code: def handle(self, data, context):
      if hasattr(self.model, "run"):
          data = torch.randn(1, 1).to(torch.float32).cpu().numpy()
          # TODO: Should we make this "modelInput configurable", feels complicated
          results = self.model.run(None, {"modelInput": data})
  
          str_results = ["Prediction Succeeded" for _ in results]
          return str_results
  
imports: import torch
  from ts.torch_handler.base_handler import BaseHandler
label_desc: Use image node_id 3 for calling the ONNXHandler obj's underlying member method code with example usage: obj.handle(data, context) and returns: str_results