__all__ = [
    "is_hccl_available", "reinit_process_group", "reduce_scatter_tensor_uneven", "all_gather_into_tensor_uneven", "all_to_all_vc"
]

from torch.distributed import _make_nccl_premul_sum as _make_hccl_premul_sum

import torch_npu


def is_available():
    """
    Returns ``True`` if the distributed package is available. Otherwise,
    ``torch.distributed`` does not expose any other APIs. Currently,
    ``torch.distributed`` is available on Linux, MacOS and Windows. Set
    ``USE_DISTRIBUTED=1`` to enable it when building PyTorch from source.
    Currently, the default value is ``USE_DISTRIBUTED=1`` for Linux and Windows,
    ``USE_DISTRIBUTED=0`` for MacOS.
    """
    return hasattr(torch_npu._C, "_c10d_npu_init")


from torch_npu._C._distributed_c10d import (
    ParallelStore,
    _verify_params_across_processes,
    _is_support_hccl_comm_name,
)


from torch_npu.distributed import tensor, nn
from .distributed_c10d import is_hccl_available, reinit_process_group, _reduce_scatter_tensor_uneven as reduce_scatter_tensor_uneven, _all_gather_into_tensor_uneven as all_gather_into_tensor_uneven, _all_to_all_vc as all_to_all_vc