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