





"""simple docstring"""


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


lowerCamelCase__				  =   logging.get_logger(__name__)

lowerCamelCase__				  =   {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

lowerCamelCase__				  =   {
    "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"
    },
}

lowerCamelCase__				  =   {"mobilebert-uncased": 512}


lowerCamelCase__				  =   {}



class      __SCREAMING_SNAKE_CASE    (						_UpperCamelCase   ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__							:Optional[Any]	     =					VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__							:Union[str, Any]	     =					PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__							:int	     =					PRETRAINED_INIT_CONFIGURATION
  SCREAMING_SNAKE_CASE__							:Union[str, Any]	     =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__							:List[str]	     =					MobileBertTokenizer

  def __init__(		self   :       str					,   __a   :       str=None					,   __a   :       List[Any]=None					,   __a   :       str=True					,   __a   :       Optional[Any]="[UNK]"					,   __a   :       Dict="[SEP]"					,   __a   :       Any="[PAD]"					,   __a   :       Dict="[CLS]"					,   __a   :       Dict="[MASK]"					,   __a   :       Dict=True					,   __a   :       Dict=None					,   **__a   :       List[Any]					,   )		->				Any:
        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					,   )

        _UpperCamelCase      :	List[Any]						=       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
        ):
              _UpperCamelCase      :	Optional[int]						=       getattr(__a					,   normalizer_state.pop("type"	)	)
              _UpperCamelCase      :	Any						=       do_lower_case
              _UpperCamelCase      :	Union[str, Any]						=       strip_accents
              _UpperCamelCase      :	List[Any]						=       tokenize_chinese_chars
              _UpperCamelCase      :	str						=       normalizer_class(**__a	)

        _UpperCamelCase      :	List[Any]						=       do_lower_case

  def    __SCREAMING_SNAKE_CASE				(		self   :       Union[str, Any]					,   __a   :       List[Any]					,   __a   :       Optional[Any]=None	)		->				Tuple:
        _UpperCamelCase      :	Optional[Any]						=       [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    __SCREAMING_SNAKE_CASE				(		self   :       Tuple					,   __a   :       List[int]					,   __a   :       Optional[List[int]] = None	)		->				List[int]:
        _UpperCamelCase      :	Any						=       [self.sep_token_id]
        _UpperCamelCase      :	int						=       [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    __SCREAMING_SNAKE_CASE				(		self   :       str					,   __a   :       str					,   __a   :       Optional[str] = None	)		->				Tuple[str]:
        _UpperCamelCase      :	int						=       self._tokenizer.model.save(__a					,   name=__a	)
        return tuple(__a	)







"""simple docstring"""


from typing import TYPE_CHECKING

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


lowerCamelCase__				  =   {
    "configuration_mask2former": [
        "MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Mask2FormerConfig",
    ],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase__				  =   ["Mask2FormerImageProcessor"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase__				  =   [
      "MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
      "Mask2FormerForUniversalSegmentation",
      "Mask2FormerModel",
      "Mask2FormerPreTrainedModel",
  ]

if TYPE_CHECKING:
  from .configuration_maskaformer import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskaFormerConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_maskaformer import MaskaFormerImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_maskaformer import (
        MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        MaskaFormerForUniversalSegmentation,
        MaskaFormerModel,
        MaskaFormerPreTrainedModel,
    )


else:
  import sys

  lowerCamelCase__				  =   _LazyModule(__name__, globals()["__file__"], _import_structure)
