/******************************************************************************* * * MIT License * * Copyright (c) 2024 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. * *******************************************************************************/ #include "unit_conv_solver.hpp" namespace { auto GetConvTestCases(miopenDataType_t datatype) { using TestCase = miopen::unit_tests::ConvTestCase; auto type_x = datatype; auto type_w = datatype; auto type_y = (datatype == miopenInt8) ? miopenInt32 : datatype; return std::vector{ // clang-format off TestCase{{1, 16, 14, 14}, {48, 16, 5, 5}, {2, 2}, {1, 1}, {1, 1}, type_x, type_w, type_y}, // clang-format on }; } auto GetConvTestCasesFull(miopenDataType_t datatype) { using TestCase = miopen::unit_tests::ConvTestCase; auto cases = std::vector{}; if(datatype == miopenInt8) { auto type_x = datatype; auto type_w = datatype; auto type_y = miopenInt32; // clang-format off // Regression test for int8, issue unknown cases.emplace_back(TestCase{{256, 1024, 14, 14}, {256, 1024, 1, 1}, {0, 0}, {1, 1}, {1, 1}, type_x, type_w, type_y}); // clang-format on } if(datatype == miopenHalf || datatype == miopenFloat) { // clang-format off // Regression test for https://github.com/ROCm/MIOpen/issues/3279 cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 7, 7}}, {datatype, {1, 1, 1, 1}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); // clang-format on } // clang-format off cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {2, 2}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {3, 3}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {3, 3}}}); if(datatype != miopenInt8) // Data is too small and will generate all zeroes { cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 1, 1}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); } cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 127, 127}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 129, 129}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); if(datatype != miopenInt8) // Data is too small and will generate all zeroes { cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 1, 1}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); } cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 127, 127}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 129, 129}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 1, 32, 32}}, {datatype, miopenTensorNCHW, {2, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 1, 32, 32}}, {datatype, miopenTensorNCHW, {4, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 1, 32, 32}}, {datatype, miopenTensorNCHW, {8, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 1, 32, 32}}, {datatype, miopenTensorNCHW, {16, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {16, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 16}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {4, 4, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 4}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {8, 4, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 4}}); if(datatype != miopenInt8) // Filter is too big { cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {1, 16, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {8, 16, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {64, 16, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); } cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 1, 32, 32}}, {datatype, miopenTensorNHWC, {2, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 1, 32, 32}}, {datatype, miopenTensorNHWC, {4, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 1, 32, 32}}, {datatype, miopenTensorNHWC, {8, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 1, 32, 32}}, {datatype, miopenTensorNHWC, {16, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 16, 32, 32}}, {datatype, miopenTensorNHWC, {16, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 16}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 16, 32, 32}}, {datatype, miopenTensorNHWC, {4, 4, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 4}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 16, 32, 32}}, {datatype, miopenTensorNHWC, {8, 4, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 4}}); if(datatype != miopenInt8) // Filter is too big { cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 16, 32, 32}}, {datatype, miopenTensorNHWC, {1, 16, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 16, 32, 32}}, {datatype, miopenTensorNHWC, {8, 16, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 16, 32, 32}}, {datatype, miopenTensorNHWC, {64, 16, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}}); } // clang-format on return cases; } const auto& GetTestParams() { static const auto params = [] { auto p = miopen::unit_tests::UnitTestConvSolverParams(Gpu::All); p.UseCpuRef(); // CPU verification return p; }(); return params; } // Subbatch chunking test case (3D convolution triggering 2-chunk processing) // MAX_GRID_SIZE = 16M, batch_chunk_size = 16M/k // n=17, k=1000000: batch_chunk_size=16, n>16 triggers 2-chunk processing auto GetSubbatchTestCase() { using TestCase = miopen::unit_tests::ConvTestCase; return std::vector{ // clang-format off TestCase{{17, 1, 1, 1, 1}, {1000000, 1, 1, 1, 1}, {0, 0, 0}, {1, 1, 1}, {1, 1, 1}, miopenHalf}, // clang-format on }; } // Subbatch chunking test case for 2D convolution (triggering 2-chunk processing) // MAX_GRID_SIZE = 16M, batch_chunk_size = 16M/k // n=1678, k=10000: batch_chunk_size=1677, n>1677 triggers 2-chunk processing // Using smaller k (10K) for faster weight allocation while still testing chunking auto GetSubbatchTestCase2D() { using TestCase = miopen::unit_tests::ConvTestCase; return std::vector{ // clang-format off TestCase{{1678, 1, 1, 1}, {10000, 1, 1, 1}, {0, 0}, {1, 1}, {1, 1}, miopenHalf}, // clang-format on }; } } // namespace using GPU_UnitTestConvSolverDirectNaiveFwd_FP16 = GPU_UnitTestConvSolverFwd_FP16; using GPU_UnitTestConvSolverDirectNaiveFwd_BFP16 = GPU_UnitTestConvSolverFwd_BFP16; using GPU_UnitTestConvSolverDirectNaiveFwd_FP32 = GPU_UnitTestConvSolverFwd_FP32; using GPU_UnitTestConvSolverDirectNaiveFwd_I8 = GPU_UnitTestConvSolverFwd_I8; using CPU_UnitTestConvSolverDirectNaiveDevApplicabilityFwd_NONE = CPU_UnitTestConvSolverDevApplicabilityFwd_NONE; TEST_P(GPU_UnitTestConvSolverDirectNaiveFwd_I8, ConvDirectNaiveConvFwd) { this->RunTest(miopen::solver::conv::ConvDirectNaiveConvFwd{}); }; TEST_P(GPU_UnitTestConvSolverDirectNaiveFwd_FP16, ConvDirectNaiveConvFwd) { this->RunTest(miopen::solver::conv::ConvDirectNaiveConvFwd{}); }; TEST_P(GPU_UnitTestConvSolverDirectNaiveFwd_BFP16, ConvDirectNaiveConvFwd) { this->RunTest(miopen::solver::conv::ConvDirectNaiveConvFwd{}); }; TEST_P(GPU_UnitTestConvSolverDirectNaiveFwd_FP32, ConvDirectNaiveConvFwd) { this->RunTest(miopen::solver::conv::ConvDirectNaiveConvFwd{}); }; TEST_P(CPU_UnitTestConvSolverDirectNaiveDevApplicabilityFwd_NONE, ConvDirectNaiveConvFwd) { this->RunTest(miopen::solver::conv::ConvDirectNaiveConvFwd{}); }; // Smoke tests INSTANTIATE_TEST_SUITE_P(Smoke, GPU_UnitTestConvSolverDirectNaiveFwd_I8, testing::Combine(testing::Values(GetTestParams()), testing::Values(miopenConvolutionAlgoDirect), testing::ValuesIn(GetConvTestCases(miopenInt8)))); INSTANTIATE_TEST_SUITE_P(Smoke, GPU_UnitTestConvSolverDirectNaiveFwd_FP16, testing::Combine(testing::Values(GetTestParams()), testing::Values(miopenConvolutionAlgoDirect), testing::ValuesIn(GetConvTestCases(miopenHalf)))); INSTANTIATE_TEST_SUITE_P(Smoke, GPU_UnitTestConvSolverDirectNaiveFwd_BFP16, testing::Combine(testing::Values(GetTestParams()), testing::Values(miopenConvolutionAlgoDirect), testing::ValuesIn(GetConvTestCases(miopenBFloat16)))); INSTANTIATE_TEST_SUITE_P(Smoke, GPU_UnitTestConvSolverDirectNaiveFwd_FP32, testing::Combine(testing::Values(GetTestParams()), testing::Values(miopenConvolutionAlgoDirect), testing::ValuesIn(GetConvTestCases(miopenFloat)))); // Device applicability test INSTANTIATE_TEST_SUITE_P(Smoke, CPU_UnitTestConvSolverDirectNaiveDevApplicabilityFwd_NONE, testing::Combine(testing::Values(GetTestParams()), testing::Values(GetConvTestCases(miopenFloat)[0]))); // Full tests INSTANTIATE_TEST_SUITE_P(Full, GPU_UnitTestConvSolverDirectNaiveFwd_I8, testing::Combine(testing::Values(GetTestParams()), testing::Values(miopenConvolutionAlgoDirect), testing::ValuesIn(GetConvTestCasesFull(miopenInt8)))); INSTANTIATE_TEST_SUITE_P(Full, GPU_UnitTestConvSolverDirectNaiveFwd_FP16, testing::Combine(testing::Values(GetTestParams()), testing::Values(miopenConvolutionAlgoDirect), testing::ValuesIn(GetConvTestCasesFull(miopenHalf)))); INSTANTIATE_TEST_SUITE_P(Full, GPU_UnitTestConvSolverDirectNaiveFwd_BFP16, testing::Combine(testing::Values(GetTestParams()), testing::Values(miopenConvolutionAlgoDirect), testing::ValuesIn(GetConvTestCasesFull(miopenBFloat16)))); INSTANTIATE_TEST_SUITE_P(Full, GPU_UnitTestConvSolverDirectNaiveFwd_FP32, testing::Combine(testing::Values(GetTestParams()), testing::Values(miopenConvolutionAlgoDirect), testing::ValuesIn(GetConvTestCasesFull(miopenFloat)))); // Full: Subbatch chunking test (tests 2-chunk processing to prevent grid dimension overflow) INSTANTIATE_TEST_SUITE_P(FullSubbatch, GPU_UnitTestConvSolverDirectNaiveFwd_FP16, testing::Combine(testing::Values(GetTestParams()), testing::Values(miopenConvolutionAlgoDirect), testing::ValuesIn(GetSubbatchTestCase()))); // Full: Subbatch chunking test for 2D (tests 2-chunk processing to prevent grid dimension overflow) INSTANTIATE_TEST_SUITE_P(FullSubbatch2D, GPU_UnitTestConvSolverDirectNaiveFwd_FP16, testing::Combine(testing::Values(GetTestParams()), testing::Values(miopenConvolutionAlgoDirect), testing::ValuesIn(GetSubbatchTestCase2D())));