





from typing import TYPE_CHECKING

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


A_												=     {
    "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:
						A_												=     ["LayoutLMv3TokenizerFast"]

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

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

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

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








def    __UpperCamelCase      (    a,     a,     a=False) ->Dict:

					if isinstance(a,     a) and isinstance(a,     a):
										lowerCamelCase__       =       len(set_a.intersection(a))

										if alternative_union:
															lowerCamelCase__       =       len(a) + len(a)
										else:
															lowerCamelCase__       =       len(set_a.union(a))

										return intersection / union

					if isinstance(a,     (list, tuple)) and isinstance(a,     (list, tuple)):
										lowerCamelCase__       =       [element for element in set_a if element in set_b]

										if alternative_union:
															lowerCamelCase__       =       len(a) + len(a)
															return len(a) / union
										else:
															lowerCamelCase__       =       set_a + [element for element in set_b if element not in set_a]
															return len(a) / len(a)

										return len(a) / len(a)
					return None


if __name__ == "__main__":
						A_												=     {"a", "b", "c", "d", "e"}
						A_												=     {"c", "d", "e", "f", "h", "i"}
						print(jaccard_similarity(set_a, set_b))

