parameters: (output, input_list, op=dist.ReduceOp.SUM, group=dist.group.WORLD)
return_statement: return _Reduce_Scatter.apply(op, group, output, *input_list)
docstring: Reduces, then scatters a list of tensors to all processes in a group.
  
      Arguments:
          output (Tensor): Output tensor.
          input_list (list[Tensor]): List of tensors to reduce and scatter.
          op (optional): One of the values from
              ``torch.distributed.ReduceOp``
              enum.  Specifies an operation used for element-wise reductions.
          group (ProcessGroup, optional): The process group to work on.
  
      Returns:
          Tensor: Output of the collective.
docstring_summary: Reduces, then scatters a list of tensors to all processes in a group.
docstring_tokens: Reduces then scatters a list of tensors to all processes in a group .
function: def reduce_scatter(output, input_list, op=dist.ReduceOp.SUM, group=dist.group.WORLD):
      """
      Reduces, then scatters a list of tensors to all processes in a group.
  
      Arguments:
          output (Tensor): Output tensor.
          input_list (list[Tensor]): List of tensors to reduce and scatter.
          op (optional): One of the values from
              ``torch.distributed.ReduceOp``
              enum.  Specifies an operation used for element-wise reductions.
          group (ProcessGroup, optional): The process group to work on.
  
      Returns:
          Tensor: Output of the collective.
  
      """
      return _Reduce_Scatter.apply(op, group, output, *input_list)
function_tokens: def reduce_scatter ( output , input_list , op = dist . ReduceOp . SUM , group = dist . group . WORLD ) : return _Reduce_Scatter . apply ( op , group , output , * input_list )