






'''simple docstring'''
import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
     import jieba

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a_					= logging.get_logger(__name__)

a_					= {'vocab_file': 'vocab.txt'}

a_					= {
    'vocab_file': {
        'openbmb/cpm-ant-10b': 'https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt',
    },
}

a_					= {
    'openbmb/cpm-ant-10b': 1_0_2_4,
}





def  _a(  UpperCamelCase__				:						int							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=collections.OrderedDict()
      with open(__SCREAMING_SNAKE_CASE,	'''r''',	encoding='''utf-8'''							) as reader:
            SCREAMING_SNAKE_CASE__     :				Any									=reader.readlines()
      for index, token in enumerate(__SCREAMING_SNAKE_CASE							):
            SCREAMING_SNAKE_CASE__     :				Any									=token.rstrip('''\n'''							)
            SCREAMING_SNAKE_CASE__     :				Any									=index
      return vocab






class      __SCREAMING_SNAKE_CASE      (			lowercase__				):




 def __init__(      self	:							Tuple					,      __lowercase	:							Optional[int]					,      __lowercase	:							str="<unk>"					,      __lowercase	:							Optional[int]=2_00      )	->						Union[str, Any]:
       SCREAMING_SNAKE_CASE__     :				Tuple									=vocab
       SCREAMING_SNAKE_CASE__     :				List[Any]									=unk_token
       SCREAMING_SNAKE_CASE__     :				List[str]									=max_input_chars_per_word




 def      __magic_name__	(      self	:							Optional[Any]					,      __lowercase	:							Any      )	->						Dict:
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=list(__lowercase      )
       if len(__lowercase      ) > self.max_input_chars_per_word:
             return [self.unk_token]

       SCREAMING_SNAKE_CASE__     :				List[Any]									=0
       SCREAMING_SNAKE_CASE__     :				Dict									=[]
       while start < len(__lowercase      ):
             SCREAMING_SNAKE_CASE__     :				str									=len(__lowercase      )
             SCREAMING_SNAKE_CASE__     :				Tuple									=None
             while start < end:
                   SCREAMING_SNAKE_CASE__     :				Optional[int]									=''''''.join(chars[start:end]      )
                   if substr in self.vocab:
                         SCREAMING_SNAKE_CASE__     :				List[Any]									=substr
                         break
                   end -= 1
             if cur_substr is None:
                   sub_tokens.append(self.unk_token      )
                   start += 1
             else:
                   sub_tokens.append(__lowercase      )
                   SCREAMING_SNAKE_CASE__     :				List[str]									=end

       return sub_tokens






class      __SCREAMING_SNAKE_CASE      (			lowercase__				):
 snake_case_  							=							VOCAB_FILES_NAMES
 snake_case_  							=							PRETRAINED_VOCAB_FILES_MAP
 snake_case_  							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 snake_case_  							=							['input_ids', 'attention_mask']
 snake_case_  							=							False




 def __init__(      self	:							Tuple					,      __lowercase	:							List[str]					,      __lowercase	:							Union[str, Any]="<d>"					,      __lowercase	:							Optional[Any]="</d>"					,      __lowercase	:							int="<s>"					,      __lowercase	:							List[str]="</s>"					,      __lowercase	:							Any="<pad>"					,      __lowercase	:							List[Any]="<unk>"					,      __lowercase	:							str="</n>"					,      __lowercase	:							int="</_>"					,      __lowercase	:							List[str]="left"					,      **__lowercase	:							str					,      )	->						Union[str, Any]:
       requires_backends(self					,      ['''jieba''']      )
       super().__init__(
           bod_token=__lowercase					,      eod_token=__lowercase					,      bos_token=__lowercase					,      eos_token=__lowercase					,      pad_token=__lowercase					,      unk_token=__lowercase					,      line_token=__lowercase					,      space_token=__lowercase					,      padding_side=__lowercase					,      **__lowercase					,      )
       SCREAMING_SNAKE_CASE__     :				Tuple									=bod_token
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=eod_token
       SCREAMING_SNAKE_CASE__     :				Any									=load_vocab(__lowercase      )
       SCREAMING_SNAKE_CASE__     :				int									=self.encoder[space_token]
       SCREAMING_SNAKE_CASE__     :				List[str]									=self.encoder[line_token]

       del self.encoder[space_token]
       del self.encoder[line_token]

       SCREAMING_SNAKE_CASE__     :				Optional[int]									=collections.OrderedDict(sorted(self.encoder.items()					,      key=lambda __lowercase      : x[1]      )      )
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									={v: k for k, v in self.encoder.items()}

       SCREAMING_SNAKE_CASE__     :				Any									=WordpieceTokenizer(vocab=self.encoder					,      unk_token=self.unk_token      )




 @property
 def      __magic_name__	(      self	:							Union[str, Any]      )	->						Union[str, Any]:
       return self.encoder[self.bod_token]




 @property
 def      __magic_name__	(      self	:							Optional[Any]      )	->						Optional[Any]:
       return self.encoder[self.eod_token]




 @property
 def      __magic_name__	(      self	:							Any      )	->						str:
       return self.encoder["\n"]




 @property
 def      __magic_name__	(      self	:							Optional[int]      )	->						Optional[Any]:
       return len(self.encoder      )




 def      __magic_name__	(      self	:							Tuple      )	->						Dict:
       return dict(self.encoder					,      **self.added_tokens_encoder      )




 def      __magic_name__	(      self	:							Union[str, Any]					,      __lowercase	:							int      )	->						Any:
       SCREAMING_SNAKE_CASE__     :				Tuple									=[]
       for x in jieba.cut(__lowercase					,      cut_all=__lowercase      ):
             output_tokens.extend(self.wordpiece_tokenizer.tokenize(__lowercase      )      )
       return output_tokens




 def      __magic_name__	(      self	:							Dict					,      __lowercase	:							str					,      **__lowercase	:							Dict      )	->						int:
       SCREAMING_SNAKE_CASE__     :				List[str]									=[i for i in token_ids if i >= 0]
       SCREAMING_SNAKE_CASE__     :				str									=[
           x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
       ]
       return super()._decode(__lowercase					,      **__lowercase      )




 def      __magic_name__	(      self	:							int					,      __lowercase	:							Union[str, Any]      )	->						int:
       return token in self.encoder




 def      __magic_name__	(      self	:							Dict					,      __lowercase	:							Any      )	->						Optional[Any]:
       return "".join(__lowercase      )




 def      __magic_name__	(      self	:							Any					,      __lowercase	:							Optional[int]      )	->						Union[str, Any]:
       return self.encoder.get(__lowercase					,      self.encoder.get(self.unk_token      )      )




 def      __magic_name__	(      self	:							List[Any]					,      __lowercase	:							Any      )	->						Optional[int]:
       return self.decoder.get(__lowercase					,      self.unk_token      )




 def      __magic_name__	(      self	:							int					,      __lowercase	:							Optional[Any]					,      __lowercase	:							int = None      )	->						Optional[int]:
       if os.path.isdir(__lowercase      ):
             SCREAMING_SNAKE_CASE__     :				Optional[Any]									=os.path.join(
                 __lowercase					,      (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )
       else:
             SCREAMING_SNAKE_CASE__     :				Dict									=(filename_prefix + '''-''' if filename_prefix else '''''') + save_directory
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=0
       if " " in self.encoder:
             SCREAMING_SNAKE_CASE__     :				List[str]									=self.encoder[''' ''']
             del self.encoder[" "]
       if "\n" in self.encoder:
             SCREAMING_SNAKE_CASE__     :				List[Any]									=self.encoder['''\n''']
             del self.encoder["\n"]
       SCREAMING_SNAKE_CASE__     :				int									=collections.OrderedDict(sorted(self.encoder.items()					,      key=lambda __lowercase      : x[1]      )      )
       with open(__lowercase					,      '''w'''					,      encoding='''utf-8'''      ) as writer:
             for token, token_index in self.encoder.items():
                   if index != token_index:
                         logger.warning(
                             F"Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."
                             ''' Please check that the vocabulary is not corrupted!'''      )
                         SCREAMING_SNAKE_CASE__     :				Dict									=token_index
                   writer.write(token + '''\n'''      )
                   index += 1
       return (vocab_file,)




 def      __magic_name__	(      self	:							List[str]					,      __lowercase	:							Optional[int]					,      __lowercase	:							int = None      )	->						Dict:
       if token_ids_a is None:
             return [self.bos_token_id] + token_ids_a
       return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a




 def      __magic_name__	(      self	:							Union[str, Any]					,      __lowercase	:							List[Any]					,      __lowercase	:							List[Any] = None					,      __lowercase	:							List[str] = False      )	->						Any:

       if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=__lowercase					,      token_ids_a=__lowercase					,      already_has_special_tokens=__lowercase      )

       if token_ids_a is not None:
             return [1] + ([0] * len(__lowercase      )) + [1] + ([0] * len(__lowercase      ))
       return [1] + ([0] * len(__lowercase      ))







'''simple docstring'''
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


a_					= get_tests_dir('fixtures/test_sentencepiece_bpe_char.model')






@require_sentencepiece
@require_tokenizers
class      __SCREAMING_SNAKE_CASE      (			lowerCamelCase	,				unittest.TestCase				):
 snake_case_  							=							SpeechTaTokenizer
 snake_case_  							=							False
 snake_case_  							=							True




 def      __magic_name__	(      self	:							int      )	->						Any:
       super().setUp()

       # We have a SentencePiece fixture for testing
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=SpeechTaTokenizer(__lowercase      )

       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=AddedToken('''<mask>'''					,      lstrip=__lowercase					,      rstrip=__lowercase      )
       SCREAMING_SNAKE_CASE__     :				List[Any]									=mask_token
       tokenizer.add_special_tokens({'''mask_token''': mask_token}      )
       tokenizer.add_tokens(['''<ctc_blank>''']      )

       tokenizer.save_pretrained(self.tmpdirname      )




 def      __magic_name__	(      self	:							Dict					,      __lowercase	:							int      )	->						Optional[int]:
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									='''this is a test'''
       SCREAMING_SNAKE_CASE__     :				int									='''this is a test'''
       return input_text, output_text




 def      __magic_name__	(      self	:							List[Any]					,      __lowercase	:							int					,      __lowercase	:							Optional[Any]=False					,      __lowercase	:							Union[str, Any]=20					,      __lowercase	:							Any=5      )	->						Any:
       SCREAMING_SNAKE_CASE__		,	SCREAMING_SNAKE_CASE__     :				int									=self.get_input_output_texts(__lowercase      )
       SCREAMING_SNAKE_CASE__     :				str									=tokenizer.encode(__lowercase					,      add_special_tokens=__lowercase      )
       SCREAMING_SNAKE_CASE__     :				str									=tokenizer.decode(__lowercase					,      clean_up_tokenization_spaces=__lowercase      )
       return text, ids




 def      __magic_name__	(      self	:							Dict      )	->						str:
       SCREAMING_SNAKE_CASE__     :				Optional[int]									='''<pad>'''
       SCREAMING_SNAKE_CASE__     :				Optional[int]									=1

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




 def      __magic_name__	(      self	:							Tuple      )	->						List[str]:
       SCREAMING_SNAKE_CASE__     :				Optional[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(__lowercase      )					,      81      )




 def      __magic_name__	(      self	:							Dict      )	->						List[str]:
       self.assertEqual(self.get_tokenizer().vocab_size					,      79      )




 def      __magic_name__	(      self	:							Optional[Any]      )	->						str:
       SCREAMING_SNAKE_CASE__     :				str									=self.get_tokenizers(do_lower_case=__lowercase      )
       for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}"      ):
                   SCREAMING_SNAKE_CASE__     :				Tuple									=tokenizer.vocab_size
                   SCREAMING_SNAKE_CASE__     :				Any									=len(__lowercase      )

                   self.assertNotEqual(__lowercase					,      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)

                   SCREAMING_SNAKE_CASE__     :				int									=['''aaaaa bbbbbb''', '''cccccccccdddddddd''']
                   SCREAMING_SNAKE_CASE__     :				List[str]									=tokenizer.add_tokens(__lowercase      )
                   SCREAMING_SNAKE_CASE__     :				List[str]									=tokenizer.vocab_size
                   SCREAMING_SNAKE_CASE__     :				Optional[int]									=len(__lowercase      )

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

                   SCREAMING_SNAKE_CASE__     :				Tuple									=tokenizer.encode('''aaaaa bbbbbb low cccccccccdddddddd l'''					,      add_special_tokens=__lowercase      )

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

                   SCREAMING_SNAKE_CASE__     :				str									={'''eos_token''': '''>>>>|||<||<<|<<''', '''pad_token''': '''<<<<<|||>|>>>>|>'''}
                   SCREAMING_SNAKE_CASE__     :				int									=tokenizer.add_special_tokens(__lowercase      )
                   SCREAMING_SNAKE_CASE__     :				List[str]									=tokenizer.vocab_size
                   SCREAMING_SNAKE_CASE__     :				int									=len(__lowercase      )

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

                   SCREAMING_SNAKE_CASE__     :				List[Any]									=tokenizer.encode(
                       '''>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l'''					,      add_special_tokens=__lowercase      )

                   self.assertGreaterEqual(len(__lowercase      )					,      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	:							Optional[Any]      )	->						Any:
       pass




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




 def      __magic_name__	(      self	:							Dict      )	->						List[Any]:
       SCREAMING_SNAKE_CASE__     :				Dict									=self.get_tokenizer()

       SCREAMING_SNAKE_CASE__     :				Optional[int]									=tokenizer.tokenize('''This is a test'''      )
       # fmt: off
       self.assertListEqual(__lowercase					,      [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(__lowercase      )					,      [4, 32, 11, 10, 12, 4, 10, 12, 4, 7, 4, 6, 5, 12, 6]					,      )

       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=tokenizer.tokenize('''I was born in 92000, and this is falsé.'''      )
       self.assertListEqual(
           __lowercase					,      [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''', '''.''']      )

       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=tokenizer.convert_tokens_to_ids(__lowercase      )
       # fmt: off
       self.assertListEqual(__lowercase					,      [4, 30, 4, 20, 7, 12, 4, 25, 8, 13, 9, 4, 10, 9, 4, 3, 23, 4, 7, 9, 14, 4, 6, 11, 10, 12, 4, 10, 12, 4, 19, 7, 15, 12, 73, 26]      )
       # fmt: on

       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=tokenizer.convert_ids_to_tokens(__lowercase      )
       self.assertListEqual(
           __lowercase					,      [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	:							List[str]      )	->						List[str]:
       # Use custom sequence because this tokenizer does not handle numbers.
       SCREAMING_SNAKE_CASE__     :				List[Any]									=[
           '''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
       SCREAMING_SNAKE_CASE__     :				str									={
           '''input_ids''': [
               [4, 32, 13, 7, 9, 12, 19, 8, 13, 18, 5, 13, 12, 4, 64, 19, 8, 13, 18, 5, 13, 15, 22, 4, 28, 9, 8, 20, 9, 4, 7, 12, 4, 24, 22, 6, 8, 13, 17, 11, 39, 6, 13, 7, 9, 12, 19, 8, 13, 18, 5, 13, 12, 4, 7, 9, 14, 4, 24, 22, 6, 8, 13, 17, 11, 39, 24, 13, 5, 6, 13, 7, 10, 9, 5, 14, 39, 25, 5, 13, 6, 63, 4, 24, 13, 8, 27, 10, 14, 5, 12, 4, 21, 5, 9, 5, 13, 7, 15, 39, 24, 16, 13, 24, 8, 12, 5, 4, 7, 13, 17, 11, 10, 6, 5, 17, 6, 16, 13, 5, 12, 4, 64, 40, 47, 54, 32, 23, 4, 53, 49, 32, 23, 4, 54, 8, 40, 47, 54, 32, 7, 23, 4, 69, 52, 43, 23, 4, 51, 10, 12, 6, 10, 15, 40, 5, 13, 6, 23, 4, 69, 52, 48, 5, 6, 26, 26, 26, 63, 4, 19, 8, 13, 4, 48, 7, 6, 16, 13, 7, 15, 4, 52, 7, 9, 21, 16, 7, 21, 5, 4, 61, 9, 14, 5, 13, 12, 6, 7, 9, 14, 10, 9, 21, 4, 64, 48, 52, 61, 63, 4, 7, 9, 14, 4, 48, 7, 6, 16, 13, 7, 15, 4, 52, 7, 9, 21, 16, 7, 21, 5, 4, 53, 5, 9, 5, 13, 7, 6, 10, 8, 9, 4, 64, 48, 52, 53, 63, 4, 20, 10, 6, 11, 4, 8, 27, 5, 13, 4, 6, 11, 10, 13, 6, 22, 39, 6, 20, 8, 4, 24, 13, 5, 6, 13, 7, 10, 9, 5, 14, 4, 18, 8, 14, 5, 15, 12, 4, 10, 9, 4, 8, 9, 5, 4, 11, 16, 9, 14, 13, 5, 14, 4, 24, 15, 16, 12, 4, 15, 7, 9, 21, 16, 7, 21, 5, 12, 4, 7, 9, 14, 4, 14, 5, 5, 24, 4, 10, 9, 6, 5, 13, 8, 24, 5, 13, 7, 25, 10, 15, 10, 6, 22, 4, 25, 5, 6, 20, 5, 5, 9, 4, 58, 7, 37, 23, 4, 49, 22, 32, 8, 13, 17, 11, 4, 7, 9, 14, 4, 32, 5, 9, 12, 8, 13, 55, 15, 8, 20, 26, 2],
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           ],
           '''attention_mask''': [
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           ]
       }
       # fmt: on

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