docstr: Join the splits of the output into a single result.
  
  Args:
      outputs (List[Any]): The reduced outputs for each output split.
  
  Returns:
      Any: The combined outputs.
docstr_tok: ["Join","the","splits","of","the","output","into","a","single","result",".","Args",":","outputs","(","List","[","Any","]",")",":","The","reduced","outputs","for","each","output","split",".","Returns",":","Any",":","The","combined","outputs","."]
code: def _combine_output_splits(self, outputs):
      """Join the splits of the output into a single result.
  
      Args:
          outputs (List[Any]): The reduced outputs for each output split.
  
      Returns:
          Any: The combined outputs.
      """
      assert len(outputs) == self.out_splits
      return torch.cat(outputs, dim=-1)
  
file_path: DeepSpeed/deepspeed/runtime/zero/tiling.py
imports: import torch
  import deepspeed
  from deepspeed.runtime.utils import partition_uniform
label_desc: Use image node_id 5 for calling the TiledLinear obj's underlying member method code with example usage: obj._combine_output_splits(outputs) and returns: torch