/* ************************************************************************** * Copyright (C) 2020-2024 Advanced Micro Devices, Inc. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE * ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS * OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY * OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF * SUCH DAMAGE. * *************************************************************************/ #pragma once #include #include #include #include "clientcommon.hpp" #include "lapack_host_reference.hpp" /* Norm of error functions */ template double norm_error(char norm_type, rocblas_int M, rocblas_int N, rocblas_int lda_gold, T* gold, T* comp, rocblas_int lda_comp = 0) { using DoublePrecisionType = std::conditional_t, rocblas_double_complex, double>; // norm type can be 'O', 'I', 'F', 'o', 'i', 'f' for one, infinity or // Frobenius norm one norm is max column sum infinity norm is max row sum // Frobenius is l2 norm of matrix entries rocblas_int lda = M; if(lda_comp <= 0) lda_comp = lda_gold; std::vector gold_double(N * lda); std::vector comp_double(N * lda); for(rocblas_int j = 0; j < N; j++) { for(rocblas_int i = 0; i < M; i++) { gold_double[i + j * lda] = DoublePrecisionType(gold[i + j * lda_gold]); comp_double[i + j * lda] = DoublePrecisionType(comp[i + j * lda_comp]); } } std::vector work(M); rocblas_int incx = 1; DoublePrecisionType alpha = -1.0; rocblas_int size = lda * N; double gold_norm = cpu_lange(norm_type, M, N, gold_double.data(), lda, work.data()); cpu_axpy(size, alpha, gold_double.data(), incx, comp_double.data(), incx); double error = cpu_lange(norm_type, M, N, comp_double.data(), lda, work.data()); if(gold_norm > 0) error /= gold_norm; return error; } template double norm_error_upperTr(char norm_type, rocblas_int M, rocblas_int N, rocblas_int lda, T* gold, T* comp) { for(rocblas_int i = 0; i < M; ++i) { for(rocblas_int j = 0; j < N; ++j) { if(i > j) { gold[i + j * lda] = T(0); comp[i + j * lda] = T(0); } } } return norm_error(norm_type, M, N, lda, gold, comp); } template double norm_error_lowerTr(char norm_type, rocblas_int M, rocblas_int N, rocblas_int lda, T* gold, T* comp) { for(rocblas_int i = 0; i < M; ++i) { for(rocblas_int j = 0; j < N; ++j) { if(i < j) { gold[i + j * lda] = T(0); comp[i + j * lda] = T(0); } } } return norm_error(norm_type, M, N, lda, gold, comp); } template S snorm(char norm_type, rocblas_int m, rocblas_int n, T* A, rocblas_int lda) { return cpu_lange(norm_type, m, n, A, lda, (S*)nullptr); }