


from typing import TYPE_CHECKING

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


__snake_case   							=						{
    '''configuration_perceiver''': ['''PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PerceiverConfig''', '''PerceiverOnnxConfig'''],
    '''tokenization_perceiver''': ['''PerceiverTokenizer'''],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case   							=						['''PerceiverFeatureExtractor''']
    __snake_case   							=						['''PerceiverImageProcessor''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case   							=						[
        '''PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''PerceiverForImageClassificationConvProcessing''',
        '''PerceiverForImageClassificationFourier''',
        '''PerceiverForImageClassificationLearned''',
        '''PerceiverForMaskedLM''',
        '''PerceiverForMultimodalAutoencoding''',
        '''PerceiverForOpticalFlow''',
        '''PerceiverForSequenceClassification''',
        '''PerceiverLayer''',
        '''PerceiverModel''',
        '''PerceiverPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_perceiver import PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP, PerceiverConfig, PerceiverOnnxConfig
    from .tokenization_perceiver import PerceiverTokenizer

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_perceiver import PerceiverFeatureExtractor
        from .image_processing_perceiver import PerceiverImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_perceiver import (
            PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST,
            PerceiverForImageClassificationConvProcessing,
            PerceiverForImageClassificationFourier,
            PerceiverForImageClassificationLearned,
            PerceiverForMaskedLM,
            PerceiverForMultimodalAutoencoding,
            PerceiverForOpticalFlow,
            PerceiverForSequenceClassification,
            PerceiverLayer,
            PerceiverModel,
            PerceiverPreTrainedModel,
        )

else:
    import sys

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






from typing import TYPE_CHECKING

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


__snake_case   							=						{
    '''configuration_autoformer''': [
        '''AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''AutoformerConfig''',
    ],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case   							=						[
        '''AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''AutoformerForPrediction''',
        '''AutoformerModel''',
        '''AutoformerPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_autoformer import (
        AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
        AutoformerConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_autoformer import (
            AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            AutoformerForPrediction,
            AutoformerModel,
            AutoformerPreTrainedModel,
        )

else:
    import sys

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


