def METHOD_NAME(self, input_dicts, fetch_dict, data_id, log_id):
    outputs = fetch_dict["transpose_0.tmp_0"]
    results = []
    for sample in outputs:
        result = []
        for idx, beam in enumerate(sample):
            if idx >= len(sample) // 2:
                break
            res = "".join(postprocess_response(beam, self.tokenizer))
            result.append(res)
        results.append(result)
    out_dict = {}
    out_dict["outputs"] = str(results)
    # the first return must be a dict or a list of dict, the dict corresponding to a batch of model output
    return out_dict, None, ""