'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_A		:      Union[str, Any]						   ={
    '''configuration_convnextv2''': [
        '''CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ConvNextV2Config''',
    ]
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _A		:      Optional[int]						   =[
     '''CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''ConvNextV2ForImageClassification''',
     '''ConvNextV2Model''',
     '''ConvNextV2PreTrainedModel''',
     '''ConvNextV2Backbone''',
 ]


if TYPE_CHECKING:
 from .configuration_convnextva import (
     CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
     ConvNextVaConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_convnextva import (
      CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST,
      ConvNextVaBackbone,
      ConvNextVaForImageClassification,
      ConvNextVaModel,
      ConvNextVaPreTrainedModel,
  )

else:
 import sys

 _A		:      List[Any]						   =_LazyModule(__name__, globals()['''__file__'''], _import_structure)
'''simple docstring'''
from typing import TYPE_CHECKING

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


_A		:      Optional[Any]						   ={
    '''configuration_mobilevitv2''': [
        '''MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MobileViTV2Config''',
        '''MobileViTV2OnnxConfig''',
    ],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _A		:      Union[str, Any]						   =[
     '''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

 _A		:      Tuple						   =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)