'''simple docstring'''




from .testing import (
    are_the_same_tensors,
    execute_subprocess_async,
    require_bnb,
    require_cpu,
    require_cuda,
    require_huggingface_suite,
    require_mps,
    require_multi_gpu,
    require_multi_xpu,
    require_safetensors,
    require_single_gpu,
    require_single_xpu,
    require_torch_min_version,
    require_tpu,
    require_xpu,
    skip,
    slow,
)
from .training import RegressionDataset, RegressionModel, RegressionModelaXPU


from .scripts import test_script, test_sync, test_ops  # isort: skip

'''simple docstring'''




from __future__ import annotations






def __lowerCAmelCase			(							UpperCamelCase__    ,  UpperCamelCase__    )     ->   list[list[int]]:
    __lowerCamelCase          =  []
    create_all_state(1    ,  UpperCamelCase__    ,  UpperCamelCase__    ,  []    ,  UpperCamelCase__    )
    return result






def __lowerCAmelCase			(							UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    ,  )     ->   None:
    if level == 0:
        total_list.append(current_list[:]    )
        return

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






def __lowerCAmelCase			(							UpperCamelCase__    )     ->   None:
    for i in total_list:
        print(*UpperCamelCase__    )


if __name__ == "__main__":
  __UpperCAmelCase												=4
  __UpperCAmelCase												=2
  __UpperCAmelCase												=generate_all_combinations(n, k)
  print_all_state(total_list)
