| // RUN: %clang++ -mllvm -force-vector-width=1 -ffast-math -fno-unroll-loops -fno-vectorize -fno-slp-vectorize -fno-exceptions -O3 %s -S -emit-llvm -o - | %opt - %loadEnzyme -enzyme -S | %lli - |
| // RUN: %clang++ -fno-unroll-loops -fno-vectorize -fno-slp-vectorize -fno-exceptions -O2 %s -S -emit-llvm -o - | %opt - %loadEnzyme -enzyme -S | %lli - |
| // RUN: %clang++ -fno-unroll-loops -fno-vectorize -fno-slp-vectorize -fno-exceptions -O1 %s -S -emit-llvm -o - | %opt - %loadEnzyme -enzyme -S | %lli - |
| // RUN: %clang++ -fno-unroll-loops -fno-vectorize -fno-slp-vectorize -fno-exceptions -O0 %s -S -emit-llvm -o - | %opt - %loadEnzyme -enzyme -S | %lli - |
| // RUN: %clang++ -fno-unroll-loops -fno-vectorize -fno-slp-vectorize -fno-exceptions -O3 %s -S -emit-llvm -o - | %opt - %loadEnzyme -enzyme -enzyme-inline=1 -S | %lli - |
| // RUN: %clang++ -fno-unroll-loops -fno-vectorize -fno-slp-vectorize -fno-exceptions -O2 %s -S -emit-llvm -o - | %opt - %loadEnzyme -enzyme -enzyme-inline=1 -S | %lli - |
| // RUN: %clang++ -fno-unroll-loops -fno-vectorize -fno-slp-vectorize -fno-exceptions -O1 %s -S -emit-llvm -o - | %opt - %loadEnzyme -enzyme -enzyme-inline=1 -S | %lli - |
| // RUN: %clang++ -fno-unroll-loops -fno-vectorize -fno-slp-vectorize -fno-exceptions -O0 %s -S -emit-llvm -o - | %opt - %loadEnzyme -enzyme -enzyme-inline=1 -S | %lli - |
| |
| #include <eigen3/Eigen/Dense> |
| #include "test_utils.h" |
| |
| using Eigen::MatrixXd; |
| |
| constexpr size_t IN = 2, OUT = 2, NUM = 2; |
| //constexpr size_t IN = 3, OUT = 7, NUM = 5; |
| |
| __attribute__((noinline)) |
| static void matvec(const Eigen::Matrix<double, IN, OUT> * __restrict W, const Eigen::Matrix<double, IN, OUT> * __restrict b, Eigen::Matrix<double, IN, OUT> * __restrict output) { |
| *output = *W + *b; |
| /* |
| for (int r = 0; r < W->rows(); r++) { |
| (*output)(r) = 0; |
| |
| for (int c = 0; c < W->cols(); c++) { |
| (*output)(r) += (*W)(r, c) * (*b)(c); |
| } |
| } |
| */ |
| } |
| |
| extern "C" { |
| double __enzyme_autodiff(void*, void*, void*, void*, void*, void*, void*); |
| } |
| |
| int main(int argc, char** argv) { |
| |
| Eigen::Matrix<double, IN, OUT> W = Eigen::Matrix<double, IN, OUT>::Constant(IN, OUT, 3.0); |
| Eigen::Matrix<double, IN, OUT> M = Eigen::Matrix<double, IN, OUT>::Constant(IN, OUT, 2.0); |
| Eigen::Matrix<double, IN, OUT> O = Eigen::Matrix<double, IN, OUT>::Constant(IN, OUT, 0.0); |
| |
| Eigen::Matrix<double, IN, OUT> Wp = Eigen::Matrix<double, IN, OUT>::Constant(IN, OUT, 0.0); |
| Eigen::Matrix<double, IN, OUT> Mp = Eigen::Matrix<double, IN, OUT>::Constant(IN, OUT, 0.0); |
| Eigen::Matrix<double, IN, OUT> Op = Eigen::Matrix<double, IN, OUT>::Constant(IN, OUT, 1.0); |
| Eigen::Matrix<double, IN, OUT> Op_orig = Op; |
| |
| __enzyme_autodiff((void*)matvec, &W, &Wp, &M, &Mp, &O, &Op); |
| |
| for(int o=0; o<OUT; o++) |
| for(int i=0; i<IN; i++) { |
| fprintf(stderr, "W(o=%d, i=%d)=%f\n", i, o, W(i, o)); |
| } |
| |
| for(int o=0; o<OUT; o++) { |
| fprintf(stderr, "M(o=%d)=%f\n", o, M(o)); |
| } |
| |
| for(int i=0; i<IN; i++) { |
| fprintf(stderr, "O(i=%d)=%f\n", i, O(i)); |
| } |
| |
| for(int o=0; o<OUT; o++) |
| for(int i=0; i<IN; i++) { |
| APPROX_EQ( Wp(i, o), 1.0 , 1e-10); |
| fprintf(stderr, "Wp(o=%d, i=%d)=%f\n", i, o, Wp(i, o)); |
| } |
| |
| for(int o=0; o<OUT; o++) { |
| double res = 0.0; |
| APPROX_EQ( Mp(o), 1.0, 1e-10); |
| fprintf(stderr, "Mp(o=%d)=%f\n", o, Mp(o)); |
| } |
| |
| for(int i=0; i<IN; i++) { |
| APPROX_EQ( Op(i), 0., 1e-10); |
| fprintf(stderr, "Op(i=%d)=%f\n", i, Op(i)); |
| } |
| //assert(0 && "false"); |
| } |