| /* |
| * Copyright (c) 2024 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 "ScatterLayer.h" |
| #include "tests/validation/Helpers.h" |
| #include "arm_compute/core/TensorShape.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace reference |
| { |
| namespace |
| { |
| |
| template <typename T> |
| T reduce_op(const T ¤t,const T &update,const ScatterFunction func) |
| { |
| switch(func) |
| { |
| case ScatterFunction::Update: |
| return update; |
| break; |
| case ScatterFunction::Add: |
| return current + update; |
| break; |
| case ScatterFunction::Sub: |
| return current - update; |
| break; |
| case ScatterFunction::Max: |
| return std::max(current, update); |
| break; |
| case ScatterFunction::Min: |
| return std::min(current, update); |
| break; |
| default: |
| ARM_COMPUTE_ERROR("Unsupported Scatter function"); |
| break; |
| } |
| } |
| |
| template float reduce_op(const float ¤t,const float &update,const ScatterFunction func); |
| } |
| |
| // NOTE: This function expects collapsed tensors as input. |
| // Batch dims for update/indices tensors should be collapsed into a single dim. |
| // Data dims should be collapsed into a single dim for both update and src tensors prior to calling this function. |
| template <typename T> |
| SimpleTensor<T> scatter_layer_internal(const SimpleTensor<T> &src, const SimpleTensor<T> &updates, const SimpleTensor<int32_t> &indices, const TensorShape &out_shape, const ScatterInfo &info) |
| { |
| // 1. If zero initialization variable is false, copy src data to dst. |
| SimpleTensor<T> dst{ out_shape, src.data_type(), 1 }; |
| if(!info.zero_initialization) |
| { |
| std::copy_n(src.data(), src.num_elements(), dst.data()); |
| } |
| |
| // Number of elements between each value of the dim being iterated through |
| const unsigned int data_stride = updates.shape().total_size_lower(updates.shape().num_dimensions() - 1); |
| const unsigned int no_output_dims = out_shape.num_dimensions(); |
| |
| // Calculate output stride at given index for all output dims. |
| std::vector<unsigned int> out_stride_at_idx(no_output_dims); |
| for (unsigned int i = 0 ; i < no_output_dims; i++) |
| { |
| out_stride_at_idx[i] = out_shape.total_size_lower(i); |
| } |
| |
| const unsigned int indices_x_dim = static_cast<unsigned int>(indices.shape()[0]); |
| const unsigned int indices_y_dim = static_cast<unsigned int>(indices.shape()[1]); |
| |
| // 2. Iterate over indices tensor y-dim and replace sections of dst tensor with relevant areas of update tensor. |
| for(unsigned int i = 0; i < indices_y_dim; i++) |
| { |
| // NOTE : Currently, indices.shape() == [X, Y, 1, 1], where X is the indices dim and Y is the batch dim |
| // Starting index for both the update and indices tensors. |
| const unsigned int update_dim_start = i * data_stride; |
| const unsigned int indices_dim_start = i * indices_x_dim; |
| bool out_of_bounds = false; |
| unsigned int out_offset_acc = 0; |
| |
| // Iterate over each indices value for the relevant batch and accumulate the offset. |
| for(unsigned int j = 0; j < indices_x_dim; j++) |
| { |
| // Get first index value with i * indices_x_dim (iterating through y-dim/batch idx), then iterate through x dim by adding k |
| const int index_value = indices[indices_dim_start + j]; |
| const unsigned int out_dim = no_output_dims - (j+1); // Calculate corresponding output dim to current index value. |
| if(index_value < static_cast<int>(out_shape[out_dim]) && index_value >= 0) |
| { |
| out_offset_acc += (index_value * out_stride_at_idx[out_dim]); // offset accumulation |
| } |
| else |
| { |
| out_of_bounds = true; |
| break; |
| } |
| } |
| |
| // If not out of bounds, copy update tensor elements to output |
| if(!out_of_bounds) |
| { |
| for (unsigned int j = 0 ; j < data_stride; j++) |
| { |
| dst[out_offset_acc + j] = reduce_op(dst[out_offset_acc + j], updates[update_dim_start + j], info.func); |
| } |
| } |
| } |
| return dst; |
| } |
| |
| template <typename T> |
| SimpleTensor<T> scatter_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &updates, const SimpleTensor<int32_t> &indices, const TensorShape &out_shape, const ScatterInfo &info) |
| { |
| return scatter_layer_internal<T>(src, updates, indices, out_shape, info); |
| } |
| |
| template SimpleTensor<float> scatter_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &updates, const SimpleTensor<int32_t> &indices, const TensorShape &out_shape, const ScatterInfo &info); |
| |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |