
from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__     :    Optional[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:
					SCREAMING_SNAKE_CASE__     :    Dict      							=					["MarkupLMTokenizerFast"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__     :    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

					SCREAMING_SNAKE_CASE__     :    Union[str, Any]      							=					_LazyModule(__name__, globals()["__file__"], _import_structure)





from ..utils import requires_backends


SCREAMING_SNAKE_CASE__     :    Union[str, Any]      							=					None

class      lowerCAmelCase__  :






		def __init__(	self	:							int							,    *SCREAMING_SNAKE_CASE__	:							Dict							,    **SCREAMING_SNAKE_CASE__	:							Tuple						)  ->							Optional[Any]:
						requires_backends(self							,    ['''detectron2''']						)







		@classmethod
		def 				__A (	cls	:							Dict							,    *SCREAMING_SNAKE_CASE__	:							Dict							,    **SCREAMING_SNAKE_CASE__	:							Tuple						)  ->							Tuple:
						requires_backends(cls							,    ['''detectron2''']						)



