mirror of
https://github.com/saymrwulf/onnxruntime.git
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2717c178cc
* Migrate winml to Microsoft Namespace (packaging changes are pending) * add ns_prefix toggle * fix packaging * Users/sheilk/add missing raw header (#3484) * add dualapipartition * wrong variable for repo root Co-authored-by: Sheil Kumar <sheilk@microsoft.com> * remove existence check to force failures * extra paren * dualapipartition needs to be referenced from the source * add microsoft.ai.machinelearning.dll to the output dir * rename the idl file so that assembly info is correctly added into the winmd * fix namespaces * update namespaces * default to microsoft, and add namespace override as build argument * update cmakesetings.json as well * remove from cmakelists.txt Co-authored-by: Sheil Kumar <sheilk@microsoft.com> Co-authored-by: Changming Sun <chasun@microsoft.com>
87 lines
No EOL
4.1 KiB
C++
87 lines
No EOL
4.1 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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namespace _winml {
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// We need to define our own type for Half since DirectX::PackedVector::Half resolves to uint16_t per its typedef declaration.
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// Templates require an actual type name to resolve correctly.
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struct Half {
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DirectX::PackedVector::HALF value;
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};
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template <typename T>
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struct TensorKindFrom {};
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template <>
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struct TensorKindFrom<winml::ITensorInt8Bit> { static const winml::TensorKind Type = winml::TensorKind::Int8; };
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template <>
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struct TensorKindFrom<winml::ITensorUInt8Bit> { static const winml::TensorKind Type = winml::TensorKind::UInt8; };
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template <>
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struct TensorKindFrom<winml::ITensorUInt16Bit> { static const winml::TensorKind Type = winml::TensorKind::UInt16; };
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template <>
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struct TensorKindFrom<winml::ITensorInt16Bit> { static const winml::TensorKind Type = winml::TensorKind::Int16; };
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template <>
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struct TensorKindFrom<winml::ITensorUInt32Bit> { static const winml::TensorKind Type = winml::TensorKind::UInt32; };
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template <>
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struct TensorKindFrom<winml::ITensorInt32Bit> { static const winml::TensorKind Type = winml::TensorKind::Int32; };
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template <>
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struct TensorKindFrom<winml::ITensorUInt64Bit> { static const winml::TensorKind Type = winml::TensorKind::UInt64; };
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template <>
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struct TensorKindFrom<winml::ITensorInt64Bit> { static const winml::TensorKind Type = winml::TensorKind::Int64; };
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template <>
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struct TensorKindFrom<winml::ITensorBoolean> { static const winml::TensorKind Type = winml::TensorKind::Boolean; };
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template <>
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struct TensorKindFrom<winml::ITensorDouble> { static const winml::TensorKind Type = winml::TensorKind::Double; };
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template <>
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struct TensorKindFrom<winml::ITensorFloat> { static const winml::TensorKind Type = winml::TensorKind::Float; };
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template <>
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struct TensorKindFrom<winml::ITensorFloat16Bit> { static const winml::TensorKind Type = winml::TensorKind::Float16; };
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template <>
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struct TensorKindFrom<winml::ITensorString> { static const winml::TensorKind Type = winml::TensorKind::String; };
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template <>
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struct TensorKindFrom<int8_t> { static const winml::TensorKind Type = winml::TensorKind::Int8; };
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template <>
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struct TensorKindFrom<uint8_t> { static const winml::TensorKind Type = winml::TensorKind::UInt8; };
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template <>
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struct TensorKindFrom<uint16_t> { static const winml::TensorKind Type = winml::TensorKind::UInt16; };
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template <>
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struct TensorKindFrom<int16_t> { static const winml::TensorKind Type = winml::TensorKind::Int16; };
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template <>
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struct TensorKindFrom<uint32_t> { static const winml::TensorKind Type = winml::TensorKind::UInt32; };
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template <>
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struct TensorKindFrom<int32_t> { static const winml::TensorKind Type = winml::TensorKind::Int32; };
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template <>
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struct TensorKindFrom<uint64_t> { static const winml::TensorKind Type = winml::TensorKind::UInt64; };
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template <>
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struct TensorKindFrom<int64_t> { static const winml::TensorKind Type = winml::TensorKind::Int64; };
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template <>
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struct TensorKindFrom<bool> { static const winml::TensorKind Type = winml::TensorKind::Boolean; };
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template <>
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struct TensorKindFrom<double> { static const winml::TensorKind Type = winml::TensorKind::Double; };
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template <>
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struct TensorKindFrom<float> { static const winml::TensorKind Type = winml::TensorKind::Float; };
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template <>
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struct TensorKindFrom<winrt::hstring> { static const winml::TensorKind Type = winml::TensorKind::String; };
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template <>
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struct TensorKindFrom<std::string> { static const winml::TensorKind Type = winml::TensorKind::String; };
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template <>
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struct TensorKindFrom<Half> { static const winml::TensorKind Type = winml::TensorKind::Float16; };
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template <typename T>
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struct TensorFeatureDescriptorFrom {
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static winml::ILearningModelFeatureDescriptor
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CreateAnonymous(
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std::vector<int64_t> shape) {
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return winrt::make<winmlp::TensorFeatureDescriptor>(
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nullptr /* set to null as values are name-less */,
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nullptr /* set to null as values are description-less */,
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TensorKindFrom<T>::Type,
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shape,
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false /* set to false as values dont have required annotations */,
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false /* set to false as this is not a tensor of unsupported metadata */);
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}
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};
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} // namespace _winml
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