


'''simple docstring'''





from typing import TYPE_CHECKING

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


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

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

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase    :						str     =							[
        '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

    __UpperCamelCase    :						Union[str, Any]     =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







def   _UpperCAmelCase       (     UpperCAmelCase      :			str      ):
      """simple docstring"""




      __lowerCamelCase     :      List[Any]       						=						hex_num.strip()
      if not hex_num:
            raise ValueError("""No value was passed to the function"""      )

      __lowerCamelCase     :      Dict       						=						hex_num[0] == """-"""
      if is_negative:
            __lowerCamelCase     :      Optional[Any]       						=						hex_num[1:]

      try:
            __lowerCamelCase     :      Any       						=						int(UpperCAmelCase						,	16      )
      except ValueError:
            raise ValueError("""Invalid value was passed to the function"""      )

      __lowerCamelCase     :      List[str]       						=						""""""
      while int_num > 0:
            __lowerCamelCase     :      Dict       						=						str(int_num % 2      ) + bin_str
            int_num >>= 1

      return int(("""-""" + bin_str) if is_negative else bin_str      )


if __name__ == "__main__":
    import doctest

    doctest.testmod()



