




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowercase_      :							List[Any]    							=					{
    'configuration_markuplm': ['MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MarkupLMConfig'],
    'feature_extraction_markuplm': ['MarkupLMFeatureExtractor'],
    'processing_markuplm': ['MarkupLMProcessor'],
    'tokenization_markuplm': ['MarkupLMTokenizer'],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_      :							List[Any]    							=					['MarkupLMTokenizerFast']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_      :							Dict    							=					[
				    'MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'MarkupLMForQuestionAnswering',
				    'MarkupLMForSequenceClassification',
				    'MarkupLMForTokenClassification',
				    'MarkupLMModel',
				    'MarkupLMPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
				from .feature_extraction_markuplm import MarkupLMFeatureExtractor
				from .processing_markuplm import MarkupLMProcessor
				from .tokenization_markuplm import MarkupLMTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_markuplm_fast import MarkupLMTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_markuplm import (
								    MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MarkupLMForQuestionAnswering,
								    MarkupLMForSequenceClassification,
								    MarkupLMForTokenClassification,
								    MarkupLMModel,
								    MarkupLMPreTrainedModel,
								)


else:
				import sys

				lowercase_      :							Union[str, Any]    							=					_LazyModule(__name__, globals()['__file__'], _import_structure)










def 				__SCREAMING_SNAKE_CASE    (     snake_case_		):

						'''simple docstring'''


						return int(snake_case_		) if x - int(snake_case_		) >= 0 else int(snake_case_		) - 1


if __name__ == "__main__":
				import doctest

				doctest.testmod()




