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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>
93 lines
No EOL
3 KiB
C++
93 lines
No EOL
3 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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#include "TensorBuffer.h"
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//
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// the Tensor class is the actual object for CPU memory buffers.
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// TensorBase contains one of these to represent the raw memory
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// GetCpuResource() returns it
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//
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namespace _winml {
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template <typename T>
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class Tensor {
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private:
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using TensorBuffer = TensorBuffer<T>;
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using TensorBufferPtr = typename TensorBuffer::TensorBufferPtr;
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TensorBufferPtr m_buffer;
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std::vector<int64_t> shape_;
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public:
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Tensor() = delete;
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Tensor(
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std::vector<int64_t> const& shape,
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wss::IBuffer buffer) : shape_(shape),
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m_buffer(
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TensorBuffer::Create(
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static_cast<uint32_t>(
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std::accumulate(
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std::begin(shape),
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std::end(shape),
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static_cast<int64_t>(1),
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std::multiplies<int64_t>())),
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buffer)) {
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}
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Tensor(
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std::vector<int64_t> const& shape) : shape_(shape),
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m_buffer(
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TensorBuffer::Create(
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static_cast<uint32_t>(
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std::accumulate(
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std::begin(shape),
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std::end(shape),
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static_cast<int64_t>(1),
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std::multiplies<int64_t>())))) {
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}
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Tensor(
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std::vector<int64_t> const&& shape) : shape_(std::move(shape)),
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m_buffer(
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TensorBuffer::Create(
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static_cast<uint32_t>(
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std::accumulate(
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std::begin(shape),
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std::end(shape),
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static_cast<int64_t>(1),
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std::multiplies<int64_t>())))) {
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}
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auto size() const {
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return m_buffer->Size();
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}
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auto size_in_bytes() const {
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return m_buffer->SizeInBytes();
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}
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auto buffer() {
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return m_buffer->Buffer();
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}
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void set(uint32_t size, const T* pData) {
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m_buffer->Set(size, pData);
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}
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void set(std::vector<T>&& other) {
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m_buffer->Set(other);
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}
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const std::vector<int64_t>& shape() const {
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return shape_;
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}
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auto get_tensor_buffer() {
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return m_buffer;
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}
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};
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} // namespace _winml
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