




'''simple docstring'''


from typing import TYPE_CHECKING

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


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

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase       			= ["ConvNextFeatureExtractor"]
     UpperCamelCase       			= ["ConvNextImageProcessor"]

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

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase       			= [
         "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

     UpperCamelCase       			= _LazyModule(__name__, globals()['''__file__'''], _import_structure)












from typing import TYPE_CHECKING

from ....utils import _LazyModule


_UpperCAmelCase		:  Dict	=   {"tokenization_tapex": ["TapexTokenizer"]}


if TYPE_CHECKING:
     from .tokenization_tapex import TapexTokenizer


else:
     import sys

     _UpperCAmelCase		:  Optional[Any]	=   _LazyModule(__name__, globals()["__file__"], _import_structure)



