derek.holloway
7502bf64a4
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452 lines
17 KiB
C++
452 lines
17 KiB
C++
/*******************************************************************************
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*
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* MIT License
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*
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* Copyright (c) 2023 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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#pragma once
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#include <miopen/bfloat16.hpp>
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#include <miopen/miopen.h>
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#include <iostream>
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#include "tensor_holder.hpp"
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#include "conv_common.hpp"
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#include "conv_tensor_gen.hpp"
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using Direction = miopen::conv::Direction;
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struct GroupConvTestConfigBase
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{
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virtual ~GroupConvTestConfigBase() = default;
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GroupConvTestConfigBase(const GroupConvTestConfigBase&) = default;
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GroupConvTestConfigBase& operator=(const GroupConvTestConfigBase&) = default;
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GroupConvTestConfigBase(GroupConvTestConfigBase&&) noexcept = default;
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GroupConvTestConfigBase& operator=(GroupConvTestConfigBase&&) noexcept = default;
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protected:
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GroupConvTestConfigBase() = default;
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};
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template <unsigned NDIM>
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struct GroupConvTestConfig : GroupConvTestConfigBase
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{
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};
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template <>
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struct GroupConvTestConfig<2u> : GroupConvTestConfigBase
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{
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struct Size2D
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{
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size_t y;
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size_t x;
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};
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size_t G;
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size_t N;
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size_t C;
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size_t k;
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Size2D img;
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Size2D filter;
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Size2D pad;
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Size2D stride;
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Size2D dilation;
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GroupConvTestConfig() = default;
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GroupConvTestConfig(size_t g_,
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size_t n_,
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size_t c_,
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size_t k_,
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Size2D img_,
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Size2D filter_,
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Size2D pad_,
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Size2D stride_,
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Size2D dilation_)
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: G(g_),
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N(n_),
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C(c_),
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k(k_),
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img(img_),
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filter(filter_),
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pad(pad_),
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stride(stride_),
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dilation(dilation_)
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{
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}
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friend std::ostream& operator<<(std::ostream& os, const GroupConvTestConfig& tc)
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{
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return os << " G:" << tc.G << " N:" << tc.N << " C:" << tc.C << " K:" << tc.k
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<< " H:" << tc.img.y << " W:" << tc.img.x << " y:" << tc.filter.y
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<< " x:" << tc.filter.x << " pad.y:" << tc.pad.y << " pad.x:" << tc.pad.x
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<< " stride.y:" << tc.stride.y << " stride.x" << tc.stride.x
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<< " dilation.y:" << tc.dilation.y << " dilation.x" << tc.dilation.x;
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}
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std::vector<size_t> GetInput() { return {N, C, img.y, img.x}; }
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std::vector<size_t> GetWeights()
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{
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EXPECT_EQUAL(C % G, 0);
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return {k, C / G, filter.y, filter.x};
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}
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miopen::ConvolutionDescriptor GetConv()
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{
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return miopen::ConvolutionDescriptor{
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2,
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miopenConvolution,
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miopenPaddingDefault,
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{static_cast<int>(pad.y), static_cast<int>(pad.x)},
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{static_cast<int>(stride.y), static_cast<int>(stride.x)},
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{static_cast<int>(dilation.y), static_cast<int>(dilation.x)},
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{0, 0},
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static_cast<int>(G),
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1.0};
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}
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template <Direction DIR>
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static std::vector<GroupConvTestConfig> GetSmokeConfigs()
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{
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if constexpr(DIR == Direction::Forward)
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{
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return {
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// clang-format off
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// g n C K img filter pad stride dilation
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{1, 32, 64, 128, {28, 28}, {3, 3}, {0, 1}, {1, 2}, {2, 1}},
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{32, 16, 32, 64, {7, 7}, {3, 3}, {1, 1}, {1, 1}, {1, 1}},
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{1, 16, 32, 64, {16, 16}, {2, 2}, {0, 0}, {3, 3}, {1, 1}},
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{4, 8, 16, 32, {32, 4}, {3, 1}, {1, 0}, {1, 1}, {1, 1}},
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// clang-format on
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};
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}
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}
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template <Direction DIR>
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static std::vector<GroupConvTestConfig> GetConfigs()
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{
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if constexpr(DIR == Direction::Forward)
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{
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// clang-format off
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return {
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// g n C K img filter pad stride dilation
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{1, 64, 1024, 2048, {14, 14}, {1, 1}, {0, 0}, {2, 2}, {1, 1}},
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{1, 256, 192, 192, {28, 28}, {3, 3}, {1, 1}, {1, 1}, {1, 1}},
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{8, 256, 192, 192, {28, 28}, {3, 3}, {1, 1}, {1, 1}, {1, 1}},
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{8, 256, 384, 384, {28, 28}, {3, 3}, {1, 1}, {1, 1}, {1, 1}},
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{32, 256, 1024, 2048, {28, 28}, {3, 3}, {1, 1}, {1, 1}, {1, 1}},
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{4, 256, 192, 192, {28, 28}, {3, 3}, {1, 1}, {2, 2}, {1, 1}},
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{8, 256, 384, 384, {28, 28}, {3, 3}, {1, 1}, {2, 2}, {1, 1}},
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{32, 256, 1024, 2048, {28, 28}, {3, 3}, {1, 1}, {2, 2}, {1, 1}},
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{1, 6, 448, 896, {118, 182}, {3, 3}, {0, 0}, {2, 2}, {1, 1}},
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{4, 256, 192, 192, {28, 28}, {1, 1}, {1, 1}, {2, 2}, {1, 1}},
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{8, 256, 384, 384, {28, 28}, {1, 1}, {1, 1}, {2, 2}, {1, 1}},
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{32, 256, 1024, 2048, {28, 28}, {1, 1}, {1, 1}, {2, 2}, {1, 1}},
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{1, 6, 448, 896, {118, 182}, {1, 1}, {0, 0}, {2, 2}, {1, 1}},
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{4, 16, 224, 224, {469, 724}, {3, 3}, {1, 1}, {2, 2}, {1, 1}},
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};
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// clang-format on
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}
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}
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};
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template <>
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struct GroupConvTestConfig<3u>
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{
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struct Size3D
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{
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size_t z;
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size_t y;
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size_t x;
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};
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size_t G;
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size_t N;
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size_t C;
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size_t k;
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Size3D img;
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Size3D filter;
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Size3D pad;
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Size3D stride;
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Size3D dilation;
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friend std::ostream& operator<<(std::ostream& os, const GroupConvTestConfig<3u>& tc)
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{
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return os << " G:" << tc.G << " N:" << tc.N << " C:" << tc.C << " K:" << tc.k
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<< " D:" << tc.img.z << " H:" << tc.img.y << " W:" << tc.img.x
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<< " z:" << tc.filter.z << " y:" << tc.filter.y << " x:" << tc.filter.x
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<< " pad.z:" << tc.pad.z << " pad.y:" << tc.pad.y << " pad.x:" << tc.pad.x
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<< " stride.z:" << tc.stride.z << " stride.y:" << tc.stride.y
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<< " stride.x:" << tc.stride.x << " dilation.z:" << tc.dilation.z
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<< " dilation.y:" << tc.dilation.y << " dilation.x:" << tc.dilation.x;
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}
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std::vector<size_t> GetInput() { return {N, C, img.z, img.y, img.x}; }
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std::vector<size_t> GetWeights()
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{
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EXPECT_EQUAL(C % G, 0);
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return {k, C / G, filter.z, filter.y, filter.x};
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}
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miopen::ConvolutionDescriptor GetConv()
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{
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return miopen::ConvolutionDescriptor{
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3,
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miopenConvolution,
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miopenPaddingDefault,
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{static_cast<int>(pad.z), static_cast<int>(pad.y), static_cast<int>(pad.x)},
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{static_cast<int>(stride.z), static_cast<int>(stride.y), static_cast<int>(stride.x)},
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{static_cast<int>(dilation.z),
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static_cast<int>(dilation.y),
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static_cast<int>(dilation.x)},
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{0, 0, 0},
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static_cast<int>(G),
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1.0};
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}
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template <Direction DIR>
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static std::vector<GroupConvTestConfig> GetSmokeConfigs()
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{
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if constexpr(DIR == Direction::Forward)
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{
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return {
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// clang-format off
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// g n C K img filter pad stride dilation
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{1, 32, 64, 128, {28, 28, 28}, {3, 3, 3}, {0, 1, 1}, {1, 2, 2}, {2, 1, 1}},
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{32, 16, 32, 64, {7, 7, 7}, {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}},
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{1, 16, 32, 64, {16, 16, 16}, {2, 2, 2}, {0, 0, 0}, {3, 3, 3}, {1, 1, 1}},
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{4, 8, 16, 32, {32, 4, 4}, {3, 1, 1}, {1, 0, 0}, {1, 1, 1}, {1, 1, 1}},
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// clang-format on
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};
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}
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}
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template <Direction DIR>
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static std::vector<GroupConvTestConfig> GetConfigs()
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{
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if constexpr(DIR == Direction::Forward)
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{
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// clang-format off
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return {
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// g n C K img filter pad stride dilation
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{1 , 128, 64 , 64 , {14, 28, 28} , {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}},
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{1 , 64 , 32 , 32 , {28, 28, 28} , {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}},
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{2 , 128, 32 , 32 , {28, 28, 28} , {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}},
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{8 , 128, 32 , 32 , {28, 28, 28} , {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}},
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{2 , 128, 32 , 32 , {28, 28, 28} , {3, 3, 3}, {0, 0, 0}, {1, 1, 1}, {1, 1, 1}},
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{8 , 64 , 32 , 32 , {28, 28, 28} , {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}},
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{16, 64 , 32 , 32 , {28, 28, 28} , {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}},
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{2 , 128, 32 , 32 , {28, 28, 28} , {3, 3, 3}, {0, 0, 0}, {2, 2, 2}, {1, 1, 1}},
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{8 , 64 , 32 , 32 , {28, 28, 28} , {3, 3, 3}, {1, 1, 1}, {2, 2, 2}, {1, 1, 1}},
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{16, 64 , 32 , 32 , {28, 28, 28} , {3, 3, 3}, {1, 1, 1}, {2, 2, 2}, {1, 1, 1}},
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{3 , 48 , 48 , 48 , {28, 28, 28} , {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}},
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{3 , 48 , 39 , 39 , {28, 28, 28} , {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}},
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{5 , 120, 60 , 60 , {28, 28, 28} , {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}},
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{1 , 6 , 448, 896, {3, 118, 182}, {1, 1, 1}, {0, 0, 0}, {1, 2, 2}, {1, 1, 1}},
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};
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// clang-format on
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}
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}
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};
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struct ConvTestCaseBase
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{
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size_t N;
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size_t C;
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size_t H;
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size_t W;
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size_t k;
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size_t y;
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size_t x;
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size_t pad_x;
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size_t pad_y;
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size_t stride_x;
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size_t stride_y;
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size_t dilation_x;
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size_t dilation_y;
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miopenConvolutionMode_t conv_mode;
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friend std::ostream& operator<<(std::ostream& os, const ConvTestCaseBase& tc)
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{
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return os << "(N: " << tc.N << " C:" << tc.C << " H:" << tc.H << " W:" << tc.W
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<< " k: " << tc.k << " y:" << tc.y << " x:" << tc.x << " pad_y:" << tc.pad_y
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<< " pad_x:" << tc.pad_x << " stride_y:" << tc.stride_y
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<< " stride_x:" << tc.stride_x << " dilation_y:" << tc.dilation_y
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<< " dilation_x:" << tc.dilation_x << " conv_mode:" << tc.conv_mode << " )";
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}
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const std::vector<size_t> GetInput() const { return {N, C, H, W}; }
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const std::vector<size_t> GetWeights() const { return {k, C, y, x}; }
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const miopen::ConvolutionDescriptor GetConv() const
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{
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return miopen::ConvolutionDescriptor{
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{static_cast<int>(pad_y), static_cast<int>(pad_x)},
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{static_cast<int>(stride_y), static_cast<int>(stride_x)},
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{static_cast<int>(dilation_y), static_cast<int>(dilation_x)}};
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}
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};
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template <typename T>
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std::vector<T> GetNetworkForFusionCompileStepTest();
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template <>
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inline std::vector<ConvTestCaseBase> GetNetworkForFusionCompileStepTest()
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{
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return {{1, 64, 56, 56, 64, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{1, 64, 56, 56, 64, 3, 3, 1, 1, 1, 1, 1, 1, miopenConvolution}};
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}
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template <typename T>
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std::vector<T> GetNetwork1();
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template <>
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inline std::vector<ConvTestCaseBase> GetNetwork1()
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{
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// pyt_mlperf_resnet50v1.5
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// N, C, H, W, k, y, x, pad_x, pad_y, stride_x, stride_y, dilation_x, dilation_y, conv_mode
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return {{64, 1024, 14, 14, 2048, 1, 1, 0, 0, 2, 2, 1, 1, miopenConvolution},
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{64, 1024, 14, 14, 256, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 1024, 14, 14, 512, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 128, 28, 28, 128, 3, 3, 1, 1, 1, 1, 1, 1, miopenConvolution},
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{64, 128, 28, 28, 512, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 128, 56, 56, 128, 3, 3, 1, 1, 2, 2, 1, 1, miopenConvolution},
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{64, 2048, 7, 7, 512, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 256, 14, 14, 1024, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 256, 14, 14, 256, 3, 3, 1, 1, 1, 1, 1, 1, miopenConvolution},
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{64, 256, 28, 28, 256, 3, 3, 1, 1, 2, 2, 1, 1, miopenConvolution},
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{64, 256, 56, 56, 128, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 256, 56, 56, 512, 1, 1, 0, 0, 2, 2, 1, 1, miopenConvolution},
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{64, 256, 56, 56, 64, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 3, 224, 224, 64, 7, 7, 3, 3, 2, 2, 1, 1, miopenConvolution},
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{64, 512, 14, 14, 512, 3, 3, 1, 1, 2, 2, 1, 1, miopenConvolution},
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{64, 512, 28, 28, 1024, 1, 1, 0, 0, 2, 2, 1, 1, miopenConvolution},
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{64, 512, 28, 28, 128, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 512, 28, 28, 256, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 512, 7, 7, 2048, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 512, 7, 7, 512, 3, 3, 1, 1, 1, 1, 1, 1, miopenConvolution},
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{64, 64, 56, 56, 256, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 64, 56, 56, 64, 1, 1, 0, 0, 1, 1, 1, 1, miopenConvolution},
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{64, 64, 56, 56, 64, 3, 3, 1, 1, 1, 1, 1, 1, miopenConvolution}};
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}
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template <typename T>
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std::vector<T> ConvTestConfigs();
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template <>
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inline std::vector<ConvTestCaseBase> ConvTestConfigs()
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{ // n c h w k y x pad_x pad_y stri_x stri_y dia_x dia_y
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return {{16, 128, 16, 16, 128, 3, 3, 1, 1, 1, 1, 1, 1, miopenConvolution},
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{64, 128, 28, 28, 128, 3, 3, 1, 1, 1, 1, 1, 1, miopenConvolution},
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{64, 256, 14, 14, 256, 3, 3, 1, 1, 1, 1, 1, 1, miopenConvolution},
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{64, 512, 7, 7, 512, 3, 3, 1, 1, 1, 1, 1, 1, miopenConvolution},
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{64, 1024, 14, 14, 1024, 3, 3, 1, 1, 1, 1, 1, 1, miopenConvolution}};
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}
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template <typename T,
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typename Tref = float,
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typename TConfig = ConvTestCaseBase,
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bool use_cpu_ref = false,
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unsigned NDIM = 2>
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struct ConvFwdSolverTestBase
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{
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protected:
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void SetUpImpl(TConfig conv_config, miopenTensorLayout_t tensor_layout)
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{
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input = tensor<T>{tensor_layout, conv_config.GetInput()};
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weights = tensor<T>{tensor_layout, conv_config.GetWeights()};
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input.generate(GenData<T>{});
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weights.generate(GenWeights<T>{});
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|
|
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conv_desc = conv_config.GetConv();
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|
|
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miopen::TensorDescriptor output_desc =
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conv_desc.GetForwardOutputTensor(input.desc, weights.desc, miopen_type<T>{});
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|
|
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output = tensor<T>{tensor_layout, output_desc.GetLengths()};
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std::fill(output.begin(), output.end(), T(0));
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|
|
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auto&& handle = get_handle();
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in_dev = handle.Write(input.data);
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wei_dev = handle.Write(weights.data);
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out_dev = handle.Write(output.data);
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}
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|
|
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void TearDownConv()
|
|
{
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ref_out = tensor<Tref>{output.desc.GetLayoutEnum().value(), output.desc.GetLengths()};
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|
if(use_cpu_ref)
|
|
{
|
|
cpu_convolution_forward(conv_desc.GetSpatialDimension(),
|
|
input,
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|
weights,
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|
ref_out,
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|
conv_desc.GetConvPads(),
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|
conv_desc.GetConvStrides(),
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|
conv_desc.GetConvDilations(),
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|
conv_desc.GetGroupCount());
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|
}
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else
|
|
{
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ref_out = ref_conv_fwd(input, weights, ref_out, conv_desc);
|
|
}
|
|
}
|
|
|
|
void ThresholdChecks()
|
|
{
|
|
auto&& handle = get_handle();
|
|
output.data = handle.Read<T>(out_dev, output.data.size());
|
|
|
|
ASSERT_FALSE(miopen::range_zero(ref_out)) << "Cpu data is all zeros";
|
|
ASSERT_FALSE(miopen::range_zero(output)) << "Gpu data is all zeros";
|
|
ASSERT_EQ(miopen::range_distance(ref_out), miopen::range_distance(output));
|
|
|
|
double tolerance = 80;
|
|
if constexpr(std::is_same_v<T, bfloat16>)
|
|
{
|
|
tolerance = 4;
|
|
}
|
|
|
|
double threshold = std::numeric_limits<T>::epsilon() * tolerance;
|
|
auto error = miopen::rms_range(ref_out, output);
|
|
|
|
ASSERT_LT(miopen::find_idx(ref_out, miopen::not_finite), 0)
|
|
<< "Non finite number found in the CPU data";
|
|
|
|
ASSERT_LT(error, threshold) << "Error beyond tolerance";
|
|
}
|
|
|
|
miopen::ConvolutionDescriptor conv_desc;
|
|
tensor<T> input;
|
|
tensor<T> weights;
|
|
tensor<T> output;
|
|
tensor<Tref> ref_out;
|
|
miopen::Allocator::ManageDataPtr in_dev;
|
|
miopen::Allocator::ManageDataPtr wei_dev;
|
|
miopen::Allocator::ManageDataPtr out_dev;
|
|
};
|