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Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

275 lines
9.2 KiB
C++

/*******************************************************************************
*
* MIT License
*
* Copyright (c) 2017 Advanced Micro Devices, Inc.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*
*******************************************************************************/
#ifndef GUARD_MIOPEN_TENSOR_DRIVER_HPP
#define GUARD_MIOPEN_TENSOR_DRIVER_HPP
#define UNPACK_VEC4(v) (v[0]), (v[1]), (v[2]), (v[3])
#include <algorithm>
#include <iterator>
#include <miopen/miopen.h>
#include <miopen/tensor.hpp>
#include <miopen/tensor_extra.hpp>
#include <miopen/tensor_layout.hpp>
#include <numeric>
#include <vector>
inline miopenTensorLayout_t StringToLayoutType(std::string layout_str)
{
miopenTensorLayout_t default_layout = miopenTensorNCHW;
if(layout_str == "NCHWc4")
return miopenTensorNCHWc4;
else if(layout_str == "NCHWc8")
return miopenTensorNCHWc8;
else if(layout_str == "CHWNc4")
return miopenTensorCHWNc4;
else if(layout_str == "CHWNc8")
return miopenTensorCHWNc8;
else if(layout_str == "NCHW")
{
return miopenTensorNCHW;
}
else if(layout_str == "NHWC")
{
return miopenTensorNHWC;
}
else if(layout_str == "NDHWC")
{
return miopenTensorNDHWC;
}
else if(layout_str == "NCDHW")
{
return miopenTensorNCDHW;
}
else
{
MIOPEN_THROW("We only support NCHWc4, NCHWc8, CHWNc4, CHWNc8, NCHW, NHWC, NDHWC, NCDHW "
"vectorized tensor layout.");
return default_layout;
}
}
inline void LengthReorder(std::vector<int>& lens, const std::initializer_list<int>& indices)
{
std::vector<int> out_lens;
out_lens.reserve(indices.size());
for(int index : indices)
{
assert(0 <= index && index < lens.size());
out_lens.push_back(std::move(lens[index]));
}
lens = std::move(out_lens);
}
inline std::size_t GetTensorVectorLength(const miopenTensorDescriptor_t& tensor)
{
std::size_t vectorLength;
int size = 0;
miopenGetTensorDescriptorSize(tensor, &size);
miopenGetNdTensorDescriptorVectorLength(tensor, &vectorLength);
return vectorLength;
}
inline std::vector<int> GetTensorLengths(const miopenTensorDescriptor_t& tensor)
{
int n;
int c;
int h;
int w;
int d;
int size = 0;
miopenGetTensorDescriptorSize(tensor, &size);
if(size == 5)
{
miopenGet5dTensorDescriptorLengths(tensor, &n, &c, &d, &h, &w);
return std::vector<int>({n, c, d, h, w});
}
else if(size == 4)
{
miopenGet4dTensorDescriptorLengths(tensor, &n, &c, &h, &w);
return std::vector<int>({n, c, h, w});
}
std::vector<int> tensor_len;
tensor_len.resize(miopen::deref(tensor).GetNumDims());
miopenGetTensorDescriptor(tensor, nullptr, tensor_len.data(), nullptr);
return tensor_len;
}
inline std::vector<int> GetTensorStrides(const miopenTensorDescriptor_t& tensor)
{
int nstride;
int cstride;
int dstride;
int hstride;
int wstride;
int size = 0;
miopenGetTensorDescriptorSize(tensor, &size);
if(size == 5)
{
miopenGet5dTensorDescriptorStrides(
tensor, &nstride, &cstride, &dstride, &hstride, &wstride);
return std::vector<int>({nstride, cstride, dstride, hstride, wstride});
}
else if(size == 4)
{
miopenGet4dTensorDescriptorStrides(tensor, &nstride, &cstride, &hstride, &wstride);
return std::vector<int>({nstride, cstride, hstride, wstride});
}
std::vector<int> tensor_strides;
tensor_strides.resize(miopen::deref(tensor).GetNumDims());
miopenGetTensorDescriptor(tensor, nullptr, nullptr, tensor_strides.data());
return tensor_strides;
}
inline int SetTensor4d(miopenTensorDescriptor_t t,
std::vector<int>& len,
miopenDataType_t data_type = miopenFloat)
{
return miopenSet4dTensorDescriptor(t, data_type, UNPACK_VEC4(len));
}
inline int SetTensorNdVector(miopenTensorDescriptor_t t,
std::vector<int>& len,
miopenTensorLayout_t layout,
miopenDataType_t data_type = miopenFloat)
{
if(layout == miopenTensorNCHWc4 || layout == miopenTensorNCHWc8 || layout == miopenTensorNHWC ||
layout == miopenTensorNCHW || layout == miopenTensorNDHWC || layout == miopenTensorNCDHW)
{
// Do nothing, MIOpen implicit logic that lens are in NCHW order.
}
else if(layout == miopenTensorCHWNc4 || layout == miopenTensorCHWNc8)
{
LengthReorder(len, {1, 2, 3, 0});
}
else
{
MIOPEN_THROW("We only support NCHWc4, NCHWc8, CHWNc4, CHWNc8, NCHW, NHWC, NDHWC, NCDHW "
"vectorized tensor layout.");
return -1;
}
return miopenSetNdTensorDescriptorWithLayout(t, data_type, layout, len.data(), len.size());
}
inline int SetTensorNd(miopenTensorDescriptor_t t,
std::vector<int>& len,
miopenDataType_t data_type = miopenFloat)
{
return miopenSetTensorDescriptor(t, data_type, len.size(), len.data(), nullptr);
}
inline int SetTensorNd(miopenTensorDescriptor_t t,
std::vector<std::size_t>& len,
miopenDataType_t data_type = miopenFloat)
{
return miopenSetTensorDescriptorV2(t, data_type, len.size(), len.data(), nullptr);
}
inline int SetTensorNd(miopenTensorDescriptor_t t,
std::vector<int>& len,
std::vector<int>& strides,
miopenDataType_t data_type = miopenFloat)
{
return miopenSetTensorDescriptor(t, data_type, len.size(), len.data(), strides.data());
}
inline int SetTensorNd(miopenTensorDescriptor_t t,
std::vector<std::size_t>& len,
std::vector<std::size_t>& strides,
miopenDataType_t data_type = miopenFloat)
{
return miopenSetTensorDescriptorV2(t, data_type, len.size(), len.data(), strides.data());
}
inline int SetTensorNd(miopenTensorDescriptor_t t,
std::vector<int>& len,
const std::string& layout,
miopenDataType_t data_type = miopenFloat)
{
if(layout.empty())
{
return SetTensorNd(t, len, data_type);
}
if(layout.size() != len.size() && layout.find('c') == std::string::npos)
{
MIOPEN_THROW("unmatched layout and dimension size");
}
if(layout.find('c') != std::string::npos)
{
return SetTensorNdVector(t, len, StringToLayoutType(layout), data_type);
}
// Dimension lengths vector 'len' comes with a default layout.
std::string len_layout = miopen::tensor_layout_get_default(layout.size());
if(len_layout.empty())
{
return SetTensorNd(t, len, data_type);
}
std::vector<std::size_t> strides2;
std::vector<std::size_t> len2(len.cbegin(), len.cend());
miopen::tensor_layout_to_strides(len2, len_layout, layout, strides2);
return SetTensorNd(t, len2, strides2, data_type);
}
// This function ignores tensor strides completely and its result should not be interpreted as
// memory required for an "unpacked" tensor. In such cases GetTensorSpace should be used instead.
// For "packed" tensors result may be interpreted as an amount of memory required for the tensor.
// The implementation is a copy-paste from miopen::TensorDescriptor.
inline size_t GetTensorSize(const miopenTensorDescriptor_t& tensor)
{
assert(miopen::deref(tensor).IsPacked() &&
"GetTensorSize should not be used on an unpacked tensor.");
const auto len = GetTensorLengths(tensor);
const size_t vectorLength = GetTensorVectorLength(tensor);
size_t sz = std::accumulate(len.begin(), len.end(), vectorLength, std::multiplies<size_t>());
return sz;
}
// The result of this function may be interpreted as a correct amount of memory required for both
// "packed" and "unpacked" tensors. In general it should be used for such purposes rather than
// GetTensorSize. Unless, of course, there is absolutely zero chance to receive an unpacked tensor.
inline size_t GetTensorSpace(const miopenTensorDescriptor_t& tensor)
{
return miopen::deref(tensor).GetElementSpace();
}
#endif // GUARD_MIOPEN_TENSOR_DRIVER_HPP