135 lines
5.2 KiB
C++
135 lines
5.2 KiB
C++
/*
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* Copyright (c) 2017-2020 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#include "SoftmaxLayer.h"
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#include "arm_compute/core/Helpers.h"
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#include "arm_compute/core/Types.h"
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#include "utils/TypePrinter.h"
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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namespace reference
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{
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template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type>
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SimpleTensor<T> softmax_layer_generic(const SimpleTensor<T> &src, float beta, int32_t axis, bool is_log)
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{
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// Create reference
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SimpleTensor<T> dst{ src.shape(), src.data_type(), 1 };
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const int32_t n_dims = static_cast<int32_t>(src.shape().num_dimensions());
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ARM_COMPUTE_ERROR_ON(axis < -n_dims || axis >= n_dims);
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const unsigned int actual_axis = static_cast<unsigned int>(wrap_around(axis, n_dims));
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Window window;
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window.use_tensor_dimensions(src.shape());
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const unsigned int axis_dimension = src.shape()[actual_axis];
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window.set(actual_axis, Window::Dimension(0, 1, 1));
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execute_window_loop(window, [&](const Coordinates & id)
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{
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// Find max along axis
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Coordinates offset(id);
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offset.set(actual_axis, 0);
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T max = *reinterpret_cast<const T *>(src(offset));
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for(unsigned int axis_id = 1; axis_id < axis_dimension; ++axis_id)
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{
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offset.set(actual_axis, axis_id);
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const T val = *reinterpret_cast<const T *>(src(offset));
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if(val > max)
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{
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max = val;
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}
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}
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// Regularize
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T sum(0.f);
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for(unsigned int axis_id = 0; axis_id < axis_dimension; ++axis_id)
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{
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offset.set(actual_axis, axis_id);
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const T val = *reinterpret_cast<const T *>(src(offset));
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T res{ (val - max) *beta };
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if(is_log)
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{
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sum += std::exp(res);
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}
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else
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{
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res = std::exp(res);
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sum += res;
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}
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*reinterpret_cast<T *>(dst(offset)) = res;
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}
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// Normalize
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for(unsigned int axis_id = 0; axis_id < axis_dimension; ++axis_id)
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{
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offset.set(actual_axis, axis_id);
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const T val = *reinterpret_cast<const T *>(dst(offset));
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if(is_log)
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{
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*reinterpret_cast<T *>(dst(offset)) = val - static_cast<T>(std::log(sum));
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}
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else
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{
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*reinterpret_cast<T *>(dst(offset)) = val / sum;
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}
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}
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});
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return dst;
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}
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template SimpleTensor<float> softmax_layer_generic(const SimpleTensor<float> &src, float beta, int32_t axis, bool is_log);
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template SimpleTensor<half> softmax_layer_generic(const SimpleTensor<half> &src, float beta, int32_t axis, bool is_log);
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template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type>
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SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis, bool is_log)
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{
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return softmax_layer_generic<T>(src, beta, axis, is_log);
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}
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template < typename T, typename std::enable_if < std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value, int >::type >
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SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis, bool is_log)
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{
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const QuantizationInfo output_quantization_info = arm_compute::get_softmax_output_quantization_info(src.data_type(), is_log);
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SimpleTensor<float> src_tmp = convert_from_asymmetric(src);
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SimpleTensor<float> dst_tmp = softmax_layer<float>(src_tmp, beta, axis, is_log);
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SimpleTensor<T> dst = convert_to_asymmetric<T>(dst_tmp, output_quantization_info);
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return dst;
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}
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template SimpleTensor<float> softmax_layer(const SimpleTensor<float> &src, float beta, int32_t axis, bool is_log);
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template SimpleTensor<half> softmax_layer(const SimpleTensor<half> &src, float beta, int32_t axis, bool is_log);
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template SimpleTensor<uint8_t> softmax_layer(const SimpleTensor<uint8_t> &src, float beta, int32_t axis, bool is_log);
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template SimpleTensor<int8_t> softmax_layer(const SimpleTensor<int8_t> &src, float beta, int32_t axis, bool is_log);
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} // namespace reference
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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