5b25dbee22
* ov2.0 IE samples modification apply code style turn off clang style check for headers order unify samples a bit add yuv nv12 reader to format_reader, helloe_nv112 sample hello_reshape_ssd ov2.0 * sync with PR 8629 preprocessing api changes * fix for slog << vector<int> * add operator<< for ov::Version from PR-8687 * Update samples/cpp/hello_nv12_input_classification/main.cpp Co-authored-by: Mikhail Nosov <mikhail.nosov@intel.com> * apply code style * change according to review comments * add const qualifier * apply code style * std::ostream for old inference engine version to make VPU plugin tests happy * apply code style * revert changes in print version for old api samples * keep inference_engine.hpp for not ov2.0 yet samples * fix merge artifacts * fix compilation * apply code style * Fixed classification sample test * Revert changes in hello_reshape_ssd sample * rebase to master, sync with PR-9054 * fix issues found by C++ tests * rebased and sync with PR-9051 * fix test result parsers for classification tests (except unicode one) * fix mismatches after merge * rebase and sync with PR-9144 Co-authored-by: Mikhail Nosov <mikhail.nosov@intel.com> Co-authored-by: antonrom23 <anton.romanov@intel.com>
67 lines
2.1 KiB
C++
67 lines
2.1 KiB
C++
// Copyright (C) 2021 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#if defined(HAVE_GPU_DEVICE_MEM_SUPPORT)
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# define HAVE_DEVICE_MEM_SUPPORT
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# include "gpu/gpu_context_api_ocl.hpp"
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#endif
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// clang-format off
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#include "inference_engine.hpp"
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#include "infer_request_wrap.hpp"
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#include "utils.hpp"
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// clang-format on
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namespace gpu {
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#ifdef HAVE_DEVICE_MEM_SUPPORT
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struct OpenCL {
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cl::Context _context;
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cl::Device _device;
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cl::CommandQueue _queue;
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explicit OpenCL(std::shared_ptr<std::vector<cl_context_properties>> media_api_context_properties = nullptr) {
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// get Intel GPU OCL device, create context and queue
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{
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std::vector<cl::Device> devices;
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std::vector<cl::Platform> platforms;
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const unsigned int refVendorID = 0x8086;
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cl::Platform::get(&platforms);
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for (auto& p : platforms) {
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p.getDevices(CL_DEVICE_TYPE_GPU, &devices);
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for (auto& d : devices) {
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if (refVendorID == d.getInfo<CL_DEVICE_VENDOR_ID>()) {
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_device = d;
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_context = cl::Context(_device);
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break;
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}
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}
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}
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cl_command_queue_properties props = CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE;
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_queue = cl::CommandQueue(_context, _device, props);
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}
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}
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explicit OpenCL(cl_context context) {
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// user-supplied context handle
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_context = cl::Context(context, true);
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_device = cl::Device(_context.getInfo<CL_CONTEXT_DEVICES>()[0].get(), true);
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cl_command_queue_properties props = CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE;
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_queue = cl::CommandQueue(_context, _device, props);
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}
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};
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#endif
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void fillRemoteBlobs(const std::vector<std::string>& inputFiles,
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const size_t& batchSize,
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benchmark_app::InputsInfo& app_inputs_info,
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std::vector<InferReqWrap::Ptr> requests,
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const InferenceEngine::ExecutableNetwork& exeNetwork);
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} // namespace gpu
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