| /* |
| * Copyright (c) 2017 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 "GEMMLowp.h" |
| |
| #include "arm_compute/core/Types.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace reference |
| { |
| template <typename T> |
| SimpleTensor<int32_t> gemmlowp_matrix_multiply_core(const SimpleTensor<T> &a, const SimpleTensor<T> &b, int32_t a_offset, int32_t b_offset) |
| { |
| TensorShape shape(b.shape()[0], a.shape()[1]); |
| |
| SimpleTensor<int32_t> c(shape, DataType::S32); |
| |
| const int K = a.shape().x(); |
| const int b_width = b.shape().x(); |
| const int rows = c.shape().y(); //M |
| const int cols = c.shape().x(); //N |
| |
| std::vector<int32_t> acc; |
| acc.resize(cols); |
| |
| for(int i = 0; i < rows; ++i) |
| { |
| for(int j = 0; j < cols; ++j) |
| { |
| acc[j] = 0; |
| } |
| for(int k = 0; k < K; ++k) |
| { |
| const int32_t tmp_a = a_offset + static_cast<int32_t>(a[k + i * K]); |
| for(int j = 0; j < b_width; ++j) |
| { |
| const int32_t tmp_b = b_offset + static_cast<int32_t>(b[j + k * b_width]); |
| const int32_t mult_as_int = tmp_a * tmp_b; |
| acc[j] += mult_as_int; |
| } |
| } |
| for(int j = 0; j < cols; ++j) |
| { |
| c[j + i * cols] = acc[j]; |
| } |
| } |
| |
| return c; |
| } |
| |
| // used to validate assembly kernels which don't know anything about offsets |
| SimpleTensor<int32_t> gemmlowp(const SimpleTensor<int8_t> &a, const SimpleTensor<int8_t> &b) |
| { |
| return gemmlowp_matrix_multiply_core(a, b, 0, 0); |
| } |
| |
| template <typename T> |
| SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, int32_t result_offset, int32_t result_mult_int, int32_t result_shift) |
| { |
| SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8); |
| |
| for(int i = 0; i < in.num_elements(); ++i) |
| { |
| const int32_t result = ((in[i] + result_offset) * result_mult_int) >> result_shift; |
| dst[i] = static_cast<uint8_t>(std::max(0, std::min(255, result))); |
| } |
| |
| return dst; |
| } |
| |
| template SimpleTensor<int32_t> gemmlowp_matrix_multiply_core(const SimpleTensor<uint8_t> &a, const SimpleTensor<uint8_t> &b, int32_t a_offset, int32_t b_offset); |
| template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<int32_t> &a, int32_t result_offset, int32_t result_mult_int, int32_t result_shift); |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |