

"""simple docstring"""




from typing import TYPE_CHECKING

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


_UpperCAmelCase		:       Optional[int]						    =	{
    """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		:       Dict						    =	["""PerceiverFeatureExtractor"""]
					_UpperCAmelCase		:       Tuple						    =	["""PerceiverImageProcessor"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:       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

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







def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   len(UpperCamelCase__				)
							for _ in range(UpperCamelCase__				):
														for i in range(_ % 2       ,							arr_size - 1       ,							2				):
																					if arr[i + 1] < arr[i]:
																												snake_case_    ,   snake_case_          =   arr[i + 1], arr[i]

							return arr


if __name__ == "__main__":
					_UpperCAmelCase		:       Dict						    =	list(range(10, 0, -1))
					print(F'''Original: {arr}. Sorted: {odd_even_transposition(arr)}''')




