mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-17 21:10:43 +00:00
87cb6fd495
* model building * fix build * winml adapter model building api * model building * make build * make build again * add model building with audio op * inplace and inorder fft * add ifft * works! * cleanup * add comments * switch to iterative rather than recursive and use parallelization * batched parallelization * fft->dft * cleanup * window functions * add melweightmatrix op * updates to make spectrogram test work * push latest * add onesided * cleanup * Clean up building apis and fix mel * cleanup * cleanup * naive stft * fix test output * middle c complete * 3 tones * cleanup * signal def new line * Add save functionality * Perf improvements, 10x improvement * cleanup * use bitreverse lookup table for performance * implement constant initializers for tensors * small changes * add matmul tests * merge issues * support add attribute * add tests for double data type windowfunctions and minor cleanup * stft onesided/and not tests * cleanup * cleanup * clean up * cleanup * remove threading attribute * forward declare orttypeinfo * warnings * fwd declare * fix warnings * 1 more warning * remove saving to e drive... * cleanup and fix stft test * add opset picker * small additions * add onnxruntime tests * add signed/unsigned * fix warning * fix warning * finish onnxruntime tests * make windows namespace build succeed * add experimental flag * add experimental api into nuget package * add experimental api build flag and add to windows ai nuget package * turn experimental for tests * add minimum opset version to new experimental domain * api cleanup * disable ms experimental ops test when --ms_experimental is not enabled * add macro behind flag * remove unused x * pr feedback Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
139 lines
3.4 KiB
C++
139 lines
3.4 KiB
C++
// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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#pragma once
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#include "LearningModelSession.g.h"
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#include "LearningModelBinding.h"
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#include "MLOperatorAuthor.h"
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#include "WinML_Lock.h"
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#include "core/providers/winml/winml_provider_factory.h"
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#include "iengine.h"
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namespace WINMLP {
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struct LearningModelSession : LearningModelSessionT<LearningModelSession, ILearningModelSessionNative> {
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/* LearningModelSession constructors (MachineLearningContract 1). */
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LearningModelSession(_winml::IEngine* engine);
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LearningModelSession(
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winml::LearningModel const& model);
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LearningModelSession(
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winml::LearningModel const& model,
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winml::LearningModelDevice const& deviceToRunOn);
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/* LearningModelSession constructors (MachineLearningContract 2). */
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LearningModelSession(
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winml::LearningModel const& model,
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winml::LearningModelDevice const& deviceToRunOn,
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winml::LearningModelSessionOptions const& sessionOptions);
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/* IClosable methods. */
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void
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Close();
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/* LearningModelSession properties (MachineLearningContract 1). */
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wfc::IPropertySet
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EvaluationProperties();
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winml::LearningModel
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Model();
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winml::LearningModelDevice
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Device();
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/* LearningModelSession methods (MachineLearningContract 1). */
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winml::LearningModelEvaluationResult
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Evaluate(
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winml::LearningModelBinding binding,
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hstring const& correlationId);
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wf::IAsyncOperation<winml::LearningModelEvaluationResult>
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EvaluateAsync(
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winml::LearningModelBinding binding,
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hstring const correlationId);
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winml::LearningModelEvaluationResult
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EvaluateFeatures(
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wfc::IMap<hstring, wf::IInspectable> const features,
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hstring const correlationId);
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wf::IAsyncOperation<winml::LearningModelEvaluationResult>
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EvaluateFeaturesAsync(
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wfc::IMap<hstring, wf::IInspectable> const features,
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hstring const correlationId);
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STDMETHOD(GetIntraOpNumThreads)
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(uint32_t* numThreads);
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public:
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/* Non-ABI methods */
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_winml::IEngine*
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GetEngine();
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void
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CheckClosed();
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// LearningModelBinding needs to leverage the lock
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CWinMLLock *
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GetDMLEPLock()
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{
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return &dml_ep_lock_;
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}
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static winml::LearningModelSession CreateInertSession(_winml::IEngine* engine);
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private:
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void
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Initialize();
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_winml::IModel*
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GetOptimizedModel();
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_winml::IModel*
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GetOptimizedModel(bool should_close_model);
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uint64_t
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Run(
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winrt::com_ptr<winmlp::LearningModelBinding> bindingImpl);
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winml::LearningModelEvaluationResult
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GetResults(
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winrt::com_ptr<winmlp::LearningModelBinding> bindingImpl,
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hstring const& correlationId,
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uint64_t fenceValueForDML);
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void
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ApplyEvaluationProperties();
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void
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ToggleProfiler();
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private:
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com_ptr<_winml::IEngineFactory> engine_factory_;
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com_ptr<_winml::IEngine> engine_;
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using MLOperatorRegistry = std::unique_ptr<IMLOperatorRegistry, void (*)(IMLOperatorRegistry*)>;
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MLOperatorRegistry operator_registry_;
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winml::LearningModel model_;
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winml::LearningModelDevice device_;
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winml::LearningModelSessionOptions session_options_;
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wfc::IPropertySet evaluation_properties_;
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// Synchronization
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CWinMLLock session_creation_lock_;
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CWinMLLock dml_ep_lock_;
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};
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} // namespace WINMLP
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namespace WINML::factory_implementation {
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struct LearningModelSession : LearningModelSessionT<LearningModelSession, implementation::LearningModelSession> {
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};
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} // namespace WINML::factory_implementation
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