


'''simple docstring'''



from __future__ import annotations

from typing import Any



def      UpperCAmelCase__   (      UpperCAmelCase_       :							Optional[int]				)	->						List[Any]:
     create_state_space_tree(__lowercase ,       [] ,       0				)



def      UpperCAmelCase__   (      UpperCAmelCase_       :							List[str] ,       UpperCAmelCase_       :							str ,       UpperCAmelCase_       :							int				)	->						int:

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

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


if __name__ == "__main__":
      A__						:   List[str]				=    [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,
)


__SCREAMING_SNAKE_CASE							=     {
    'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __SCREAMING_SNAKE_CASE							=     [
     'MEGA_PRETRAINED_MODEL_ARCHIVE_LIST',
     'MegaForCausalLM',
     'MegaForMaskedLM',
     'MegaForMultipleChoice',
     'MegaForQuestionAnswering',
     'MegaForSequenceClassification',
     'MegaForTokenClassification',
     'MegaModel',
     'MegaPreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_mega import MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP, MegaConfig, MegaOnnxConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mega import (
      MEGA_PRETRAINED_MODEL_ARCHIVE_LIST,
      MegaForCausalLM,
      MegaForMaskedLM,
      MegaForMultipleChoice,
      MegaForQuestionAnswering,
      MegaForSequenceClassification,
      MegaForTokenClassification,
      MegaModel,
      MegaPreTrainedModel,
  )

else:
 import sys

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