derek.holloway
7502bf64a4
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317 lines
22 KiB
C++
317 lines
22 KiB
C++
/*******************************************************************************
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*
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* MIT License
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*
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* Copyright (c) 2024 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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#include "unit_conv_solver.hpp"
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namespace {
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auto GetConvTestCases(miopenDataType_t datatype)
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{
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using TestCase = miopen::unit_tests::ConvTestCase;
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auto type_x = datatype;
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auto type_w = datatype;
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auto type_y = (datatype == miopenInt8) ? miopenInt32 : datatype;
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return std::vector{
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// clang-format off
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TestCase{{1, 16, 14, 14}, {48, 16, 5, 5}, {2, 2}, {1, 1}, {1, 1}, type_x, type_w, type_y},
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// clang-format on
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};
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}
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auto GetConvTestCasesFull(miopenDataType_t datatype)
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{
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using TestCase = miopen::unit_tests::ConvTestCase;
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auto cases = std::vector<TestCase>{};
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if(datatype == miopenInt8)
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{
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auto type_x = datatype;
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auto type_w = datatype;
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auto type_y = miopenInt32;
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// clang-format off
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// Regression test for int8, issue unknown
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cases.emplace_back(TestCase{{256, 1024, 14, 14}, {256, 1024, 1, 1}, {0, 0}, {1, 1}, {1, 1}, type_x, type_w, type_y});
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// clang-format on
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}
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if(datatype == miopenHalf || datatype == miopenFloat)
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{
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// clang-format off
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// Regression test for https://github.com/ROCm/MIOpen/issues/3279
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 7, 7}}, {datatype, {1, 1, 1, 1}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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// clang-format on
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}
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// clang-format off
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {2, 2}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {1, 1}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {1, 1}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {2, 2}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {2, 2}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {2, 2}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {3, 3}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{1, 1}, {3, 3}, {3, 3}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{2, 2}, {3, 3}, {3, 3}}});
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if(datatype != miopenInt8) // Data is too small and will generate all zeroes
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{
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 1, 1}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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}
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 127, 127}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {1, 1, 129, 129}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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if(datatype != miopenInt8) // Data is too small and will generate all zeroes
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{
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 1, 1}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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}
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 127, 127}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {1, 1, 129, 129}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 1, 32, 32}}, {datatype, miopenTensorNCHW, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 1, 32, 32}}, {datatype, miopenTensorNCHW, {2, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 1, 32, 32}}, {datatype, miopenTensorNCHW, {4, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 1, 32, 32}}, {datatype, miopenTensorNCHW, {8, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 1, 32, 32}}, {datatype, miopenTensorNCHW, {16, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {16, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 16}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {4, 4, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 4}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {8, 4, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 4}});
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if(datatype != miopenInt8) // Filter is too big
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{
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {1, 16, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {8, 16, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNCHW, {64, 16, 32, 32}}, {datatype, miopenTensorNCHW, {64, 16, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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}
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 1, 32, 32}}, {datatype, miopenTensorNHWC, {1, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 1, 32, 32}}, {datatype, miopenTensorNHWC, {2, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 1, 32, 32}}, {datatype, miopenTensorNHWC, {4, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 1, 32, 32}}, {datatype, miopenTensorNHWC, {8, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 1, 32, 32}}, {datatype, miopenTensorNHWC, {16, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 16, 32, 32}}, {datatype, miopenTensorNHWC, {16, 1, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 16}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 16, 32, 32}}, {datatype, miopenTensorNHWC, {4, 4, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 4}});
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cases.emplace_back(TestCase{{datatype, miopenTensorNHWC, {64, 16, 32, 32}}, {datatype, miopenTensorNHWC, {8, 4, 3, 3}}, datatype, {{0, 0}, {1, 1}, {1, 1}, 4}});
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if(datatype != miopenInt8) // Filter is too big
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{
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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())));
|