code: def _graph_replay(self, *inputs, **kwargs):
      for i in range(len(inputs)):
          if torch.is_tensor(inputs[i]):
              self.static_inputs[self.iter][i].copy_(inputs[i])
      for k in kwargs:
          if torch.is_tensor(kwargs[k]):
              self.static_kwargs[self.iter][k].copy_(kwargs[k])
      self._cuda_graphs[self.iter].replay()
      return self.static_output[self.iter]
  
file_path: H2O/h2o_flexgen/benchmark/third_party/DeepSpeed/deepspeed/model_implementations/transformers/clip_encoder.py
imports: import torch
label_desc: Use image node_id 3 for calling the DSClipEncoder obj's underlying member method code with example usage: obj._graph_replay() and returns: self