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79436a2d5b
Updated several DML EP files to avoid warning C5038: data member 'member1' will be initialized after data member 'member2' / base class 'base_class' More information: https://docs.microsoft.com/en-us/cpp/error-messages/compiler-warnings/c5038?view=msvc-160
69 lines
No EOL
3.5 KiB
C++
69 lines
No EOL
3.5 KiB
C++
#include "lib/Api.Experimental/pch/pch.h"
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#include "LearningModelInputs.h"
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#include "LearningModelOperator.h"
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#include "LearningModelSession.h"
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#include "LearningModelBuilder.h"
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#include "TensorFeatureDescriptor.h"
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#include "..\Api\inc\ILotusValueProviderPrivate.h"
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namespace WINML_EXPERIMENTALP {
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LearningModelInputs::LearningModelInputs(winml_experimental::LearningModelBuilder builder) : input_descriptors_(winrt::single_threaded_vector<winml::ILearningModelFeatureDescriptor>()),
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input_default_values_(winrt::single_threaded_vector<wf::IInspectable>()),
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constant_descriptors_(winrt::single_threaded_vector<winml::ILearningModelFeatureDescriptor>()),
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constant_values_(winrt::single_threaded_vector<wf::IInspectable>()),
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builder_(builder) {
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}
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winml_experimental::LearningModelBuilder LearningModelInputs::AddInput(winml::ILearningModelFeatureDescriptor const& input, Windows::Foundation::IInspectable const& default_value, bool is_constant) {
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// Perform model update inside the builder
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auto model = builder_.as<winml_experimentalp::LearningModelBuilder>()->UseModel();
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auto descriptor_provider = input.as<_winml::IDescriptorInfoProvider>();
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auto input_name = _winml::Strings::UTF8FromHString(input.Name());
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winrt::com_ptr<_winml::IValue> default_value_ivalue;
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if (default_value) {
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auto default_value_value_provider = default_value.as<_winml::ILotusValueProviderPrivate>();
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// Create the Binding Context to pass to the feature value
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_winml::BindingContext context{
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_winml::BindingType::kInput,
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builder_.as<winml_experimentalp::LearningModelBuilder>()->InertSession(),
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nullptr,
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nullptr,
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{} // SubresourceId is set by callee
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};
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default_value_value_provider->GetValue(context, default_value_ivalue.put());
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}
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model->AddModelInput(input_name.c_str(), descriptor_provider.get(), is_constant, default_value_ivalue.get());
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return builder_;
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}
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winml_experimental::LearningModelBuilder LearningModelInputs::Add(winml::ILearningModelFeatureDescriptor const& input) {
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return AddInput(input, nullptr, false);
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}
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winml_experimental::LearningModelBuilder LearningModelInputs::Add(hstring const& input_name, hstring const& input_description, Windows::Foundation::IInspectable const& default_value) {
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if (auto tensor = default_value.try_as<winml::ITensor>()) {
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auto shape = tensor.Shape();
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std::vector<int64_t> shape_vector(begin(shape), end(shape));
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auto descriptor = winrt::make<winmlp::TensorFeatureDescriptor>(input_name, input_description, tensor.TensorKind(), shape_vector);
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return AddInput(descriptor, default_value, false);
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}
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WINML_THROW_HR(E_UNEXPECTED);
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}
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winml_experimental::LearningModelBuilder LearningModelInputs::AddConstant(hstring const& input_name, Windows::Foundation::IInspectable const& value) {
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if (auto tensor = value.try_as<winml::ITensor>()) {
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winrt::hstring no_description_for_constants = L"";
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auto shape = tensor.Shape();
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std::vector<int64_t> shape_vector(begin(shape), end(shape));
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auto descriptor = winrt::make<winmlp::TensorFeatureDescriptor>(input_name, no_description_for_constants, tensor.TensorKind(), shape_vector);
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return AddInput(descriptor, value, true);
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}
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WINML_THROW_HR(E_UNEXPECTED);
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}
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} // namespace WINML_EXPERIMENTALP
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