0, 5, 1_3, 6, 2_3, 4, 6_9, 5_2, 4_8, 5, 6, 2_6, 2_6, 2_6, 6_3, 4, 1_9, 8, 1_3, 4, 4_8, 7, 6, 1_6, 1_3, 7, 1_5, 4, 5_2, 7, 9, 2_1, 1_6, 7, 2_1, 5, 4, 6_1, 9, 1_4, 5, 1_3, 1_2, 6, 7, 9, 1_4, 1_0, 9, 2_1, 4, 6_4, 4_8, 5_2, 6_1, 6_3, 4, 7, 9, 1_4, 4, 4_8, 7, 6, 1_6, 1_3, 7, 1_5, 4, 5_2, 7, 9, 2_1, 1_6, 7, 2_1, 5, 4, 5_3, 5, 9, 5, 1_3, 7, 6, 1_0, 8, 9, 4, 6_4, 4_8, 5_2, 5_3, 6_3, 4, 2_0, 1_0, 6, 1_1, 4, 8, 2_7, 5, 1_3, 4, 6, 1_1, 1_0, 1_3, 6, 2_2, 3_9, 6, 2_0, 8, 4, 2_4, 1_3, 5, 6, 1_3, 7, 1_0, 9, 5, 1_4, 4, 1_8, 8, 1_4, 5, 1_5, 1_2, 4, 1_0, 9, 4, 8, 9, 5, 4, 1_1, 1_6, 9, 1_4, 1_3, 5, 1_4, 4, 2_4, 1_5, 1_6, 1_2, 4, 1_5, 7, 9, 2_1, 1_6, 7, 2_1, 5, 1_2, 4, 7, 9, 1_4, 4, 1_4, 5, 5, 2_4, 4, 1_0, 9, 6, 5, 1_3, 8, 2_4, 5, 1_3, 7, 2_5, 1_0, 1_5, 1_0, 6, 2_2, 4, 2_5, 5, 6, 2_0, 5, 5, 9, 4, 5_8, 7, 3_7, 2_3, 4, 4_9, 2_2, 3_2, 8, 1_3, 1_7, 1_1, 4, 7, 9, 1_4, 4, 3_2, 5, 9, 1_2, 8, 1_3, 5_5, 1_5, 8, 2_0, 2_6, 2],
              [4, 4_0, 4_7, 5_4, 3_2, 4, 1_0, 1_2, 4, 1_4, 5, 1_2, 1_0, 2_1, 9, 5, 1_4, 4, 6, 8, 4, 2_4, 1_3, 5, 3_9, 6, 1_3, 7, 1_0, 9, 4, 1_4, 5, 5, 2_4, 4, 2_5, 1_0, 1_4, 1_0, 1_3, 5, 1_7, 6, 1_0, 8, 9, 7, 1_5, 4, 1_3, 5, 2_4, 1_3, 5, 1_2, 5, 9, 6, 7, 6, 1_0, 8, 9, 1_2, 4, 1_9, 1_3, 8, 1_8, 4, 1_6, 9, 1_5, 7, 2_5, 5, 1_5, 5, 1_4, 4, 6, 5, 3_7, 6, 4, 2_5, 2_2, 4, 4_6, 8, 1_0, 9, 6, 1_5, 2_2, 4, 1_7, 8, 9, 1_4, 1_0, 6, 1_0, 8, 9, 1_0, 9, 2_1, 4, 8, 9, 4, 2_5, 8, 6, 1_1, 4, 1_5, 5, 1_9, 6, 4, 7, 9, 1_4, 4, 1_3, 1_0, 2_1, 1_1, 6, 4, 1_7, 8, 9, 6, 5, 3_7, 6, 4, 1_0, 9, 4, 7, 1_5, 1_5, 4, 1_5, 7, 2_2, 5, 1_3, 1_2, 2_6, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
              [4, 3_2, 1_1, 5, 4, 4_5, 1_6, 1_0, 1_7, 2_8, 4, 2_5, 1_3, 8, 2_0, 9, 4, 1_9, 8, 3_7, 4, 4_6, 1_6, 1_8, 2_4, 1_2, 4, 8, 2_7, 5, 1_3, 4, 6, 1_1, 5, 4, 1_5, 7, 5_7, 2_2, 4, 1_4, 8, 2_1, 2_6, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
          ],
          '''attention_mask''': [
              [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
              [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
              [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
          ]
      }
      # fmt: on

      self.tokenizer_integration_test_util(
          expected_encoding=lowerCAmelCase_			,			model_name='''microsoft/speecht5_asr'''			,			revision='''c5ef64c71905caeccde0e4462ef3f9077224c524'''			,			sequences=lowerCAmelCase_			,			)





import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict






@pytest.mark.parametrize(
    '''files'''		,		[
        ['''full:README.md''', '''dataset_infos.json'''],
        ['''empty:README.md''', '''dataset_infos.json'''],
        ['''dataset_infos.json'''],
        ['''full:README.md'''],
    ]		,		)
def   lowerCamelCase__							(					a		,		a      )      ->   Any:
   _A:  Any					=       tmp_path_factory.mktemp('''dset_infos_dir'''      )
   if "full:README.md" in files:
      with open(dataset_infos_dir / '''README.md'''		,		'''w'''      ) as f:
         f.write('''---\ndataset_info:\n  dataset_size: 42\n---'''      )
   if "empty:README.md" in files:
      with open(dataset_infos_dir / '''README.md'''		,		'''w'''      ) as f:
         f.write(''''''      )
    # we want to support dataset_infos.json for backward compatibility
   if "dataset_infos.json" in files:
      with open(dataset_infos_dir / '''dataset_infos.json'''		,		'''w'''      ) as f:
         f.write('''{"default": {"dataset_size": 42}}'''      )
   _A:  Optional[int]					=       DatasetInfosDict.from_directory(a      )
   assert dataset_infos
   assert dataset_infos["default"].dataset_size == 42






@pytest.mark.parametrize(
    '''dataset_info'''		,		[
        DatasetInfo(),
        DatasetInfo(
            description='''foo'''		,		features=Features({'''a''': Value('''int32'''      )}      )		,		builder_name='''builder'''		,		config_name='''config'''		,		version='''1.0.0'''		,		splits=[{'''name''': '''train'''}]		,		download_size=42		,		),
    ]		,		)
def   lowerCamelCase__							(					a		,		a      )      ->   Any:
   _A:  int					=       str(a      )
   dataset_info.write_to_directory(a      )
   _A:  str					=       DatasetInfo.from_directory(a      )
   assert dataset_info == reloaded
   assert os.path.exists(os.path.join(a		,		'''dataset_info.json'''      )      )






def   lowerCamelCase__							(					)      ->   Any:
   _A:  int					=       DatasetInfo(
       description='''foo'''		,		citation='''bar'''		,		homepage='''https://foo.bar'''		,		license='''CC0'''		,		features=Features({'''a''': Value('''int32'''      )}      )		,		post_processed={}		,		supervised_keys=()		,		task_templates=[]		,		builder_name='''builder'''		,		config_name='''config'''		,		version='''1.0.0'''		,		splits=[{'''name''': '''train''', '''num_examples''': 42}]		,		download_checksums={}		,		download_size=13_37		,		post_processing_size=4_42		,		dataset_size=12_34		,		size_in_bytes=13_37 + 4_42 + 12_34		,		)
   _A:  Optional[Any]					=       dataset_info._to_yaml_dict()
   assert sorted(a      ) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML      )
   for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
      assert key in dataset_info_yaml_dict
      assert isinstance(dataset_info_yaml_dict[key]		,		(list, dict, int, str)      )
   _A:  str					=       yaml.safe_dump(a      )
   _A:  Optional[int]					=       yaml.safe_load(a      )
   assert dataset_info_yaml_dict == reloaded






def   lowerCamelCase__							(					)      ->   int:
   _A:  Union[str, Any]					=       DatasetInfo()
   _A:  Union[str, Any]					=       dataset_info._to_yaml_dict()
   assert dataset_info_yaml_dict == {}






@pytest.mark.parametrize(
    '''dataset_infos_dict'''		,		[
        DatasetInfosDict(),
        DatasetInfosDict({'''default''': DatasetInfo()}      ),
        DatasetInfosDict({'''my_config_name''': DatasetInfo()}      ),
        DatasetInfosDict(
            {
                '''default''': DatasetInfo(
                    description='''foo'''		,		features=Features({'''a''': Value('''int32'''      )}      )		,		builder_name='''builder'''		,		config_name='''config'''		,		version='''1.0.0'''		,		splits=[{'''name''': '''train'''}]		,		download_size=42		,		)
            }      ),
        DatasetInfosDict(
            {
                '''v1''': DatasetInfo(dataset_size=42      ),
                '''v2''': DatasetInfo(dataset_size=13_37      ),
            }      ),
    ]		,		)
def   lowerCamelCase__							(					a		,		a      )      ->   Optional[int]:
   _A:  Optional[int]					=       str(a      )
   dataset_infos_dict.write_to_directory(a      )
   _A:  Union[str, Any]					=       DatasetInfosDict.from_directory(a      )

   # the config_name of the dataset_infos_dict take over the attribute
   for config_name, dataset_info in dataset_infos_dict.items():
      _A:  Optional[Any]					=       config_name
      # the yaml representation doesn't include fields like description or citation
      # so we just test that we can recover what we can from the yaml
      _A:  Any					=       DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()      )
   assert dataset_infos_dict == reloaded

   if dataset_infos_dict:
      assert os.path.exists(os.path.join(a		,		'''README.md'''      )      )



