

from __future__ import annotations

from typing import Any





def      A__					(			__A  :						Optional[Any]			)					->List[Any]:
      create_state_space_tree(snake_case__     ,				[]     ,				0			)





def      A__					(			__A  :						Tuple     ,				__A  :						str     ,				__A  :						int			)					->Dict:

      if index == len(snake_case__			):
            print(snake_case__			)
            return

      create_state_space_tree(snake_case__     ,				snake_case__     ,				index + 1			)
      current_subsequence.append(sequence[index]			)
      create_state_space_tree(snake_case__     ,				snake_case__     ,				index + 1			)
      current_subsequence.pop()


if __name__ == "__main__":
   _lowerCamelCase      :					Any					    =      [3, 1, 2, 4]
   generate_all_subsequences(seq)

   seq.clear()
   seq.extend(['''A''', '''B''', '''C'''])
   generate_all_subsequences(seq)










"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


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

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCAmelCase       =				[
							    "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

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

