/* ************************************************************************ * Copyright (C) 2020-2025 Advanced Micro Devices, Inc. All rights reserved. * * 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 cop- * ies 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 IM- * PLIED, 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 CONNE- * CTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. * * * ************************************************************************ */ #include "testing_gesvdj.hpp" using ::testing::Combine; using ::testing::TestWithParam; using ::testing::Values; using ::testing::ValuesIn; using namespace std; typedef std::tuple, vector> gesvdj_tuple; // each size_range vector is a {m, n, fa}; // if fa = 0 then no fast algorithm is allowed // if fa = 1 fast algorithm is used when possible // each opt_range vector is a {lda, ldu, ldv, jobz, econ}; // if ldx = -1 then ldx < limit (invalid size) // if ldx = 0 then ldx = limit // if ldx = 1 then ldx > limit // if jobz = 0 then no singular vectors are computed // if jobz = 1 then compute singular vectors // case when m = 1, n = 1, jobz = 3, and econ = 0 will also execute the bad // arguments test (null handle, null pointers and invalid values) // for checkin_lapack tests const vector> size_range = { // normal (valid) samples {1, 1, 0}, {20, 20, 0}, {30, 30, 0}, {32, 30, 0}, {4, 32, 0}, {32, 4, 0}, }; const vector> opt_range = { // normal (valid) samples {1, 1, 1, 0, 0}, {0, 0, 1, 0, 0}, {0, 1, 0, 0, 0}, {1, 0, 0, 1, 1}, {1, 0, 1, 1, 0}, {1, 1, 0, 1, 0}, {0, 0, 0, 1, 1}, }; // // for daily_lapack tests // const vector> large_size_range = {{120, 100, 0}, {300, 120, 0}}; // const vector> large_opt_range = {{0, 0, 0, 0, 0}, // {0, 0, 1, 1, 1}, // {0, 1, 0, 1, 0}, // {1, 0, 0, 0, 0}}; template Arguments gesvdj_setup_arguments(gesvdj_tuple tup, bool STRIDED) { vector size = std::get<0>(tup); vector opt = std::get<1>(tup); Arguments arg; // sizes rocblas_int m = size[0]; rocblas_int n = size[1]; arg.set("m", m); arg.set("n", n); // leading dimensions arg.set("lda", m + opt[0] * 10); arg.set("ldu", m + opt[1] * 10); arg.set("ldv", n + opt[2] * 10); // vector options if(opt[3] == 0) arg.set("jobz", 'N'); else arg.set("jobz", 'V'); if(!STRIDED) arg.set("econ", opt[4]); arg.set("tolerance", 2 * get_epsilon()); arg.set("max_sweeps", 100); arg.set("sort_eig", 1); // only testing standard use case/defaults for strides arg.timing = 0; return arg; } template class GESVDJ_BASE : public ::TestWithParam { protected: void TearDown() override { ASSERT_EQ(hipGetLastError(), hipSuccess); } template void run_tests() { Arguments arg = gesvdj_setup_arguments(GetParam(), STRIDED); if(arg.peek("m") == 1 && arg.peek("n") == 1 && arg.peek("jobz") == 'N' && (STRIDED || arg.peek("econ") == 0)) testing_gesvdj_bad_arg(); arg.batch_count = (BATCHED || STRIDED ? 3 : 1); testing_gesvdj(arg); } }; class GESVDJ : public GESVDJ_BASE { }; class GESVDJ_FORTRAN : public GESVDJ_BASE { }; class GESVDJ_COMPAT : public GESVDJ_BASE { }; // non-batch tests TEST_P(GESVDJ, __float) { run_tests(); } TEST_P(GESVDJ, __double) { run_tests(); } TEST_P(GESVDJ, __float_complex) { run_tests(); } TEST_P(GESVDJ, __double_complex) { run_tests(); } TEST_P(GESVDJ_FORTRAN, __float) { run_tests(); } TEST_P(GESVDJ_FORTRAN, __double) { run_tests(); } TEST_P(GESVDJ_FORTRAN, __float_complex) { run_tests(); } TEST_P(GESVDJ_FORTRAN, __double_complex) { run_tests(); } TEST_P(GESVDJ_COMPAT, __float) { run_tests(); } TEST_P(GESVDJ_COMPAT, __double) { run_tests(); } TEST_P(GESVDJ_COMPAT, __float_complex) { run_tests(); } TEST_P(GESVDJ_COMPAT, __double_complex) { run_tests(); } // strided_batched tests TEST_P(GESVDJ, strided_batched__float) { run_tests(); } TEST_P(GESVDJ, strided_batched__double) { run_tests(); } TEST_P(GESVDJ, strided_batched__float_complex) { run_tests(); } TEST_P(GESVDJ, strided_batched__double_complex) { run_tests(); } TEST_P(GESVDJ_FORTRAN, strided_batched__float) { run_tests(); } TEST_P(GESVDJ_FORTRAN, strided_batched__double) { run_tests(); } TEST_P(GESVDJ_FORTRAN, strided_batched__float_complex) { run_tests(); } TEST_P(GESVDJ_FORTRAN, strided_batched__double_complex) { run_tests(); } TEST_P(GESVDJ_COMPAT, strided_batched__float) { run_tests(); } TEST_P(GESVDJ_COMPAT, strided_batched__double) { run_tests(); } TEST_P(GESVDJ_COMPAT, strided_batched__float_complex) { run_tests(); } TEST_P(GESVDJ_COMPAT, strided_batched__double_complex) { run_tests(); } // INSTANTIATE_TEST_SUITE_P(daily_lapack, // GESVDJ, // Combine(ValuesIn(large_size_range), ValuesIn(large_opt_range))); INSTANTIATE_TEST_SUITE_P(checkin_lapack, GESVDJ, Combine(ValuesIn(size_range), ValuesIn(opt_range))); // INSTANTIATE_TEST_SUITE_P(daily_lapack, // GESVDJ_FORTRAN, // Combine(ValuesIn(large_size_range), ValuesIn(large_opt_range))); INSTANTIATE_TEST_SUITE_P(checkin_lapack, GESVDJ_FORTRAN, Combine(ValuesIn(size_range), ValuesIn(opt_range))); // INSTANTIATE_TEST_SUITE_P(daily_lapack, // GESVDJ_COMPAT, // Combine(ValuesIn(large_size_range), ValuesIn(large_opt_range))); INSTANTIATE_TEST_SUITE_P(checkin_lapack, GESVDJ_COMPAT, Combine(ValuesIn(size_range), ValuesIn(opt_range)));