mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-30 23:18:20 +00:00
129 lines
4.2 KiB
C
129 lines
4.2 KiB
C
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// 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 "TensorKindFrom.h"
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#include "MapFeatureDescriptor.h"
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#include "TensorFeatureDescriptor.h"
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namespace Windows::AI::MachineLearning {
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//
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// MapBase
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//
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// This is the base class for all data based Map types.
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//
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// Supported derived classes:
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// <String, Float>, <String, Int64>, <String, Double>, <String, String>
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// <Int64, Float>, <Int64, Int64>, <Int64, Double>, <Int64, String>
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//
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template <
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typename TDerived,
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typename TKey,
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typename TValue>
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struct MapBase : winrt::implements<
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MapBase<TDerived, TKey, TValue>,
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winrt::Windows::AI::MachineLearning::ILearningModelFeatureValue,
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WinML::IMapFeatureValue,
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WinML::ILotusValueProviderPrivate> {
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static_assert(
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std::is_same<TKey, int64_t>::value ||
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std::is_same<TKey, winrt::hstring>::value,
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"Map keys must be int64_t or winrt::hstring!");
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static_assert(
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std::is_same<TValue, int64_t>::value ||
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std::is_same<TValue, double>::value ||
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std::is_same<TValue, float>::value ||
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std::is_same<TValue, winrt::hstring>::value,
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"Map values must be int64_t, double, float, or winrt::hstring!");
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using ABIMap = ::winrt::Windows::Foundation::Collections::IMap<TKey, TValue>;
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using ABIMapView = ::winrt::Windows::Foundation::Collections::IMapView<TKey, TValue>;
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MapBase(ABIMap const& data) : data_(data) {}
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static winrt::Windows::AI::MachineLearning::ILearningModelFeatureValue Create() {
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auto abiMap = winrt::single_threaded_map<TKey, TValue>();
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return winrt::make<TDerived>(abiMap);
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}
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static winrt::Windows::AI::MachineLearning::ILearningModelFeatureValue Create(const ABIMap& data) {
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return winrt::make<TDerived>(data);
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}
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static winrt::Windows::AI::MachineLearning::ILearningModelFeatureValue Create(const ABIMapView& data) {
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auto abiMap = winrt::single_threaded_map<TKey, TValue>();
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for (const auto& pair : data) {
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auto key = pair.Key();
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auto value = pair.Value();
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abiMap.Insert(key, value);
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}
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return winrt::make<TDerived>(abiMap);
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}
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// ILearningModelFeatureValue implementation
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winrt::Windows::AI::MachineLearning::LearningModelFeatureKind Kind() {
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return winrt::Windows::AI::MachineLearning::LearningModelFeatureKind::Map;
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}
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STDMETHOD(get_KeyKind)
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(winrt::Windows::AI::MachineLearning::TensorKind* kind) {
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FAIL_FAST_IF_NULL(kind);
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*kind = TensorKindFrom<TKey>::Type;
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return S_OK;
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}
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STDMETHOD(get_ValueDescriptor)
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(winrt::Windows::AI::MachineLearning::ILearningModelFeatureDescriptor* result) {
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FAIL_FAST_IF_NULL(result);
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*result = TensorFeatureDescriptorFrom<TValue>::CreateAnonymous(std::vector<int64_t>{});
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return S_OK;
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}
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STDMETHOD(GetValue)
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(WinML::BindingContext& context, IValue** out) {
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auto session = context.session.as<winrt::Windows::AI::MachineLearning::implementation::LearningModelSession>();
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auto engine = session->GetEngine();
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if (context.type == WinML::BindingType::kInput) {
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RETURN_IF_FAILED(engine->CreateMapValue(reinterpret_cast<::IInspectable*>(winrt::get_abi(data_)), TensorKindFrom<TKey>::Type, TensorKindFrom<TValue>::Type, out));
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} else {
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RETURN_IF_FAILED(engine->CreateNullValue(out));
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}
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return S_OK;
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}
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STDMETHOD(IsPlaceholder)
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(bool* pIsPlaceHolder) {
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FAIL_FAST_IF_NULL(pIsPlaceHolder);
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*pIsPlaceHolder = false;
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return S_OK;
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}
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STDMETHOD(UpdateSourceResourceData)
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(BindingContext& context, IValue* value) {
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data_.Clear();
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auto session = context.session.as<winrt::Windows::AI::MachineLearning::implementation::LearningModelSession>();
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auto engine = session->GetEngine();
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RETURN_IF_FAILED(engine->FillFromMapValue(reinterpret_cast<::IInspectable*>(winrt::get_abi(data_)), TensorKindFrom<TKey>::Type, TensorKindFrom<TValue>::Type, value));
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return S_OK;
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}
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STDMETHOD(AbiRepresentation)
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(
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winrt::Windows::Foundation::IInspectable& abiRepresentation) {
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data_.as(abiRepresentation);
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return S_OK;
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}
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private:
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ABIMap data_;
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};
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} // namespace Windows::AI::MachineLearning
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