'''simple docstring'''




from typing import TYPE_CHECKING

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


_lowercase						: Union[str, 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:
						_lowercase						: List[Any]						=						["PerceiverFeatureExtractor"]
						_lowercase						: List[str]						=						["PerceiverImageProcessor"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase						: Optional[int]						=						[
						    "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

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






'''simple docstring'''




def 							lowerCamelCase	(      UpperCAmelCase__       :					list )			->      list:
							if any(not isinstance(UpperCAmelCase__      ,      UpperCAmelCase__ ) or x < 0 for x in sequence ):
														raise TypeError("""Sequence must be list of non-negative integers""" )
							for _ in range(len(UpperCAmelCase__ ) ):
														for i, (rod_upper, rod_lower) in enumerate(zip(UpperCAmelCase__      ,      sequence[1:] ) ):
																					if rod_upper > rod_lower:
																												sequence[i] -= rod_upper - rod_lower
																												sequence[i + 1] += rod_upper - rod_lower
							return sequence


if __name__ == "__main__":
						assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
						assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]





