37 lines
1.4 KiB
C++
37 lines
1.4 KiB
C++
#include <openvino/openvino.hpp>
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int main() {
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ov::Core core;
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// Read a network in IR, PaddlePaddle, or ONNX format:
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std::shared_ptr<ov::Model> model = core.read_model("sample.xml");
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{
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//! [part4]
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// Example 1
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ov::CompiledModel compiled_model0 = core.compile_model(model, "AUTO",
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ov::hint::model_priority(ov::hint::Priority::HIGH));
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ov::CompiledModel compiled_model1 = core.compile_model(model, "AUTO",
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ov::hint::model_priority(ov::hint::Priority::MEDIUM));
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ov::CompiledModel compiled_model2 = core.compile_model(model, "AUTO",
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ov::hint::model_priority(ov::hint::Priority::LOW));
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/************
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Assume that all the devices (CPU, GPU, and MYRIAD) can support all the models.
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Result: compiled_model0 will use GPU, compiled_model1 will use MYRIAD, compiled_model2 will use CPU.
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************/
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// Example 2
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ov::CompiledModel compiled_model3 = core.compile_model(model, "AUTO",
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ov::hint::model_priority(ov::hint::Priority::LOW));
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ov::CompiledModel compiled_model4 = core.compile_model(model, "AUTO",
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ov::hint::model_priority(ov::hint::Priority::MEDIUM));
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ov::CompiledModel compiled_model5 = core.compile_model(model, "AUTO",
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ov::hint::model_priority(ov::hint::Priority::LOW));
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/************
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Assume that all the devices (CPU, GPU, and MYRIAD) can support all the models.
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Result: compiled_model3 will use GPU, compiled_model4 will use GPU, compiled_model5 will use MYRIAD.
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************/
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//! [part4]
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}
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return 0;
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}
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