| /* |
| * Copyright (c) 2017 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_DATASET_POOLING_LAYER_DATASET_H__ |
| #define __ARM_COMPUTE_TEST_DATASET_POOLING_LAYER_DATASET_H__ |
| |
| #include "TypePrinter.h" |
| |
| #include "arm_compute/core/TensorShape.h" |
| #include "arm_compute/core/Types.h" |
| #include "dataset/GenericDataset.h" |
| |
| #include <type_traits> |
| |
| #ifdef BOOST |
| #include "boost_wrapper.h" |
| #endif |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| class PoolingLayerDataObject |
| { |
| public: |
| operator std::string() const |
| { |
| std::stringstream ss; |
| ss << "PoolingLayer"; |
| ss << "_I" << src_shape; |
| ss << "_S_" << info.pool_size(); |
| ss << "_F_" << info.pool_type(); |
| ss << "_PS" << info.pad_stride_info(); |
| return ss.str(); |
| } |
| |
| friend std::ostream &operator<<(std::ostream &s, const PoolingLayerDataObject &obj) |
| { |
| s << static_cast<std::string>(obj); |
| return s; |
| } |
| |
| public: |
| TensorShape src_shape; |
| TensorShape dst_shape; |
| PoolingLayerInfo info; |
| }; |
| |
| template <unsigned int Size> |
| using PoolingLayerDataset = GenericDataset<PoolingLayerDataObject, Size>; |
| |
| class AlexNetPoolingLayerDataset final : public PoolingLayerDataset<3> |
| { |
| public: |
| AlexNetPoolingLayerDataset() |
| : GenericDataset |
| { |
| PoolingLayerDataObject{ TensorShape(55U, 55U, 96U), TensorShape(27U, 27U, 96U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| PoolingLayerDataObject{ TensorShape(27U, 27U, 256U), TensorShape(13U, 13U, 256U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| PoolingLayerDataObject{ TensorShape(13U, 13U, 256U), TensorShape(6U, 6U, 256U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| } |
| { |
| } |
| |
| ~AlexNetPoolingLayerDataset() = default; |
| }; |
| |
| class LeNet5PoolingLayerDataset final : public PoolingLayerDataset<2> |
| { |
| public: |
| LeNet5PoolingLayerDataset() |
| : GenericDataset |
| { |
| PoolingLayerDataObject{ TensorShape(24U, 24U, 20U), TensorShape(12U, 12U, 20U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| PoolingLayerDataObject{ TensorShape(8U, 8U, 50U), TensorShape(4U, 4U, 50U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| } |
| { |
| } |
| |
| ~LeNet5PoolingLayerDataset() = default; |
| }; |
| |
| class GoogLeNetPoolingLayerDataset final : public PoolingLayerDataset<10> |
| { |
| public: |
| GoogLeNetPoolingLayerDataset() |
| : GenericDataset |
| { |
| // FIXME: Add support for 7x7 pooling layer pool5/7x7_s1 |
| // pool1/3x3_s2 |
| PoolingLayerDataObject{ TensorShape(112U, 112U, 64U), TensorShape(56U, 56U, 64U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)) }, |
| // pool2/3x3_s2 |
| PoolingLayerDataObject{ TensorShape(56U, 56U, 192U), TensorShape(28U, 28U, 192U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)) }, |
| // inception_3a/pool |
| PoolingLayerDataObject{ TensorShape(28U, 28U, 192U), TensorShape(28U, 28U, 192U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| // inception_3b/pool |
| PoolingLayerDataObject{ TensorShape(28U, 28U, 256U), TensorShape(28U, 28U, 256U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| // pool3/3x3_s2 |
| PoolingLayerDataObject{ TensorShape(28U, 28U, 480U), TensorShape(14U, 14U, 480U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)) }, |
| // inception_4a/pool |
| PoolingLayerDataObject{ TensorShape(14U, 14U, 480U), TensorShape(14U, 14U, 480U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| // inception_4b/pool, inception_4c/pool, inception_4d/pool |
| PoolingLayerDataObject{ TensorShape(14U, 14U, 512U), TensorShape(14U, 14U, 512U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| // inception_4e/pool |
| PoolingLayerDataObject{ TensorShape(14U, 14U, 528U), TensorShape(14U, 14U, 528U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| // pool4/3x3_s2 |
| PoolingLayerDataObject{ TensorShape(14U, 14U, 832U), TensorShape(7U, 7U, 832U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)) }, |
| // inception_5a/pool, inception_5b/pool |
| PoolingLayerDataObject{ TensorShape(7U, 7U, 832U), TensorShape(7U, 7U, 832U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| } |
| { |
| } |
| |
| ~GoogLeNetPoolingLayerDataset() = default; |
| }; |
| |
| class RandomPoolingLayerDataset final : public PoolingLayerDataset<8> |
| { |
| public: |
| RandomPoolingLayerDataset() |
| : GenericDataset |
| { |
| PoolingLayerDataObject{ TensorShape(27U, 27U, 16U), TensorShape(13U, 13U, 16U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| PoolingLayerDataObject{ TensorShape(13U, 13U, 32U), TensorShape(6U, 6U, 32U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| PoolingLayerDataObject{ TensorShape(24U, 24U, 10U), TensorShape(12U, 12U, 10U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| PoolingLayerDataObject{ TensorShape(8U, 8U, 30U), TensorShape(4U, 4U, 30U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| PoolingLayerDataObject{ TensorShape(27U, 27U, 16U), TensorShape(13U, 13U, 16U), PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| PoolingLayerDataObject{ TensorShape(13U, 13U, 32U), TensorShape(6U, 6U, 32U), PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| PoolingLayerDataObject{ TensorShape(24U, 24U, 10U), TensorShape(12U, 12U, 10U), PoolingLayerInfo(PoolingType::AVG, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| PoolingLayerDataObject{ TensorShape(8U, 8U, 30U), TensorShape(4U, 4U, 30U), PoolingLayerInfo(PoolingType::AVG, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| } |
| { |
| } |
| |
| ~RandomPoolingLayerDataset() = default; |
| }; |
| } // namespace test |
| } // namespace arm_compute |
| #endif //__ARM_COMPUTE_TEST_DATASET_POOLING_LAYER_DATASET_H__ |