



from __future__ import annotations



def __lowerCAmelCase (     SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_  ):
			lowercase__					  =				[]
			lowercase__					  =				[]
			lowercase__					  =				0
			lowercase__					  =				sum(SCREAMING_SNAKE_CASE_  )
			create_state_space_tree(SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_  )
			return result



def __lowerCAmelCase (     SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  ):
			if sum(SCREAMING_SNAKE_CASE_  ) > max_sum or (remaining_nums_sum + sum(SCREAMING_SNAKE_CASE_  )) < max_sum:
						return
			if sum(SCREAMING_SNAKE_CASE_  ) == max_sum:
						result.append(SCREAMING_SNAKE_CASE_  )
						return
			for index in range(SCREAMING_SNAKE_CASE_						,  len(SCREAMING_SNAKE_CASE_  )  ):
						create_state_space_tree(
						    SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  index + 1						,  [*path, nums[index]]						,  SCREAMING_SNAKE_CASE_						,  remaining_nums_sum - nums[index]						,  )
lowercase_								=     [3, 34, 4, 12, 5, 2]
lowercase_								=     9
lowercase_								=     generate_sum_of_subsets_soln(nums, max_sum)




print(*result)









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase_								=     {
    """configuration_timesformer""": ["""TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TimesformerConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase_								=     [
							    """TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TimesformerModel""",
							    """TimesformerForVideoClassification""",
							    """TimesformerPreTrainedModel""",
							]

if TYPE_CHECKING:
							from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_timesformer import (
														    TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TimesformerForVideoClassification,
														    TimesformerModel,
														    TimesformerPreTrainedModel,
														)

else:
							import sys

							lowercase_								=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




