Remove unnecessary files
This commit is contained in:
nums11
Родитель
869246a4cd
Коммит
c1733a9e94
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@ -736,7 +736,7 @@ namespace WinMLSamplesGallery.Samples
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.SetOutput("C", "SubOutput"))
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.Operators.Add(new LearningModelOperator("Transpose") // Move the output back to NHWC (this is what efficientnet requires)
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.SetInput("data", "SubOutput")
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.SetAttribute("perm", TensorInt64Bit.CreateFromArray(new long[] { 4 }, new long[] { 0, 2, 3, 1 })) // 0,3,1,2
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.SetAttribute("perm", TensorInt64Bit.CreateFromArray(new long[] { 4 }, new long[] { 0, 2, 3, 1 }))
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.SetOutput("transposed", "Output"));
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return builder.CreateModel();
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@ -1,10 +0,0 @@
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using System;
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using System.Collections.Generic;
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using System.Text;
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namespace WinMLSamplesGallery.TestNamespace
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{
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class TestClass
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{
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}
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}
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Разница между файлами не показана из-за своего большого размера
Загрузить разницу
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@ -1,714 +0,0 @@
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//#include "pch.h"
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//
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//// dwayne_sanity_test_app.cpp : This file contains the 'main' function. Program execution begins and ends there.
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////
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//
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//#define NOMINMAX
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//#define WIN32_LEAN_AND_MEAN
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//
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//#include <iostream>
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//#include <cstdio>
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//#include <algorithm>
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//#include <numeric>
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//#include <functional>
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//#include <utility>
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//#include <string_view>
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//#include <span>
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//#include <optional>
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//#include <memory>
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//
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//#include <windows.h>
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//#include <d3d12.h>
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//#include <wrl/client.h>
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////#include "dml_provider_factory.h"
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//#include "C:\Users\numform\Windows-Machine-Learning\Samples\WinMLSamplesGallery\packages\Microsoft.ML.OnnxRuntime.DirectML.1.10.0\build\native\include\dml_provider_factory.h"
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////#include "onnxruntime_cxx_api.h"
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//#include "C:\Users\numform\Windows-Machine-Learning\Samples\WinMLSamplesGallery\packages\Microsoft.ML.OnnxRuntime.DirectML.1.10.0\build\native\include\onnxruntime_cxx_api.h"
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//
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//////////////////////////////////////////////////////////////////////////////////
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//
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//#define THROW_IF_FAILED(hr) {HRESULT localHr = (hr); if (FAILED(hr)) throw hr;}
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//#define RETURN_IF_FAILED(hr) {HRESULT localHr = (hr); if (FAILED(hr)) return hr;}
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//#define THROW_IF_NOT_OK(status) {auto localStatus = (status); if (localStatus) throw E_FAIL;}
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//#define RETURN_HR_IF_NOT_OK(status) {auto localStatus = (status); if (localStatus) return E_FAIL;}
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//
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//template <typename T>
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//using BaseType =
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//std::remove_cv_t<
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// std::remove_reference_t<
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// std::remove_pointer_t<
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// std::remove_all_extents_t<T>
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// >
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// >
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//>;
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//
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//template<typename T>
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//using deleting_unique_ptr = std::unique_ptr<T, std::function<void(T*)>>;
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//
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//template <typename C, typename T = BaseType<decltype(*std::declval<C>().data())>>
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//T GetElementCount(C const& range)
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//{
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// return std::accumulate(range.begin(), range.end(), static_cast<T>(1), std::multiplies<T>());
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//};
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//
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//////////////////////////////////////////////////////////////////////////////////
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//
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//Ort::Value CreateTensorValueUsingD3DResource(
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// ID3D12Device* d3dDevice,
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// OrtDmlApi const& ortDmlApi,
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// Ort::MemoryInfo const& memoryInformation,
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// std::span<const int64_t> dimensions,
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// ONNXTensorElementDataType elementDataType,
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// size_t elementByteSize,
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// /*out*/ void** dmlEpResourceWrapper
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//);
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//
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//////////////////////////////////////////////////////////////////////////////////
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//
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//int main()
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//{
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// // Squeezenet opset v7 https://github.com/onnx/models/blob/master/vision/classification/squeezenet/README.md
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// const wchar_t* modelFilePath = L"./squeezenet1.1-7.onnx";
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// const char* modelInputTensorName = "data";
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// const char* modelOutputTensorName = "squeezenet0_flatten0_reshape0";
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// const std::array<int64_t, 4> inputShape = { 1, 3, 224, 224 };
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// const std::array<int64_t, 2> outputShape = { 1, 1000 };
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//
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// const bool passTensorsAsD3DResources = true;
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//
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// LARGE_INTEGER startTime;
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// LARGE_INTEGER d3dDeviceCreationTime;
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// LARGE_INTEGER sessionCreationTime;
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// LARGE_INTEGER tensorCreationTime;
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// LARGE_INTEGER bindingTime;
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// LARGE_INTEGER runTime;
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// LARGE_INTEGER synchronizeOutputsTime;
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// LARGE_INTEGER cpuFrequency;
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// QueryPerformanceFrequency(&cpuFrequency);
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// QueryPerformanceCounter(&startTime);
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//
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// try
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// {
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// Microsoft::WRL::ComPtr<ID3D12Device> d3d12Device;
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// THROW_IF_FAILED(D3D12CreateDevice(nullptr, D3D_FEATURE_LEVEL_11_0, IID_PPV_ARGS(&d3d12Device)));
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// QueryPerformanceCounter(&d3dDeviceCreationTime);
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//
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// OrtApi const& ortApi = Ort::GetApi(); // Uses ORT_API_VERSION
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// const OrtDmlApi* ortDmlApi;
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// THROW_IF_NOT_OK(ortApi.GetExecutionProviderApi("DML", ORT_API_VERSION, reinterpret_cast<const void**>(&ortDmlApi)));
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//
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// // ONNX Runtime setup
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// Ort::Env ortEnvironment(ORT_LOGGING_LEVEL_WARNING, "DirectML_Direct3D_TensorAllocation_Test");
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// Ort::SessionOptions sessionOptions;
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// sessionOptions.SetExecutionMode(ExecutionMode::ORT_SEQUENTIAL);
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// sessionOptions.DisableMemPattern();
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// sessionOptions.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_ALL);
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// ortApi.AddFreeDimensionOverrideByName(sessionOptions, "batch_size", 1);
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// OrtSessionOptionsAppendExecutionProvider_DML(sessionOptions, 0);
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// Ort::Session session = Ort::Session(ortEnvironment, modelFilePath, sessionOptions);
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// QueryPerformanceCounter(&sessionCreationTime);
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//
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// Ort::IoBinding ioBinding = Ort::IoBinding::IoBinding(session);
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// const char* memoryInformationName = passTensorsAsD3DResources ? "DML" : "Cpu";
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// Ort::MemoryInfo memoryInformation(memoryInformationName, OrtAllocatorType::OrtDeviceAllocator, 0, OrtMemType::OrtMemTypeDefault);
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// // Not needed: Ort::Allocator allocator(session, memoryInformation);
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//
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// // Create input tensor.
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// Ort::Value inputTensor(nullptr);
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// std::vector<float> inputTensorValues(static_cast<size_t>(GetElementCount(inputShape)), 0.0f);
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// std::iota(inputTensorValues.begin(), inputTensorValues.end(), 0.0f);
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// Microsoft::WRL::ComPtr<IUnknown> inputTensorEpWrapper;
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//
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// if (passTensorsAsD3DResources)
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// {
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// // Create empty D3D resource for input.
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// inputTensor = CreateTensorValueUsingD3DResource(
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// d3d12Device.Get(),
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// *ortDmlApi,
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// memoryInformation,
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// inputShape,
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// ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT,
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// sizeof(float),
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// /*out*/ IID_PPV_ARGS_Helper(inputTensorEpWrapper.GetAddressOf())
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// );
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// }
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// else // CPU tensor
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// {
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// inputTensor = Ort::Value::CreateTensor<float>(memoryInformation, inputTensorValues.data(), inputTensorValues.size(), inputShape.data(), 4);
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// }
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//
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// // Create output tensor on device memory.
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// Ort::Value outputTensor(nullptr);
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// std::vector<float> outputTensorValues(static_cast<size_t>(GetElementCount(outputShape)), 0.0f);
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// Microsoft::WRL::ComPtr<IUnknown> outputTensorEpWrapper;
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//
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// if (passTensorsAsD3DResources)
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// {
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// outputTensor = CreateTensorValueUsingD3DResource(
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// d3d12Device.Get(),
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// *ortDmlApi,
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// memoryInformation,
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// outputShape,
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// ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT,
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// sizeof(float),
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// /*out*/ IID_PPV_ARGS_Helper(outputTensorEpWrapper.GetAddressOf())
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// );
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// }
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// else // CPU tensor
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// {
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// outputTensor = Ort::Value::CreateTensor<float>(memoryInformation, outputTensorValues.data(), outputTensorValues.size(), outputShape.data(), 4);
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// }
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//
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// QueryPerformanceCounter(&tensorCreationTime);
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//
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// ////////////////////////////////////////
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// // Bind the tensor inputs to the model, and run it.
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// ioBinding.BindInput(modelInputTensorName, inputTensor);
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// ioBinding.BindOutput(modelOutputTensorName, outputTensor);
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// ioBinding.SynchronizeInputs();
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// QueryPerformanceCounter(&bindingTime);
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//
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// Ort::RunOptions runOptions;
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//
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// // TODO: Upload inputTensorValues to GPU inputTensor.
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//
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// printf("Beginning execution.\n");
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// printf("Running Session.\n");
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// session.Run(runOptions, ioBinding);
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// QueryPerformanceCounter(&runTime);
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// printf("Synchronizing outputs.\n");
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// ioBinding.SynchronizeOutputs();
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// QueryPerformanceCounter(&synchronizeOutputsTime);
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// printf("Finished execution.\n");
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//
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// auto printDuration = [=](char const* message, LARGE_INTEGER qpcTime) mutable
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// {
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// double durationMs = static_cast<double>(qpcTime.QuadPart - startTime.QuadPart);
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// durationMs /= static_cast<double>(cpuFrequency.QuadPart);
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// durationMs *= 1000.0;
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// printf("%s % 12.6f\n", message, durationMs);
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//
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// startTime = qpcTime;
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// };
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// printDuration("d3dDeviceCreationTime ...", d3dDeviceCreationTime);
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// printDuration("sessionCreationTime .....", sessionCreationTime);
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// printDuration("tensorCreationTime ......", tensorCreationTime);
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// printDuration("bindingTime .............", bindingTime);
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// printDuration("runTime .................", runTime);
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// printDuration("synchronizeOutputsTime ..", synchronizeOutputsTime);
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//
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// // TODO: Download inputTensorValues from GPU outputTensor.
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//
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// ////////////////////////////////////////
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// // Print the top results if the output tensors were on the CPU.
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// if (!passTensorsAsD3DResources)
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// {
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//#if 1 // Print first 10 values.
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// int min = 0;
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// if (outputTensorValues.size() < size_t(10))
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// min = outputTensorValues.size();
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// else
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// min = size_t(10);
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// for (int i = 0; i <= min; ++i)
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// {
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// printf("output[%d] = %f\n", i, outputTensorValues[i]);
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// }
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//#else // Print top 10.
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// std::vector<uint32_t> indices(outputTensorValues.size(), 0);
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// std::iota(indices.begin(), indices.end(), 0);
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// sort(
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// indices.begin(),
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// indices.end(),
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// [&](uint32_t a, uint32_t b)
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// {
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// return (outputTensorValues[a] > outputTensorValues[b]);
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// }
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// );
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// for (int i = 0; i <= std::min(indices.size(), size_t(10)); ++i)
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// {
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// printf("output[%d] = %f\n", indices[i], outputTensorValues[indices[i]]);
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// }
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//#endif
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// }
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// }
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// catch (Ort::Exception const& exception)
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// {
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// printf("Error running model inference: %s\n", exception.what());
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// return EXIT_FAILURE;
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// }
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// catch (std::exception const& exception)
|
||||
// {
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// printf("Error running model inference: %s\n", exception.what());
|
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// return EXIT_FAILURE;
|
||||
// }
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//
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// return 0;
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//}
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//
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||||
//Microsoft::WRL::ComPtr<ID3D12Resource> CreateD3D12ResourceForTensor(
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// ID3D12Device* d3dDevice,
|
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// size_t elementByteSize,
|
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// std::span<const int64_t> tensorDimensions
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//)
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//{
|
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// // Try to allocate the backing memory for the caller
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// auto bufferSize = GetElementCount(tensorDimensions);
|
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// size_t bufferByteSize = static_cast<size_t>(bufferSize * elementByteSize);
|
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//
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// // DML needs the resources' sizes to be a multiple of 4 bytes
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// (bufferByteSize += 3) &= ~3;
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//
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||||
// D3D12_HEAP_PROPERTIES heapProperties = {
|
||||
// D3D12_HEAP_TYPE_DEFAULT,
|
||||
// D3D12_CPU_PAGE_PROPERTY_UNKNOWN,
|
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// D3D12_MEMORY_POOL_UNKNOWN,
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// 0,
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||||
// 0
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||||
// };
|
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// D3D12_RESOURCE_DESC resourceDesc = {
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// D3D12_RESOURCE_DIMENSION_BUFFER,
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||||
// 0,
|
||||
// static_cast<uint64_t>(bufferByteSize),
|
||||
// 1,
|
||||
// 1,
|
||||
// 1,
|
||||
// DXGI_FORMAT_UNKNOWN,
|
||||
// {1, 0},
|
||||
// D3D12_TEXTURE_LAYOUT_ROW_MAJOR,
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||||
// D3D12_RESOURCE_FLAG_ALLOW_UNORDERED_ACCESS
|
||||
// };
|
||||
//
|
||||
// Microsoft::WRL::ComPtr<ID3D12Resource> gpuResource;
|
||||
// THROW_IF_FAILED(d3dDevice->CreateCommittedResource(
|
||||
// &heapProperties,
|
||||
// D3D12_HEAP_FLAG_NONE,
|
||||
// &resourceDesc,
|
||||
// D3D12_RESOURCE_STATE_COMMON,
|
||||
// nullptr,
|
||||
// __uuidof(ID3D12Resource),
|
||||
// /*out*/ &gpuResource
|
||||
// ));
|
||||
//
|
||||
// return gpuResource;
|
||||
//}
|
||||
//
|
||||
//Ort::Value CreateTensorValueFromExistingD3DResource(
|
||||
// OrtDmlApi const& ortDmlApi,
|
||||
// Ort::MemoryInfo const& memoryInformation,
|
||||
// ID3D12Resource* d3dResource,
|
||||
// std::span<const int64_t> tensorDimensions,
|
||||
// ONNXTensorElementDataType elementDataType,
|
||||
// /*out*/ void** dmlEpResourceWrapper // Must stay alive with Ort::Value.
|
||||
//)
|
||||
//{
|
||||
// *dmlEpResourceWrapper = nullptr;
|
||||
//
|
||||
// void* dmlAllocatorResource;
|
||||
// THROW_IF_NOT_OK(ortDmlApi.CreateGPUAllocationFromD3DResource(d3dResource, &dmlAllocatorResource));
|
||||
// auto deleter = [&](void*) {ortDmlApi.FreeGPUAllocation(dmlAllocatorResource); };
|
||||
// deleting_unique_ptr<void> dmlAllocatorResourceCleanup(dmlAllocatorResource, deleter);
|
||||
//
|
||||
// size_t tensorByteSize = static_cast<size_t>(d3dResource->GetDesc().Width);
|
||||
// Ort::Value newValue(
|
||||
// Ort::Value::CreateTensor(
|
||||
// memoryInformation,
|
||||
// dmlAllocatorResource,
|
||||
// tensorByteSize,
|
||||
// tensorDimensions.data(),
|
||||
// tensorDimensions.size(),
|
||||
// elementDataType
|
||||
// )
|
||||
// );
|
||||
//
|
||||
// // Return values and the wrapped resource.
|
||||
// // TODO: Is there some way to get Ort::Value to just own the D3DResource
|
||||
// // directly so that it gets freed after execution or session destruction?
|
||||
// *dmlEpResourceWrapper = dmlAllocatorResource;
|
||||
// dmlAllocatorResourceCleanup.release();
|
||||
//
|
||||
// return newValue;
|
||||
//}
|
||||
//
|
||||
//Ort::Value CreateTensorValueUsingD3DResource(
|
||||
// ID3D12Device* d3d12Device,
|
||||
// OrtDmlApi const& ortDmlApi,
|
||||
// Ort::MemoryInfo const& memoryInformation,
|
||||
// std::span<const int64_t> tensorDimensions,
|
||||
// ONNXTensorElementDataType elementDataType,
|
||||
// size_t elementByteSize,
|
||||
// /*out*/ void** dmlEpResourceWrapper // Must stay alive with Ort::Value.
|
||||
//)
|
||||
//{
|
||||
// // Create empty resource (values don't matter because we won't read them back anyway).
|
||||
// Microsoft::WRL::ComPtr<ID3D12Resource> d3dResource = CreateD3D12ResourceForTensor(
|
||||
// d3d12Device,
|
||||
// sizeof(float),
|
||||
// tensorDimensions
|
||||
// );
|
||||
//
|
||||
// return CreateTensorValueFromExistingD3DResource(
|
||||
// ortDmlApi,
|
||||
// memoryInformation,
|
||||
// d3dResource.Get(),
|
||||
// tensorDimensions,
|
||||
// ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT,
|
||||
// /*out*/ dmlEpResourceWrapper
|
||||
// );
|
||||
//}
|
||||
#include "pch.h"
|
||||
//
|
||||
//// dwayne_sanity_test_app.cpp : This file contains the 'main' function. Program execution begins and ends there.
|
||||
////
|
||||
//
|
||||
//#define NOMINMAX
|
||||
//#define WIN32_LEAN_AND_MEAN
|
||||
//
|
||||
//#include <iostream>
|
||||
//#include <cstdio>
|
||||
//#include <algorithm>
|
||||
//#include <numeric>
|
||||
//#include <functional>
|
||||
//#include <utility>
|
||||
//#include <string_view>
|
||||
//#include <span>
|
||||
//#include <optional>
|
||||
//#include <memory>
|
||||
//
|
||||
//#include <windows.h>
|
||||
//#include <d3d12.h>
|
||||
//#include <wrl/client.h>
|
||||
////#include "dml_provider_factory.h"
|
||||
//#include "C:\Users\numform\Windows-Machine-Learning\Samples\WinMLSamplesGallery\packages\Microsoft.ML.OnnxRuntime.DirectML.1.10.0\build\native\include\dml_provider_factory.h"
|
||||
////#include "onnxruntime_cxx_api.h"
|
||||
//#include "C:\Users\numform\Windows-Machine-Learning\Samples\WinMLSamplesGallery\packages\Microsoft.ML.OnnxRuntime.DirectML.1.10.0\build\native\include\onnxruntime_cxx_api.h"
|
||||
//
|
||||
//////////////////////////////////////////////////////////////////////////////////
|
||||
//
|
||||
//#define THROW_IF_FAILED(hr) {HRESULT localHr = (hr); if (FAILED(hr)) throw hr;}
|
||||
//#define RETURN_IF_FAILED(hr) {HRESULT localHr = (hr); if (FAILED(hr)) return hr;}
|
||||
//#define THROW_IF_NOT_OK(status) {auto localStatus = (status); if (localStatus) throw E_FAIL;}
|
||||
//#define RETURN_HR_IF_NOT_OK(status) {auto localStatus = (status); if (localStatus) return E_FAIL;}
|
||||
//
|
||||
//template <typename T>
|
||||
//using BaseType =
|
||||
//std::remove_cv_t<
|
||||
// std::remove_reference_t<
|
||||
// std::remove_pointer_t<
|
||||
// std::remove_all_extents_t<T>
|
||||
// >
|
||||
// >
|
||||
//>;
|
||||
//
|
||||
//template<typename T>
|
||||
//using deleting_unique_ptr = std::unique_ptr<T, std::function<void(T*)>>;
|
||||
//
|
||||
//template <typename C, typename T = BaseType<decltype(*std::declval<C>().data())>>
|
||||
//T GetElementCount(C const& range)
|
||||
//{
|
||||
// return std::accumulate(range.begin(), range.end(), static_cast<T>(1), std::multiplies<T>());
|
||||
//};
|
||||
//
|
||||
//////////////////////////////////////////////////////////////////////////////////
|
||||
//
|
||||
//Ort::Value CreateTensorValueUsingD3DResource(
|
||||
// ID3D12Device* d3dDevice,
|
||||
// OrtDmlApi const& ortDmlApi,
|
||||
// Ort::MemoryInfo const& memoryInformation,
|
||||
// std::span<const int64_t> dimensions,
|
||||
// ONNXTensorElementDataType elementDataType,
|
||||
// size_t elementByteSize,
|
||||
// /*out*/ void** dmlEpResourceWrapper
|
||||
//);
|
||||
//
|
||||
//////////////////////////////////////////////////////////////////////////////////
|
||||
//
|
||||
//int main()
|
||||
//{
|
||||
// // Squeezenet opset v7 https://github.com/onnx/models/blob/master/vision/classification/squeezenet/README.md
|
||||
// const wchar_t* modelFilePath = L"./squeezenet1.1-7.onnx";
|
||||
// const char* modelInputTensorName = "data";
|
||||
// const char* modelOutputTensorName = "squeezenet0_flatten0_reshape0";
|
||||
// const std::array<int64_t, 4> inputShape = { 1, 3, 224, 224 };
|
||||
// const std::array<int64_t, 2> outputShape = { 1, 1000 };
|
||||
//
|
||||
// const bool passTensorsAsD3DResources = true;
|
||||
//
|
||||
// LARGE_INTEGER startTime;
|
||||
// LARGE_INTEGER d3dDeviceCreationTime;
|
||||
// LARGE_INTEGER sessionCreationTime;
|
||||
// LARGE_INTEGER tensorCreationTime;
|
||||
// LARGE_INTEGER bindingTime;
|
||||
// LARGE_INTEGER runTime;
|
||||
// LARGE_INTEGER synchronizeOutputsTime;
|
||||
// LARGE_INTEGER cpuFrequency;
|
||||
// QueryPerformanceFrequency(&cpuFrequency);
|
||||
// QueryPerformanceCounter(&startTime);
|
||||
//
|
||||
// try
|
||||
// {
|
||||
// Microsoft::WRL::ComPtr<ID3D12Device> d3d12Device;
|
||||
// THROW_IF_FAILED(D3D12CreateDevice(nullptr, D3D_FEATURE_LEVEL_11_0, IID_PPV_ARGS(&d3d12Device)));
|
||||
// QueryPerformanceCounter(&d3dDeviceCreationTime);
|
||||
//
|
||||
// OrtApi const& ortApi = Ort::GetApi(); // Uses ORT_API_VERSION
|
||||
// const OrtDmlApi* ortDmlApi;
|
||||
// THROW_IF_NOT_OK(ortApi.GetExecutionProviderApi("DML", ORT_API_VERSION, reinterpret_cast<const void**>(&ortDmlApi)));
|
||||
//
|
||||
// // ONNX Runtime setup
|
||||
// Ort::Env ortEnvironment(ORT_LOGGING_LEVEL_WARNING, "DirectML_Direct3D_TensorAllocation_Test");
|
||||
// Ort::SessionOptions sessionOptions;
|
||||
// sessionOptions.SetExecutionMode(ExecutionMode::ORT_SEQUENTIAL);
|
||||
// sessionOptions.DisableMemPattern();
|
||||
// sessionOptions.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_ALL);
|
||||
// ortApi.AddFreeDimensionOverrideByName(sessionOptions, "batch_size", 1);
|
||||
// OrtSessionOptionsAppendExecutionProvider_DML(sessionOptions, 0);
|
||||
// Ort::Session session = Ort::Session(ortEnvironment, modelFilePath, sessionOptions);
|
||||
// QueryPerformanceCounter(&sessionCreationTime);
|
||||
//
|
||||
// Ort::IoBinding ioBinding = Ort::IoBinding::IoBinding(session);
|
||||
// const char* memoryInformationName = passTensorsAsD3DResources ? "DML" : "Cpu";
|
||||
// Ort::MemoryInfo memoryInformation(memoryInformationName, OrtAllocatorType::OrtDeviceAllocator, 0, OrtMemType::OrtMemTypeDefault);
|
||||
// // Not needed: Ort::Allocator allocator(session, memoryInformation);
|
||||
//
|
||||
// // Create input tensor.
|
||||
// Ort::Value inputTensor(nullptr);
|
||||
// std::vector<float> inputTensorValues(static_cast<size_t>(GetElementCount(inputShape)), 0.0f);
|
||||
// std::iota(inputTensorValues.begin(), inputTensorValues.end(), 0.0f);
|
||||
// Microsoft::WRL::ComPtr<IUnknown> inputTensorEpWrapper;
|
||||
//
|
||||
// if (passTensorsAsD3DResources)
|
||||
// {
|
||||
// // Create empty D3D resource for input.
|
||||
// inputTensor = CreateTensorValueUsingD3DResource(
|
||||
// d3d12Device.Get(),
|
||||
// *ortDmlApi,
|
||||
// memoryInformation,
|
||||
// inputShape,
|
||||
// ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT,
|
||||
// sizeof(float),
|
||||
// /*out*/ IID_PPV_ARGS_Helper(inputTensorEpWrapper.GetAddressOf())
|
||||
// );
|
||||
// }
|
||||
// else // CPU tensor
|
||||
// {
|
||||
// inputTensor = Ort::Value::CreateTensor<float>(memoryInformation, inputTensorValues.data(), inputTensorValues.size(), inputShape.data(), 4);
|
||||
// }
|
||||
//
|
||||
// // Create output tensor on device memory.
|
||||
// Ort::Value outputTensor(nullptr);
|
||||
// std::vector<float> outputTensorValues(static_cast<size_t>(GetElementCount(outputShape)), 0.0f);
|
||||
// Microsoft::WRL::ComPtr<IUnknown> outputTensorEpWrapper;
|
||||
//
|
||||
// if (passTensorsAsD3DResources)
|
||||
// {
|
||||
// outputTensor = CreateTensorValueUsingD3DResource(
|
||||
// d3d12Device.Get(),
|
||||
// *ortDmlApi,
|
||||
// memoryInformation,
|
||||
// outputShape,
|
||||
// ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT,
|
||||
// sizeof(float),
|
||||
// /*out*/ IID_PPV_ARGS_Helper(outputTensorEpWrapper.GetAddressOf())
|
||||
// );
|
||||
// }
|
||||
// else // CPU tensor
|
||||
// {
|
||||
// outputTensor = Ort::Value::CreateTensor<float>(memoryInformation, outputTensorValues.data(), outputTensorValues.size(), outputShape.data(), 4);
|
||||
// }
|
||||
//
|
||||
// QueryPerformanceCounter(&tensorCreationTime);
|
||||
//
|
||||
// ////////////////////////////////////////
|
||||
// // Bind the tensor inputs to the model, and run it.
|
||||
// ioBinding.BindInput(modelInputTensorName, inputTensor);
|
||||
// ioBinding.BindOutput(modelOutputTensorName, outputTensor);
|
||||
// ioBinding.SynchronizeInputs();
|
||||
// QueryPerformanceCounter(&bindingTime);
|
||||
//
|
||||
// Ort::RunOptions runOptions;
|
||||
//
|
||||
// // TODO: Upload inputTensorValues to GPU inputTensor.
|
||||
//
|
||||
// printf("Beginning execution.\n");
|
||||
// printf("Running Session.\n");
|
||||
// session.Run(runOptions, ioBinding);
|
||||
// QueryPerformanceCounter(&runTime);
|
||||
// printf("Synchronizing outputs.\n");
|
||||
// ioBinding.SynchronizeOutputs();
|
||||
// QueryPerformanceCounter(&synchronizeOutputsTime);
|
||||
// printf("Finished execution.\n");
|
||||
//
|
||||
// auto printDuration = [=](char const* message, LARGE_INTEGER qpcTime) mutable
|
||||
// {
|
||||
// double durationMs = static_cast<double>(qpcTime.QuadPart - startTime.QuadPart);
|
||||
// durationMs /= static_cast<double>(cpuFrequency.QuadPart);
|
||||
// durationMs *= 1000.0;
|
||||
// printf("%s % 12.6f\n", message, durationMs);
|
||||
//
|
||||
// startTime = qpcTime;
|
||||
// };
|
||||
// printDuration("d3dDeviceCreationTime ...", d3dDeviceCreationTime);
|
||||
// printDuration("sessionCreationTime .....", sessionCreationTime);
|
||||
// printDuration("tensorCreationTime ......", tensorCreationTime);
|
||||
// printDuration("bindingTime .............", bindingTime);
|
||||
// printDuration("runTime .................", runTime);
|
||||
// printDuration("synchronizeOutputsTime ..", synchronizeOutputsTime);
|
||||
//
|
||||
// // TODO: Download inputTensorValues from GPU outputTensor.
|
||||
//
|
||||
// ////////////////////////////////////////
|
||||
// // Print the top results if the output tensors were on the CPU.
|
||||
// if (!passTensorsAsD3DResources)
|
||||
// {
|
||||
//#if 1 // Print first 10 values.
|
||||
// int min = 0;
|
||||
// if (outputTensorValues.size() < size_t(10))
|
||||
// min = outputTensorValues.size();
|
||||
// else
|
||||
// min = size_t(10);
|
||||
// for (int i = 0; i <= min; ++i)
|
||||
// {
|
||||
// printf("output[%d] = %f\n", i, outputTensorValues[i]);
|
||||
// }
|
||||
//#else // Print top 10.
|
||||
// std::vector<uint32_t> indices(outputTensorValues.size(), 0);
|
||||
// std::iota(indices.begin(), indices.end(), 0);
|
||||
// sort(
|
||||
// indices.begin(),
|
||||
// indices.end(),
|
||||
// [&](uint32_t a, uint32_t b)
|
||||
// {
|
||||
// return (outputTensorValues[a] > outputTensorValues[b]);
|
||||
// }
|
||||
// );
|
||||
// for (int i = 0; i <= std::min(indices.size(), size_t(10)); ++i)
|
||||
// {
|
||||
// printf("output[%d] = %f\n", indices[i], outputTensorValues[indices[i]]);
|
||||
// }
|
||||
//#endif
|
||||
// }
|
||||
// }
|
||||
// catch (Ort::Exception const& exception)
|
||||
// {
|
||||
// printf("Error running model inference: %s\n", exception.what());
|
||||
// return EXIT_FAILURE;
|
||||
// }
|
||||
// catch (std::exception const& exception)
|
||||
// {
|
||||
// printf("Error running model inference: %s\n", exception.what());
|
||||
// return EXIT_FAILURE;
|
||||
// }
|
||||
//
|
||||
// return 0;
|
||||
//}
|
||||
//
|
||||
//Microsoft::WRL::ComPtr<ID3D12Resource> CreateD3D12ResourceForTensor(
|
||||
// ID3D12Device* d3dDevice,
|
||||
// size_t elementByteSize,
|
||||
// std::span<const int64_t> tensorDimensions
|
||||
//)
|
||||
//{
|
||||
// // Try to allocate the backing memory for the caller
|
||||
// auto bufferSize = GetElementCount(tensorDimensions);
|
||||
// size_t bufferByteSize = static_cast<size_t>(bufferSize * elementByteSize);
|
||||
//
|
||||
// // DML needs the resources' sizes to be a multiple of 4 bytes
|
||||
// (bufferByteSize += 3) &= ~3;
|
||||
//
|
||||
// D3D12_HEAP_PROPERTIES heapProperties = {
|
||||
// D3D12_HEAP_TYPE_DEFAULT,
|
||||
// D3D12_CPU_PAGE_PROPERTY_UNKNOWN,
|
||||
// D3D12_MEMORY_POOL_UNKNOWN,
|
||||
// 0,
|
||||
// 0
|
||||
// };
|
||||
// D3D12_RESOURCE_DESC resourceDesc = {
|
||||
// D3D12_RESOURCE_DIMENSION_BUFFER,
|
||||
// 0,
|
||||
// static_cast<uint64_t>(bufferByteSize),
|
||||
// 1,
|
||||
// 1,
|
||||
// 1,
|
||||
// DXGI_FORMAT_UNKNOWN,
|
||||
// {1, 0},
|
||||
// D3D12_TEXTURE_LAYOUT_ROW_MAJOR,
|
||||
// D3D12_RESOURCE_FLAG_ALLOW_UNORDERED_ACCESS
|
||||
// };
|
||||
//
|
||||
// Microsoft::WRL::ComPtr<ID3D12Resource> gpuResource;
|
||||
// THROW_IF_FAILED(d3dDevice->CreateCommittedResource(
|
||||
// &heapProperties,
|
||||
// D3D12_HEAP_FLAG_NONE,
|
||||
// &resourceDesc,
|
||||
// D3D12_RESOURCE_STATE_COMMON,
|
||||
// nullptr,
|
||||
// __uuidof(ID3D12Resource),
|
||||
// /*out*/ &gpuResource
|
||||
// ));
|
||||
//
|
||||
// return gpuResource;
|
||||
//}
|
||||
//
|
||||
//Ort::Value CreateTensorValueFromExistingD3DResource(
|
||||
// OrtDmlApi const& ortDmlApi,
|
||||
// Ort::MemoryInfo const& memoryInformation,
|
||||
// ID3D12Resource* d3dResource,
|
||||
// std::span<const int64_t> tensorDimensions,
|
||||
// ONNXTensorElementDataType elementDataType,
|
||||
// /*out*/ void** dmlEpResourceWrapper // Must stay alive with Ort::Value.
|
||||
//)
|
||||
//{
|
||||
// *dmlEpResourceWrapper = nullptr;
|
||||
//
|
||||
// void* dmlAllocatorResource;
|
||||
// THROW_IF_NOT_OK(ortDmlApi.CreateGPUAllocationFromD3DResource(d3dResource, &dmlAllocatorResource));
|
||||
// auto deleter = [&](void*) {ortDmlApi.FreeGPUAllocation(dmlAllocatorResource); };
|
||||
// deleting_unique_ptr<void> dmlAllocatorResourceCleanup(dmlAllocatorResource, deleter);
|
||||
//
|
||||
// size_t tensorByteSize = static_cast<size_t>(d3dResource->GetDesc().Width);
|
||||
// Ort::Value newValue(
|
||||
// Ort::Value::CreateTensor(
|
||||
// memoryInformation,
|
||||
// dmlAllocatorResource,
|
||||
// tensorByteSize,
|
||||
// tensorDimensions.data(),
|
||||
// tensorDimensions.size(),
|
||||
// elementDataType
|
||||
// )
|
||||
// );
|
||||
//
|
||||
// // Return values and the wrapped resource.
|
||||
// // TODO: Is there some way to get Ort::Value to just own the D3DResource
|
||||
// // directly so that it gets freed after execution or session destruction?
|
||||
// *dmlEpResourceWrapper = dmlAllocatorResource;
|
||||
// dmlAllocatorResourceCleanup.release();
|
||||
//
|
||||
// return newValue;
|
||||
//}
|
||||
//
|
||||
//Ort::Value CreateTensorValueUsingD3DResource(
|
||||
// ID3D12Device* d3d12Device,
|
||||
// OrtDmlApi const& ortDmlApi,
|
||||
// Ort::MemoryInfo const& memoryInformation,
|
||||
// std::span<const int64_t> tensorDimensions,
|
||||
// ONNXTensorElementDataType elementDataType,
|
||||
// size_t elementByteSize,
|
||||
// /*out*/ void** dmlEpResourceWrapper // Must stay alive with Ort::Value.
|
||||
//)
|
||||
//{
|
||||
// // Create empty resource (values don't matter because we won't read them back anyway).
|
||||
// Microsoft::WRL::ComPtr<ID3D12Resource> d3dResource = CreateD3D12ResourceForTensor(
|
||||
// d3d12Device,
|
||||
// sizeof(float),
|
||||
// tensorDimensions
|
||||
// );
|
||||
//
|
||||
// return CreateTensorValueFromExistingD3DResource(
|
||||
// ortDmlApi,
|
||||
// memoryInformation,
|
||||
// d3dResource.Get(),
|
||||
// tensorDimensions,
|
||||
// ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT,
|
||||
// /*out*/ dmlEpResourceWrapper
|
||||
// );
|
||||
//}
|
||||
Загрузка…
Ссылка в новой задаче