mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-25 22:26:24 +00:00
130 lines
3.4 KiB
C++
130 lines
3.4 KiB
C++
// Copyright (c) Microsoft Corporation.
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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 "WinML_Lock.h"
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#include "WinMLAdapter.h"
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namespace winrt::Windows::AI::MachineLearning::implementation {
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struct LearningModelSession : LearningModelSessionT<LearningModelSession> {
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/* LearningModelSession constructors (MachineLearningContract 1). */
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LearningModelSession() = delete;
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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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public:
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/* Non-ABI methods */
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onnxruntime::IExecutionProvider*
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GetExecutionProvider();
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std::unique_ptr<onnxruntime::IOBinding>
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CreateSessionBinding();
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private:
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void
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Initialize();
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std::unique_ptr<_winmla::ModelProto>
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GetOptimizedModel();
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std::unique_ptr<_winmla::ModelProto>
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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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void
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CheckClosed();
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private:
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std::unique_ptr<onnxruntime::InferenceSession> inference_session_;
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// reference to the active execution provider. weak
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onnxruntime::IExecutionProvider* p_cached_execution_provider = nullptr;
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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 evaluate_lock_;
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// is_first_evaluate_ is used as a heuristic to determine
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// when the dml upload heap can be trimmed.
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bool is_first_evaluate_ = true;
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};
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} // namespace winrt::Windows::AI::MachineLearning::implementation
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namespace winrt::Windows::AI::MachineLearning::factory_implementation {
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struct LearningModelSession : LearningModelSessionT<LearningModelSession, implementation::LearningModelSession> {
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};
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} // namespace winrt::Windows::AI::MachineLearning::factory_implementation
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