104 lines
3.6 KiB
C++
104 lines
3.6 KiB
C++
/*
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* Copyright (c) 2017-2019 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 "L2NormalizeLayer.h"
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#include "ReductionOperation.h"
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#include "tests/validation/Helpers.h"
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#include <algorithm>
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#include <cmath>
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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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namespace
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{
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TensorShape get_output_shape(TensorShape shape, unsigned int axis)
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{
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TensorShape output_shape(shape);
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output_shape.set(axis, 1);
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return output_shape;
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}
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} // namespace
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template <typename T>
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SimpleTensor<T> l2_normalize(const SimpleTensor<T> &src, unsigned int axis, float epsilon)
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{
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// Create reference
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SimpleTensor<T> dst{ src.shape(), src.data_type() };
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// Reduce across given axis
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SimpleTensor<T> sum = reduction_operation<T, T>(src, get_output_shape(src.shape(), axis), axis, ReductionOperation::SUM_SQUARE);
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// Compute reference
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const int upper_dims = src.shape().total_size_upper(axis + 1);
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const int lower_dims = src.shape().total_size_lower(axis + 1);
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const int lower_dims_sum = sum.shape().total_size_lower(axis + 1);
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for(int du = 0; du < upper_dims; ++du)
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{
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const T *src_row_ptr = src.data() + du * lower_dims;
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T *dst_row_ptr = dst.data() + du * lower_dims;
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switch(axis)
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{
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case 0:
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{
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const int elems = src.shape()[0];
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const T normalization_value = sqrt(std::max(sum[du], static_cast<T>(epsilon)));
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std::transform(src_row_ptr, src_row_ptr + elems, dst_row_ptr, [normalization_value](T val)
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{
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return val / normalization_value;
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});
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}
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break;
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case 1:
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case 2:
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{
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for(int ld = 0; ld < lower_dims; ++ld)
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{
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const T normalization_value = sqrt(std::max(sum[ld % lower_dims_sum + du * lower_dims_sum], static_cast<T>(epsilon)));
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dst_row_ptr[ld] = src_row_ptr[ld] / normalization_value;
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}
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}
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break;
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default:
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ARM_COMPUTE_ERROR("Axis not supported");
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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> l2_normalize(const SimpleTensor<float> &src, unsigned int axis, float epsilon);
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template SimpleTensor<half> l2_normalize(const SimpleTensor<half> &src, unsigned int axis, float epsilon);
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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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