




from typing import TYPE_CHECKING

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


lowercase_     :    Tuple      =			{
    '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:
	lowercase_     :    Optional[Any]      =			[
	    'SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'SamModel',
	    'SamPreTrainedModel',
	]
try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase_     :    str      =			[
	    'TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'TFSamModel',
	    'TFSamPreTrainedModel',
	]
try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase_     :    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

	lowercase_     :    str      =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)










from __future__ import annotations

from collections.abc import Generator


def 							__SCREAMING_SNAKE_CASE  (      snake_case_						):

						'''simple docstring'''


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

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


def 							__SCREAMING_SNAKE_CASE  (      ):

						'''simple docstring'''


						_UpperCAmelCase													=					43
						_UpperCAmelCase													=					tuple(collatz_sequence(snake_case_						)						)
						print(snake_case_						)
						print(f"""Collatz sequence from {n} took {len(snake_case_						)} steps."""						)


if __name__ == "__main__":
				main()




