Compute Library
 22.05
Pooling3dLayer.cpp
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24 #include "arm_compute/core/Types.h"
28 #include "tests/NEON/Accessor.h"
30 #include "tests/datasets/Pooling3dLayerDataset.h"
31 #include "tests/datasets/PoolingTypesDataset.h"
32 #include "tests/datasets/ShapeDatasets.h"
34 #include "tests/framework/Macros.h"
37 #include "tests/validation/fixtures/Pooling3dLayerFixture.h"
38 
39 namespace arm_compute
40 {
41 namespace test
42 {
43 namespace validation
44 {
45 namespace
46 {
47 /** Input data sets for floating-point data types */
48 const auto Pooling3dLayerDatasetFP = combine(combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size3D(2, 3, 2) })),
49  framework::dataset::make("Stride", { Size3D(1, 1, 1), Size3D(2, 1, 1), Size3D(1, 2, 1), Size3D(2, 2, 1) })),
50  framework::dataset::make("Padding", { Padding3D(0, 1, 0), Padding3D(1, 1, 1) })),
51  framework::dataset::make("ExcludePadding", { true, false }));
52 
53 const auto Pooling3dLayerDatasetFPSmall = combine(combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size3D(2, 2, 2), Size3D(3, 3, 3) })),
54  framework::dataset::make("Stride", { Size3D(2, 2, 2), Size3D(2, 1, 1) })),
55  framework::dataset::make("Padding", { Padding3D(0, 0, 0), Padding3D(1, 1, 1), Padding3D(1, 0, 0) })),
56  framework::dataset::make("ExcludePadding", { true, false }));
57 
58 const auto Pooling3dLayerDatasetQASYMM8Small = combine(combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }),
59  framework::dataset::make("PoolingSize", { Size3D(3, 3, 3) })),
60  framework::dataset::make("Stride", { Size3D(1, 1, 1), Size3D(2, 1, 1), Size3D(1, 2, 1), Size3D(2, 2, 1) })),
61  framework::dataset::make("Padding", { Padding3D(0, 0, 0), Padding3D(1, 1, 1), Padding3D(1, 0, 0) })),
62  framework::dataset::make("ExcludePadding", { true }));
63 
64 const auto Pooling3dLayerDatasetQASYMM8Large = combine(combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }),
65  framework::dataset::make("PoolingSize", { Size3D(3, 3, 3) })),
66  framework::dataset::make("Stride", { Size3D(1, 1, 1), Size3D(2, 2, 1) })),
67  framework::dataset::make("Padding", { Padding3D(0, 0, 0), Padding3D(1, 1, 0) })),
68  framework::dataset::make("ExcludePadding", { true }));
69 
70 using ShapeDataset = framework::dataset::ContainerDataset<std::vector<TensorShape>>;
71 
72 constexpr AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for 32-bit floating-point type */
73 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
74 constexpr AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for 16-bit floating-point type */
75 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
76 constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for unsigned 8-bit asymmetric type */
77 constexpr AbsoluteTolerance<int8_t> tolerance_qasymm8_s(1); /**< Tolerance value for comparing reference's output against implementation's output for signed 8-bit asymmetric type */
78 
79 const auto qasymm8_in_qinfo_dataset = framework::dataset::make("InputQuantInfo", { QuantizationInfo(.2f, 10) });
80 const auto qasymm8_out_qinfo_dataset = framework::dataset::make("OutputQuantInfo",
81 {
82  QuantizationInfo(.2f, 10), // Same qinfo
83  QuantizationInfo(.1f, 5), // Multiplier <= 1
84  QuantizationInfo(2.f, 3) // Multiplier > 1
85 });
86 
87 const auto qasymm8_signed_in_qinfo_dataset = framework::dataset::make("InputQuantInfo", { QuantizationInfo(.2f, -10) });
88 const auto qasymm8_signed_out_qinfo_dataset = framework::dataset::make("OutputQuantInfo",
89 {
90  QuantizationInfo(.2f, -10), // Same qinfo
91  QuantizationInfo(.1f, -5), // Multiplier <= 1
92  QuantizationInfo(2.f, -3) // Multiplier > 1
93 });
94 
95 } //namespace
96 
97 TEST_SUITE(NEON)
98 TEST_SUITE(Pooling3dLayer)
99 
100 // *INDENT-OFF*
101 // clang-format off
102 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
103  framework::dataset::make("InputInfo", { TensorInfo(TensorShape(2U, 27U, 13U, 4U, 3U), 1, DataType::F32, DataLayout::NDHWC), // Mismatching data type
104  TensorInfo(TensorShape(2U, 27U, 13U, 4U, 2U), 1, DataType::F32, DataLayout::NDHWC), // Invalid pad/size combination
105  TensorInfo(TensorShape(2U, 27U, 13U, 4U, 2U), 1, DataType::F32, DataLayout::NDHWC), // Invalid pad/size combination
106  TensorInfo(TensorShape(2U, 27U, 13U, 4U, 3U), 1, DataType::F32, DataLayout::NDHWC), // Invalid output shape
107  TensorInfo(TensorShape(5U, 13U, 15U, 2U, 3U), 1, DataType::F32, DataLayout::NDHWC), // Global Pooling
108  TensorInfo(TensorShape(13U,13U, 5U, 1U, 2U), 1, DataType::F32, DataLayout::NDHWC), // Invalid output Global Pooling
110  TensorInfo(TensorShape(5U, 13U, 13U, 4U, 4U), 1, DataType::F32, DataLayout::NDHWC), // Invalid data type
111  TensorInfo(TensorShape(5U, 13U, 13U, 4U, 4U), 1, DataType::F32, DataLayout::NHWC), // Invalid data layout
117  }),
122  TensorInfo(TensorShape(5U, 1U, 1U, 1U, 3U), 1, DataType::F32, DataLayout::NDHWC), // Global pooling applied
123  TensorInfo(TensorShape(5U, 2U, 2U, 2U, 2U), 1, DataType::F32, DataLayout::NDHWC), // Invalid output Global Pooling
125  TensorInfo(TensorShape(5U, 12U, 12U, 3U, 4U), 1, DataType::QASYMM8, DataLayout::NDHWC), // Invalid data type
126  TensorInfo(TensorShape(5U, 12U, 12U, 3U, 4U), 1, DataType::F32, DataLayout::NDHWC), // Invalid data layout
128  TensorInfo(TensorShape(1U, 15U, 1U, 2U, 4U), 1, DataType::F32, DataLayout::NDHWC), // size larger than height
132  })),
133  framework::dataset::make("PoolInfo", { Pooling3dLayerInfo(PoolingType::AVG, 3, Size3D(1, 1, 1), Padding3D(0, 0, 0)),
134  Pooling3dLayerInfo(PoolingType::AVG, 2, Size3D(1, 1, 1), Padding3D(2, 0, 0)),
135  Pooling3dLayerInfo(PoolingType::AVG, 2, Size3D(1, 1, 1), Padding3D(0, 0, 0)),
136  Pooling3dLayerInfo(PoolingType::L2, 3, Size3D(1, 1, 1), Padding3D(0, 0, 0)),
140  Pooling3dLayerInfo(PoolingType::AVG, 2, Size3D(1U, 1U, 1U), Padding3D(), false),
141  Pooling3dLayerInfo(PoolingType::AVG, 2, Size3D(1U, 1U, 1U), Padding3D(), false),
143  Pooling3dLayerInfo(PoolingType::MAX, 2, Size3D(1, 1, 2), Padding3D(0, 0, 0), false),
144  Pooling3dLayerInfo(PoolingType::AVG, 2, Size3D(2U, 2U, 2U), Padding3D(), false),
145  Pooling3dLayerInfo(PoolingType::AVG, 1, Size3D(2U, 2U, 2U), Padding3D(2, 2, 2), true), // pool size is equal to the padding size
146  Pooling3dLayerInfo(PoolingType::AVG, 1, Size3D(2U, 2U, 2U), Padding3D(2, 2, 2), false), // pool size is equal to the padding size
147  Pooling3dLayerInfo(PoolingType::AVG, 3, Size3D(2U, 2U, 2U), Padding3D(2,1,2,2,1,2), false, false, DimensionRoundingType::CEIL), // CEIL with asymmetric Padding
148  })),
149  framework::dataset::make("Expected", { false, false, false, false, true, false, false, false, false, true , false, true, false, false, false})),
150  input_info, output_info, pool_info, expected)
151 {
152  bool is_valid = bool(NEPooling3dLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), pool_info));
154 }
155 // clang-format on
156 // *INDENT-ON*
157 
158 template <typename T>
159 using NEPoolingLayer3dFixture = Pooling3dLayerValidationFixture<Tensor, Accessor, NEPooling3dLayer, T>;
160 
161 template <typename T>
162 using NESpecial3dPoolingLayerFixture = SpecialPooling3dLayerValidationFixture<Tensor, Accessor, NEPooling3dLayer, T>;
163 
164 template <typename T>
165 using NEPooling3dLayerGlobalFixture = Pooling3dLayerGlobalValidationFixture<Tensor, Accessor, NEPooling3dLayer, T>;
166 
167 // clang-format on
168 // *INDENT-ON*
169 TEST_SUITE(Float)
170 TEST_SUITE(FP32)
171 
172 FIXTURE_DATA_TEST_CASE(RunSpecial, NESpecial3dPoolingLayerFixture<float>, framework::DatasetMode::ALL, datasets::Pooling3dLayerDatasetSpecial() * framework::dataset::make("DataType", DataType::F32))
173 {
174  // Validate output
175  validate(Accessor(_target), _reference, tolerance_f32);
176 }
177 
178 FIXTURE_DATA_TEST_CASE(RunSmall, NEPoolingLayer3dFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::Small5dShapes(), combine(Pooling3dLayerDatasetFPSmall,
180 {
181  // Validate output
182  validate(Accessor(_target), _reference, tolerance_f32);
183 }
184 
186  combine(datasets::Large5dShapes(), combine(Pooling3dLayerDatasetFPSmall, framework::dataset::make("DataType", DataType::F32))))
187 {
188  // Validate output
189  validate(Accessor(_target), _reference, tolerance_f32);
190 }
191 
192 TEST_SUITE(GlobalPooling)
193 // *INDENT-OFF*
194 // clang-format off
197  framework::dataset::make("InputShape", { TensorShape(3U, 27U, 13U, 4U),
198  TensorShape(4U, 27U, 13U, 4U, 2U)
199  }),
201  framework::dataset::make("PoolingSize", { Size3D(27, 13, 4) })),
202  framework::dataset::make("Strides", Size3D(1, 1, 1))),
203  framework::dataset::make("Paddings", Padding3D(0, 0, 0))),
204  framework::dataset::make("ExcludePadding", {false, true})),
206 {
207  // Validate output
208  validate(Accessor(_target), _reference, tolerance_f32);
209 }
210 
213  framework::dataset::make("InputShape", { TensorShape(27U, 13U, 4U, 3U),
214  TensorShape(27U, 13U, 4U, 4U, 2U)
215  }),
218 {
219  // Validate output
220  validate(Accessor(_target), _reference, tolerance_f32);
221 }
222 
225  framework::dataset::make("InputShape", { TensorShape(4U, 79U, 37U, 11U),
226  TensorShape(4U, 79U, 37U, 11U, 2U)
227  }),
229  framework::dataset::make("PoolingSize", { Size3D(79, 37, 11) })),
230  framework::dataset::make("Strides", Size3D(1, 1, 1))),
231  framework::dataset::make("Paddings", Padding3D(0, 0, 0))),
232  framework::dataset::make("ExcludePadding", {false, true})),
234 {
235  // Validate output
236  validate(Accessor(_target), _reference, tolerance_f32);
237 }
238 
239 TEST_SUITE_END() // GlobalPooling
240 TEST_SUITE_END() // FP32
241 
242 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
243 TEST_SUITE(FP16)
244 
245 FIXTURE_DATA_TEST_CASE(RunSmall, NEPoolingLayer3dFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::Small5x5Shapes(), combine(Pooling3dLayerDatasetFPSmall,
247 {
248  // Validate output
249  validate(Accessor(_target), _reference, tolerance_f16);
250 }
251 
252 
253 FIXTURE_DATA_TEST_CASE(RunLarge, NEPoolingLayer3dFixture<half>, framework::DatasetMode::NIGHTLY, combine(datasets::Large5dShapes(), combine(Pooling3dLayerDatasetFP,
254  framework::dataset::make("DataType",
255  DataType::F16))))
256 {
257  // Validate output
258  validate(Accessor(_target), _reference, tolerance_f16);
259 }
260 
261 TEST_SUITE(GlobalPooling)
262 // *INDENT-OFF*
263 // clang-format off
266  framework::dataset::make("InputShape", { TensorShape(3U, 27U, 13U, 4U),
267  TensorShape(4U, 27U, 13U, 4U, 2U)
268  }),
270  framework::dataset::make("PoolingSize", { Size3D(27, 13, 4) })),
271  framework::dataset::make("Strides", Size3D(1, 1, 1))),
272  framework::dataset::make("Paddings", Padding3D(0, 0, 0))),
273  framework::dataset::make("ExcludePadding", {false, true})),
275 {
276  // Validate output
277  validate(Accessor(_target), _reference, tolerance_f16);
278 }
279 
280 
283  framework::dataset::make("InputShape", { TensorShape(27U, 13U, 4U, 3U),
284  TensorShape(27U, 13U, 4U, 4U, 2U)
285  }),
288 {
289  // Validate output
290  validate(Accessor(_target), _reference, tolerance_f16);
291 }
292 
295  framework::dataset::make("InputShape", { TensorShape(4U, 79U, 37U, 11U),
296  TensorShape(4U, 79U, 37U, 11U, 2U)
297  }),
299  framework::dataset::make("PoolingSize", { Size3D(79, 37, 11) })),
300  framework::dataset::make("Strides", Size3D(1, 1, 1))),
301  framework::dataset::make("Paddings", Padding3D(0, 0, 0))),
302  framework::dataset::make("ExcludePadding", false)),
304 {
305  // Validate output
306  validate(Accessor(_target), _reference, tolerance_f16);
307 }
308 
309 // clang-format on
310 // *INDENT-ON*
311 TEST_SUITE_END() // GlobalPooling
312 TEST_SUITE_END() // FP16
313 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
314 TEST_SUITE_END() // Float
315 TEST_SUITE(Quantized)
316 
317 template <typename T>
318 using NEPooling3dLayerQuantizedFixture = Pooling3dLayerValidationQuantizedFixture<Tensor, Accessor, NEPooling3dLayer, T>;
319 
321 FIXTURE_DATA_TEST_CASE(RunSmall, NEPooling3dLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::Small5dShapes(),
322  combine(Pooling3dLayerDatasetQASYMM8Small,
323  framework::dataset::make("DataType", DataType::QASYMM8))),
324  qasymm8_in_qinfo_dataset),
325  qasymm8_out_qinfo_dataset))
326 {
327  // Validate output
328  validate(Accessor(_target), _reference, tolerance_qasymm8);
329 }
330 
331 FIXTURE_DATA_TEST_CASE(RunLarge, NEPooling3dLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::Large5dShapes(),
332  combine(Pooling3dLayerDatasetQASYMM8Large,
334  qasymm8_in_qinfo_dataset),
335  qasymm8_out_qinfo_dataset))
336 {
337  // Validate output
338  validate(Accessor(_target), _reference, tolerance_qasymm8);
339 }
340 
341 TEST_SUITE_END() // QASYMM8
342 
344 
345 FIXTURE_DATA_TEST_CASE(RunSmall, NEPooling3dLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::Small5dShapes(),
346  combine(Pooling3dLayerDatasetQASYMM8Small,
347  framework::dataset::make("DataType", DataType::QASYMM8_SIGNED))),
348  qasymm8_signed_in_qinfo_dataset),
349  qasymm8_signed_out_qinfo_dataset))
350 {
351  // Validate output
352  validate(Accessor(_target), _reference, tolerance_qasymm8_s);
353 }
354 
355 TEST_SUITE_END() // QASYMM8_SIGNED
356 TEST_SUITE_END() // Quantized
357 TEST_SUITE_END() // Pooling3dLayer
358 TEST_SUITE_END() // NEON
359 } // namespace validation
360 } // namespace test
361 } // namespace arm_compute
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Pooling3dLayerInfo &pool_info)
Static function to check if given info will lead to a valid configuration of NEPooling3dLayer.
Shape of a tensor.
Definition: TensorShape.h:39
RelativeTolerance< float > tolerance_f32(0.001f)
F32 Tolerance value for comparing reference&#39;s output against implementation&#39;s output for floating poi...
SpecialPooling3dLayerValidationFixture< Tensor, Accessor, NEPooling3dLayer, T > NESpecial3dPoolingLayerFixture
Class for specifying the size of a 3D shape or object.
Definition: Size3D.h:32
1 channel, 1 F32 per channel
ARM_COMPUTE_EXPECT(has_error==expected, framework::LogLevel::ERRORS)
std::enable_if< is_container< T >::value, ContainerDataset< T > >::type make(std::string name, T &&values)
Helper function to create a ContainerDataset.
Copyright (c) 2017-2022 Arm Limited.
1 channel, 1 F16 per channel
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16), }), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16, QuantizationInfo(1.f/32768.f, 0)), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16, QuantizationInfo(1.f/32768.f, 0)), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16, QuantizationInfo(1.f/32768.f, 0)), })), framework::dataset::make("ActivationInfo", { ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::SQRT), })), framework::dataset::make("Expected", { false, true, true, true, false, false, true, true, false })), input_info, output_info, act_info, expected)
Accessor implementation for Tensor objects.
Definition: Accessor.h:35
DatasetMode
Possible dataset modes.
Definition: DatasetModes.h:40
TEST_SUITE_END() FIXTURE_DATA_TEST_CASE(RunSmall
[CLActivationLayer Test snippet]
quantized, asymmetric fixed-point 8-bit number unsigned
Pooling Layer Information struct.
Definition: Types.h:1281
Pooling3dLayerGlobalValidationFixture< Tensor, Accessor, NEPooling3dLayer, T > NEPooling3dLayerGlobalFixture
validate(CLAccessor(output_state), expected_output)
Num samples, depth, height, width, channels.
FIXTURE_DATA_TEST_CASE(RunSmall, CLAbsLayerFixture< half >, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F16)))
Definition: AbsLayer.cpp:50
Num samples, height, width, channels.
Store the tensor&#39;s metadata.
Definition: TensorInfo.h:43
quantized, asymmetric fixed-point 8-bit number signed
RelativeTolerance< half_float::half > tolerance_f16(half(0.2))
F16 Tolerance value for comparing reference&#39;s output against implementation&#39;s output for floating poi...
zip(zip(framework::dataset::make("Weights", { TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U, 1U), 1, DataType::F32), }), framework::dataset::make("MVBGInfo",{ TensorInfo(TensorShape(2U), 1, DataType::F32), TensorInfo(TensorShape(2U), 1, DataType::F16), TensorInfo(TensorShape(5U), 1, DataType::F32), })), framework::dataset::make("Expected", { true, false, false}))
TEST_SUITE(QASYMM8_to_F32) FIXTURE_DATA_TEST_CASE(RunSmall
DataType
Available data types.
Definition: Types.h:79
combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)))
Definition: AbsLayer.cpp:65
Pooling3dLayerValidationFixture< Tensor, Accessor, NEPooling3dLayer, T > NEPoolingLayer3dFixture
Padding information for 3D operations like Conv3d.
Definition: Types.h:786