/** * Copyright 2020 Huawei Technologies Co., Ltd * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #ifndef MINDSPORE_SERVING_WORKER_MODEL_H #define MINDSPORE_SERVING_WORKER_MODEL_H #include #include #include #include #include "common/serving_common.h" #include "common/instance.h" #include "common/servable.h" #include "worker/inference/inference.h" namespace mindspore::serving { class ServableBase { public: ServableBase() = default; virtual ~ServableBase() = default; virtual Status Predict(const std::vector &input, std::vector *output) = 0; virtual std::vector GetInputInfos() const = 0; virtual std::vector GetOutputInfos() const = 0; virtual uint64_t GetBatchSize() const = 0; virtual TensorBasePtr MakeInferenceTensor(DataType data_type, const std::vector &shape) const { return nullptr; } }; class AscendModelServable : public ServableBase { public: AscendModelServable(const std::shared_ptr &session, uint32_t model_id) : session_(session), model_id_(model_id) {} ~AscendModelServable() = default; Status Predict(const std::vector &input, std::vector *output) override; std::vector GetInputInfos() const override; std::vector GetOutputInfos() const override; uint64_t GetBatchSize() const override; TensorBasePtr MakeInferenceTensor(DataType data_type, const std::vector &shape) const override; private: std::shared_ptr session_{nullptr}; uint32_t model_id_ = 0; }; } // namespace mindspore::serving #endif // MINDSPORE_SERVING_WORKER_MODEL_H