

"""simple docstring"""




from typing import TYPE_CHECKING

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


A_							:			Any											= {
    "configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextConfig", "ConvNextOnnxConfig"]
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_							:			str											= ["ConvNextFeatureExtractor"]
						A_							:			Optional[Any]											= ["ConvNextImageProcessor"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_							:			str											= [
						    "CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "ConvNextForImageClassification",
						    "ConvNextModel",
						    "ConvNextPreTrainedModel",
						    "ConvNextBackbone",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_							:			Optional[int]											= [
						    "TFConvNextForImageClassification",
						    "TFConvNextModel",
						    "TFConvNextPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_convnext import ConvNextFeatureExtractor
												from .image_processing_convnext import ConvNextImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_convnext import (
												    CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ConvNextBackbone,
												    ConvNextForImageClassification,
												    ConvNextModel,
												    ConvNextPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
						import sys

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





"""simple docstring"""




from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
    LineByLineTextDataset,
    LineByLineWithRefDataset,
    LineByLineWithSOPTextDataset,
    TextDataset,
    TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments


