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Diffstat (limited to 'tests/validation/reference/GEMMLowp.cpp')
-rw-r--r-- | tests/validation/reference/GEMMLowp.cpp | 208 |
1 files changed, 208 insertions, 0 deletions
diff --git a/tests/validation/reference/GEMMLowp.cpp b/tests/validation/reference/GEMMLowp.cpp new file mode 100644 index 0000000000..8e41aef46a --- /dev/null +++ b/tests/validation/reference/GEMMLowp.cpp @@ -0,0 +1,208 @@ +/* + * 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 |