
from typing import TYPE_CHECKING

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


A_		:     Union[str, Any]        =     {
    '''configuration_efficientformer''': [
        '''EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''EfficientFormerConfig''',
    ]
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:     Any        =     ['''EfficientFormerImageProcessor''']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:     Dict        =     [
         '''EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''EfficientFormerForImageClassification''',
         '''EfficientFormerForImageClassificationWithTeacher''',
         '''EfficientFormerModel''',
         '''EfficientFormerPreTrainedModel''',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:     List[Any]        =     [
         '''TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''TFEfficientFormerForImageClassification''',
         '''TFEfficientFormerForImageClassificationWithTeacher''',
         '''TFEfficientFormerModel''',
         '''TFEfficientFormerPreTrainedModel''',
     ]

if TYPE_CHECKING:
     from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .image_processing_efficientformer import EfficientFormerImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_efficientformer import (
              EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              EfficientFormerForImageClassification,
              EfficientFormerForImageClassificationWithTeacher,
              EfficientFormerModel,
              EfficientFormerPreTrainedModel,
          )
     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_efficientformer import (
              TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFEfficientFormerForImageClassification,
              TFEfficientFormerForImageClassificationWithTeacher,
              TFEfficientFormerModel,
              TFEfficientFormerPreTrainedModel,
          )

else:
     import sys

     A_		:     Optional[Any]        =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A_		:     Optional[int]        =     {
    '''configuration_instructblip''': [
        '''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''InstructBlipConfig''',
        '''InstructBlipQFormerConfig''',
        '''InstructBlipVisionConfig''',
    ],
    '''processing_instructblip''': ['''InstructBlipProcessor'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:     List[Any]        =     [
         '''INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''InstructBlipQFormerModel''',
         '''InstructBlipPreTrainedModel''',
         '''InstructBlipForConditionalGeneration''',
         '''InstructBlipVisionModel''',
     ]

if TYPE_CHECKING:
     from .configuration_instructblip import (
         INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
         InstructBlipConfig,
         InstructBlipQFormerConfig,
         InstructBlipVisionConfig,
     )
     from .processing_instructblip import InstructBlipProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_instructblip import (
              INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
              InstructBlipForConditionalGeneration,
              InstructBlipPreTrainedModel,
              InstructBlipQFormerModel,
              InstructBlipVisionModel,
          )

else:
     import sys

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

