blob: 5c80351da238f88a2a42dc047a0460319d6b4f6f [file] [log] [blame]
ramelg0137515692022-02-26 22:06:20 +00001/*
2 * Copyright (c) 2022 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
25#include "arm_compute/core/TensorShape.h"
26#include "tests/framework/datasets/Datasets.h"
27
28#include "arm_compute/core/Types.h"
29#include "arm_compute/runtime/CL/CLTensor.h"
30#include "arm_compute/runtime/CL/CLTensorAllocator.h"
31#include "arm_compute/runtime/CL/functions/CLPooling3dLayer.h"
32#include "tests/CL/CLAccessor.h"
33#include "tests/PaddingCalculator.h"
34#include "tests/datasets/Pooling3dLayerDataset.h"
35#include "tests/datasets/PoolingTypesDataset.h"
36#include "tests/datasets/ShapeDatasets.h"
37#include "tests/framework/Asserts.h"
38#include "tests/framework/Macros.h"
39#include "tests/framework/datasets/Datasets.h"
40#include "tests/validation/Validation.h"
41#include "tests/validation/fixtures/Pooling3dLayerFixture.h"
42
43namespace arm_compute
44{
45namespace test
46{
47namespace validation
48{
49namespace
50{
51/** Input data sets for floating-point data types */
52const auto Pooling3dLayerDatasetFP = combine(combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size3D(2, 3, 2) })),
53 framework::dataset::make("Stride", { Size3D(1, 1, 1), Size3D(2, 1, 1), Size3D(1, 2, 1), Size3D(2, 2, 1) })),
54 framework::dataset::make("Padding", { Padding3D(0, 1, 0), Padding3D(1, 1, 1) })),
55 framework::dataset::make("ExcludePadding", { true, false }));
56
57const auto Pooling3dLayerDatasetFPSmall = combine(combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size3D(2, 2, 2), Size3D(3, 3, 3) })),
58 framework::dataset::make("Stride", { Size3D(2, 2, 2), Size3D(2, 1, 1) })),
59 framework::dataset::make("Padding", { Padding3D(0, 0, 0), Padding3D(1, 1, 1), Padding3D(1, 0, 0) })),
60 framework::dataset::make("ExcludePadding", { true, false }));
61
62using ShapeDataset = framework::dataset::ContainerDataset<std::vector<TensorShape>>;
63
64constexpr AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for 32-bit floating-point type */
65constexpr AbsoluteTolerance<float> tolerance_f16(0.1f); /**< Tolerance value for comparing reference's output against implementation's output for 16-bit floating-point type */
66
67} // namespace
68
69TEST_SUITE(CL)
70TEST_SUITE(Pooling3dLayer)
71
72// *INDENT-OFF*
73// clang-format off
74DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
75 framework::dataset::make("InputInfo", { TensorInfo(TensorShape(2U, 27U, 13U, 4U, 3U), 1, DataType::F32, DataLayout::NDHWC), // Mismatching data type
76 TensorInfo(TensorShape(2U, 27U, 13U, 4U, 2U), 1, DataType::F32, DataLayout::NDHWC), // Invalid pad/size combination
77 TensorInfo(TensorShape(2U, 27U, 13U, 4U, 2U), 1, DataType::F32, DataLayout::NDHWC), // Invalid pad/size combination
78 TensorInfo(TensorShape(2U, 27U, 13U, 4U, 3U), 1, DataType::F32, DataLayout::NDHWC), // Invalid output shape
79 TensorInfo(TensorShape(5U, 13U, 15U, 2U, 3U), 1, DataType::F32, DataLayout::NDHWC), // Global Pooling
80 TensorInfo(TensorShape(13U,13U, 5U, 1U, 2U), 1, DataType::F32, DataLayout::NDHWC), // Invalid output Global Pooling
81 TensorInfo(TensorShape(5U, 13U, 13U, 4U, 4U), 1, DataType::F32, DataLayout::NDHWC), // Invalid data type
82 TensorInfo(TensorShape(5U, 13U, 13U, 4U, 4U), 1, DataType::F32, DataLayout::NDHWC),
83 TensorInfo(TensorShape(5U, 13U, 13U, 5U, 4U), 1, DataType::F32, DataLayout::NDHWC),
84 TensorInfo(TensorShape(1U, 16U, 1U, 3U, 4U), 1, DataType::F32, DataLayout::NDHWC),
85 TensorInfo(TensorShape(5U, 13U, 13U, 4U, 3U), 1, DataType::F32, DataLayout::NDHWC),
86 TensorInfo(TensorShape(5U, 13U, 13U, 4U, 2U), 1, DataType::F32, DataLayout::NDHWC),
87 TensorInfo(TensorShape(5U, 13U, 13U, 4U, 3U), 1, DataType::F32, DataLayout::NDHWC),
88 TensorInfo(TensorShape(5U, 13U, 13U, 4U, 3U), 1, DataType::F32, DataLayout::NDHWC),
89 }),
90 framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(2U, 25U, 11U, 3U, 3U), 1, DataType::F16, DataLayout::NDHWC),
91 TensorInfo(TensorShape(2U, 30U, 11U, 3U, 2U), 1, DataType::F32, DataLayout::NDHWC),
92 TensorInfo(TensorShape(2U, 25U, 16U, 3U, 2U), 1, DataType::F32, DataLayout::NDHWC),
93 TensorInfo(TensorShape(2U, 27U, 13U, 3U, 3U), 1, DataType::F32, DataLayout::NDHWC),
94 TensorInfo(TensorShape(5U, 1U, 1U, 1U, 3U), 1, DataType::F32, DataLayout::NDHWC), // Global pooling applied
95 TensorInfo(TensorShape(5U, 2U, 2U, 2U, 2U), 1, DataType::F32, DataLayout::NDHWC), // Invalid output Global Pooling
96 TensorInfo(TensorShape(5U, 12U, 12U, 3U, 4U), 1, DataType::F32, DataLayout::NDHWC),
97 TensorInfo(TensorShape(5U, 12U, 12U, 3U, 4U), 1, DataType::QASYMM8, DataLayout::NDHWC), // Invalid data type
98 TensorInfo(TensorShape(5U, 1U, 1U, 1U, 4U), 1, DataType::F32, DataLayout::NDHWC),
99 TensorInfo(TensorShape(1U, 15U, 1U, 2U, 4U), 1, DataType::F32, DataLayout::NDHWC), // Output width larger than input
100 TensorInfo(TensorShape(5U, 6U, 6U, 2U, 3U), 1, DataType::F32, DataLayout::NDHWC),
101 TensorInfo(TensorShape(5U, 6U, 6U, 2U, 2U), 1, DataType::F32, DataLayout::NDHWC),
102 TensorInfo(TensorShape(5U, 6U, 6U, 2U, 3U), 1, DataType::F32, DataLayout::NDHWC),
103 TensorInfo(TensorShape(5U, 6U, 6U, 2U, 3U), 1, DataType::F32, DataLayout::NDHWC),
104 })),
105 framework::dataset::make("PoolInfo", { Pooling3dLayerInfo(PoolingType::AVG, 3, Size3D(1, 1, 1), Padding3D(0, 0, 0)),
106 Pooling3dLayerInfo(PoolingType::AVG, 2, Size3D(1, 1, 1), Padding3D(2, 0, 0)),
107 Pooling3dLayerInfo(PoolingType::AVG, 2, Size3D(1, 1, 1), Padding3D(0, 0, 0)),
108 Pooling3dLayerInfo(PoolingType::L2, 3, Size3D(1, 1, 1), Padding3D(0, 0, 0)),
109 Pooling3dLayerInfo(PoolingType::AVG),
110 Pooling3dLayerInfo(PoolingType::MAX),
111 Pooling3dLayerInfo(PoolingType::AVG, 2, Size3D(), Padding3D(), false),
112 Pooling3dLayerInfo(PoolingType::AVG, 2, Size3D(1U, 1U, 1U), Padding3D(), false),
113 Pooling3dLayerInfo(PoolingType::AVG),
114 Pooling3dLayerInfo(PoolingType::MAX, 2, Size3D(1, 1, 2), Padding3D(0, 0, 0), false),
115 Pooling3dLayerInfo(PoolingType::AVG, 2, Size3D(2U, 2U, 2U), Padding3D(), false),
116 Pooling3dLayerInfo(PoolingType::AVG, 1, Size3D(2U, 2U, 2U), Padding3D(2, 2, 2), true), // Pool size is smaller than the padding size with padding excluded
117 Pooling3dLayerInfo(PoolingType::AVG, 1, Size3D(2U, 2U, 2U), Padding3D(2, 2, 2), false), // Pool size is smaller than the padding size with padding included
118 Pooling3dLayerInfo(PoolingType::AVG, 3, Size3D(2U, 2U, 2U), Padding3D(2,1,2,2,1,2), false, false, DimensionRoundingType::CEIL), // CEIL with asymmetric Padding
119 })),
120 framework::dataset::make("Expected", { false, false, false, false, true, false, false, false, true , false, true, false, false, false})),
121 input_info, output_info, pool_info, expected)
122{
123 ARM_COMPUTE_EXPECT(bool(CLPooling3dLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), pool_info)) == expected, framework::LogLevel::ERRORS);
124}
125
126
127template <typename T>
128using CLPooling3dLayerFixture = Pooling3dLayerValidationFixture<CLTensor, CLAccessor, CLPooling3dLayer, T>;
129
130template <typename T>
131using CLSpecialPooling3dLayerFixture = SpecialPooling3dLayerValidationFixture<CLTensor, CLAccessor, CLPooling3dLayer, T>;
132
133template <typename T>
134using CLPooling3dLayerGlobalFixture = Pooling3dLayerGlobalValidationFixture<CLTensor, CLAccessor, CLPooling3dLayer, T>;
135
136// clang-format on
137// *INDENT-ON*
138TEST_SUITE(Float)
139TEST_SUITE(FP32)
140
141FIXTURE_DATA_TEST_CASE(RunSpecial, CLSpecialPooling3dLayerFixture<float>, framework::DatasetMode::ALL, datasets::Pooling3dLayerDatasetSpecial() * framework::dataset::make("DataType", DataType::F32))
142{
143 // Validate output
144 validate(CLAccessor(_target), _reference, tolerance_f32);
145}
146
147FIXTURE_DATA_TEST_CASE(RunSmall, CLPooling3dLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::Small5dShapes(), combine(Pooling3dLayerDatasetFPSmall,
148 framework::dataset::make("DataType", DataType::F32))))
149{
150 // Validate output
151 validate(CLAccessor(_target), _reference, tolerance_f32);
152}
153
154FIXTURE_DATA_TEST_CASE(RunLarge, CLPooling3dLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::Large5dShapes(), combine(Pooling3dLayerDatasetFP,
155 framework::dataset::make("DataType",
156 DataType::F32))))
157{
158 // Validate output
159 validate(CLAccessor(_target), _reference, tolerance_f32);
160}
161
162TEST_SUITE(GlobalPooling)
163// *INDENT-OFF*
164// clang-format off
165FIXTURE_DATA_TEST_CASE(RunSmall, CLPooling3dLayerFixture<float>, framework::DatasetMode::ALL,
166 combine(combine(combine(combine(combine(combine(
167 framework::dataset::make("InputShape", { TensorShape(3U, 27U, 13U, 4U),
168 TensorShape(4U, 27U, 13U, 4U, 2U)
169 }),
170 framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::L2, PoolingType::MAX })),
171 framework::dataset::make("PoolingSize", { Size3D(27, 13, 4) })),
172 framework::dataset::make("Strides", Size3D(1, 1, 1))),
173 framework::dataset::make("Paddings", Padding3D(0, 0, 0))),
174 framework::dataset::make("ExcludePadding", false)),
175 framework::dataset::make("DataType", DataType::F32)))
176{
177 // Validate output
178 validate(CLAccessor(_target), _reference, tolerance_f32);
179}
180
181FIXTURE_DATA_TEST_CASE(RunSmallGlobal, CLPooling3dLayerGlobalFixture<float>, framework::DatasetMode::ALL,
182 combine(combine(
183 framework::dataset::make("InputShape", { TensorShape(27U, 13U, 4U, 3U),
184 TensorShape(27U, 13U, 4U, 4U, 2U)
185 }),
186 framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::L2, PoolingType::MAX })),
187 framework::dataset::make("DataType", DataType::F32)))
188{
189 // Validate output
190 validate(CLAccessor(_target), _reference, tolerance_f32);
191}
192FIXTURE_DATA_TEST_CASE(RunLarge, CLPooling3dLayerFixture<float>, framework::DatasetMode::NIGHTLY,
193 combine(combine(combine(combine(combine(combine(
194 framework::dataset::make("InputShape", { TensorShape(4U, 79U, 37U, 11U),
195 TensorShape(4U, 79U, 37U, 11U, 2U)
196 }),
197 framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::L2, PoolingType::MAX })),
198 framework::dataset::make("PoolingSize", { Size3D(79, 37, 11) })),
199 framework::dataset::make("Strides", Size3D(1, 1, 1))),
200 framework::dataset::make("Paddings", Padding3D(0, 0, 0))),
201 framework::dataset::make("ExcludePadding", false)),
202 framework::dataset::make("DataType", DataType::F32)))
203{
204 // Validate output
205 validate(CLAccessor(_target), _reference, tolerance_f32);
206}
207// clang-format on
208// *INDENT-ON*
209TEST_SUITE_END() // GlobalPooling
210TEST_SUITE_END() // FP32
211
212TEST_SUITE(FP16)
213
214FIXTURE_DATA_TEST_CASE(RunSmall, CLPooling3dLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::Small5x5Shapes(), combine(Pooling3dLayerDatasetFPSmall,
215 framework::dataset::make("DataType", DataType::F16))))
216{
217 // Validate output
218 validate(CLAccessor(_target), _reference, tolerance_f16);
219}
220
221FIXTURE_DATA_TEST_CASE(RunLarge, CLPooling3dLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(datasets::Large5dShapes(), combine(Pooling3dLayerDatasetFP,
222 framework::dataset::make("DataType",
223 DataType::F16))))
224{
225 // Validate output
226 validate(CLAccessor(_target), _reference, tolerance_f16);
227}
228
229TEST_SUITE(GlobalPooling)
230// *INDENT-OFF*
231// clang-format off
232FIXTURE_DATA_TEST_CASE(RunSmall, CLPooling3dLayerFixture<half>, framework::DatasetMode::ALL,
233 combine(combine(combine(combine(combine(combine(
234 framework::dataset::make("InputShape", { TensorShape(3U, 27U, 13U, 4U),
235 TensorShape(4U, 27U, 13U, 4U, 2U)
236 }),
237 framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::L2, PoolingType::MAX })),
238 framework::dataset::make("PoolingSize", { Size3D(27, 13, 4) })),
239 framework::dataset::make("Strides", Size3D(1, 1, 1))),
240 framework::dataset::make("Paddings", Padding3D(0, 0, 0))),
241 framework::dataset::make("ExcludePadding", false)),
242 framework::dataset::make("DataType", DataType::F16)))
243{
244 // Validate output
245 validate(CLAccessor(_target), _reference, tolerance_f16);
246}
247
248FIXTURE_DATA_TEST_CASE(RunSmallGlobal, CLPooling3dLayerGlobalFixture<half>, framework::DatasetMode::ALL,
249 combine(combine(
250 framework::dataset::make("InputShape", { TensorShape(27U, 13U, 4U, 3U),
251 TensorShape(27U, 13U, 4U, 4U, 2U)
252 }),
253 framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::L2, PoolingType::MAX })),
254 framework::dataset::make("DataType", DataType::F16)))
255{
256 // Validate output
257 validate(CLAccessor(_target), _reference, tolerance_f16);
258}
259FIXTURE_DATA_TEST_CASE(RunLarge, CLPooling3dLayerFixture<half>, framework::DatasetMode::NIGHTLY,
260 combine(combine(combine(combine(combine(combine(
261 framework::dataset::make("InputShape", { TensorShape(4U, 79U, 37U, 11U),
262 TensorShape(4U, 79U, 37U, 11U, 2U)
263 }),
264 framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::L2, PoolingType::MAX })),
265 framework::dataset::make("PoolingSize", { Size3D(79, 37, 11) })),
266 framework::dataset::make("Strides", Size3D(1, 1, 1))),
267 framework::dataset::make("Paddings", Padding3D(0, 0, 0))),
268 framework::dataset::make("ExcludePadding", false)),
269 framework::dataset::make("DataType", DataType::F16)))
270{
271 // Validate output
272 validate(CLAccessor(_target), _reference, tolerance_f16);
273}
274// clang-format on
275// *INDENT-ON*
276TEST_SUITE_END() // GlobalPooling
277TEST_SUITE_END() // FP16
278TEST_SUITE_END() // Float
279TEST_SUITE_END() // Pooling3dLayer
280TEST_SUITE_END() // CL
281} // namespace validation
282} // namespace test
283} // namespace arm_compute