fix package
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2d7e4adf44
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0e2d1d9749
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@ -255,9 +255,9 @@ build_lite() {
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else
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make -j$THREAD_NUM && make install
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cp -r ${BASEPATH}/output/tmp/mindspore*/runtime ${BASEPATH}/mindspore/lite/tools/benchmark
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cmake ${LITE_CMAKE_ARGS} -DBUILD_FIRST=off --target benchmark "${BASEPATH}/mindspore/lite"
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make -j$THREAD_NUM && make install && make package
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cmake ${LITE_CMAKE_ARGS} -DBUILD_FIRST=off "${BASEPATH}/mindspore/lite"
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cmake --build "${BASEPATH}/mindspore/lite/build" --target benchmark -j$THREAD_NUM
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make install && make package
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if [[ "${local_lite_platform}" == "x86_64" ]]; then
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if [ "${JAVA_HOME}" ]; then
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echo -e "\e[31mJAVA_HOME=$JAVA_HOME \e[0m"
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@ -639,16 +639,16 @@ int SvpSysInit() {
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HI_S32 ret = HI_SUCCESS;
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VB_CONFIG_S struVbConf;
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ret = HI_MPI_SYS_Exit();
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if (HI_SUCCESS != ret) {
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if (ret != HI_SUCCESS) {
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MS_LOG(ERROR) << "HI_MPI_SYS_Exit failed!";
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return RET_ERROR;
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}
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ret = HI_MPI_VB_Exit();
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if (HI_SUCCESS != ret) {
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if (ret != HI_SUCCESS) {
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MS_LOG(WARNING) << "HI_MPI_VB_Exit failed!";
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ret = HI_MPI_SYS_Init();
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if (HI_SUCCESS != ret) {
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if (ret != HI_SUCCESS) {
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MS_LOG(ERROR) << "Error:HI_MPI_SYS_Init failed!";
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return RET_ERROR;
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}
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@ -661,19 +661,19 @@ int SvpSysInit() {
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struVbConf.astCommPool[1].u32BlkCnt = 1;
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ret = HI_MPI_VB_SetConfig((const VB_CONFIG_S *)&struVbConf);
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if (HI_SUCCESS != ret) {
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if (ret != HI_SUCCESS) {
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MS_LOG(ERROR) << "Error:HI_MPI_VB_SetConf failed!";
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return RET_ERROR;
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}
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ret = HI_MPI_VB_Init();
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if (HI_SUCCESS != ret) {
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if (ret != HI_SUCCESS) {
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MS_LOG(ERROR) << "Error:HI_MPI_VB_Init failed!";
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return RET_ERROR;
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}
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ret = HI_MPI_SYS_Init();
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if (HI_SUCCESS != ret) {
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if (ret != HI_SUCCESS) {
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MS_LOG(ERROR) << "Error:HI_MPI_SYS_Init failed!";
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return RET_ERROR;
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}
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@ -685,13 +685,13 @@ int SvpSysExit() {
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HI_S32 ret = HI_SUCCESS;
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ret = HI_MPI_SYS_Exit();
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if (HI_SUCCESS != ret) {
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if (ret != HI_SUCCESS) {
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MS_LOG(ERROR) << "HI_MPI_SYS_Exit failed!";
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return RET_ERROR;
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}
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ret = HI_MPI_VB_Exit();
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if (HI_SUCCESS != ret) {
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if (ret != HI_SUCCESS) {
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MS_LOG(WARNING) << "HI_MPI_VB_Exit failed!";
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return RET_OK;
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}
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@ -45,7 +45,7 @@ int CustomCPUKernel::Prepare() {
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if (nnie::NNIEManager::GetInstance()->Init(reinterpret_cast<char *>(inputs_[inputs_.size() - 1].MutableData()),
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static_cast<int>(inputs_[inputs_.size() - 1].ElementNum()), inputs_)) {
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// LOGW("Load WK Model Fail");
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LOGI("Load WK Model Fail");
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return RET_OK;
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}
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load_model_ = true;
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@ -73,12 +73,12 @@ int CustomCPUKernel::Execute() {
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}
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run_seg_ = seg_id_;
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if (nnie::NNIEManager::GetInstance()->FillData(&inputs_, run_seg_)) {
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if (nnie::NNIEManager::GetInstance()->FillData(&inputs_, run_seg_) != RET_OK) {
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LOGE("Fail Fill Data");
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return RET_ERROR;
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}
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if (nnie::NNIEManager::GetInstance()->Run(&outputs_, run_seg_, outputs_shapes_)) {
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if (nnie::NNIEManager::GetInstance()->Run(&outputs_, run_seg_, outputs_shapes_) != RET_OK) {
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LOGE("Fail WK Run");
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return RET_ERROR;
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}
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@ -70,9 +70,6 @@ int GetCustomShape(const mindspore::schema::Custom *op, const std::string &attr,
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char *save_ptr = nullptr;
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res = strtok_r(buf, delims, &save_ptr);
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while (res != nullptr) {
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// 待补完
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// outputs[id]->format_ = input->format_;
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// outputs[id]->data_type_ = kNumberTypeFloat32;
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int64_t ndims = strtol(res, &res, kDecimal);
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int j = 0;
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std::vector<int64_t> shape;
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@ -791,8 +791,8 @@ int NnieCommCreate(NnieRunCfg *nnie_run_cfg, char *model_buf, int size,
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j = GetFillIndex(inputs, inputs.size() - 1, model->model_.astSeg[0].astSrcNode[0].szName);
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if (j == (inputs.size() - 1)) {
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j = 0;
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// LOGW("input tensor name(%s) can't match wk node name(%s).", inputs[0].Name().c_str(),
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// model->model_.astSeg[0].astSrcNode[0].szName);
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LOGI("input tensor name(%s) can't match wk node name(%s).", inputs[0].Name().c_str(),
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model->model_.astSeg[0].astSrcNode[0].szName);
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}
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if (CheckMsShapeN(nnie_run_cfg, inputs[j].Shape(), model->model_.astSeg[0].astSrcNode[0]) != RET_OK) {
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return RET_ERROR;
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@ -107,8 +107,8 @@ int NNIEManager::GetOutputData(std::vector<mindspore::MSTensor> *outputs,
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j = GetFillIndex(*outputs, output_size, nnie_cfg_.param_.model_->astSeg[seg_idx].astDstNode[i].szName);
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if (j == output_size) {
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j = i;
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// LOGW("output tensor name(%s) can't match wk node name(%s).", (*outputs)[j].Name().c_str(),
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// nnie_cfg_.param_.model_->astSeg[seg_idx].astDstNode[i].szName);
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LOGI("output tensor name(%s) can't match wk node name(%s).", (*outputs)[j].Name().c_str(),
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nnie_cfg_.param_.model_->astSeg[seg_idx].astDstNode[i].szName);
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}
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auto input_data_type = (*outputs)[j].DataType();
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@ -196,8 +196,8 @@ int NNIEManager::FillData(std::vector<mindspore::MSTensor> *inputs, unsigned int
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continue;
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} else {
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j = i;
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// LOGW("input tensor name(%s) can't match wk node name(%s).", (*inputs)[i].Name().c_str(),
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// nnie_cfg_.param_.model_->astSeg[seg_id].astSrcNode[i].szName);
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LOGI("input tensor name(%s) can't match wk node name(%s).", (*inputs)[i].Name().c_str(),
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nnie_cfg_.param_.model_->astSeg[seg_id].astSrcNode[i].szName);
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}
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}
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@ -37,6 +37,14 @@
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} \
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} while (0)
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#define LOGI(format, ...) \
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do { \
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if (0) { \
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fprintf(stderr, "\n[Warning] " LOG_TAG1 " [" __FILE__ ":%d] %s] ", __LINE__, __FUNCTION__); \
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fprintf(stderr, format, ##__VA_ARGS__); \
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} \
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} while (0)
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constexpr int kMaxSize = 1024;
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constexpr int kDecimal = 10;
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@ -55,10 +55,6 @@ Status ProposalInterface::Infer(std::vector<mindspore::MSTensor> *inputs, std::v
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size_t id = 0;
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while (id < outputs->size()) {
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// 待补完
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// outputs[id]->format_ = input->format_;
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// outputs[id]->data_type_ = kNumberTypeFloat32;
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// 设置type为int
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std::vector<int64_t> shape{-1, COORDI_NUM};
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(*outputs)[id].SetShape(shape);
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(*outputs)[id].SetDataType(DataType::kNumberTypeFloat32);
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@ -46,8 +46,8 @@ function linux_release_package()
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mkdir -p ${output_path}/release/linux/nnie/
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cp ${input_path}/ubuntu_x86/avx/*.tar.gz* ${output_path}/release/linux/
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cp ${input_path}/linux_aarch32/*.tar.gz* ${output_path}/release/linux/
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cp ${input_path}/ubuntu_x86/nnie/3516D/*.tar.gz* ${output_path}/release/linux/nnie/
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cp -r ${input_path}/linux_aarch32/nnie/Hi* ${output_path}/release/linux/nnie/
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cp ${input_path}/ubuntu_x86/nnie/Hi3516D/*.tar.gz* ${output_path}/release/linux/nnie/
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}
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function windows_release_package()
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