| /* |
| * Copyright (c) 2019 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 "ConcatenateLayer.h" |
| |
| #include "tests/validation/Helpers.h" |
| #include "tests/validation/reference/Permute.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace reference |
| { |
| namespace |
| { |
| template <typename T> |
| SimpleTensor<T> widthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst) |
| { |
| // Create reference |
| std::vector<TensorShape> shapes; |
| shapes.reserve(srcs.size()); |
| for(const auto &src : srcs) |
| { |
| shapes.emplace_back(src.shape()); |
| } |
| // Compute reference |
| int width_offset = 0; |
| const int width_out = dst.shape().x(); |
| // Set output tensor to 0 |
| std::fill_n(dst.data(), dst.num_elements(), 0); |
| for(const auto &src : srcs) |
| { |
| ARM_COMPUTE_ERROR_ON(width_offset >= width_out); |
| |
| const int width = src.shape().x(); |
| const int height = src.shape().y(); |
| const int depth = src.shape().z(); |
| const int upper_dims = src.shape().total_size() / (width * height * depth); |
| |
| const T *src_ptr = src.data(); |
| T *dst_ptr = dst.data(); |
| |
| for(int u = 0; u < upper_dims; ++u) |
| { |
| for(int d = 0; d < depth; ++d) |
| { |
| for(int r = 0; r < height; ++r) |
| { |
| const int offset = u * height * depth + d * height + r; |
| if(is_data_type_quantized(src.data_type()) && src.quantization_info() != dst.quantization_info()) |
| { |
| const UniformQuantizationInfo iq_info = src.quantization_info().uniform(); |
| const UniformQuantizationInfo oq_info = dst.quantization_info().uniform(); |
| |
| if(src.data_type() == DataType::QASYMM8) |
| { |
| std::transform(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out, [&](T t) |
| { |
| const float dequantized_input = dequantize_qasymm8(t, iq_info); |
| return quantize_qasymm8(dequantized_input, oq_info); |
| }); |
| } |
| else |
| { |
| std::transform(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out, [&](T t) |
| { |
| const float dequantized_input = dequantize_qasymm8_signed(t, iq_info); |
| return quantize_qasymm8_signed(dequantized_input, oq_info); |
| }); |
| } |
| src_ptr += width; |
| } |
| else |
| { |
| std::copy(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out); |
| src_ptr += width; |
| } |
| } |
| } |
| } |
| width_offset += width; |
| } |
| return dst; |
| } |
| |
| template SimpleTensor<float> widthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs, SimpleTensor<float> &dst); |
| template SimpleTensor<half> widthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs, SimpleTensor<half> &dst); |
| template SimpleTensor<uint8_t> widthconcatenate_layer(const std::vector<SimpleTensor<uint8_t>> &srcs, SimpleTensor<uint8_t> &dst); |
| template SimpleTensor<int8_t> widthconcatenate_layer(const std::vector<SimpleTensor<int8_t>> &srcs, SimpleTensor<int8_t> &dst); |
| } // namespace |
| |
| template <typename T> |
| SimpleTensor<T> concatenate_layer(std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst, unsigned int axis) |
| { |
| switch(axis) |
| { |
| case Window::DimX: |
| { |
| return widthconcatenate_layer(srcs, dst); |
| } |
| case Window::DimY: |
| { |
| for(auto &t : srcs) |
| { |
| t = reference::permute<T>(t, PermutationVector(1U, 0U)); |
| } |
| dst = reference::permute<T>(dst, PermutationVector(1U, 0U)); |
| return reference::permute<T>(widthconcatenate_layer(srcs, dst), PermutationVector(1U, 0U)); |
| } |
| case Window::DimZ: |
| { |
| for(auto &t : srcs) |
| { |
| t = reference::permute<T>(t, PermutationVector(2U, 1U, 0U)); |
| } |
| dst = reference::permute<T>(dst, PermutationVector(2U, 1U, 0U)); |
| return reference::permute<T>(widthconcatenate_layer(srcs, dst), PermutationVector(2U, 1U, 0U)); |
| } |
| case 3: |
| { |
| for(auto &t : srcs) |
| { |
| t = reference::permute<T>(t, PermutationVector(3U, 2U, 1U, 0U)); |
| } |
| dst = reference::permute<T>(dst, PermutationVector(3U, 2U, 1U, 0U)); |
| auto ret = reference::permute<T>(widthconcatenate_layer(srcs, dst), PermutationVector(3U, 2U, 1U, 0U)); |
| return ret; |
| } |
| default: |
| { |
| ARM_COMPUTE_ERROR("Not supported"); |
| return dst; |
| } |
| } |
| } |
| |
| template SimpleTensor<float> concatenate_layer(std::vector<SimpleTensor<float>> &srcs, SimpleTensor<float> &dst, unsigned int axis); |
| template SimpleTensor<half> concatenate_layer(std::vector<SimpleTensor<half>> &srcs, SimpleTensor<half> &dst, unsigned int axis); |
| template SimpleTensor<uint8_t> concatenate_layer(std::vector<SimpleTensor<uint8_t>> &srcs, SimpleTensor<uint8_t> &dst, unsigned int axis); |
| template SimpleTensor<int8_t> concatenate_layer(std::vector<SimpleTensor<int8_t>> &srcs, SimpleTensor<int8_t> &dst, unsigned int axis); |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |