





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase				:       Union[str, Any]	   =				{
    """configuration_xlm_roberta_xl""": [
        """XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """XLMRobertaXLConfig""",
        """XLMRobertaXLOnnxConfig""",
    ],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCAmelCase				:       Any	   =				[
        """XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """XLMRobertaXLForCausalLM""",
        """XLMRobertaXLForMaskedLM""",
        """XLMRobertaXLForMultipleChoice""",
        """XLMRobertaXLForQuestionAnswering""",
        """XLMRobertaXLForSequenceClassification""",
        """XLMRobertaXLForTokenClassification""",
        """XLMRobertaXLModel""",
        """XLMRobertaXLPreTrainedModel""",
    ]

if TYPE_CHECKING:
    from .configuration_xlm_roberta_xl import (
        XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP,
        XLMRobertaXLConfig,
        XLMRobertaXLOnnxConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_xlm_roberta_xl import (
            XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
            XLMRobertaXLForCausalLM,
            XLMRobertaXLForMaskedLM,
            XLMRobertaXLForMultipleChoice,
            XLMRobertaXLForQuestionAnswering,
            XLMRobertaXLForSequenceClassification,
            XLMRobertaXLForTokenClassification,
            XLMRobertaXLModel,
            XLMRobertaXLPreTrainedModel,
        )

else:
    import sys

    _UpperCAmelCase				:       Dict	   =				_LazyModule(__name__, globals()["""__file__"""], _import_structure)












from __future__ import annotations

from typing import Any


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase )			->     None:
    create_state_space_tree(_UpperCAmelCase						,	[]						,	0 )


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase						,	_UpperCAmelCase						,	_UpperCAmelCase )			->     None:

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

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


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

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





