[DOCS] Python snippets for Query device page (#10789)
* create python snippets * remove redundant space
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#include <openvino/runtime/core.hpp>
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# Copyright (C) 2018-2022 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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#
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int main() {
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//! [get_available_devices]
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ov::Core core;
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std::vector<std::string> available_devices = core.get_available_devices();
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//! [get_available_devices]
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from openvino.runtime import Core
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//! [hetero_priorities]
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auto device_priorites = core.get_property("HETERO", ov::device::priorities);
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//! [hetero_priorities]
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# [get_available_devices]
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core = Core()
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available_devices = core.available_devices
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# [get_available_devices]
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//! [cpu_device_name]
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auto cpu_device_name = core.get_property("CPU", ov::device::full_name);
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//! [cpu_device_name]
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# [cpu_device_name]
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cpu_device_name = core.get_property("CPU", "FULL_DEVICE_NAME")
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# [cpu_device_name]
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auto model = core.read_model("sample.xml");
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{
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//! [compile_model_with_property]
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auto compiled_model = core.compile_model(model, "CPU",
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ov::hint::performance_mode(ov::hint::PerformanceMode::THROUGHPUT),
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ov::hint::inference_precision(ov::element::f32));
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//! [compile_model_with_property]
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}
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model = core.read_model(model="sample.xml")
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# [compile_model_with_property]
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config = {"PERFORMANCE_HINT": "THROUGHPUT",
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"INFERENCE_PRECISION_HINT": "f32"}
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compiled_model = core.compile_model(model, "CPU", config)
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# [compile_model_with_property]
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{
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//! [optimal_number_of_infer_requests]
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auto compiled_model = core.compile_model(model, "CPU");
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auto nireq = compiled_model.get_property(ov::optimal_number_of_infer_requests);
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//! [optimal_number_of_infer_requests]
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}
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{
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//! [core_set_property_then_compile]
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// set letency hint is a default for CPU
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core.set_property("CPU", ov::hint::performance_mode(ov::hint::PerformanceMode::LATENCY));
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// compiled with latency configuration hint
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auto compiled_model_latency = core.compile_model(model, "CPU");
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// compiled with overriden ov::hint::performance_mode value
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auto compiled_model_thrp = core.compile_model(model, "CPU",
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ov::hint::performance_mode(ov::hint::PerformanceMode::THROUGHPUT));
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//! [core_set_property_then_compile]
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}
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# [optimal_number_of_infer_requests]
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compiled_model = core.compile_model(model, "CPU")
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nireq = compiled_model.get_property("OPTIMAL_NUMBER_OF_INFER_REQUESTS");
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# [optimal_number_of_infer_requests]
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{
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//! [device_thermal]
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auto compiled_model = core.compile_model(model, "MYRIAD");
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float temperature = compiled_model.get_property(ov::device::thermal);
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//! [device_thermal]
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}
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{
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//! [inference_num_threads]
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auto compiled_model = core.compile_model(model, "CPU");
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auto nthreads = compiled_model.get_property(ov::inference_num_threads);
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//! [inference_num_threads]
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}
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# [core_set_property_then_compile]
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# latency hint is a default for CPU
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core.set_property("CPU", {"PERFORMANCE_HINT": "LATENCY"})
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# compiled with latency configuration hint
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compiled_model_latency = core.compile_model(model, "CPU")
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# compiled with overriden performance hint value
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config = {"PERFORMANCE_HINT": "THROUGHPUT"}
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compiled_model_thrp = core.compile_model(model, "CPU", config)
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# [core_set_property_then_compile]
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{
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//! [multi_device]
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auto compiled_model = core.compile_model(model, "MULTI",
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ov::device::priorities("CPU", "GPU"));
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// change the order of priorities
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compiled_model.set_property(ov::device::priorities("GPU", "CPU"));
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//! [multi_device]
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}
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return 0;
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}
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# [device_thermal]
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compiled_model = core.compile_model(model, "MYRIAD")
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temperature = compiled_model.get_property("DEVICE_THERMAL")
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# [device_thermal]
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# [inference_num_threads]
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compiled_model = core.compile_model(model, "CPU")
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nthreads = compiled_model.get_property("INFERENCE_NUM_THREADS")
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# [inference_num_threads]
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# [multi_device]
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config = {"MULTI_DEVICE_PRIORITIES": "CPU,GPU"}
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compiled_model = core.compile_model(model, "MULTI", config)
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# change the order of priorities
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compiled_model.set_property({"MULTI_DEVICE_PRIORITIES": "GPU,CPU"})
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# [multi_device]
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