from typing import TYPE_CHECKING

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


A_	     =   {
    "configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MobileViTConfig", "MobileViTOnnxConfig"],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_	     =   ["MobileViTFeatureExtractor"]
						A_	     =   ["MobileViTImageProcessor"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_	     =   [
						    "MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "MobileViTForImageClassification",
						    "MobileViTForSemanticSegmentation",
						    "MobileViTModel",
						    "MobileViTPreTrainedModel",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_	     =   [
						    "TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "TFMobileViTForImageClassification",
						    "TFMobileViTForSemanticSegmentation",
						    "TFMobileViTModel",
						    "TFMobileViTPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_mobilevit import MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTConfig, MobileViTOnnxConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_mobilevit import MobileViTFeatureExtractor
												from .image_processing_mobilevit import MobileViTImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_mobilevit import (
												    MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    MobileViTForImageClassification,
												    MobileViTForSemanticSegmentation,
												    MobileViTModel,
												    MobileViTPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_mobilevit import (
												    TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFMobileViTForImageClassification,
												    TFMobileViTForSemanticSegmentation,
												    TFMobileViTModel,
												    TFMobileViTPreTrainedModel,
												)


else:
						import sys

						A_	     =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)













import warnings

from ...utils import logging
from .image_processing_deit import DeiTImageProcessor


__a   :							Any						= logging.get_logger(__name__)


class    __lowercase   (						lowercase_	):







     '''simple docstring'''




     def __init__(					self							:      Union[str, Any]			,						*UpperCamelCase_							:      Tuple			,						**UpperCamelCase_							:      Tuple					):


         """simple docstring"""



         warnings.warn(
             """The class DeiTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
             """ use DeiTImageProcessor instead."""			,						UpperCamelCase_			,						)
         super().__init__(*UpperCamelCase_			,						**UpperCamelCase_					)




