Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2017 ARM Limited. |
| 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | #ifndef __ARM_COMPUTE_TEST_DATASET_POOLING_LAYER_DATASET_H__ |
| 25 | #define __ARM_COMPUTE_TEST_DATASET_POOLING_LAYER_DATASET_H__ |
| 26 | |
| 27 | #include "TypePrinter.h" |
| 28 | |
| 29 | #include "arm_compute/core/TensorShape.h" |
| 30 | #include "arm_compute/core/Types.h" |
| 31 | #include "dataset/GenericDataset.h" |
| 32 | |
| 33 | #include <type_traits> |
| 34 | |
| 35 | #ifdef BOOST |
| 36 | #include "boost_wrapper.h" |
| 37 | #endif |
| 38 | |
| 39 | namespace arm_compute |
| 40 | { |
| 41 | namespace test |
| 42 | { |
| 43 | class PoolingLayerDataObject |
| 44 | { |
| 45 | public: |
| 46 | operator std::string() const |
| 47 | { |
| 48 | std::stringstream ss; |
| 49 | ss << "PoolingLayer"; |
| 50 | ss << "_I" << src_shape; |
| 51 | ss << "_S_" << info.pool_size(); |
| 52 | ss << "_F_" << info.pool_type(); |
| 53 | ss << "_PS" << info.pad_stride_info(); |
| 54 | return ss.str(); |
| 55 | } |
| 56 | |
| 57 | friend std::ostream &operator<<(std::ostream &s, const PoolingLayerDataObject &obj) |
| 58 | { |
| 59 | s << static_cast<std::string>(obj); |
| 60 | return s; |
| 61 | } |
| 62 | |
| 63 | public: |
| 64 | TensorShape src_shape; |
| 65 | TensorShape dst_shape; |
| 66 | PoolingLayerInfo info; |
| 67 | }; |
| 68 | |
| 69 | template <unsigned int Size> |
| 70 | using PoolingLayerDataset = GenericDataset<PoolingLayerDataObject, Size>; |
| 71 | |
| 72 | class AlexNetPoolingLayerDataset final : public PoolingLayerDataset<3> |
| 73 | { |
| 74 | public: |
| 75 | AlexNetPoolingLayerDataset() |
| 76 | : GenericDataset |
| 77 | { |
| 78 | PoolingLayerDataObject{ TensorShape(55U, 55U, 96U), TensorShape(27U, 27U, 96U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| 79 | PoolingLayerDataObject{ TensorShape(27U, 27U, 256U), TensorShape(13U, 13U, 256U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| 80 | PoolingLayerDataObject{ TensorShape(13U, 13U, 256U), TensorShape(6U, 6U, 256U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| 81 | } |
| 82 | { |
| 83 | } |
| 84 | |
| 85 | ~AlexNetPoolingLayerDataset() = default; |
| 86 | }; |
| 87 | |
| 88 | class LeNet5PoolingLayerDataset final : public PoolingLayerDataset<2> |
| 89 | { |
| 90 | public: |
| 91 | LeNet5PoolingLayerDataset() |
| 92 | : GenericDataset |
| 93 | { |
| 94 | PoolingLayerDataObject{ TensorShape(24U, 24U, 20U), TensorShape(12U, 12U, 20U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| 95 | PoolingLayerDataObject{ TensorShape(8U, 8U, 50U), TensorShape(4U, 4U, 50U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| 96 | } |
| 97 | { |
| 98 | } |
| 99 | |
| 100 | ~LeNet5PoolingLayerDataset() = default; |
| 101 | }; |
| 102 | |
| 103 | class GoogLeNetPoolingLayerDataset final : public PoolingLayerDataset<10> |
| 104 | { |
| 105 | public: |
| 106 | GoogLeNetPoolingLayerDataset() |
| 107 | : GenericDataset |
| 108 | { |
| 109 | // FIXME: Add support for 7x7 pooling layer pool5/7x7_s1 |
| 110 | // pool1/3x3_s2 |
| 111 | PoolingLayerDataObject{ TensorShape(112U, 112U, 64U), TensorShape(56U, 56U, 64U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)) }, |
| 112 | // pool2/3x3_s2 |
| 113 | PoolingLayerDataObject{ TensorShape(56U, 56U, 192U), TensorShape(28U, 28U, 192U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)) }, |
| 114 | // inception_3a/pool |
| 115 | PoolingLayerDataObject{ TensorShape(28U, 28U, 192U), TensorShape(28U, 28U, 192U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| 116 | // inception_3b/pool |
| 117 | PoolingLayerDataObject{ TensorShape(28U, 28U, 256U), TensorShape(28U, 28U, 256U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| 118 | // pool3/3x3_s2 |
| 119 | PoolingLayerDataObject{ TensorShape(28U, 28U, 480U), TensorShape(14U, 14U, 480U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)) }, |
| 120 | // inception_4a/pool |
| 121 | PoolingLayerDataObject{ TensorShape(14U, 14U, 480U), TensorShape(14U, 14U, 480U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| 122 | // inception_4b/pool, inception_4c/pool, inception_4d/pool |
| 123 | PoolingLayerDataObject{ TensorShape(14U, 14U, 512U), TensorShape(14U, 14U, 512U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| 124 | // inception_4e/pool |
| 125 | PoolingLayerDataObject{ TensorShape(14U, 14U, 528U), TensorShape(14U, 14U, 528U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| 126 | // pool4/3x3_s2 |
| 127 | PoolingLayerDataObject{ TensorShape(14U, 14U, 832U), TensorShape(7U, 7U, 832U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)) }, |
| 128 | // inception_5a/pool, inception_5b/pool |
| 129 | PoolingLayerDataObject{ TensorShape(7U, 7U, 832U), TensorShape(7U, 7U, 832U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)) }, |
| 130 | } |
| 131 | { |
| 132 | } |
| 133 | |
| 134 | ~GoogLeNetPoolingLayerDataset() = default; |
| 135 | }; |
| 136 | |
| 137 | class RandomPoolingLayerDataset final : public PoolingLayerDataset<8> |
| 138 | { |
| 139 | public: |
| 140 | RandomPoolingLayerDataset() |
| 141 | : GenericDataset |
| 142 | { |
| 143 | PoolingLayerDataObject{ TensorShape(27U, 27U, 16U), TensorShape(13U, 13U, 16U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| 144 | PoolingLayerDataObject{ TensorShape(13U, 13U, 32U), TensorShape(6U, 6U, 32U), PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| 145 | PoolingLayerDataObject{ TensorShape(24U, 24U, 10U), TensorShape(12U, 12U, 10U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| 146 | PoolingLayerDataObject{ TensorShape(8U, 8U, 30U), TensorShape(4U, 4U, 30U), PoolingLayerInfo(PoolingType::MAX, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| 147 | PoolingLayerDataObject{ TensorShape(27U, 27U, 16U), TensorShape(13U, 13U, 16U), PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| 148 | PoolingLayerDataObject{ TensorShape(13U, 13U, 32U), TensorShape(6U, 6U, 32U), PoolingLayerInfo(PoolingType::AVG, 3, PadStrideInfo(2, 2, 0, 0)) }, |
| 149 | PoolingLayerDataObject{ TensorShape(24U, 24U, 10U), TensorShape(12U, 12U, 10U), PoolingLayerInfo(PoolingType::AVG, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| 150 | PoolingLayerDataObject{ TensorShape(8U, 8U, 30U), TensorShape(4U, 4U, 30U), PoolingLayerInfo(PoolingType::AVG, 2, PadStrideInfo(2, 2, 0, 0)) }, |
| 151 | } |
| 152 | { |
| 153 | } |
| 154 | |
| 155 | ~RandomPoolingLayerDataset() = default; |
| 156 | }; |
| 157 | } // namespace test |
| 158 | } // namespace arm_compute |
| 159 | #endif //__ARM_COMPUTE_TEST_DATASET_POOLING_LAYER_DATASET_H__ |