


"""simple docstring"""
def 						lowercase				(	_snake_case		: int	)	->str:
	"""simple docstring"""





	if not isinstance(_snake_case	,  _snake_case	) or not all(
	    isinstance(_snake_case	,  _snake_case	) and item >= 0 for item in citations	):
		raise ValueError('''The citations should be a list of non negative integers.'''	)

	citations.sort()
	__snake_case      :		str         =							len(_snake_case	)

	for i in range(_snake_case	):
		if citations[len_citations - 1 - i] <= i:
			return i

	return len_citations


if __name__ == "__main__":
			import doctest

			doctest.testmod()










'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


SCREAMING_SNAKE_CASE__     : Dict				=   {"""configuration_detr""": ["""DETR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DetrConfig""", """DetrOnnxConfig"""]}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__     : List[Any]				=   ["""DetrFeatureExtractor"""]
							SCREAMING_SNAKE_CASE__     : str				=   ["""DetrImageProcessor"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__     : Optional[Any]				=   [
							    """DETR_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """DetrForObjectDetection""",
							    """DetrForSegmentation""",
							    """DetrModel""",
							    """DetrPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_detr import DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DetrConfig, DetrOnnxConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_detr import DetrFeatureExtractor
														from .image_processing_detr import DetrImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_detr import (
														    DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DetrForObjectDetection,
														    DetrForSegmentation,
														    DetrModel,
														    DetrPreTrainedModel,
														)

else:
							import sys

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