Function l2_normalize

tests/validation/reference/L2NormalizeLayer.cpp:51–96

template <typename T>
SimpleTensor<T> l2_normalize(const SimpleTensor<T> &src, unsigned int axis, float epsilon)
{
    // Create reference
    SimpleTensor<T> dst{src.shape(), src.data_type()};

    // Reduce across given axis
    SimpleTensor<T> sum =
        reduction_operation<T, T>(src, get_output_shape(src.shape(), axis), axis, ReductionOperation::SUM_SQUARE);

    // Compute reference
    const int upper_dims     = src.shape().total_size_upper(axis + 1);
    const int lower_dims     = src.shape().total_size_lower(axis + 1);
    const int lower_dims_sum = sum.shape().total_size_lower(axis + 1);

    for (int du = 0; du < upper_dims; ++du)
    {
        const T *src_row_ptr = src.data() + du * lower_dims;
        T       *dst_row_ptr = dst.data() + du * lower_dims;
        switch (axis)
        {
            case 0:
            {
                const int elems               = src.shape()[0];
                const T   normalization_value = sqrt(std::max(sum[du], static_cast<T>(epsilon)));
                std::transform(src_row_ptr, src_row_ptr + elems, dst_row_ptr,
                               [normalization_value](T val) { return val / normalization_value; });
            }
            break;
            case 1:
            case 2:
            {
                for (int ld = 0; ld < lower_dims; ++ld)
                {
                    const T normalization_value =
                        sqrt(std::max(sum[ld % lower_dims_sum + du * lower_dims_sum], static_cast<T>(epsilon)));
                    dst_row_ptr[ld] = src_row_ptr[ld] / normalization_value;
                }
            }
            break;
            default:
                ARM_COMPUTE_ERROR("Axis not supported");
        }
    }

    return dst;
}

template SimpleTensor<float> l2_normalize(const SimpleTensor<float> &src, unsigned int axis, float epsilon);
template SimpleTensor<half>  l2_normalize(const SimpleTensor<half> &src, unsigned int axis, float epsilon);