


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


SCREAMING_SNAKE_CASE							    =							{
    'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
    'tokenization_m2m_100': ['M2M100Tokenizer'],
}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE							    =							[
      'M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST',
      'M2M100ForConditionalGeneration',
      'M2M100Model',
      'M2M100PreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
  from .tokenization_mam_aaa import MaMaaaTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_mam_aaa import (
        M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
        MaMaaaForConditionalGeneration,
        MaMaaaModel,
        MaMaaaPreTrainedModel,
    )


else:
  import sys

  SCREAMING_SNAKE_CASE							    =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer


SCREAMING_SNAKE_CASE							    =							logging.get_logger(__name__)

SCREAMING_SNAKE_CASE							    =							{'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

SCREAMING_SNAKE_CASE							    =							{
    'vocab_file': {'mobilebert-uncased': 'https://huggingface.co/google/mobilebert-uncased/resolve/main/vocab.txt'},
    'tokenizer_file': {
        'mobilebert-uncased': 'https://huggingface.co/google/mobilebert-uncased/resolve/main/tokenizer.json'
    },
}

SCREAMING_SNAKE_CASE							    =							{'mobilebert-uncased': 5_1_2}


SCREAMING_SNAKE_CASE							    =							{}


class     __UpperCAmelCase							(       __A							):


     """simple docstring"""
     _lowerCamelCase   =      VOCAB_FILES_NAMES
     _lowerCamelCase   =      PRETRAINED_VOCAB_FILES_MAP
     _lowerCamelCase   =      PRETRAINED_INIT_CONFIGURATION
     _lowerCamelCase   =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _lowerCamelCase   =      MobileBertTokenizer


     def __init__(	self  ,       __A=None  ,       __A=None  ,       __A=True  ,       __A="[UNK]"  ,       __A="[SEP]"  ,       __A="[PAD]"  ,       __A="[CLS]"  ,       __A="[MASK]"  ,       __A=True  ,       __A=None  ,       **__A  ,       ):
        super().__init__(
            __A  ,       tokenizer_file=__A  ,       do_lower_case=__A  ,       unk_token=__A  ,       sep_token=__A  ,       pad_token=__A  ,       cls_token=__A  ,       mask_token=__A  ,       tokenize_chinese_chars=__A  ,       strip_accents=__A  ,       **__A  ,       )

        __a					=  json.loads(self.backend_tokenizer.normalizer.__getstate__()    )
        if (
            normalizer_state.get("""lowercase"""  ,       __A    ) != do_lower_case
            or normalizer_state.get("""strip_accents"""  ,       __A    ) != strip_accents
            or normalizer_state.get("""handle_chinese_chars"""  ,       __A    ) != tokenize_chinese_chars
        ):
           __a					=  getattr(__A  ,       normalizer_state.pop("""type"""    )    )
           __a					=  do_lower_case
           __a					=  strip_accents
           __a					=  tokenize_chinese_chars
           __a					=  normalizer_class(**__A    )

        __a					=  do_lower_case


     def 	snake_case_  (	self  ,       __A  ,       __A=None    ):
        __a					=  [self.cls_token_id] + token_ids_a + [self.sep_token_id]

        if token_ids_a:
           output += token_ids_a + [self.sep_token_id]

        return output


     def 	snake_case_  (	self  ,       __A  ,       __A = None    ):
        __a					=  [self.sep_token_id]
        __a					=  [self.cls_token_id]
        if token_ids_a is None:
           return len(cls + token_ids_a + sep    ) * [0]
        return len(cls + token_ids_a + sep    ) * [0] + len(token_ids_a + sep    ) * [1]


     def 	snake_case_  (	self  ,       __A  ,       __A = None    ):
        __a					=  self._tokenizer.model.save(__A  ,       name=__A    )
        return tuple(__A    )



