| /* |
| * 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" |
| #include "tests/validation/reference/UtilsQuantizedAsymm.h" |
| |
| #include <limits> |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace reference |
| { |
| namespace |
| { |
| template <typename T> |
| void quantize_down_int32_to_uint8_scale(const SimpleTensor<T> *in, const SimpleTensor<T> *bias, SimpleTensor<uint8_t> *dst, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, |
| int32_t min, int32_t max) |
| { |
| const int cols_in = in->shape().x(); |
| |
| for(int i = 0; i < in->num_elements(); ++i) |
| { |
| int32_t result = ((*in)[i] + result_offset); |
| |
| if(bias != nullptr) |
| { |
| result += (*bias)[i % cols_in]; |
| } |
| |
| result *= result_mult_int; |
| |
| result >>= result_shift; |
| |
| // Bounded ReLu |
| if(min != max) |
| { |
| result = std::max(min, std::min(max, result)); |
| } |
| |
| (*dst)[i] = static_cast<uint8_t>(std::max(0, std::min(255, result))); |
| } |
| } |
| |
| template <typename T> |
| void quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> *in, const SimpleTensor<T> *bias, SimpleTensor<uint8_t> *dst, int32_t result_fixedpoint_multiplier, int32_t result_shift, |
| int32_t result_offset_after_shift, int32_t min, int32_t max) |
| { |
| const int cols_in = in->shape().x(); |
| |
| for(int i = 0; i < in->num_elements(); ++i) |
| { |
| int32_t result = (*in)[i]; |
| |
| if(bias != nullptr) |
| { |
| result += (*bias)[i % cols_in]; |
| } |
| |
| // Fixed point multiplication |
| result = asymm_rounding_divide_by_pow2(asymm_int_mult(result, result_fixedpoint_multiplier), result_shift); |
| result += result_offset_after_shift; |
| |
| // Bounded ReLu |
| if(min != max) |
| { |
| result = std::max(min, std::min(max, result)); |
| } |
| |
| (*dst)[i] = static_cast<uint8_t>(std::max(0, std::min(255, result))); |
| } |
| } |
| } // namespace |
| |
| template <typename T_out, typename T_in> |
| SimpleTensor<T_out> gemmlowp_matrix_multiply_core(const SimpleTensor<T_in> &a, const SimpleTensor<T_in> &b, int32_t a_offset, int32_t b_offset) |
| { |
| static_assert(std::is_same<typename std::decay<T_out>::type, int32_t>::value, "Only int32_t is allowed for the output"); |
| |
| TensorShape shape(b.shape()[0], a.shape()[1]); |
| DataType dt = std::is_same<T_out, int32_t>::value ? DataType::S32 : DataType::U32; |
| SimpleTensor<T_out> c(shape, dt); |
| |
| 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<T_out> 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 T_out tmp_a = a_offset + static_cast<T_out>(a[k + i * K]); |
| for(int j = 0; j < b_width; ++j) |
| { |
| const T_out tmp_b = b_offset + static_cast<T_out>(b[j + k * b_width]); |
| const T_out 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 |
| template <typename T1, typename T2> |
| SimpleTensor<T1> gemmlowp(const SimpleTensor<T2> &a, const SimpleTensor<T2> &b) |
| { |
| return gemmlowp_matrix_multiply_core<T1, T2>(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, int32_t min, int32_t max) |
| { |
| SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8); |
| |
| quantize_down_int32_to_uint8_scale<T>(&in, nullptr, &dst, result_offset, result_mult_int, result_shift, min, max); |
| |
| return dst; |
| } |
| |
| template <typename T> |
| SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_offset, int32_t result_mult_int, int32_t result_shift, |
| int32_t min, int32_t max) |
| { |
| SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8); |
| |
| quantize_down_int32_to_uint8_scale<T>(&in, &bias, &dst, result_offset, result_mult_int, result_shift, min, max); |
| |
| return dst; |
| } |
| |
| template <typename T> |
| SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, int32_t result_fixedpoint_multiplier, int32_t result_shift, |
| int32_t result_offset_after_shift, int32_t min, |
| int32_t max) |
| { |
| SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8); |
| |
| quantize_down_int32_to_uint8_scale_by_fixedpoint<T>(&in, nullptr, &dst, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max); |
| |
| return dst; |
| } |
| |
| template <typename T> |
| SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_fixedpoint_multiplier, int32_t result_shift, |
| int32_t result_offset_after_shift, int32_t min, int32_t max) |
| { |
| SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8); |
| |
| quantize_down_int32_to_uint8_scale_by_fixedpoint<T>(&in, &bias, &dst, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max); |
| |
| return dst; |
| } |
| |
| template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, int32_t result_fixedpoint_multiplier, int32_t result_shift, |
| int32_t result_offset_after_shift, int32_t min, int32_t max); |
| template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, int32_t result_fixedpoint_multiplier, |
| int32_t result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max); |
| 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, int32_t min, |
| int32_t max); |
| template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, int32_t result_offset, int32_t result_mult_int, |
| int32_t result_shift, int32_t min, int32_t max); |
| template SimpleTensor<int32_t> gemmlowp_matrix_multiply_core(const SimpleTensor<int8_t> &a, const SimpleTensor<int8_t> &b, int32_t a_offset, int32_t b_offset); |
| 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<int32_t> gemmlowp(const SimpleTensor<int8_t> &a, const SimpleTensor<int8_t> &b); |
| template SimpleTensor<int32_t> gemmlowp(const SimpleTensor<uint8_t> &a, const SimpleTensor<uint8_t> &b); |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |