






from __future__ import annotations

from collections.abc import Generator



def        _lowerCamelCase(      lowerCAmelCase__					:		int   ):





				'''simple docstring'''







				if not isinstance(lowerCAmelCase__     ,     lowerCAmelCase__   ) or n < 1:
								raise Exception('Sequence only defined for positive integers'   )

				yield n
				while n != 1:
								if n % 2 == 0:
												n //= 2
								else:
												SCREAMING_SNAKE_CASE_ :						Tuple    				= 3 * n + 1
								yield n



def        _lowerCamelCase(      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_ :						Any    				= 43
				SCREAMING_SNAKE_CASE_ :						Optional[Any]    				= tuple(collatz_sequence(lowerCAmelCase__   )   )
				print(lowerCAmelCase__   )
				print(F'''Collatz sequence from {n} took {len(lowerCAmelCase__   )} steps.'''   )


if __name__ == "__main__":
				main()







from typing import TYPE_CHECKING

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


A										=      {'configuration_detr': ['DETR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DetrConfig', 'DetrOnnxConfig']}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				A										=      ['DetrFeatureExtractor']
				A										=      ['DetrImageProcessor']

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

				A										=      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)