




from typing import TYPE_CHECKING

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


_lowerCamelCase  :			List[Any]        =       {
    '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:
		_lowerCamelCase  :			Optional[Any]        =       ['LayoutLMv3TokenizerFast']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase  :			List[str]        =       [
		    'LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'LayoutLMv3ForQuestionAnswering',
		    'LayoutLMv3ForSequenceClassification',
		    'LayoutLMv3ForTokenClassification',
		    'LayoutLMv3Model',
		    'LayoutLMv3PreTrainedModel',
		]

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

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase  :			Optional[Any]        =       ['LayoutLMv3FeatureExtractor']
		_lowerCamelCase  :			List[Any]        =       ['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

		_lowerCamelCase  :			List[Any]        =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)











"""simple docstring"""

from typing import TYPE_CHECKING

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


_lowerCamelCase  :			Optional[Any]        =       {
    'configuration_mask2former': [
        'MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Mask2FormerConfig',
    ],
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase  :			int        =       ['Mask2FormerImageProcessor']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase  :			Tuple        =       [
		    'MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'Mask2FormerForUniversalSegmentation',
		    'Mask2FormerModel',
		    'Mask2FormerPreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_maskaformer import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskaFormerConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .image_processing_maskaformer import MaskaFormerImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_maskaformer import (
				    MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MaskaFormerForUniversalSegmentation,
				    MaskaFormerModel,
				    MaskaFormerPreTrainedModel,
				)


else:
		import sys

		_lowerCamelCase  :			Optional[Any]        =       _LazyModule(__name__, globals()['__file__'], _import_structure)





