from typing import TYPE_CHECKING

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


__snake_case         =     {'''configuration_regnet''': ['''REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RegNetConfig''']}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __snake_case         =     [
         '''REGNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''RegNetForImageClassification''',
         '''RegNetModel''',
         '''RegNetPreTrainedModel''',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __snake_case         =     [
         '''TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''TFRegNetForImageClassification''',
         '''TFRegNetModel''',
         '''TFRegNetPreTrainedModel''',
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __snake_case         =     [
         '''FlaxRegNetForImageClassification''',
         '''FlaxRegNetModel''',
         '''FlaxRegNetPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_regnet import (
              REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              RegNetForImageClassification,
              RegNetModel,
              RegNetPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_regnet import (
              TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFRegNetForImageClassification,
              TFRegNetModel,
              TFRegNetPreTrainedModel,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_regnet import (
              FlaxRegNetForImageClassification,
              FlaxRegNetModel,
              FlaxRegNetPreTrainedModel,
          )


else:
     import sys

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

from typing import TYPE_CHECKING

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


__snake_case         =     {
    '''configuration_mobilevitv2''': [
        '''MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MobileViTV2Config''',
        '''MobileViTV2OnnxConfig''',
    ],
}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __snake_case         =     [
         '''MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''MobileViTV2ForImageClassification''',
         '''MobileViTV2ForSemanticSegmentation''',
         '''MobileViTV2Model''',
         '''MobileViTV2PreTrainedModel''',
     ]

if TYPE_CHECKING:
     from .configuration_mobilevitva import (
         MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
         MobileViTVaConfig,
         MobileViTVaOnnxConfig,
     )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_mobilevitva import (
              MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
              MobileViTVaForImageClassification,
              MobileViTVaForSemanticSegmentation,
              MobileViTVaModel,
              MobileViTVaPreTrainedModel,
          )

else:
     import sys

     __snake_case         =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
