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Layer dev paulm (#2507)

Browse source 
* commetns for dml graph transformer
fixed ort value passing using the allocatir info

* fixed and coded maps and sequences across the abi

* cleaned up w4's
cleaned up the model info ABI
delayload directml.dll from winml

* cleaned up namepsace aliases.
renamed _winmla to winmla
this was good PR feedback from tiago a while back.
This commit is contained in:
Paul McDaniel 2019-11-27 15:50:49 -08:00 committed by GitHub
parent 197fd9ea3d
commit 301d407b39
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
21 changed files with 71 additions and 106 deletions
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2
winml/dll/module.cpp
View file

@ -67,7 +67,7 @@ extern "C" BOOL WINAPI DllMain(_In_ HINSTANCE hInstance, DWORD dwReason, _In_ vo
extern "C" HRESULT WINAPI MLCreateOperatorRegistry(_COM_Outptr_ IMLOperatorRegistry** registry) try {
*registry = nullptr;
winrt::com_ptr<_winmla::IWinMLAdapter> adapter;
winrt::com_ptr<winmla::IWinMLAdapter> adapter;
WINML_THROW_IF_FAILED(OrtGetWinMLAdapter(adapter.put()));
return adapter->GetCustomRegistry(registry);
}

8
winml/lib/Api.Core/CpuOrtSessionBuilder.cpp
View file

@ -56,7 +56,7 @@ CpuOrtSessionBuilder::CreateSessionOptions(
HRESULT
CpuOrtSessionBuilder::CreateSession(
OrtSessionOptions* options,
_winmla::IInferenceSession** p_session,
winmla::IInferenceSession** p_session,
onnxruntime::IExecutionProvider** pp_provider) {
RETURN_HR_IF_NULL(E_POINTER, p_session);
RETURN_HR_IF_NULL(E_POINTER, pp_provider);
@ -79,15 +79,15 @@ CpuOrtSessionBuilder::CreateSession(
ORT_THROW_IF_ERROR(session->RegisterExecutionProvider(std::move(cpu_provider)));
// assign the session to the out parameter
auto sessionptr = wil::MakeOrThrow<_winmla::InferenceSession>(session.release());
RETURN_IF_FAILED(sessionptr.CopyTo(_uuidof(_winmla::IInferenceSession), (void**)p_session));
auto sessionptr = wil::MakeOrThrow<winmla::InferenceSession>(session.release());
RETURN_IF_FAILED(sessionptr.CopyTo(_uuidof(winmla::IInferenceSession), (void**)p_session));
return S_OK;
}
HRESULT
CpuOrtSessionBuilder::Initialize(
_winmla::IInferenceSession* p_session,
winmla::IInferenceSession* p_session,
onnxruntime::IExecutionProvider* /*p_provider*/
) {
ORT_THROW_IF_ERROR(p_session->get()->Initialize());

6
winml/lib/Api.Core/CpuOrtSessionBuilder.h
View file

@ -9,7 +9,7 @@ namespace Windows::AI::MachineLearning::Adapter {
class CpuOrtSessionBuilder : public Microsoft::WRL::RuntimeClass <
Microsoft::WRL::RuntimeClassFlags<Microsoft::WRL::ClassicCom>,
_winmla::IOrtSessionBuilder> {
winmla::IOrtSessionBuilder> {
public:
CpuOrtSessionBuilder();
@ -19,11 +19,11 @@ class CpuOrtSessionBuilder : public Microsoft::WRL::RuntimeClass <
HRESULT STDMETHODCALLTYPE CreateSession(
OrtSessionOptions* options,
_winmla::IInferenceSession** p_session,
winmla::IInferenceSession** p_session,
onnxruntime::IExecutionProvider** pp_provider) override;
HRESULT STDMETHODCALLTYPE Initialize(
_winmla::IInferenceSession* p_session,
winmla::IInferenceSession* p_session,
onnxruntime::IExecutionProvider* p_provider) override;
};

8
winml/lib/Api.Core/DmlOrtSessionBuilder.cpp
View file

@ -106,7 +106,7 @@ Microsoft::WRL::ComPtr<IDMLDevice> CreateDmlDevice(ID3D12Device* d3d12Device) {
HRESULT DmlOrtSessionBuilder::CreateSession(
OrtSessionOptions* options,
_winmla::IInferenceSession** p_session,
winmla::IInferenceSession** p_session,
onnxruntime::IExecutionProvider** pp_provider) {
RETURN_HR_IF_NULL(E_POINTER, p_session);
RETURN_HR_IF_NULL(E_POINTER, pp_provider);
@ -126,14 +126,14 @@ HRESULT DmlOrtSessionBuilder::CreateSession(
ORT_THROW_IF_ERROR(session->RegisterExecutionProvider(std::move(gpu_provider)));
// assign the session to the out parameter
auto sessionptr = wil::MakeOrThrow<_winmla::InferenceSession>(session.release());
RETURN_IF_FAILED(sessionptr.CopyTo(_uuidof(_winmla::IInferenceSession), (void**)p_session));
auto sessionptr = wil::MakeOrThrow<winmla::InferenceSession>(session.release());
RETURN_IF_FAILED(sessionptr.CopyTo(_uuidof(winmla::IInferenceSession), (void**)p_session));
return S_OK;
}
HRESULT DmlOrtSessionBuilder::Initialize(
_winmla::IInferenceSession* p_session,
winmla::IInferenceSession* p_session,
onnxruntime::IExecutionProvider* p_provider) {
RETURN_HR_IF_NULL(E_INVALIDARG, p_session);
RETURN_HR_IF_NULL(E_INVALIDARG, p_provider);

6
winml/lib/Api.Core/DmlOrtSessionBuilder.h
View file

@ -9,7 +9,7 @@ namespace Windows::AI::MachineLearning::Adapter {
class DmlOrtSessionBuilder : public Microsoft::WRL::RuntimeClass <
Microsoft::WRL::RuntimeClassFlags<Microsoft::WRL::ClassicCom>,
_winmla::IOrtSessionBuilder> {
winmla::IOrtSessionBuilder> {
public:
DmlOrtSessionBuilder(ID3D12Device* device, ID3D12CommandQueue* queue);
@ -19,11 +19,11 @@ class DmlOrtSessionBuilder : public Microsoft::WRL::RuntimeClass <
HRESULT STDMETHODCALLTYPE CreateSession(
OrtSessionOptions* options,
_winmla::IInferenceSession** p_session,
winmla::IInferenceSession** p_session,
onnxruntime::IExecutionProvider** pp_provider) override;
HRESULT STDMETHODCALLTYPE Initialize(
_winmla::IInferenceSession* p_session,
winmla::IInferenceSession* p_session,
onnxruntime::IExecutionProvider* p_provider) override;
private:

2
winml/lib/Api.Core/FeatureDescriptorFactory.cpp
View file

@ -473,7 +473,7 @@ GetTensorType(
has_unsupported_image_metadata);
if (is_tensor_improperly_annotated_as_image) {
TraceLoggingWrite(_winmla::winml_trace_logging_provider,
TraceLoggingWrite(winmla::winml_trace_logging_provider,
"WinMLInputValidation",
TraceLoggingKeyword(WINML_PROVIDER_KEYWORD_DEFAULT),
TraceLoggingLevel(WINEVENT_LEVEL_WARNING),

14
winml/lib/Api.Core/LotusEnvironment.cpp
View file

@ -15,7 +15,7 @@ void Windows::AI::MachineLearning::CWinMLLogSink::SendImpl(
switch (message.Severity()) {
case (onnxruntime::logging::Severity::kFATAL): //Telemetry
TraceLoggingWrite(
_winmla::winml_trace_logging_provider,
winmla::winml_trace_logging_provider,
"WinMLLogSink",
TelemetryPrivacyDataTag(PDT_ProductAndServicePerformance),
TraceLoggingKeyword(WINML_PROVIDER_KEYWORD_DEFAULT),
@ -29,7 +29,7 @@ void Windows::AI::MachineLearning::CWinMLLogSink::SendImpl(
break;
case (onnxruntime::logging::Severity::kERROR): //Telemetry
TraceLoggingWrite(
_winmla::winml_trace_logging_provider,
winmla::winml_trace_logging_provider,
"WinMLLogSink",
TelemetryPrivacyDataTag(PDT_ProductAndServicePerformance),
TraceLoggingKeyword(WINML_PROVIDER_KEYWORD_DEFAULT),
@ -43,7 +43,7 @@ void Windows::AI::MachineLearning::CWinMLLogSink::SendImpl(
break;
case (onnxruntime::logging::Severity::kWARNING):
TraceLoggingWrite(
_winmla::winml_trace_logging_provider,
winmla::winml_trace_logging_provider,
"WinMLLogSink",
TraceLoggingKeyword(WINML_PROVIDER_KEYWORD_DEFAULT),
TraceLoggingLevel(WINEVENT_LEVEL_WARNING),
@ -55,7 +55,7 @@ void Windows::AI::MachineLearning::CWinMLLogSink::SendImpl(
break;
case (onnxruntime::logging::Severity::kINFO):
TraceLoggingWrite(
_winmla::winml_trace_logging_provider,
winmla::winml_trace_logging_provider,
"WinMLLogSink",
TraceLoggingKeyword(WINML_PROVIDER_KEYWORD_DEFAULT),
TraceLoggingLevel(WINEVENT_LEVEL_INFO),
@ -69,7 +69,7 @@ void Windows::AI::MachineLearning::CWinMLLogSink::SendImpl(
__fallthrough; //Default is Verbose too.
default:
TraceLoggingWrite(
_winmla::winml_trace_logging_provider,
winmla::winml_trace_logging_provider,
"WinMLLogSink",
TraceLoggingKeyword(WINML_PROVIDER_KEYWORD_DEFAULT),
TraceLoggingLevel(WINEVENT_LEVEL_VERBOSE),
@ -87,7 +87,7 @@ void Windows::AI::MachineLearning::CWinMLLogSink::SendImpl(
void Windows::AI::MachineLearning::CWinMLLogSink::SendProfileEvent(onnxruntime::profiling::EventRecord& eventRecord) const {
if (eventRecord.cat == onnxruntime::profiling::EventCategory::NODE_EVENT) {
TraceLoggingWrite(
_winmla::winml_trace_logging_provider,
winmla::winml_trace_logging_provider,
"OnnxRuntimeProfiling",
TraceLoggingKeyword(WINML_PROVIDER_KEYWORD_LOTUS_PROFILING),
TraceLoggingLevel(WINEVENT_LEVEL_VERBOSE),
@ -102,7 +102,7 @@ void Windows::AI::MachineLearning::CWinMLLogSink::SendProfileEvent(onnxruntime::
TraceLoggingString(eventRecord.args["provider"].c_str(), "Execution Provider"));
} else {
TraceLoggingWrite(
_winmla::winml_trace_logging_provider,
winmla::winml_trace_logging_provider,
"OnnxRuntimeProfiling",
TraceLoggingKeyword(WINML_PROVIDER_KEYWORD_LOTUS_PROFILING),
TraceLoggingLevel(WINEVENT_LEVEL_VERBOSE),

23
winml/lib/Api.Core/inc/WinMLAdapter.h
View file

@ -141,27 +141,4 @@ private:
std::shared_ptr<onnxruntime::InferenceSession> session_;
};
// header only code to enable smart pointers on abstract ort objects
template <typename T>
class OrtObject {
public:
OrtObject() {
p_ = nullptr;
}
OrtObject(T* m) {
p_ = m;
}
virtual ~OrtObject() {
if (p_ != nullptr) {
ReleaseOrtObject(p_);
}
}
T* get() { return p_; }
private:
T* p_;
};
} // namespace Windows::AI::MachineLearning::Adapter

6
winml/lib/Api/ImageFeatureValue.cpp
View file

@ -346,7 +346,7 @@ static void GPUTensorize(
com_ptr<LearningModelSession> spSession,
void* pAllocatedResource,
WinML::BindingContext& context) {
com_ptr<_winmla::IWinMLAdapter> adapter;
com_ptr<winmla::IWinMLAdapter> adapter;
WINML_THROW_IF_FAILED(OrtGetWinMLAdapter(adapter.put()));
auto d3dResource =
@ -505,7 +505,7 @@ HRESULT ImageFeatureValue::GetOrtValue(WinML::BindingContext& context, OrtValue*
auto provider = spSession->GetExecutionProvider();
// and the adapter
com_ptr<_winmla::IWinMLAdapter> adapter;
com_ptr<winmla::IWinMLAdapter> adapter;
WINML_THROW_IF_FAILED(OrtGetWinMLAdapter(adapter.put()));
// create the OrtValue
@ -552,7 +552,7 @@ HRESULT ImageFeatureValue::UpdateSourceResourceData(BindingContext& context, Ort
auto spSession = context.session.as<LearningModelSession>();
auto spDevice = spSession->Device().as<LearningModelDevice>();
com_ptr<_winmla::IWinMLAdapter> adapter;
com_ptr<winmla::IWinMLAdapter> adapter;
WINML_THROW_IF_FAILED(OrtGetWinMLAdapter(adapter.put()));
// Get the output tensor raw data

10
winml/lib/Api/LearningModel.cpp
View file

@ -253,9 +253,9 @@ LearningModel::LoadFromStream(
}
WINML_CATCH_ALL
_winmla::IModelProto*
winmla::IModelProto*
LearningModel::DetachModelProto() {
com_ptr<_winmla::IModelProto> detached_model_proto;
com_ptr<winmla::IModelProto> detached_model_proto;
if (model_proto_ != nullptr) {
detached_model_proto.attach(model_proto_.detach());
@ -265,15 +265,15 @@ LearningModel::DetachModelProto() {
return detached_model_proto.detach();
}
_winmla::IModelProto*
winmla::IModelProto*
LearningModel::CopyModelProto() {
if (model_proto_ == nullptr) {
return nullptr;
}
com_ptr<_winmla::IWinMLAdapter> adapter;
com_ptr<winmla::IWinMLAdapter> adapter;
WINML_THROW_IF_FAILED(OrtGetWinMLAdapter(adapter.put()));
com_ptr<_winmla::IModelProto> model_proto;
com_ptr<winmla::IModelProto> model_proto;
WINML_THROW_IF_FAILED(adapter->CreateModelProto(model_proto_.get(), model_proto.put()));
return model_proto.detach();

33
winml/lib/Api/LearningModel.h
View file

@ -91,35 +91,22 @@ struct LearningModel : LearningModelT<LearningModel> {
public:
/* Non-ABI methods */
bool
IsDisposed();
IMLOperatorRegistry*
GetOperatorRegistry();
_winmla::IModelProto*
DetachModelProto();
_winmla::IModelProto*
CopyModelProto();
bool IsDisposed();
IMLOperatorRegistry* GetOperatorRegistry();
winmla::IModelProto* DetachModelProto();
winmla::IModelProto* CopyModelProto();
private:
void
Initialize();
void
LogCreationEvent(
bool fromStream = false);
void
ModelUseFP16(
void Initialize();
void LogCreationEvent(bool fromStream = false);
void ModelUseFP16(
winml::ILearningModelFeatureDescriptor descriptor,
bool& use_fp16);
private:
com_ptr<_winmla::IWinMLAdapter> adapter_;
com_ptr<_winmla::IModelProto> model_proto_;
com_ptr<_winmla::IModelInfo> model_info_;
com_ptr<winmla::IWinMLAdapter> adapter_;
com_ptr<winmla::IModelProto> model_proto_;
com_ptr<winmla::IModelInfo> model_info_;
ILearningModelOperatorProvider operator_provider_;
};

3
winml/lib/Api/LearningModelBinding.cpp
View file

@ -613,7 +613,8 @@ void LearningModelBinding::BindUnboundOutputs()
// Add all unbound outputs to binding collection
for (const auto& unbound_output : unbound_output_names) {
WINML_THROW_IF_FAILED(BindOutput(unbound_output, Ort::Value(nullptr)));
Ort::Value out(nullptr);
WINML_THROW_IF_FAILED(BindOutput(unbound_output, out));
}
}

2
winml/lib/Api/LearningModelBinding.h
View file

@ -74,7 +74,7 @@ struct LearningModelBinding : LearningModelBindingT<LearningModelBinding, ILearn
std::unordered_map<std::string, ProviderInfo> m_providers;
com_ptr<_winmla::IWinMLAdapter> adapter_;
com_ptr<winmla::IWinMLAdapter> adapter_;
std::vector<std::string> input_names_;
std::vector<Ort::Value> inputs_;
std::vector<std::string> output_names_;

20
winml/lib/Api/LearningModelSession.cpp
View file

@ -50,7 +50,7 @@ LearningModelSession::LearningModelSession(
}
WINML_CATCH_ALL
_winmla::IModelProto*
winmla::IModelProto*
LearningModelSession::GetOptimizedModel() {
// Get the model proto
@ -61,9 +61,9 @@ LearningModelSession::GetOptimizedModel() {
return GetOptimizedModel(should_close_model);
}
_winmla::IModelProto*
winmla::IModelProto*
LearningModelSession::GetOptimizedModel(bool should_close_model) {
com_ptr<_winmla::IModelProto> model_proto;
com_ptr<winmla::IModelProto> model_proto;
{
// Lock the model detach/copy since multiple threads can access concurrently
@ -81,7 +81,7 @@ LearningModelSession::GetOptimizedModel(bool should_close_model) {
}
// Ensure that the model is runnable on the device
com_ptr<_winmla::IWinMLAdapter> adapter;
com_ptr<winmla::IWinMLAdapter> adapter;
WINML_THROW_IF_FAILED(OrtGetWinMLAdapter(adapter.put()));
WINML_THROW_IF_FAILED(adapter->EnsureModelDeviceCompatibility(model_, model_proto.get(), device_.as<winmlp::LearningModelDevice>()->GetD3DDeviceCache()->IsFloat16Supported()));
@ -94,16 +94,16 @@ void LearningModelSession::Initialize() {
_winmlt::EventCategory::kSessionCreation);
// Get the optimized model proto from the learning model
com_ptr<_winmla::IModelProto> model_proto;
com_ptr<winmla::IModelProto> model_proto;
model_proto.attach(GetOptimizedModel());
// Create the session builder
auto device_impl = device_.as<winmlp::LearningModelDevice>();
com_ptr<_winmla::IWinMLAdapter> adapter;
com_ptr<winmla::IWinMLAdapter> adapter;
WINML_THROW_IF_FAILED(OrtGetWinMLAdapter(adapter.put()));
com_ptr<_winmla::IOrtSessionBuilder> session_builder;
com_ptr<winmla::IOrtSessionBuilder> session_builder;
WINML_THROW_IF_FAILED(adapter->CreateOrtSessionBuilder(
device_impl->GetD3DDevice(),
device_impl->GetDeviceQueue(),
@ -121,7 +121,7 @@ void LearningModelSession::Initialize() {
session_options_.BatchSizeOverride()));
}
com_ptr<_winmla::IInferenceSession> session;
com_ptr<winmla::IInferenceSession> session;
WINML_THROW_IF_FAILED(session_builder->CreateSession(
options, session.put(), &cached_execution_provider_));
@ -397,7 +397,7 @@ void LearningModelSession::ApplyEvaluationProperties() try {
if (evaluation_properties_) {
auto is_debug_output_enabled = evaluation_properties_.HasKey(c_enable_debug_output);
if (is_debug_output_enabled) {
com_ptr<_winmla::IWinMLAdapter> adapter;
com_ptr<winmla::IWinMLAdapter> adapter;
WINML_THROW_IF_FAILED(OrtGetWinMLAdapter(adapter.put()));
adapter->EnableDebugOutput();
}
@ -425,7 +425,7 @@ LearningModelSession::GetExecutionProvider() {
return cached_execution_provider_;
}
_winmla::IInferenceSession*
winmla::IInferenceSession*
LearningModelSession::GetIInferenceSession() {
return inference_session_.get();
}

8
winml/lib/Api/LearningModelSession.h
View file

@ -68,7 +68,7 @@ struct LearningModelSession : LearningModelSessionT<LearningModelSession> {
onnxruntime::IExecutionProvider*
GetExecutionProvider();
_winmla::IInferenceSession*
winmla::IInferenceSession*
GetIInferenceSession();
void
@ -78,10 +78,10 @@ struct LearningModelSession : LearningModelSessionT<LearningModelSession> {
void
Initialize();
_winmla::IModelProto*
winmla::IModelProto*
GetOptimizedModel();
_winmla::IModelProto*
winmla::IModelProto*
GetOptimizedModel(bool should_close_model);
uint64_t
@ -101,7 +101,7 @@ struct LearningModelSession : LearningModelSessionT<LearningModelSession> {
ToggleProfiler();
private:
com_ptr<_winmla::IInferenceSession> inference_session_;
com_ptr<winmla::IInferenceSession> inference_session_;
// reference to the active execution provider. weak
onnxruntime::IExecutionProvider* cached_execution_provider_ = nullptr;

2
winml/lib/Api/impl/MapBase.h
View file

@ -143,7 +143,7 @@ struct MapBase : winrt::implements<
}
template <typename TLotusKey, typename TLotusValue>
static onnxruntime::MLDataType GetLotusType(_winmla::IWinMLAdapter* adapter) {
static onnxruntime::MLDataType GetLotusType(winmla::IWinMLAdapter* adapter) {
return adapter->GetMapType(TensorKindFrom<TLotusKey>::Type, TensorKindFrom<TLotusValue>::Type);
}

4
winml/lib/Api/impl/SequenceBase.h
View file

@ -217,13 +217,13 @@ struct SequenceBase : public winrt::implements<
*ort_value = Ort::Value::CreateSequence(sequence_values).release();
return S_OK;
/* winrt::com_ptr<_winmla::IWinMLAdapter> adapter;
/* winrt::com_ptr<winmla::IWinMLAdapter> adapter;
RETURN_IF_FAILED(OrtGetWinMLAdapter(adapter.put()));
auto lotus_type = adapter->GetVectorMapType(
TensorKindFrom<ValidLotusType<T>::TKey>::Type,
TensorKindFrom<ValidLotusType<T>::TValue>::Type);
winrt::com_ptr<_winmla::IOrtValue> ml_value_out;
winrt::com_ptr<winmla::IOrtValue> ml_value_out;
adapter->CreateOrtValue(lotus_data_.get(), lotus_type, ml_value_out.put());
*ml_value = ml_value_out.detach();*/

8
winml/lib/Api/impl/Tensor.h
View file

@ -28,13 +28,13 @@ class Tensor {
TensorBufferPtr m_buffer;
std::vector<int64_t> shape_;
winrt::com_ptr<_winmla::IWinMLAdapter> adapter_;
winrt::com_ptr<winmla::IWinMLAdapter> adapter_;
public:
Tensor() = delete;
Tensor(
_winmla::IWinMLAdapter* adapter,
winmla::IWinMLAdapter* adapter,
std::vector<int64_t> const& shape,
winrt::Windows::Storage::Streams::IBuffer buffer) : shape_(shape),
m_buffer(
@ -50,7 +50,7 @@ class Tensor {
}
Tensor(
_winmla::IWinMLAdapter* adapter,
winmla::IWinMLAdapter* adapter,
std::vector<int64_t> const& shape) : shape_(shape),
m_buffer(
TensorBuffer::Create(
@ -64,7 +64,7 @@ class Tensor {
}
Tensor(
_winmla::IWinMLAdapter* adapter,
winmla::IWinMLAdapter* adapter,
std::vector<int64_t> const&& shape) : shape_(std::move(shape)),
m_buffer(
TensorBuffer::Create(

2
winml/lib/Api/impl/TensorBase.h
View file

@ -834,7 +834,7 @@ struct TensorBase : TBase {
std::shared_ptr<TensorResources<T>> m_resources;
std::vector<winrt::weak_ref<TensorMemoryBufferReference<T>>> m_outstandingReferences;
bool m_isClosed = false;
winrt::com_ptr<_winmla::IWinMLAdapter> adapter_;
winrt::com_ptr<winmla::IWinMLAdapter> adapter_;
};
} // namespace Windows::AI::MachineLearning

4
winml/lib/Api/impl/TensorMemoryBufferReference.h
View file

@ -25,7 +25,7 @@ struct DMLResource {
winrt::com_ptr<ID3D12Resource> DXResource;
UINT64 resource_width_;
void* ExecutionProviderAllocatedResource = nullptr;
winrt::com_ptr<_winmla::IWinMLAdapter> adapter_;
winrt::com_ptr<winmla::IWinMLAdapter> adapter_;
};
template <typename T>
@ -47,7 +47,7 @@ struct TensorResources {
try {
// Lazily allocate the cpu resource on call to GetBuffer
if (CpuResource == nullptr) {
winrt::com_ptr<_winmla::IWinMLAdapter> adapter;
winrt::com_ptr<winmla::IWinMLAdapter> adapter;
WINML_THROW_IF_FAILED(OrtGetWinMLAdapter(adapter.put()));
CpuResource = std::make_shared<WinML::Tensor<T>>(adapter.get(), shape);
}

6
winml/lib/Common/inc/NamespaceAliases.h
View file

@ -30,11 +30,11 @@ namespace winml = ::winrt::Windows::AI::MachineLearning;
namespace winrt::Windows::AI::MachineLearning::implementation {}
namespace winmlp = ::winrt::Windows::AI::MachineLearning::implementation;
namespace Windows::AI::MachineLearning::Adapter {}
namespace winmla = ::Windows::AI::MachineLearning::Adapter;
namespace Windows::AI::MachineLearning {}
namespace WinML = ::Windows::AI::MachineLearning;
namespace Windows::AI::MachineLearning::Telemetry {}
namespace _winmlt = ::Windows::AI::MachineLearning::Telemetry;
namespace Windows::AI::MachineLearning::Adapter {}
namespace _winmla = ::Windows::AI::MachineLearning::Adapter;