

"""simple docstring"""




from typing import TYPE_CHECKING

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


_lowercase   :	Any												=						{
    '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:
				_lowercase   :	Dict												=						['LayoutLMv2TokenizerFast']

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowercase   :	List[Any]												=						['LayoutLMv2FeatureExtractor']
				_lowercase   :	Any												=						['LayoutLMv2ImageProcessor']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowercase   :	Tuple												=						[
				    '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

				_lowercase   :	int												=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







'''simple docstring'''

def    a__							(							lowercase   :	int,   lowercase   :	int,   lowercase   :	int )						->						float:





     """simple docstring"""

     _UpperCamelCase							       =			(num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
     # formula for sum of series
     return total







def    a__							(							)						->						Tuple:





     """simple docstring"""

     print(sum_of_series(1,   1,   10 ) )


if __name__ == "__main__":
   import doctest

   doctest.testmod()



