





from typing import TYPE_CHECKING

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


UpperCamelCase__											= {
    "configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
    "processing_layoutlmv2": ["LayoutLMv2Processor"],
    "tokenization_layoutlmv2": ["LayoutLMv2Tokenizer"],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__											= ["LayoutLMv2TokenizerFast"]

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__											= ["LayoutLMv2FeatureExtractor"]
					UpperCamelCase__											= ["LayoutLMv2ImageProcessor"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__											= [
					    "LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "LayoutLMv2ForQuestionAnswering",
					    "LayoutLMv2ForSequenceClassification",
					    "LayoutLMv2ForTokenClassification",
					    "LayoutLMv2Layer",
					    "LayoutLMv2Model",
					    "LayoutLMv2PreTrainedModel",
					]

if TYPE_CHECKING:
					from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
					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_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_layoutlmva import (
										    LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
										    LayoutLMvaForQuestionAnswering,
										    LayoutLMvaForSequenceClassification,
										    LayoutLMvaForTokenClassification,
										    LayoutLMvaLayer,
										    LayoutLMvaModel,
										    LayoutLMvaPreTrainedModel,
										)
else:
					import sys

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











def     _UpperCamelCase     (a__   :int       ):






							"""simple docstring"""





							if divisor % 5 == 0 or divisor % 2 == 0:
														return 0
							UpperCamelCase__				     =			1
							UpperCamelCase__				     =			1
							while repunit:
														UpperCamelCase__				     =			(10 * repunit + 1) % divisor
														repunit_index += 1
							return repunit_index





def     _UpperCamelCase     (a__   :int = 100_0000       ):






							"""simple docstring"""





							UpperCamelCase__				     =			limit - 1
							if divisor % 2 == 0:
														divisor += 1
							while least_divisible_repunit(a__       ) <= limit:
														divisor += 2
							return divisor


if __name__ == "__main__":
					print(f"""{solution() = }""")




