




"""simple docstring"""



from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE    =	{
    "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:
      SCREAMING_SNAKE_CASE    =	["LayoutLMv3TokenizerFast"]

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

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

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

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











"""simple docstring"""



import baseaa







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		bytes:
 return baseaa.aaaencode(string.encode("utf-8"						)						)







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		str:
 return baseaa.aaadecode(lowercase_						).decode("utf-8"						)


if __name__ == "__main__":
      import doctest

      doctest.testmod()





