Method RecordPRun

tensorflow/python/client/session_ref.cc:276–307

  }

  Status RecordPRun(Session* session, const string& handle,
                    const std::vector<std::pair<string, Tensor> >& inputs,
                    const std::vector<string>& output_names,
                    std::vector<Tensor>* outputs) {
    ReplayOp op;
    RunStepRequest* req = op.mutable_run_step();
    RunStepResponse* resp = op.mutable_run_step_response();
    req->set_session_handle(SessionToHandle(session));

    // Mark this step as a partial run for replay.
    req->set_partial_run_handle(handle);
    for (auto& input : inputs) {
      auto* feed = req->add_feed();
      feed->set_name(input.first);
      input.second.AsProtoField(feed->mutable_tensor());
    }

    for (auto& output : output_names) {
      req->add_fetch(output);
    }

    RUN_WITH_TIMESTAMP(PRun, handle, inputs, output_names, outputs);

    for (size_t i = 0; i < outputs->size(); ++i) {
      const Tensor& tensor = (*outputs)[i];
      NamedTensorProto* tproto = resp->add_tensor();
      tensor.AsProtoField(tproto->mutable_tensor());
      tproto->set_name(output_names[i]);
    }

    return Flush(op);
  }

  Status RecordMakeCallable(Session* session,
                            const CallableOptions& callable_options,