

"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


__lowerCamelCase										=		{
    "configuration_layoutlmv3": [
        "LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "LayoutLMv3Config",
        "LayoutLMv3OnnxConfig",
    ],
    "processing_layoutlmv3": ["LayoutLMv3Processor"],
    "tokenization_layoutlmv3": ["LayoutLMv3Tokenizer"],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCamelCase										=		["LayoutLMv3TokenizerFast"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCamelCase										=		[
     "LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST",
     "LayoutLMv3ForQuestionAnswering",
     "LayoutLMv3ForSequenceClassification",
     "LayoutLMv3ForTokenClassification",
     "LayoutLMv3Model",
     "LayoutLMv3PreTrainedModel",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCamelCase										=		[
     "TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST",
     "TFLayoutLMv3ForQuestionAnswering",
     "TFLayoutLMv3ForSequenceClassification",
     "TFLayoutLMv3ForTokenClassification",
     "TFLayoutLMv3Model",
     "TFLayoutLMv3PreTrainedModel",
 ]

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCamelCase										=		["LayoutLMv3FeatureExtractor"]
 __lowerCamelCase										=		["LayoutLMv3ImageProcessor"]


if TYPE_CHECKING:
 from .configuration_layoutlmva import (
     LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP,
     LayoutLMvaConfig,
     LayoutLMvaOnnxConfig,
 )
 from .processing_layoutlmva import LayoutLMvaProcessor
 from .tokenization_layoutlmva import LayoutLMvaTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_layoutlmva import (
      LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
      LayoutLMvaForQuestionAnswering,
      LayoutLMvaForSequenceClassification,
      LayoutLMvaForTokenClassification,
      LayoutLMvaModel,
      LayoutLMvaPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_layoutlmva import (
      TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFLayoutLMvaForQuestionAnswering,
      TFLayoutLMvaForSequenceClassification,
      TFLayoutLMvaForTokenClassification,
      TFLayoutLMvaModel,
      TFLayoutLMvaPreTrainedModel,
  )

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor
  from .image_processing_layoutlmva import LayoutLMvaImageProcessor

else:
 import sys

 __lowerCamelCase										=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




"""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_bert import BertTokenizer


__lowerCamelCase										=		logging.get_logger(__name__)

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

__lowerCamelCase										=		{
    "vocab_file": {
        "bert-base-uncased": "https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt",
        "bert-large-uncased": "https://huggingface.co/bert-large-uncased/resolve/main/vocab.txt",
        "bert-base-cased": "https://huggingface.co/bert-base-cased/resolve/main/vocab.txt",
        "bert-large-cased": "https://huggingface.co/bert-large-cased/resolve/main/vocab.txt",
        "bert-base-multilingual-uncased": (
            "https://huggingface.co/bert-base-multilingual-uncased/resolve/main/vocab.txt"
        ),
        "bert-base-multilingual-cased": "https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt",
        "bert-base-chinese": "https://huggingface.co/bert-base-chinese/resolve/main/vocab.txt",
        "bert-base-german-cased": "https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt",
        "bert-large-uncased-whole-word-masking": (
            "https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/vocab.txt"
        ),
        "bert-large-cased-whole-word-masking": (
            "https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/vocab.txt"
        ),
        "bert-large-uncased-whole-word-masking-finetuned-squad": (
            "https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt"
        ),
        "bert-large-cased-whole-word-masking-finetuned-squad": (
            "https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt"
        ),
        "bert-base-cased-finetuned-mrpc": (
            "https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/vocab.txt"
        ),
        "bert-base-german-dbmdz-cased": "https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/vocab.txt",
        "bert-base-german-dbmdz-uncased": (
            "https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/vocab.txt"
        ),
        "TurkuNLP/bert-base-finnish-cased-v1": (
            "https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/vocab.txt"
        ),
        "TurkuNLP/bert-base-finnish-uncased-v1": (
            "https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/vocab.txt"
        ),
        "wietsedv/bert-base-dutch-cased": (
            "https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "bert-base-uncased": "https://huggingface.co/bert-base-uncased/resolve/main/tokenizer.json",
        "bert-large-uncased": "https://huggingface.co/bert-large-uncased/resolve/main/tokenizer.json",
        "bert-base-cased": "https://huggingface.co/bert-base-cased/resolve/main/tokenizer.json",
        "bert-large-cased": "https://huggingface.co/bert-large-cased/resolve/main/tokenizer.json",
        "bert-base-multilingual-uncased": (
            "https://huggingface.co/bert-base-multilingual-uncased/resolve/main/tokenizer.json"
        ),
        "bert-base-multilingual-cased": (
            "https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer.json"
        ),
        "bert-base-chinese": "https://huggingface.co/bert-base-chinese/resolve/main/tokenizer.json",
        "bert-base-german-cased": "https://huggingface.co/bert-base-german-cased/resolve/main/tokenizer.json",
        "bert-large-uncased-whole-word-masking": (
            "https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/tokenizer.json"
        ),
        "bert-large-cased-whole-word-masking": (
            "https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/tokenizer.json"
        ),
        "bert-large-uncased-whole-word-masking-finetuned-squad": (
            "https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json"
        ),
        "bert-large-cased-whole-word-masking-finetuned-squad": (
            "https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json"
        ),
        "bert-base-cased-finetuned-mrpc": (
            "https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/tokenizer.json"
        ),
        "bert-base-german-dbmdz-cased": (
            "https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/tokenizer.json"
        ),
        "bert-base-german-dbmdz-uncased": (
            "https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/tokenizer.json"
        ),
        "TurkuNLP/bert-base-finnish-cased-v1": (
            "https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/tokenizer.json"
        ),
        "TurkuNLP/bert-base-finnish-uncased-v1": (
            "https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/tokenizer.json"
        ),
        "wietsedv/bert-base-dutch-cased": (
            "https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/tokenizer.json"
        ),
    },
}

__lowerCamelCase										=		{
    "bert-base-uncased": 5_12,
    "bert-large-uncased": 5_12,
    "bert-base-cased": 5_12,
    "bert-large-cased": 5_12,
    "bert-base-multilingual-uncased": 5_12,
    "bert-base-multilingual-cased": 5_12,
    "bert-base-chinese": 5_12,
    "bert-base-german-cased": 5_12,
    "bert-large-uncased-whole-word-masking": 5_12,
    "bert-large-cased-whole-word-masking": 5_12,
    "bert-large-uncased-whole-word-masking-finetuned-squad": 5_12,
    "bert-large-cased-whole-word-masking-finetuned-squad": 5_12,
    "bert-base-cased-finetuned-mrpc": 5_12,
    "bert-base-german-dbmdz-cased": 5_12,
    "bert-base-german-dbmdz-uncased": 5_12,
    "TurkuNLP/bert-base-finnish-cased-v1": 5_12,
    "TurkuNLP/bert-base-finnish-uncased-v1": 5_12,
    "wietsedv/bert-base-dutch-cased": 5_12,
}

__lowerCamelCase										=		{
    "bert-base-uncased": {"do_lower_case": True},
    "bert-large-uncased": {"do_lower_case": True},
    "bert-base-cased": {"do_lower_case": False},
    "bert-large-cased": {"do_lower_case": False},
    "bert-base-multilingual-uncased": {"do_lower_case": True},
    "bert-base-multilingual-cased": {"do_lower_case": False},
    "bert-base-chinese": {"do_lower_case": False},
    "bert-base-german-cased": {"do_lower_case": False},
    "bert-large-uncased-whole-word-masking": {"do_lower_case": True},
    "bert-large-cased-whole-word-masking": {"do_lower_case": False},
    "bert-large-uncased-whole-word-masking-finetuned-squad": {"do_lower_case": True},
    "bert-large-cased-whole-word-masking-finetuned-squad": {"do_lower_case": False},
    "bert-base-cased-finetuned-mrpc": {"do_lower_case": False},
    "bert-base-german-dbmdz-cased": {"do_lower_case": False},
    "bert-base-german-dbmdz-uncased": {"do_lower_case": True},
    "TurkuNLP/bert-base-finnish-cased-v1": {"do_lower_case": False},
    "TurkuNLP/bert-base-finnish-uncased-v1": {"do_lower_case": True},
    "wietsedv/bert-base-dutch-cased": {"do_lower_case": False},
}
class        _lowercase					(     __UpperCAmelCase     ):
     _lowerCamelCase     =       VOCAB_FILES_NAMES
     _lowerCamelCase     =       PRETRAINED_VOCAB_FILES_MAP
     _lowerCamelCase     =       PRETRAINED_INIT_CONFIGURATION
     _lowerCamelCase     =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _lowerCamelCase     =       BertTokenizer







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

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

      __magic_name__     =      do_lower_case







     def 	lowerCAmelCase__    (      self ,						UpperCamelCase_ ,						UpperCamelCase_=None       ):
      __magic_name__     =      [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 	lowerCAmelCase__    (      self ,						UpperCamelCase_ ,						UpperCamelCase_ = None       ):
      __magic_name__     =      [self.sep_token_id]
      __magic_name__     =      [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 	lowerCAmelCase__    (      self ,						UpperCamelCase_ ,						UpperCamelCase_ = None       ):
      __magic_name__     =      self._tokenizer.model.save(UpperCamelCase_ ,						name=UpperCamelCase_       )
      return tuple(UpperCamelCase_       )

