Freddie Liardet | f727ef4 | 2021-10-18 13:28:57 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2021 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 | #include "arm_compute/core/Helpers.h" |
| 25 | #include "arm_compute/core/Types.h" |
| 26 | #include "arm_compute/runtime/NEON/functions/NEConv3D.h" |
| 27 | #include "arm_compute/runtime/Tensor.h" |
| 28 | #include "arm_compute/runtime/TensorAllocator.h" |
| 29 | #include "tests/NEON/Accessor.h" |
| 30 | #include "tests/PaddingCalculator.h" |
| 31 | #include "tests/datasets/ShapeDatasets.h" |
| 32 | #include "tests/framework/Asserts.h" |
| 33 | #include "tests/framework/Macros.h" |
| 34 | #include "tests/framework/datasets/Datasets.h" |
| 35 | #include "tests/validation/Validation.h" |
| 36 | #include "tests/validation/fixtures/DirectConvolution3DFixture.h" |
| 37 | |
| 38 | namespace arm_compute |
| 39 | { |
| 40 | namespace test |
| 41 | { |
| 42 | namespace validation |
| 43 | { |
| 44 | namespace |
| 45 | { |
| 46 | #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| 47 | const RelativeTolerance<half_float::half> rel_tolerance_f16(half_float::half(0.2f)); /**< Relative tolerance value for FP16 types */ |
| 48 | const AbsoluteTolerance<float> abs_tolerance_f16(0.2f); /**< Absolute tolerance for FP16 types */ |
| 49 | constexpr float tolerance_num = 0.07f; /**< Tolerance number for the FP16 implementation */ |
| 50 | #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| 51 | constexpr AbsoluteTolerance<float> tolerance_fp32(0.001f); /**< Tolerance for floating point tests */ |
| 52 | constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance for quantized tests */ |
| 53 | |
| 54 | /** Activation function Dataset*/ |
| 55 | const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", |
| 56 | { |
| 57 | ActivationLayerInfo(), |
| 58 | ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) |
| 59 | }); |
| 60 | |
| 61 | const auto data_precommit = combine(combine(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip( |
| 62 | datasets::SmallDirectConv3DShapes(), |
| 63 | framework::dataset::make("StrideX", { 1, 5, 8 })), |
| 64 | framework::dataset::make("StrideY", { 1, 2, 3 })), |
| 65 | framework::dataset::make("StrideZ", { 1, 2, 1 })), |
| 66 | framework::dataset::make("PadX", { 0, 1, 2 })), |
| 67 | framework::dataset::make("PadY", { 0, 2, 1 })), |
| 68 | framework::dataset::make("PadZ", { 0, 3, 5 })), |
| 69 | framework::dataset::make("KernelWidth", { 3, 5, 9 })), |
| 70 | framework::dataset::make("KernelHeight", { 2, 1, 3 })), |
| 71 | framework::dataset::make("KernelDepth", { 1, 2, 3 })), |
| 72 | framework::dataset::make("NumKernels", { 2, 3, 8 })), |
| 73 | framework::dataset::make("HasBias", { true, false })), |
| 74 | ActivationFunctionsDataset); |
| 75 | } // namespace |
| 76 | |
| 77 | TEST_SUITE(NEON) |
| 78 | TEST_SUITE(Convolution3D) |
| 79 | |
| 80 | // *INDENT-OFF* |
| 81 | // clang-format off |
| 82 | DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( |
| 83 | framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Mismatching data type input/weights |
| 84 | TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Mismatching input feature maps |
| 85 | TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid weights dimensions |
| 86 | TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NHWC), // Invalid data layout |
| 87 | TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid biases size |
| 88 | TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid biases dimensions |
| 89 | TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid output size |
Freddie Liardet | 69df64f | 2021-10-26 14:06:47 +0100 | [diff] [blame] | 90 | TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::U32, DataLayout::NDHWC), // Invalid data type |
Freddie Liardet | f727ef4 | 2021-10-18 13:28:57 +0100 | [diff] [blame] | 91 | }), |
| 92 | framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F16), |
| 93 | TensorInfo(TensorShape(4U, 3U, 3U, 3U, 3U), 1U, DataType::F32), |
| 94 | TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U, 3U), 1U, DataType::F32), |
| 95 | TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32), |
| 96 | TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32), |
| 97 | TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32), |
| 98 | TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32), |
Freddie Liardet | 69df64f | 2021-10-26 14:06:47 +0100 | [diff] [blame] | 99 | TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::U32), |
Freddie Liardet | f727ef4 | 2021-10-18 13:28:57 +0100 | [diff] [blame] | 100 | })), |
| 101 | framework::dataset::make("BiasesInfo",{ TensorInfo(TensorShape(4U), 1U, DataType::F32), |
| 102 | TensorInfo(TensorShape(4U), 1U, DataType::F32), |
| 103 | TensorInfo(TensorShape(4U), 1U, DataType::F32), |
| 104 | TensorInfo(TensorShape(4U), 1U, DataType::F32), |
| 105 | TensorInfo(TensorShape(3U), 1U, DataType::F32), |
| 106 | TensorInfo(TensorShape(4U, 2U), 1U, DataType::F32), |
| 107 | TensorInfo(TensorShape(4U), 1U, DataType::F32), |
Freddie Liardet | 69df64f | 2021-10-26 14:06:47 +0100 | [diff] [blame] | 108 | TensorInfo(TensorShape(4U), 1U, DataType::F32), |
Freddie Liardet | f727ef4 | 2021-10-18 13:28:57 +0100 | [diff] [blame] | 109 | })), |
| 110 | framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| 111 | TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| 112 | TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| 113 | TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| 114 | TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| 115 | TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| 116 | TensorInfo(TensorShape(26U, 11U, 4U), 1U, DataType::F32), |
Freddie Liardet | 69df64f | 2021-10-26 14:06:47 +0100 | [diff] [blame] | 117 | TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::U32), |
Freddie Liardet | f727ef4 | 2021-10-18 13:28:57 +0100 | [diff] [blame] | 118 | })), |
Freddie Liardet | 69df64f | 2021-10-26 14:06:47 +0100 | [diff] [blame] | 119 | framework::dataset::make("Expected", { false, false, false, false, false, false, false, false})), |
Freddie Liardet | f727ef4 | 2021-10-18 13:28:57 +0100 | [diff] [blame] | 120 | input_info, weights_info, biases_info, output_info, expected) |
| 121 | { |
| 122 | const Conv3dInfo conv3d_info(Size3D(1, 1, 1), Padding3D(0, 0, 0), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false); |
| 123 | bool is_valid = bool(NEConv3D::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv3d_info)); |
| 124 | ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); |
| 125 | } |
| 126 | // clang-format on |
| 127 | // *INDENT-ON* |
| 128 | |
| 129 | template <typename T> |
| 130 | using NEDirectConvolution3DFixture = DirectConvolution3DValidationFixture<Tensor, Accessor, NEConv3D, T>; |
| 131 | |
| 132 | TEST_SUITE(Float) |
| 133 | TEST_SUITE(FP32) |
| 134 | FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(data_precommit, |
| 135 | framework::dataset::make("DataType", DataType::F32)), |
| 136 | framework::dataset::make("DataLayout", { DataLayout::NDHWC }))) |
| 137 | { |
| 138 | // Validate output |
| 139 | validate(Accessor(_target), _reference, tolerance_fp32); |
| 140 | } |
| 141 | TEST_SUITE_END() // FP32 |
| 142 | |
| 143 | #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| 144 | TEST_SUITE(FP16) |
| 145 | FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(data_precommit, |
| 146 | framework::dataset::make("DataType", DataType::F16)), |
| 147 | framework::dataset::make("DataLayout", { DataLayout::NDHWC }))) |
| 148 | { |
| 149 | // Validate output |
| 150 | validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_f16); |
| 151 | } |
| 152 | TEST_SUITE_END() // FP16 |
| 153 | #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| 154 | |
| 155 | TEST_SUITE_END() // Float |
| 156 | |
| 157 | template <typename T> |
| 158 | using NEDirectConvolution3DQuantizedFixture = DirectConvolution3DValidationQuantizedFixture<Tensor, Accessor, NEConv3D, T>; |
| 159 | |
| 160 | TEST_SUITE(Quantized) |
| 161 | TEST_SUITE(QASYMM8) |
| 162 | FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, |
| 163 | combine(combine(combine(combine(combine(combine(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip( |
| 164 | framework::dataset::make("InputShape", { TensorShape(7U, 5U, 3U, 13U, 3U), |
| 165 | TensorShape(15U, 7U, 11U, 7U), |
| 166 | TensorShape(19U, 5U, 16U, 4U), |
| 167 | TensorShape(13U, 5U, 17U, 2U) |
| 168 | }), |
| 169 | framework::dataset::make("StrideX", { 1, 3, 2, 1 })), |
| 170 | framework::dataset::make("StrideY", { 2, 1, 3, 1 })), |
| 171 | framework::dataset::make("StrideZ", { 3, 2, 1, 1 })), |
| 172 | framework::dataset::make("PadX", { 0, 2, 1, 0 })), |
| 173 | framework::dataset::make("PadY", { 1, 0, 2, 0 })), |
| 174 | framework::dataset::make("PadZ", { 2, 1, 0, 0 })), |
| 175 | framework::dataset::make("KernelWidth", { 3, 7, 5, 1 })), |
| 176 | framework::dataset::make("KernelHeight", { 5, 3, 7, 1 })), |
| 177 | framework::dataset::make("KernelDepth", { 7, 5, 3, 1 })), |
| 178 | framework::dataset::make("NumKernels", { 5, 3, 1, 11 })), |
| 179 | framework::dataset::make("HasBias", { true, true, true, false })), |
| 180 | framework::dataset::make("Activation", ActivationLayerInfo())), |
| 181 | framework::dataset::make("DataType", DataType::QASYMM8)), |
| 182 | framework::dataset::make("DataLayout", DataLayout::NDHWC)), |
| 183 | framework::dataset::make("SrcQuantizationInfo", QuantizationInfo(0.1f, 10))), |
| 184 | framework::dataset::make("WeightsQuantizationInfo", QuantizationInfo(0.3f, 20))), |
| 185 | framework::dataset::make("DstQuantizationInfo", QuantizationInfo(0.2f, 5)))) |
| 186 | { |
| 187 | validate(Accessor(_target), _reference, tolerance_qasymm8); |
| 188 | } |
| 189 | |
| 190 | TEST_SUITE_END() // QASYMM8 |
| 191 | |
| 192 | TEST_SUITE(QASYMM8_SIGNED) |
| 193 | FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, |
| 194 | combine(combine(combine(combine(combine(combine(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip( |
| 195 | framework::dataset::make("InputShape", { TensorShape(7U, 5U, 3U, 13U, 3U), |
| 196 | TensorShape(15U, 7U, 11U, 7U), |
| 197 | TensorShape(19U, 5U, 16U, 4U), |
| 198 | TensorShape(13U, 5U, 17U, 2U) |
| 199 | }), |
| 200 | framework::dataset::make("StrideX", { 1, 3, 2, 1 })), |
| 201 | framework::dataset::make("StrideY", { 2, 1, 3, 1 })), |
| 202 | framework::dataset::make("StrideZ", { 3, 2, 1, 1 })), |
| 203 | framework::dataset::make("PadX", { 0, 2, 1, 0 })), |
| 204 | framework::dataset::make("PadY", { 1, 0, 2, 0 })), |
| 205 | framework::dataset::make("PadZ", { 2, 1, 0, 0 })), |
| 206 | framework::dataset::make("KernelWidth", { 3, 7, 5, 1 })), |
| 207 | framework::dataset::make("KernelHeight", { 5, 3, 7, 1 })), |
| 208 | framework::dataset::make("KernelDepth", { 7, 5, 3, 1 })), |
| 209 | framework::dataset::make("NumKernels", { 5, 3, 1, 11 })), |
| 210 | framework::dataset::make("HasBias", { true, true, true, false })), |
| 211 | framework::dataset::make("Activation", ActivationLayerInfo())), |
| 212 | framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), |
| 213 | framework::dataset::make("DataLayout", DataLayout::NDHWC)), |
| 214 | framework::dataset::make("SrcQuantizationInfo", QuantizationInfo(0.1f, 10))), |
| 215 | framework::dataset::make("WeightsQuantizationInfo", QuantizationInfo(0.3f, 20))), |
| 216 | framework::dataset::make("DstQuantizationInfo", QuantizationInfo(0.2f, 5)))) |
| 217 | { |
| 218 | validate(Accessor(_target), _reference, tolerance_qasymm8); |
| 219 | } |
| 220 | |
| 221 | TEST_SUITE_END() // QASYMM8_SIGNED |
| 222 | TEST_SUITE_END() // Quantized |
| 223 | |
| 224 | TEST_SUITE_END() // Convolution3D |
| 225 | TEST_SUITE_END() // Neon |
| 226 | } // namespace validation |
| 227 | } // namespace test |
| 228 | } // namespace arm_compute |