9bc7ebda7b
* Added more information about tensor names * Fixed comment and added documentation for extensions * Fixed typo
104 lines
4.2 KiB
C++
104 lines
4.2 KiB
C++
// Copyright (C) 2018-2021 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#include <ie_core.hpp>
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int main() {
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//! [ie:create_core]
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InferenceEngine::Core core;
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//! [ie:create_core]
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//! [ie:read_model]
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InferenceEngine::CNNNetwork network = core.ReadNetwork("model.xml");
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//! [ie:read_model]
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InferenceEngine::InputsDataMap inputs = network.getInputsInfo();
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InferenceEngine::OutputsDataMap outputs = network.getOutputsInfo();
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//! [ie:compile_model]
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InferenceEngine::ExecutableNetwork exec_network = core.LoadNetwork(network, "CPU");
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//! [ie:compile_model]
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//! [ie:create_infer_request]
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InferenceEngine::InferRequest infer_request = exec_network.CreateInferRequest();
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//! [ie:create_infer_request]
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//! [ie:get_input_tensor]
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InferenceEngine::Blob::Ptr input_blob1 = infer_request.GetBlob(inputs.begin()->first);
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// fill first blob
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InferenceEngine::MemoryBlob::Ptr minput1 = InferenceEngine::as<InferenceEngine::MemoryBlob>(input_blob1);
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if (minput1) {
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// locked memory holder should be alive all time while access to its
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// buffer happens
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auto minputHolder = minput1->wmap();
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// Original I64 precision was converted to I32
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auto data = minputHolder.as<InferenceEngine::PrecisionTrait<InferenceEngine::Precision::I32>::value_type*>();
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// Fill data ...
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}
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InferenceEngine::Blob::Ptr input_blob2 = infer_request.GetBlob("data2");
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// fill first blob
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InferenceEngine::MemoryBlob::Ptr minput2 = InferenceEngine::as<InferenceEngine::MemoryBlob>(input_blob2);
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if (minput2) {
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// locked memory holder should be alive all time while access to its
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// buffer happens
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auto minputHolder = minput2->wmap();
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// Original I64 precision was converted to I32
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auto data = minputHolder.as<InferenceEngine::PrecisionTrait<InferenceEngine::Precision::I32>::value_type*>();
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// Fill data ...
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}
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//! [ie:get_input_tensor]
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//! [ie:inference]
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infer_request.Infer();
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//! [ie:inference]
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//! [ie:start_async_and_wait]
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// NOTE: For demonstration purposes we are trying to set callback
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// which restarts inference inside one more time, so two inferences happen here
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// Start inference without blocking current thread
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auto restart_once = true;
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infer_request.SetCompletionCallback<std::function<void(InferenceEngine::InferRequest, InferenceEngine::StatusCode)>>(
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[&, restart_once](InferenceEngine::InferRequest request, InferenceEngine::StatusCode status) mutable {
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if (status != InferenceEngine::OK) {
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// Process error code
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} else {
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// Extract inference result
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InferenceEngine::Blob::Ptr output_blob = request.GetBlob(outputs.begin()->first);
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// Restart inference if needed
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if (restart_once) {
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request.StartAsync();
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restart_once = false;
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}
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}
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});
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infer_request.StartAsync();
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// Get inference status immediately
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InferenceEngine::StatusCode status = infer_request.Wait(InferenceEngine::InferRequest::STATUS_ONLY);
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// Wait for 1 milisecond
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status = infer_request.Wait(1);
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// Wait for inference completion
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infer_request.Wait(InferenceEngine::InferRequest::RESULT_READY);
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//! [ie:start_async_and_wait]
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//! [ie:get_output_tensor]
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InferenceEngine::Blob::Ptr output_blob = infer_request.GetBlob(outputs.begin()->first);
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InferenceEngine::MemoryBlob::Ptr moutput = InferenceEngine::as<InferenceEngine::MemoryBlob>(output_blob);
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if (moutput) {
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// locked memory holder should be alive all time while access to its
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// buffer happens
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auto minputHolder = moutput->rmap();
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// Original I64 precision was converted to I32
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auto data =
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minputHolder.as<const InferenceEngine::PrecisionTrait<InferenceEngine::Precision::I32>::value_type*>();
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// process output data
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}
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//! [ie:get_output_tensor]
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//! [ie:load_old_extension]
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core.AddExtension(std::make_shared<InferenceEngine::Extension>("path_to_extension_library.so"));
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//! [ie:load_old_extension]
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return 0;
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}
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