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Diffstat (limited to 'tests/validation/reference/YOLOLayer.cpp')
-rw-r--r-- | tests/validation/reference/YOLOLayer.cpp | 84 |
1 files changed, 0 insertions, 84 deletions
diff --git a/tests/validation/reference/YOLOLayer.cpp b/tests/validation/reference/YOLOLayer.cpp deleted file mode 100644 index fbc81f1af9..0000000000 --- a/tests/validation/reference/YOLOLayer.cpp +++ /dev/null @@ -1,84 +0,0 @@ -/* - * Copyright (c) 2018-2020 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 "YOLOLayer.h" - -#include "ActivationLayer.h" - -#include "arm_compute/core/Types.h" -#include "tests/validation/Helpers.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> yolo_layer(const SimpleTensor<T> &src, const ActivationLayerInfo &info, int32_t num_classes) -{ - // Create reference - SimpleTensor<T> dst{ src.shape(), src.data_type() }; - - // Compute reference - const T a(info.a()); - const T b(info.b()); - - const uint32_t num_elements = src.num_elements(); -#if defined(_OPENMP) - #pragma omp parallel for -#endif /* _OPENMP */ - for(uint32_t i = 0; i < num_elements; ++i) - { - const size_t z = index2coord(dst.shape(), i).z() % (num_classes + 5); - - if(z != 2 && z != 3) - { - dst[i] = activate_float<T>(src[i], a, b, info.activation()); - } - else - { - dst[i] = src[i]; - } - } - - return dst; -} - -template <> -SimpleTensor<uint8_t> yolo_layer<uint8_t>(const SimpleTensor<uint8_t> &src, const ActivationLayerInfo &info, int32_t num_classes) -{ - SimpleTensor<float> src_tmp = convert_from_asymmetric(src); - SimpleTensor<float> dst_tmp = yolo_layer<float>(src_tmp, info, num_classes); - SimpleTensor<uint8_t> dst = convert_to_asymmetric<uint8_t>(dst_tmp, src.quantization_info()); - return dst; -} - -template SimpleTensor<float> yolo_layer(const SimpleTensor<float> &src, const ActivationLayerInfo &info, int32_t num_classes); -template SimpleTensor<half> yolo_layer(const SimpleTensor<half> &src, const ActivationLayerInfo &info, int32_t num_classes); -} // namespace reference -} // namespace validation -} // namespace test -} // namespace arm_compute |