mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-25 22:26:24 +00:00
5350abe19d
this is a big PR. we are going to move it up to layer_dev , which is still a L3 so we are still safe to do work there agile. we are going to move this into the L3 so that ryan can start doing intergration testing. we will pause for a full code review and integration test result prior to going into the L2. >>>> raw comments from previous commits >>> * LearningModelSession is cleaned up to use the adapter, and parts of binding are. * moved everything in the winmladapter made it all nano-com using, WRL to construct objects in the ORT side. base interfaces for everythign for winml to call cleaned up a bunch of winml to use the base interfaces. * more pieces * GetData across the abi. * renamed some namepsace cleaned up OrtValue cleaned up Tensor cleaned up custom ops. everything *but* learnignmodel should be clean * make sure it's building. winml.dll is still a monolith.
151 lines
No EOL
4.9 KiB
C++
151 lines
No EOL
4.9 KiB
C++
// Copyright (c) Microsoft Corporation.
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// Licensed under the MIT License.
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#include "pch.h"
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// Needed to work around the fact that OnnxRuntime defines ERROR
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#ifdef ERROR
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#undef ERROR
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#endif
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#include "core/session/inference_session.h"
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// Restore ERROR define
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#define ERROR 0
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#include "DmlOrtSessionBuilder.h"
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// winml includes
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#include "core/providers/dml/GraphTransformers/GraphTransformerHelpers.h"
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#include "inc/CustomRegistryHelper.h"
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#include "core/providers/dml/DmlExecutionProvider/inc/DmlExecutionProvider.h"
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#include "LearningModelDevice.h"
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#include "core/providers/dml/DmlExecutionProvider/src/MLOperatorAuthorImpl.h"
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// ort includes
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#include "core/framework/op_kernel.h"
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#include "core/framework/op_node_proto_helper.h"
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#include "core/framework/customRegistry.h"
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#include "core/framework/data_transfer.h"
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using namespace Windows::AI::MachineLearning;
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namespace Windows::AI::MachineLearning::Adapter {
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DmlOrtSessionBuilder::DmlOrtSessionBuilder(
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ID3D12Device* device,
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ID3D12CommandQueue* queue){
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device_.copy_from(device);
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queue_.copy_from(queue);
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}
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HRESULT
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DmlOrtSessionBuilder::CreateSessionOptions(
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onnxruntime::SessionOptions* p_options) {
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RETURN_HR_IF_NULL(E_POINTER, p_options);
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*p_options = onnxruntime::SessionOptions();
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p_options->graph_optimization_level = onnxruntime::TransformerLevel::Level3;
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// Disable the mem pattern session option for DML. It will cause problems with how memory is allocated.
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p_options->enable_mem_pattern = false;
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return S_OK;
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}
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static HRESULT
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RegisterCustomRegistry(
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onnxruntime::InferenceSession* p_session,
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IMLOperatorRegistry* registry) {
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if (registry != nullptr) {
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RETURN_HR_IF_NULL(E_POINTER, p_session);
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auto custom_registries = GetLotusCustomRegistries(registry);
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// Register
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for (auto& custom_registry : custom_registries) {
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ORT_THROW_IF_ERROR(p_session->RegisterCustomRegistry(custom_registry));
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}
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}
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return S_OK;
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}
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Microsoft::WRL::ComPtr<IDMLDevice> CreateDmlDevice(ID3D12Device* d3d12Device) {
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// Dynamically load DML to avoid WinML taking a static dependency on DirectML.dll
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wil::unique_hmodule dmlDll(LoadLibraryW(L"DirectML.dll"));
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THROW_LAST_ERROR_IF(!dmlDll);
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auto dmlCreateDevice1Fn = reinterpret_cast<decltype(&DMLCreateDevice1)>(
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GetProcAddress(dmlDll.get(), "DMLCreateDevice1"));
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THROW_LAST_ERROR_IF(!dmlCreateDevice1Fn);
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DML_CREATE_DEVICE_FLAGS dmlFlags = DML_CREATE_DEVICE_FLAG_NONE;
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// Enable the DML debug layer in DEBUG builds, if the D3D12 debug layer is also enabled
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#if _DEBUG
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Microsoft::WRL::ComPtr<ID3D12DebugDevice> d3d12DebugDevice;
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if (SUCCEEDED(d3d12Device->QueryInterface(IID_PPV_ARGS(&d3d12DebugDevice)))) {
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d3d12DebugDevice = nullptr;
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dmlFlags |= DML_CREATE_DEVICE_FLAG_DEBUG;
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}
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#endif
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Microsoft::WRL::ComPtr<IDMLDevice> dmlDevice;
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THROW_IF_FAILED(dmlCreateDevice1Fn(d3d12Device, dmlFlags, DML_FEATURE_LEVEL_2_0, IID_PPV_ARGS(&dmlDevice)));
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// Keep DirectML.dll loaded by leaking the handle. This is equivalent behavior to if we delay-loaded the DLL.
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dmlDll.release();
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return dmlDevice;
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}
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HRESULT DmlOrtSessionBuilder::CreateSession(
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const onnxruntime::SessionOptions& options,
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_winmla::IInferenceSession** p_session,
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onnxruntime::IExecutionProvider** pp_provider) {
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RETURN_HR_IF_NULL(E_POINTER, p_session);
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RETURN_HR_IF_NULL(E_POINTER, pp_provider);
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RETURN_HR_IF(E_POINTER, *pp_provider != nullptr);
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auto p_d3d_device = device_.get();
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auto p_queue = queue_.get();
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Microsoft::WRL::ComPtr<IDMLDevice> dmlDevice = CreateDmlDevice(p_d3d_device);
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std::unique_ptr<onnxruntime::IExecutionProvider> gpu_provider = Dml::CreateExecutionProvider(dmlDevice.Get(), p_queue);
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auto session = std::make_unique<onnxruntime::InferenceSession>(options);
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// Cache the provider's raw pointer
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*pp_provider = gpu_provider.get();
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ORT_THROW_IF_ERROR(session->RegisterExecutionProvider(std::move(gpu_provider)));
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// assign the session to the out parameter
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auto sessionptr = wil::MakeOrThrow<_winmla::InferenceSession>(session.release());
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RETURN_IF_FAILED(sessionptr.CopyTo(_uuidof(_winmla::IInferenceSession), (void**)p_session));
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return S_OK;
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}
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HRESULT DmlOrtSessionBuilder::Initialize(
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_winmla::IInferenceSession* p_session,
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onnxruntime::IExecutionProvider* p_provider) {
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RETURN_HR_IF_NULL(E_INVALIDARG, p_session);
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RETURN_HR_IF_NULL(E_INVALIDARG, p_provider);
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// OnnxRuntime uses the default rounding mode when calling the session's allocator.
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// During initialization, OnnxRuntime allocates weights, which are permanent across session
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// lifetime and can be large, so shouldn't be rounded.
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Dml::SetDefaultRoundingMode(p_provider, AllocatorRoundingMode::Disabled);
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ORT_THROW_IF_ERROR(p_session->get()->Initialize());
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Dml::SetDefaultRoundingMode(p_provider, AllocatorRoundingMode::Enabled);
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// Flush the D3D12 work from the DML execution provider
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Dml::FlushContext(p_provider);
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return S_OK;
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}
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} // Windows::AI::MachineLearning::Adapter
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