mirror of
https://github.com/openharmony/neural_network_runtime.git
synced 2026-07-01 08:12:02 -04:00
yangyongjie
91 lines
3.0 KiB
C++
91 lines
3.0 KiB
C++
/*
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* Copyright (c) 2022 Huawei Device Co., Ltd.
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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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#include "execution_plan.h"
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#include <vector>
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#include "common/log.h"
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#include "interfaces/oem/cpp_api/cpp_type.h"
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namespace OHOS {
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namespace NeuralNetworkRuntime {
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OH_NN_ReturnCode ExecutionPlan::Run(const std::vector<std::shared_ptr<NNTensor>>& inputTensors,
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std::vector<std::shared_ptr<NNTensor>>& outputTensors)
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{
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OH_NN_ReturnCode ret {OH_NN_FAILED};
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IOTensor tensor;
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std::vector<IOTensor> inputIOTensors;
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size_t inputSize = inputTensors.size();
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size_t outputSize = outputTensors.size();
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for (size_t i = 0; i < inputSize; ++i) {
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inputTensors[i]->ConvertToIOTensor(tensor);
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inputIOTensors.emplace_back(std::move(tensor));
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}
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std::vector<IOTensor> outputIOTensors;
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for (size_t i = 0; i < outputSize; ++i) {
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outputTensors[i]->ConvertToIOTensor(tensor);
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outputIOTensors.emplace_back(std::move(tensor));
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}
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std::vector<std::vector<int32_t>> outputsDims;
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std::vector<bool> isSufficientDataBuffer;
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ret = m_preparedModel->Run(inputIOTensors, outputIOTensors, outputsDims, isSufficientDataBuffer);
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if (ret != OH_NN_SUCCESS) {
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LOGE("PrepardModel Run() failed.");
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return ret;
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}
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// Check if the output buffer is sufficient
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bool bufferFailed {false};
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for (size_t i = 0; i < outputSize; ++i) {
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if (!isSufficientDataBuffer[i]) {
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// Print all output indices with insufficient buffer, don't return until traversing all outputs.
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LOGE("Run failed, Output %zu does not have enough buffer to store the data.", i);
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bufferFailed = true;
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}
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}
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if (bufferFailed) {
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return OH_NN_FAILED;
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}
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// Set the output NNTensor's dimensions from output IOTensor if it is dynamic.
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// NNTensor::SetDimensions will check if the tensor buffer is enough for the new dimensions.
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for (size_t i = 0; i < outputSize; ++i) {
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ret = outputTensors[i]->SetDimensions(outputsDims[i]);
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if (ret != OH_NN_SUCCESS) {
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LOGE("Run failed, error happened when setting output tensor's dimensions, output id: %zu.", i);
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return ret;
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}
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}
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return OH_NN_SUCCESS;
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}
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std::shared_ptr<Device> ExecutionPlan::GetInputDevice() const
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{
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return m_device;
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}
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std::shared_ptr<Device> ExecutionPlan::GetOutputDevice() const
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{
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return m_device;
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}
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} // NeuralNetworkRuntime
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} // OHOS
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