code: def _all_gather_base(output_tensor, input_tensor, group=group.WORLD):
      """
      Single tensor all gather. Gathers a single tensor from all ranks, and puts them in a single output tensor.
  
      Args:
          output_tensor (Tensor): Output tensor. It should contain
              correctly-sized tensors to be used for output of the collective.
          input_tensor (Tensor): Tensor to be broadcast from current process.
          group (ProcessGroup, optional): The process group to work on. If None,
              the default process group will be used.
          async_op (bool, optional): Whether this op should be an async op
  
      Returns:
          Async work handle, if async_op is set to True.
          None, if not async_op or if not part of the group
  
      Examples:
          >>> # All tensors below are of torch.int64 dtype.
          >>> # We have 2 process groups, 2 ranks.
          >>> # xdoctest: +SKIP("incorrect want text")
          >>> output_tensor = torch.zeros(2, dtype=torch.int64)
          >>> output_tensor
          [tensor([0, 0])] # Rank 0 and 1
          >>> tensor = torch.arange(1, dtype=torch.int64) + 1 + rank
          >>> tensor
          tensor([1]) # Rank 0
          tensor([2]) # Rank 1
          >>> dist.all_gather_base(output_tensor, tensor)
          >>> output_tensor
          tensor([1,2]) # Rank 0
          tensor([1,2]) # Rank 1
  
      .. warning::
          `_all_gather_base` is experimental and subject to change.
          It is the caller's responsibility to ensure the output_tensor
          is correctly sized.
  
      """
      return _AllGatherBase.apply(output_tensor, input_tensor, group)
  
imports: import torch
  import torch.distributed
  from torch.autograd import Function
label_desc: Use image node_id 7 for calling a global function with example usage: _all_gather_base(output_tensor, input_tensor, group) and returns: _AllGatherBase