forked from OSSInnovation/mindspore
87 lines
3.4 KiB
C++
87 lines
3.4 KiB
C++
/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_INCLUDE_MS_SESSION_H
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#define MINDSPORE_INCLUDE_MS_SESSION_H
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#include <memory>
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#include <vector>
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#include <string>
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#include "include/infer_tensor.h"
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#include "include/infer_log.h"
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namespace mindspore {
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namespace inference {
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enum StatusCode { SUCCESS = 0, FAILED, INVALID_INPUTS };
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class Status {
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public:
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Status() : status_code_(FAILED) {}
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Status(enum StatusCode status_code, const std::string &status_msg = "")
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: status_code_(status_code), status_msg_(status_msg) {}
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~Status() = default;
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bool IsSuccess() const { return status_code_ == SUCCESS; }
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enum StatusCode StatusCode() const { return status_code_; }
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std::string StatusMessage() const { return status_msg_; }
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bool operator==(const Status &other) const { return status_code_ == other.status_code_; }
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bool operator==(enum StatusCode other_code) const { return status_code_ == other_code; }
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bool operator!=(const Status &other) const { return status_code_ != other.status_code_; }
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bool operator!=(enum StatusCode other_code) const { return status_code_ != other_code; }
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operator bool() const = delete;
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Status &operator<(const LogStream &stream) noexcept __attribute__((visibility("default"))) {
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status_msg_ = stream.sstream_->str();
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return *this;
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}
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private:
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enum StatusCode status_code_;
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std::string status_msg_;
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};
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class MS_API InferSession {
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public:
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InferSession() = default;
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virtual ~InferSession() = default;
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virtual Status InitEnv(const std::string &device_type, uint32_t device_id) = 0;
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virtual Status FinalizeEnv() = 0;
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virtual Status LoadModelFromFile(const std::string &file_name, uint32_t &model_id) = 0;
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virtual Status UnloadModel(uint32_t model_id) = 0;
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// override this method to avoid request/reply data copy
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virtual Status ExecuteModel(uint32_t model_id, const RequestBase &request, ReplyBase &reply) = 0;
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virtual Status ExecuteModel(uint32_t model_id, const std::vector<InferTensor> &inputs,
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std::vector<InferTensor> &outputs) {
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VectorInferTensorWrapRequest request(inputs);
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VectorInferTensorWrapReply reply(outputs);
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return ExecuteModel(model_id, request, reply);
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}
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// default not support input data preprocess(decode, resize, crop, crop&paste, etc.)
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virtual Status ExecuteModel(uint32_t /*model_id*/,
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const ImagesRequestBase & /*images_inputs*/, // images for preprocess
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const RequestBase & /*request*/, ReplyBase & /*reply*/) {
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return FAILED;
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}
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virtual Status GetModelInputsInfo(uint32_t graph_id, std::vector<inference::InferTensor> *tensor_list) const {
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Status status(SUCCESS);
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return status;
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}
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static std::shared_ptr<InferSession> CreateSession(const std::string &device, uint32_t device_id);
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};
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} // namespace inference
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} // namespace mindspore
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#endif // MINDSPORE_INCLUDE_MS_SESSION_H
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