forked from huawei/mindspore2022
82 lines
2.6 KiB
C++
82 lines
2.6 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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#include <queue>
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#include <memory>
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#include "src/mindrt_executor.h"
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#include "src/lite_mindrt.h"
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#include "include/errorcode.h"
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namespace mindspore::lite {
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int MindrtExecutor::Prepare(const std::vector<kernel::LiteKernel *> &kernels) {
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auto ret = MindrtInit();
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if (ret != RET_OK) {
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MS_LOG(ERROR) << "MindrtInit failed";
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return ret;
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}
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auto kernelSize = kernels.size();
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opActors_ = CreateOpActor(kernels);
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if (opActors_.size() != kernelSize) {
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MS_LOG(ERROR) << "CreateOpActor failed";
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return RET_ERROR;
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}
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for (size_t i = 0; i < kernelSize; i++) {
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if (kernels[i]->in_kernels().size() == 0) {
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auto inTensorSize = kernels[i]->in_tensors().size();
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for (size_t j = 0; j < inTensorSize; j++) {
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auto data =
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std::make_shared<OpData<Tensor>>(opActors_[i]->GetAID(), kernels[i]->in_tensors()[j], static_cast<int>(j));
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inputData_.emplace_back(data);
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}
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}
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if (kernels[i]->out_kernels().size() == 0) {
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auto outTensorSize = kernels[i]->out_tensors().size();
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for (size_t j = 0; j < outTensorSize; j++) {
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auto data =
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std::make_shared<OpData<Tensor>>(opActors_[i]->GetAID(), kernels[i]->out_tensors()[j], static_cast<int>(j));
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outputData_.emplace_back(data);
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}
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}
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}
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return RET_OK;
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}
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int MindrtExecutor::Run(const std::vector<Tensor *> &in_tensors, const std::vector<Tensor *> &out_tensors,
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const std::vector<kernel::LiteKernel *> &kernels, mindspore::Allocator *allocator,
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const KernelCallBack &before, const KernelCallBack &after) {
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MS_ASSERT(nullptr != allocator);
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if (kernels.front()->Type() != schema::PrimitiveType_Merge) {
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auto ret = this->CheckInputs(in_tensors);
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if (RET_OK != ret) {
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MS_LOG(ERROR) << "CheckInputs failed";
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return ret;
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}
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}
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// clear ref_count
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for (auto *kernel : kernels) {
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for (auto *tensor : kernel->in_tensors()) {
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tensor->set_ref_count(0);
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}
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}
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return MindrtRun<Tensor>(inputData_, &outputData_, &before, &after);
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}
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} // namespace mindspore::lite
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