
from typing import TYPE_CHECKING

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


lowerCamelCase_						     =					{'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BeitConfig''', '''BeitOnnxConfig''']}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_						     =					['''BeitFeatureExtractor''']
    lowerCamelCase_						     =					['''BeitImageProcessor''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_						     =					[
        '''BEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''BeitForImageClassification''',
        '''BeitForMaskedImageModeling''',
        '''BeitForSemanticSegmentation''',
        '''BeitModel''',
        '''BeitPreTrainedModel''',
    ]


try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_						     =					[
        '''FlaxBeitForImageClassification''',
        '''FlaxBeitForMaskedImageModeling''',
        '''FlaxBeitModel''',
        '''FlaxBeitPreTrainedModel''',
    ]

if TYPE_CHECKING:
    from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_beit import BeitFeatureExtractor
        from .image_processing_beit import BeitImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_beit import (
            BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
            BeitForImageClassification,
            BeitForMaskedImageModeling,
            BeitForSemanticSegmentation,
            BeitModel,
            BeitPreTrainedModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_beit import (
            FlaxBeitForImageClassification,
            FlaxBeitForMaskedImageModeling,
            FlaxBeitModel,
            FlaxBeitPreTrainedModel,
        )


else:
    import sys

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







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCamelCase_						     =					{
    '''configuration_canine''': ['''CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CanineConfig'''],
    '''tokenization_canine''': ['''CanineTokenizer'''],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_						     =					[
        '''CANINE_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''CanineForMultipleChoice''',
        '''CanineForQuestionAnswering''',
        '''CanineForSequenceClassification''',
        '''CanineForTokenClassification''',
        '''CanineLayer''',
        '''CanineModel''',
        '''CaninePreTrainedModel''',
        '''load_tf_weights_in_canine''',
    ]


if TYPE_CHECKING:
    from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
    from .tokenization_canine import CanineTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_canine import (
            CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
            CanineForMultipleChoice,
            CanineForQuestionAnswering,
            CanineForSequenceClassification,
            CanineForTokenClassification,
            CanineLayer,
            CanineModel,
            CaninePreTrainedModel,
            load_tf_weights_in_canine,
        )


else:
    import sys

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





