


from typing import TYPE_CHECKING

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


A      :    str		=					{
    "configuration_perceiver": ["PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP", "PerceiverConfig", "PerceiverOnnxConfig"],
    "tokenization_perceiver": ["PerceiverTokenizer"],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A      :    List[Any]		=					["PerceiverFeatureExtractor"]
    A      :    str		=					["PerceiverImageProcessor"]

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

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







'''simple docstring'''





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase		)		-> float:
      snake_case__  :    str    						=      (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
      # formula for sum of series
      return total





def 						__snake_case(				)		-> List[str]:
      print(sum_of_series(1     ,   1     ,   10		)		)


if __name__ == "__main__":
       import doctest

       doctest.testmod()
