| /* |
| * Copyright (c) 2017-2018 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 "SoftmaxLayer.h" |
| |
| #include "arm_compute/core/Types.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> softmax_layer(const SimpleTensor<T> &src, float beta) |
| { |
| // Create reference |
| SimpleTensor<T> dst{ src.shape(), src.data_type(), 1 }; |
| |
| const bool is_4D_input = (src.shape().num_dimensions() > 2); |
| |
| // Compute reference. Lower dims are |
| // - the number of columns for the 2D case |
| // - the collapsing of the first three dimensions (i.e., the flattened dimension of each batch) in the 4D case |
| const int lower_dims = (is_4D_input ? src.shape()[2] * src.shape()[1] * src.shape()[0] : src.shape()[0]); |
| const int upper_dims = src.num_elements() / lower_dims; |
| |
| for(int r = 0; r < upper_dims; ++r) |
| { |
| const T *src_row_ptr = src.data() + r * lower_dims; |
| T *dst_row_ptr = dst.data() + r * lower_dims; |
| |
| // Find max |
| const T max = *std::max_element(src_row_ptr, src_row_ptr + lower_dims); |
| |
| // Regularize |
| T sum(0.f); |
| std::transform(src_row_ptr, src_row_ptr + lower_dims, dst_row_ptr, [&sum, max, beta](T val) |
| { |
| const T res(std::exp((val - max) * beta)); |
| sum += res; |
| return res; |
| }); |
| |
| // Normalize |
| std::transform(dst_row_ptr, dst_row_ptr + lower_dims, dst_row_ptr, [sum](T val) |
| { |
| return val / sum; |
| }); |
| } |
| |
| return dst; |
| } |
| |
| template <typename T, typename std::enable_if<std::is_same<T, uint8_t>::value, int>::type> |
| SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta) |
| { |
| // Note: Output quantization info should always have scale = 1/256 and offset = 0 |
| const QuantizationInfo output_quantization_info = QuantizationInfo(1.f / 256, 0); |
| |
| SimpleTensor<float> src_tmp = convert_from_asymmetric(src); |
| SimpleTensor<float> dst_tmp = softmax_layer<float>(src_tmp, beta); |
| SimpleTensor<T> dst = convert_to_asymmetric(dst_tmp, output_quantization_info); |
| return dst; |
| } |
| |
| template SimpleTensor<float> softmax_layer(const SimpleTensor<float> &src, float beta); |
| template SimpleTensor<half> softmax_layer(const SimpleTensor<half> &src, float beta); |
| template SimpleTensor<uint8_t> softmax_layer(const SimpleTensor<uint8_t> &src, float beta); |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |