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[Enhancement] Load openvino model from memory (#2027)

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* fix cpu docker (different openvino ver for python & sdk)

* load openvino model from memory

* fix lint
This commit is contained in:
Chen Xin 2023-04-28 16:13:14 +08:00 committed by GitHub
parent ca773a78f0
commit bc79c0dd2b
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GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 11 additions and 23 deletions
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24
csrc/mmdeploy/net/openvino/openvino_net.cpp
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@ -77,30 +77,18 @@ Result<void> OpenVINONet::Init(const Value& args) {
auto model = context["model"].get<Model>(); auto model = context["model"].get<Model>();
OUTCOME_TRY(auto config, model.GetModelConfig(name)); OUTCOME_TRY(auto config, model.GetModelConfig(name));
// TODO: read network with stream
// save xml and bin to temp file
auto tmp_dir = fs::temp_directory_path();
std::string tmp_xml = (tmp_dir / fs::path("tmp.xml")).string();
std::string tmp_bin = (tmp_dir / fs::path("tmp.bin")).string();
OUTCOME_TRY(auto raw_xml, model.ReadFile(config.net)); OUTCOME_TRY(auto raw_xml, model.ReadFile(config.net));
OUTCOME_TRY(auto raw_bin, model.ReadFile(config.weights)); OUTCOME_TRY(auto raw_bin, model.ReadFile(config.weights));
auto ov_tensor = InferenceEngine::TensorDesc(InferenceEngine::Precision::U8, {raw_bin.size()},
try { InferenceEngine::Layout::C);
std::ofstream xml_out(tmp_xml, std::ios::binary); auto ov_blob = InferenceEngine::make_shared_blob<uint8_t>(ov_tensor);
xml_out << raw_xml; ov_blob->allocate();
xml_out.close(); memcpy(ov_blob->buffer(), raw_bin.data(), ov_blob->byteSize());
std::ofstream bin_out(tmp_bin, std::ios::binary);
bin_out << raw_bin;
bin_out.close();
} catch (const std::exception& e) {
MMDEPLOY_ERROR("unhandled exception when creating tmp xml/bin: {}", e.what());
return Status(eFail);
}
try { try {
// create cnnnetwork // create cnnnetwork
core_ = InferenceEngine::Core(); core_ = InferenceEngine::Core();
network_ = core_.ReadNetwork(tmp_xml, tmp_bin); network_ = core_.ReadNetwork(raw_xml, std::move(ov_blob));
// set input tensor // set input tensor
InferenceEngine::InputsDataMap input_info = network_.getInputsInfo(); InferenceEngine::InputsDataMap input_info = network_.getInputsInfo();

10
docker/CPU/Dockerfile
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@ -1,4 +1,4 @@
FROM openvino/ubuntu18_dev:2021.4.2 FROM openvino/ubuntu20_dev:2022.3.0
ARG PYTHON_VERSION=3.8 ARG PYTHON_VERSION=3.8
ARG TORCH_VERSION=1.10.0 ARG TORCH_VERSION=1.10.0
ARG TORCHVISION_VERSION=0.11.0 ARG TORCHVISION_VERSION=0.11.0
@ -57,7 +57,7 @@ RUN if [ ${USE_SRC_INSIDE} == true ] ; \
RUN /opt/conda/bin/pip install torch==${TORCH_VERSION}+cpu torchvision==${TORCHVISION_VERSION}+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html \ RUN /opt/conda/bin/pip install torch==${TORCH_VERSION}+cpu torchvision==${TORCHVISION_VERSION}+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html \
&& /opt/conda/bin/pip install --no-cache-dir openmim && /opt/conda/bin/pip install --no-cache-dir openmim
RUN /opt/conda/bin/mim install --no-cache-dir "mmcv"${MMCV_VERSION} onnxruntime==${ONNXRUNTIME_VERSION} openvino-dev mmengine${MMENGINE_VERSION} RUN /opt/conda/bin/mim install --no-cache-dir "mmcv"${MMCV_VERSION} onnxruntime==${ONNXRUNTIME_VERSION} openvino-dev==2022.3.0 mmengine${MMENGINE_VERSION}
ENV PATH /opt/conda/bin:$PATH ENV PATH /opt/conda/bin:$PATH
WORKDIR /root/workspace WORKDIR /root/workspace
@ -100,14 +100,14 @@ RUN git clone -b main https://github.com/open-mmlab/mmdeploy.git &&\
/opt/conda/bin/mim install -e . /opt/conda/bin/mim install -e .
### build SDK ### build SDK
ENV LD_LIBRARY_PATH="/root/workspace/mmdeploy/build/lib:/opt/intel/openvino/deployment_tools/ngraph/lib:/opt/intel/openvino/deployment_tools/inference_engine/lib/intel64:${LD_LIBRARY_PATH}" ENV LD_LIBRARY_PATH="/root/workspace/mmdeploy/build/lib:${LD_LIBRARY_PATH}"
RUN cd mmdeploy && rm -rf build/CM* && mkdir -p build && cd build && cmake .. \ RUN cd mmdeploy && rm -rf build/CM* && mkdir -p build && cd build && cmake .. \
-DMMDEPLOY_BUILD_SDK=ON \ -DMMDEPLOY_BUILD_SDK=ON \
-DMMDEPLOY_BUILD_EXAMPLES=ON \ -DMMDEPLOY_BUILD_EXAMPLES=ON \
-DCMAKE_CXX_COMPILER=g++-7 \ -DCMAKE_CXX_COMPILER=g++-9 \
-DONNXRUNTIME_DIR=${ONNXRUNTIME_DIR} \ -DONNXRUNTIME_DIR=${ONNXRUNTIME_DIR} \
-Dncnn_DIR=/root/workspace/ncnn/build/install/lib/cmake/ncnn \ -Dncnn_DIR=/root/workspace/ncnn/build/install/lib/cmake/ncnn \
-DInferenceEngine_DIR=/opt/intel/openvino/deployment_tools/inference_engine/share \ -DInferenceEngine_DIR=/opt/intel/openvino/runtime/cmake \
-DMMDEPLOY_TARGET_DEVICES=cpu \ -DMMDEPLOY_TARGET_DEVICES=cpu \
-DMMDEPLOY_BUILD_SDK_PYTHON_API=ON \ -DMMDEPLOY_BUILD_SDK_PYTHON_API=ON \
-DMMDEPLOY_TARGET_BACKENDS="ort;ncnn;openvino" \ -DMMDEPLOY_TARGET_BACKENDS="ort;ncnn;openvino" \