| /* |
| * Copyright (c) 2017-2018 ARM Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * 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 "GEMM.h" |
| |
| #include "arm_compute/core/Types.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace reference |
| { |
| template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type> |
| SimpleTensor<T> gemm(const SimpleTensor<T> &a, const SimpleTensor<T> &b, const SimpleTensor<T> &c, float alpha, float beta) |
| { |
| // Create reference |
| SimpleTensor<T> dst{ c.shape(), c.data_type(), 1 }; |
| |
| // Compute reference |
| const int M = a.shape().y(); |
| const int N = b.shape().x(); |
| const int K = a.shape().x(); |
| const int D = a.shape().z(); // Number of matrices in a batch |
| const int W = a.shape()[3]; // Number of batched-gemm (Winograd case) |
| |
| const int a_stride_z = K * M; |
| const int a_stride_w = K * M * D; |
| |
| const int b_stride_z = b.shape().num_dimensions() > 2 ? N * K : 0; // Do not slide the matrix B along the 3th dimension in case matrix B has less than 3 dimensions |
| const int b_stride_w = b.shape().num_dimensions() > 3 ? K * N * D : 0; // Do not slide the matrix B along the 4th dimension in case matrix B has less than 4 dimensions |
| |
| const int c_stride_z = N * M; |
| const int c_stride_w = N * M * D; |
| |
| for(int w = 0; w < W; ++w) |
| { |
| for(int depth = 0; depth < D; ++depth) |
| { |
| const int base_addr_a = depth * a_stride_z + w * a_stride_w; |
| const int base_addr_b = depth * b_stride_z + w * b_stride_w; |
| const int base_addr_c = depth * c_stride_z + w * c_stride_w; |
| |
| for(int row = 0; row < M; ++row) |
| { |
| for(int col = 0; col < N; ++col) |
| { |
| T acc(0); |
| |
| for(int k = 0; k < K; ++k) |
| { |
| acc += a[base_addr_a + k + row * K] * b[base_addr_b + col + k * N]; |
| } |
| |
| // Finalize the result: alpha * A * B + beta * C |
| dst[base_addr_c + col + row * N] = alpha * acc + beta * c[base_addr_c + col + row * N]; |
| } |
| } |
| } |
| } |
| |
| return dst; |
| } |
| |
| template SimpleTensor<float> gemm(const SimpleTensor<float> &a, const SimpleTensor<float> &b, const SimpleTensor<float> &c, float alpha, float beta); |
| template SimpleTensor<half> gemm(const SimpleTensor<half> &a, const SimpleTensor<half> &b, const SimpleTensor<half> &c, float alpha, float beta); |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |