| /* |
| * Copyright (c) 2018-2019, 2023 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. |
| */ |
| #ifndef ARM_COMPUTE_TEST_BATCH_TO_SPACE_LAYER_DATASET |
| #define ARM_COMPUTE_TEST_BATCH_TO_SPACE_LAYER_DATASET |
| |
| #include "utils/TypePrinter.h" |
| |
| #include "arm_compute/core/TensorShape.h" |
| #include "arm_compute/core/Types.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace datasets |
| { |
| class BatchToSpaceLayerDataset |
| { |
| public: |
| using type = std::tuple<TensorShape, std::vector<int32_t>, CropInfo, TensorShape>; |
| |
| struct iterator |
| { |
| iterator(std::vector<TensorShape>::const_iterator src_it, |
| std::vector<std::vector<int32_t>>::const_iterator block_shape_it, |
| std::vector<CropInfo>::const_iterator crop_info_it, |
| std::vector<TensorShape>::const_iterator dst_it) |
| : _src_it{ std::move(src_it) }, |
| _block_shape_it{ std::move(block_shape_it) }, |
| _crop_info_it{ std::move(crop_info_it) }, |
| _dst_it{ std::move(dst_it) } |
| { |
| } |
| |
| std::string description() const |
| { |
| std::stringstream description; |
| description << "In=" << *_src_it << ":"; |
| description << "BlockShape=" << *_block_shape_it << ":"; |
| description << "CropInfo=" << *_crop_info_it << ":"; |
| description << "Out=" << *_dst_it; |
| return description.str(); |
| } |
| |
| BatchToSpaceLayerDataset::type operator*() const |
| { |
| return std::make_tuple(*_src_it, *_block_shape_it, *_crop_info_it, *_dst_it); |
| } |
| |
| iterator &operator++() |
| { |
| ++_src_it; |
| ++_block_shape_it; |
| ++_crop_info_it; |
| ++_dst_it; |
| |
| return *this; |
| } |
| |
| private: |
| std::vector<TensorShape>::const_iterator _src_it; |
| std::vector<std::vector<int32_t>>::const_iterator _block_shape_it; |
| std::vector<CropInfo>::const_iterator _crop_info_it; |
| std::vector<TensorShape>::const_iterator _dst_it; |
| }; |
| |
| iterator begin() const |
| { |
| return iterator(_src_shapes.begin(), _block_shapes.begin(), _crop_infos.begin(), _dst_shapes.begin()); |
| } |
| |
| int size() const |
| { |
| return std::min(std::min(std::min(_src_shapes.size(), _block_shapes.size()), _crop_infos.size()), _dst_shapes.size()); |
| } |
| |
| void add_config(const TensorShape &src, const std::vector<int32_t> &block_shape, const CropInfo &crop_info, const TensorShape &dst) |
| { |
| _src_shapes.emplace_back(std::move(src)); |
| _block_shapes.emplace_back(std::move(block_shape)); |
| _crop_infos.emplace_back(std::move(crop_info)); |
| _dst_shapes.emplace_back(std::move(dst)); |
| } |
| |
| protected: |
| BatchToSpaceLayerDataset() = default; |
| BatchToSpaceLayerDataset(BatchToSpaceLayerDataset &&) = default; |
| |
| private: |
| std::vector<TensorShape> _src_shapes{}; |
| std::vector<std::vector<int32_t>> _block_shapes{}; |
| std::vector<CropInfo> _crop_infos{}; |
| std::vector<TensorShape> _dst_shapes{}; |
| }; |
| |
| /** Follow NCHW data layout across all datasets. I.e. |
| * TensorShape(Width(X), Height(Y), Channel(Z), Batch(W)) |
| */ |
| |
| class SmallBatchToSpaceLayerDataset final : public BatchToSpaceLayerDataset |
| { |
| public: |
| SmallBatchToSpaceLayerDataset() |
| { |
| // Block size = 1 (effectively no batch to space) |
| add_config(TensorShape(1U, 1U, 1U, 4U), { 1U, 1U }, CropInfo(), TensorShape(1U, 1U, 1U, 4U)); |
| add_config(TensorShape(8U, 2U, 4U, 3U), { 1U, 1U }, CropInfo(), TensorShape(8U, 2U, 4U, 3U)); |
| // Same block size in both x and y |
| add_config(TensorShape(3U, 2U, 1U, 4U), { 2U, 2U }, CropInfo(), TensorShape(6U, 4U, 1U, 1U)); |
| add_config(TensorShape(1U, 3U, 2U, 9U), { 3U, 3U }, CropInfo(), TensorShape(3U, 9U, 2U, 1U)); |
| // Different block size in x and y |
| add_config(TensorShape(5U, 7U, 7U, 4U), { 2U, 1U }, CropInfo(), TensorShape(10U, 7U, 7U, 2U)); |
| add_config(TensorShape(3U, 3U, 1U, 8U), { 1U, 2U }, CropInfo(), TensorShape(3U, 6U, 1U, 4U)); |
| add_config(TensorShape(5U, 2U, 2U, 6U), { 3U, 2U }, CropInfo(), TensorShape(15U, 4U, 2U, 1U)); |
| } |
| }; |
| |
| /** Relative small shapes that are still large enough to leave room for testing cropping of the output shape |
| */ |
| class SmallBatchToSpaceLayerWithCroppingDataset final : public BatchToSpaceLayerDataset |
| { |
| public: |
| SmallBatchToSpaceLayerWithCroppingDataset() |
| { |
| // Crop in both dims |
| add_config(TensorShape(5U, 3U, 2U, 8U), { 2U, 2U }, CropInfo(1U, 1U, 2U, 1U), TensorShape(8U, 3U, 2U, 2U)); |
| // Left crop in x dim |
| add_config(TensorShape(1U, 1U, 1U, 20U), { 4U, 5U }, CropInfo(2U, 1U, 0U, 2U), TensorShape(1U, 3U, 1U, 1U)); |
| // Left crop in y dim |
| add_config(TensorShape(3U, 1U, 1U, 8U), { 2U, 4U }, CropInfo(0U, 0U, 2U, 1U), TensorShape(6U, 1U, 1U, 1U)); |
| } |
| }; |
| class LargeBatchToSpaceLayerDataset final : public BatchToSpaceLayerDataset |
| { |
| public: |
| LargeBatchToSpaceLayerDataset() |
| { |
| // Same block size in both x and y |
| add_config(TensorShape(64U, 32U, 2U, 4U), { 2U, 2U }, CropInfo(), TensorShape(128U, 64U, 2U, 1U)); |
| add_config(TensorShape(128U, 16U, 2U, 18U), { 3U, 3U }, CropInfo(), TensorShape(384U, 48U, 2U, 2U)); |
| // Different block size in x and y |
| add_config(TensorShape(16U, 8U, 2U, 8U), { 4U, 1U }, CropInfo(), TensorShape(64U, 8U, 2U, 2U)); |
| add_config(TensorShape(8U, 16U, 2U, 8U), { 2U, 4U }, CropInfo(), TensorShape(16U, 64U, 2U, 1U)); |
| } |
| }; |
| } // namespace datasets |
| } // namespace test |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_TEST_BATCH_TO_SPACE_LAYER_DATASET */ |