





from typing import TYPE_CHECKING

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


__lowerCAmelCase			:Dict	 =     {
    'configuration_sam': [
        'SAM_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SamConfig',
        'SamMaskDecoderConfig',
        'SamPromptEncoderConfig',
        'SamVisionConfig',
    ],
    'processing_sam': ['SamProcessor'],
}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase			:Tuple	 =     [
							    'SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'SamModel',
							    'SamPreTrainedModel',
							]
try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase			:List[str]	 =     [
							    'TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'TFSamModel',
							    'TFSamPreTrainedModel',
							]
try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase			:Union[str, Any]	 =     ['SamImageProcessor']


if TYPE_CHECKING:
							from .configuration_sam import (
							    SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    SamConfig,
							    SamMaskDecoderConfig,
							    SamPromptEncoderConfig,
							    SamVisionConfig,
							)
							from .processing_sam import SamProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .image_processing_sam import SamImageProcessor

else:
							import sys

							__lowerCAmelCase			:Tuple	 =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






from __future__ import annotations

from collections.abc import Generator







def  A					(				UpperCAmelCase					):
					if not isinstance(UpperCAmelCase	,	UpperCAmelCase					) or n < 1:
										raise Exception("Sequence only defined for positive integers"					)

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







def  A					(				):
					_snake_case							:       Dict												= 43
					_snake_case							:       List[str]												= tuple(collatz_sequence(UpperCAmelCase					)					)
					print(UpperCAmelCase					)
					print(F"""Collatz sequence from {n} took {len(UpperCAmelCase					)} steps."""					)


if __name__ == "__main__":
							main()