1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
|
/*
* Copyright (c) 2017-2020 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.
*/
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/CL/CLTensorAllocator.h"
#include "arm_compute/runtime/CL/functions/CLPoolingLayer.h"
#include "tests/CL/CLAccessor.h"
#include "tests/PaddingCalculator.h"
#include "tests/datasets/PoolingLayerDataset.h"
#include "tests/datasets/PoolingTypesDataset.h"
#include "tests/datasets/ShapeDatasets.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
#include "tests/validation/Validation.h"
#include "tests/validation/fixtures/PoolingLayerFixture.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace
{
/** Input data sets for floating-point data types */
const auto PoolingLayerDatasetFP = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3), Size2D(5, 7) })),
framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
framework::dataset::make("ExcludePadding", { true, false }));
const auto PoolingLayerDatasetFPSmall = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3) })),
framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0) })),
framework::dataset::make("ExcludePadding", { true, false }));
/** Input data sets for asymmetric data type */
const auto PoolingLayerDatasetQASYMM8 = combine(concat(combine(combine(framework::dataset::make("PoolingType",
{
PoolingType::MAX, PoolingType::AVG,
}),
framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3) })),
framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
combine(combine(framework::dataset::make("PoolingType", { PoolingType::AVG }), framework::dataset::make("PoolingSize", { Size2D(5, 7) })), framework::dataset::make("PadStride", { PadStrideInfo(2, 1, 0, 0) }))),
framework::dataset::make("ExcludePadding", { true }));
const auto PoolingLayerDatasetQASYMM8Small = combine(combine(combine(framework::dataset::make("PoolingType",
{
PoolingType::MAX, PoolingType::AVG,
}),
framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(5, 7) })),
framework::dataset::make("PadStride", { PadStrideInfo(1, 2, 1, 1) })),
framework::dataset::make("ExcludePadding", { true }));
constexpr AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for 32-bit floating-point type */
constexpr AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for 16-bit floating-point type */
constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for 8-bit asymmetric type */
constexpr AbsoluteTolerance<int8_t> tolerance_qasymm8_s(1); /**< Tolerance value for comparing reference's output against implementation's output for 8-bit signed asymmetric type */
const auto pool_data_layout_dataset = framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC });
const auto pool_fp_mixed_precision_dataset = framework::dataset::make("FpMixedPrecision", { true, false });
} // namespace
TEST_SUITE(CL)
TEST_SUITE(PoolingLayer)
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data type
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Window shrink
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid pad/size combination
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid pad/size combination
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), // Invalid parameters
TensorInfo(TensorShape(15U, 13U, 5U), 1, DataType::F32), // Non-rectangular Global Pooling
TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32), // Invalid output Global Pooling
TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::QASYMM8), // Invalid exclude_padding = false with quantized type, no actual padding and NHWC
TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32),
}),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(25U, 16U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8),
TensorInfo(TensorShape(1U, 1U, 5U), 1, DataType::F32),
TensorInfo(TensorShape(2U, 2U, 5U), 1, DataType::F32),
TensorInfo(TensorShape(12U, 12U, 5U), 1, DataType::QASYMM8),
TensorInfo(TensorShape(1U, 1U, 5U), 1, DataType::F32),
})),
framework::dataset::make("PoolInfo", { PoolingLayerInfo(PoolingType::AVG, 3, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 0)),
PoolingLayerInfo(PoolingType::AVG, 3, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 0)),
PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NCHW, PadStrideInfo(1, 1, 2, 0)),
PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 2)),
PoolingLayerInfo(PoolingType::L2, 3, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 0)),
PoolingLayerInfo(PoolingType::AVG, DataLayout::NCHW),
PoolingLayerInfo(PoolingType::MAX, DataLayout::NCHW),
PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NHWC, PadStrideInfo(), false),
PoolingLayerInfo(PoolingType::AVG, DataLayout::NCHW),
})),
framework::dataset::make("Expected", { false, false, false, false, false, true, false, false, true })),
input_info, output_info, pool_info, expected)
{
ARM_COMPUTE_EXPECT(bool(CLPoolingLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), pool_info)) == expected, framework::LogLevel::ERRORS);
}
// clang-format on
// *INDENT-ON*
template <typename T>
using CLPoolingLayerFixture = PoolingLayerValidationFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
template <typename T>
using CLSpecialPoolingLayerFixture = SpecialPoolingLayerValidationFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
template <typename T>
using CLMixedPrecesionPoolingLayerFixture = PoolingLayerValidationMixedPrecisionFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
TEST_SUITE(Float)
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSpecial, CLSpecialPoolingLayerFixture<float>, framework::DatasetMode::ALL, datasets::PoolingLayerDatasetSpecial() * framework::dataset::make("DataType", DataType::F32))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
}
FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetFPSmall,
framework::dataset::make("DataType",
DataType::F32))),
pool_data_layout_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
}
FIXTURE_DATA_TEST_CASE(RunLarge, CLPoolingLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), combine(PoolingLayerDatasetFP,
framework::dataset::make("DataType",
DataType::F32))),
pool_data_layout_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
}
TEST_SUITE_END() // FP32
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall, CLMixedPrecesionPoolingLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetFPSmall,
framework::dataset::make("DataType", DataType::F16))),
pool_data_layout_dataset),
pool_fp_mixed_precision_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16);
}
FIXTURE_DATA_TEST_CASE(RunLarge, CLMixedPrecesionPoolingLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), combine(PoolingLayerDatasetFP,
framework::dataset::make("DataType", DataType::F16))),
pool_data_layout_dataset),
pool_fp_mixed_precision_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16);
}
TEST_SUITE_END() // FP16
TEST_SUITE_END() // Float
TEST_SUITE(Quantized)
template <typename T>
using CLPoolingLayerQuantizedFixture = PoolingLayerValidationQuantizedFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
TEST_SUITE(QASYMM8)
FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetQASYMM8Small,
framework::dataset::make("DataType", DataType::QASYMM8))),
pool_data_layout_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
TEST_SUITE_END() // QASYMM8
TEST_SUITE(QASYMM8_SIGNED)
FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetQASYMM8Small,
framework::dataset::make("DataType", DataType::QASYMM8_SIGNED))),
pool_data_layout_dataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8_s);
}
TEST_SUITE_END() // QASYMM8_SIGNED
TEST_SUITE_END() // Quantized
TEST_SUITE_END() // PoolingLayer
TEST_SUITE_END() // CL
} // namespace validation
} // namespace test
} // namespace arm_compute
|
