code: def _create_cuda_graph(self, *inputs, **kwargs):
      # warmup to create the workspace and cublas handle
      cuda_stream = torch.cuda.Stream()
      cuda_stream.wait_stream(torch.cuda.current_stream())
      with torch.cuda.stream(cuda_stream):
          for i in range(3):
              ret = self._forward(*inputs, **kwargs)
      torch.cuda.current_stream().wait_stream(cuda_stream)
  
      # create cuda_graph and assign static_inputs and static_outputs
      self._cuda_graphs[self.iter] = get_accelerator().create_graph()
      self.static_inputs[self.iter] = inputs
      self.static_kwargs[self.iter] = kwargs
  
      with get_accelerator().capture_to_graph(
          self._cuda_graphs[self.iter]
      ):
          self.static_output[self.iter] = self._forward(
              *self.static_inputs[self.iter],
              **self.static_kwargs[self.iter],
          )
  
      self.cuda_graph_created[self.iter] = True
  
file_path: deepspeed/deepspeed/model_implementations/transformers/clip_encoder.py
imports: import torch
  from deepspeed.accelerator import get_accelerator
  from ..features.cuda_graph import CUDAGraph
label_desc: Use image node_id 5 for calling the DSClipEncoder obj's underlying member method code with example usage: obj._create_cuda_graph() without return types