



'''simple docstring'''






from typing import TYPE_CHECKING

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


UpperCamelCase__:   Optional[int]								=			{"configuration_beit": ["BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BeitConfig", "BeitOnnxConfig"]}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__:   Optional[int]								=			["BeitFeatureExtractor"]
						UpperCamelCase__:   Dict								=			["BeitImageProcessor"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__:   int								=			[
						    "BEIT_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "BeitForImageClassification",
						    "BeitForMaskedImageModeling",
						    "BeitForSemanticSegmentation",
						    "BeitModel",
						    "BeitPreTrainedModel",
						]


try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__:   Union[str, Any]								=			[
						    "FlaxBeitForImageClassification",
						    "FlaxBeitForMaskedImageModeling",
						    "FlaxBeitModel",
						    "FlaxBeitPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_beit import BeitFeatureExtractor
												from .image_processing_beit import BeitImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_beit import (
												    BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    BeitForImageClassification,
												    BeitForMaskedImageModeling,
												    BeitForSemanticSegmentation,
												    BeitModel,
												    BeitPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_beit import (
												    FlaxBeitForImageClassification,
												    FlaxBeitForMaskedImageModeling,
												    FlaxBeitModel,
												    FlaxBeitPreTrainedModel,
												)


else:
						import sys

						UpperCamelCase__:   List[str]								=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)













import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


lowercase  							=					logging.get_logger(__name__)




class  UpperCamelCase_      (			snake_case_				):



	'''simple docstring'''




	def __init__(       self       ,			*a       ,			**a					)       ->    None:
								warnings.warn(
								    'The class PerceiverFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
								    ' Please use PerceiverImageProcessor instead.'       ,			a       ,			)
								super().__init__(*a       ,			**a					)





