



from typing import TYPE_CHECKING

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


UpperCAmelCase_							:      List[str]      =  {
    "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:
						UpperCAmelCase_							:      Optional[Any]      =  ["LayoutLMv3TokenizerFast"]

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

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

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

						UpperCAmelCase_							:      Tuple      =  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










def  UpperCamelCase						(       _A			:				int			,							_A			:				int    )->       int:





						"""simple docstring"""





						return int((input_a, input_a).count(0    ) == 0    )
def  UpperCamelCase						(       )->       None:





						"""simple docstring"""





						assert and_gate(0			,							0    ) == 0
						assert and_gate(0			,							1    ) == 0
						assert and_gate(1			,							0    ) == 0
						assert and_gate(1			,							1    ) == 1


if __name__ == "__main__":
						test_and_gate()
						print(and_gate(1, 0))
						print(and_gate(0, 0))
						print(and_gate(0, 1))
						print(and_gate(1, 1))





