


from .data_collator import (
    DataCollatorForLanguageModeling,
    DataCollatorForPermutationLanguageModeling,
    DataCollatorForSeqaSeq,
    DataCollatorForSOP,
    DataCollatorForTokenClassification,
    DataCollatorForWholeWordMask,
    DataCollatorWithPadding,
    DefaultDataCollator,
    default_data_collator,
)
from .metrics import glue_compute_metrics, xnli_compute_metrics
from .processors import (
    DataProcessor,
    InputExample,
    InputFeatures,
    SingleSentenceClassificationProcessor,
    SquadExample,
    SquadFeatures,
    SquadVaProcessor,
    SquadVaProcessor,
    glue_convert_examples_to_features,
    glue_output_modes,
    glue_processors,
    glue_tasks_num_labels,
    squad_convert_examples_to_features,
    xnli_output_modes,
    xnli_processors,
    xnli_tasks_num_labels,
)




'''simple docstring'''

from __future__ import annotations

def _SCREAMING_SNAKE_CASE      (A  , A       )       ->       list[list[int]]:






       """simple docstring"""







       lowercase__      			= []
       create_all_state(1  , A  , A  , []  , A       )
       return result

def _SCREAMING_SNAKE_CASE      (A  , A  , A  , A  , A  , )       ->       None:






       """simple docstring"""







       if level == 0:
              total_list.append(current_list[:]       )
              return

       for i in range(A  , total_number - level + 2       ):
              current_list.append(A       )
              create_all_state(i + 1  , A  , level - 1  , A  , A       )
              current_list.pop()

def _SCREAMING_SNAKE_CASE      (A       )       ->       None:






       """simple docstring"""







       for i in total_list:
              print(*A       )


if __name__ == "__main__":
 lowerCamelCase							:   Tuple  						=	4
 lowerCamelCase							:   Union[str, Any]  						=	2
 lowerCamelCase							:   Dict  						=	generate_all_combinations(n, k)
 print_all_state(total_list)




