



'''simple docstring'''


from typing import TYPE_CHECKING

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


lowercase_      :				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:
						lowercase_      :				Tuple   					=    ['''LayoutLMv3TokenizerFast''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowercase_      :				Optional[Any]   					=    [
						    '''LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''LayoutLMv3ForQuestionAnswering''',
						    '''LayoutLMv3ForSequenceClassification''',
						    '''LayoutLMv3ForTokenClassification''',
						    '''LayoutLMv3Model''',
						    '''LayoutLMv3PreTrainedModel''',
						]

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

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowercase_      :				Optional[int]   					=    ['''LayoutLMv3FeatureExtractor''']
						lowercase_      :				int   					=    ['''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

						lowercase_      :				Tuple   					=    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







'''simple docstring'''


def      SCREAMING_SNAKE_CASE				(				):
						lowercase        =							[]
						lowercase        =							1

						while len(lowercase_						) < 1E6:
												constant.append(str(lowercase_						)						)
												i += 1

						lowercase        =							"""""".join(lowercase_						)

						return (
						    int(constant[0]						)
						    * int(constant[9]						)
						    * int(constant[99]						)
						    * int(constant[999]						)
						    * int(constant[9999]						)
						    * int(constant[9_9999]						)
						    * int(constant[99_9999]						)
						)


if __name__ == "__main__":
						print(solution())


