

'''simple docstring'''
from typing import TYPE_CHECKING

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


lowerCamelCase			:				Any 			=					{"configuration_beit": ["BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BeitConfig", "BeitOnnxConfig"]}

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

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


try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase			:				str 			=					[
					    "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

					lowerCamelCase			:				int 			=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



'''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig


lowerCamelCase			:				Optional[Any] 			=					logging.get_logger(__name__)

lowerCamelCase			:				Optional[Any] 			=					"T5Config"







class 							A__   (	A__  ):
  A__					=    'mt5'
  A__					=    MTaConfig







class 							A__   (	A__  ):
  A__					=    'mt5'
  A__					=    MTaConfig







class 							A__   (	A__  ):
  A__					=    'mt5'
  A__					=    MTaConfig
