class_docstr: Pipeline Model
class_docstr_tok: ["Pipeline","Model"]
code: def execute(self, requests):
      responses = []
      batch_inputs = []
      for request in requests:
          in_0 = pb_utils.get_input_tensor_by_name(
              request, "INPUT0"
          ).as_numpy()
          for item in in_0:
              arg = item[0]
              inputs = from_json(arg)
              batch_inputs.append(inputs)
  
          results = self.pipe.batch(batch_inputs)
          batch_inputs = []
          outputs = []
          for q in results:
              ret = self._get_result(q)
              outputs.append(ret)
          ret_str = to_json(outputs)
          out_tensor_0 = pb_utils.Tensor(
              "OUTPUT0", np.array([ret_str], np.object_)
          )
          responses.append(pb_utils.InferenceResponse([out_tensor_0]))
      return responses
  
file_path: towhee/towhee/serve/triton/bls/pipeline_model.py
imports: import logging
  from pathlib import Path
  import numpy
  import dill
  from towhee.serve.triton.bls.python_backend_wrapper import pb_utils
  from towhee.runtime.runtime_pipeline import RuntimePipeline
  from towhee.utils.serializer import to_json, from_json
label_desc: Use image node_id 5 for calling the TritonPythonModel obj's underlying member method code with example usage: obj.execute(requests) and returns: responses