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Diffstat (limited to 'tests/validation/CPP/GEMMLowp.cpp')
| -rw-r--r-- | tests/validation/CPP/GEMMLowp.cpp | 208 |
1 files changed, 0 insertions, 208 deletions
diff --git a/tests/validation/CPP/GEMMLowp.cpp b/tests/validation/CPP/GEMMLowp.cpp deleted file mode 100644 index 92878947c8..0000000000 --- a/tests/validation/CPP/GEMMLowp.cpp +++ /dev/null @@ -1,208 +0,0 @@ -/* - * 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/CPP/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 |