1 /*
2 * Copyright (c) 2017-2021 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/Types.h"
25 #include "arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h"
26 #include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
27 #include "arm_compute/runtime/NEON/functions/NEFuseBatchNormalization.h"
28 #include "arm_compute/runtime/Tensor.h"
29 #include "arm_compute/runtime/TensorAllocator.h"
30 #include "tests/NEON/Accessor.h"
31 #include "tests/PaddingCalculator.h"
32 #include "tests/datasets/RandomBatchNormalizationLayerDataset.h"
33 #include "tests/datasets/ShapeDatasets.h"
34 #include "tests/datasets/SmallConvolutionLayerDataset.h"
35 #include "tests/framework/Asserts.h"
36 #include "tests/framework/Macros.h"
37 #include "tests/framework/datasets/Datasets.h"
38 #include "tests/validation/Helpers.h"
39 #include "tests/validation/Validation.h"
40 #include "tests/validation/fixtures/BatchNormalizationLayerFixture.h"
41 #include "tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h"
42
43 namespace arm_compute
44 {
45 namespace test
46 {
47 namespace validation
48 {
49 namespace
50 {
51 RelativeTolerance<float> rel_tolerance_f32(0.05f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
52 constexpr AbsoluteTolerance<float> abs_tolerance_f32(0.0001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
53 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
54 constexpr AbsoluteTolerance<float> abs_tolerance_f16(0.015f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
55 #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
56
57 const auto act_infos = framework::dataset::make("ActivationInfo",
58 {
59 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
60 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
61 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
62 });
63 const auto common_fusion_dataset = combine(combine(combine(framework::dataset::make("UseBias", { false, true }),
64 framework::dataset::make("UseBeta", { false, true })),
65 framework::dataset::make("UseGamma", { false, true })),
66 framework::dataset::make("Epsilon", { 0.001f }));
67 } // namespace
68
69 TEST_SUITE(NEON)
70 TEST_SUITE(BatchNormalizationLayer)
71
72 template <typename T>
73 using NEBatchNormalizationLayerFixture = BatchNormalizationLayerValidationFixture<Tensor, Accessor, NEBatchNormalizationLayer, T>;
74
75 // *INDENT-OFF*
76 // clang-format off
77 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
78 framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
79 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types
80 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types
81 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Invalid mean/var/beta/gamma shape
82 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Fused activation's a < b
83 }),
84 framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
85 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
86 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
87 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
88 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
89 })),
90 framework::dataset::make("MVBGInfo",{ TensorInfo(TensorShape(2U), 1, DataType::F32),
91 TensorInfo(TensorShape(2U), 1, DataType::F16),
92 TensorInfo(TensorShape(2U), 1, DataType::F32),
93 TensorInfo(TensorShape(5U), 1, DataType::F32),
94 TensorInfo(TensorShape(2U), 1, DataType::F32),
95 })),
96 framework::dataset::make("ActivationLayerInfo",{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
97 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
98 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
99 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f),
100 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 2.f, 6.f),
101 })),
102 framework::dataset::make("Expected", { true, false, false, false, false})),
103 input_info, output_info, mvbg_info, act_info, expected)
104 {
105 const auto &mean_info = mvbg_info;
106 const auto &var_info = mvbg_info;
107 const auto &beta_info = mvbg_info;
108 const auto &gamma_info = mvbg_info;
109 bool has_error = bool(NEBatchNormalizationLayer::validate(
110 &input_info.clone()->set_is_resizable(false), output_info.total_size() ? &output_info.clone()->set_is_resizable(false) : nullptr,
111 &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false),
112 &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f, act_info));
113 ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
114 }
115 // clang-format on
116 // *INDENT-ON*
117
118 TEST_SUITE(Float)
TEST_SUITE(FP32)119 TEST_SUITE(FP32)
120 FIXTURE_DATA_TEST_CASE(RandomSmall, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallRandomBatchNormalizationLayerDataset(),
121 combine(framework::dataset::make("UseBeta", { false, true }),
122 framework::dataset::make("UseGamma", { false, true }))),
123 act_infos),
124 framework::dataset::make("DataType", DataType::F32)),
125 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
126 {
127 // Validate output
128 validate(Accessor(_target), _reference, abs_tolerance_f32, 0);
129 }
130 FIXTURE_DATA_TEST_CASE(RandomLarge, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeRandomBatchNormalizationLayerDataset(),
131 combine(framework::dataset::make("UseBeta", { false, true }),
132 framework::dataset::make("UseGamma", { false, true }))),
133 act_infos),
134 framework::dataset::make("DataType", DataType::F32)),
135 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
136 {
137 // Validate output
138 validate(Accessor(_target), _reference, abs_tolerance_f32, 0);
139 }
140 TEST_SUITE_END() // F32
141
142 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(FP16)143 TEST_SUITE(FP16)
144 FIXTURE_DATA_TEST_CASE(RandomSmall, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallRandomBatchNormalizationLayerDataset(),
145 combine(framework::dataset::make("UseBeta", { false, true }),
146 framework::dataset::make("UseGamma", { false, true }))),
147 framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
148 framework::dataset::make("DataType", DataType::F16)),
149 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
150 {
151 // Validate output
152 validate(Accessor(_target), _reference, abs_tolerance_f16, 0);
153 }
154
155 FIXTURE_DATA_TEST_CASE(RandomLarge, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::LargeRandomBatchNormalizationLayerDataset(),
156 combine(framework::dataset::make("UseBeta", { false, true }),
157 framework::dataset::make("UseGamma", { false, true }))),
158 framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
159 framework::dataset::make("DataType", DataType::F16)),
160 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
161 {
162 // Validate output
163 validate(Accessor(_target), _reference, abs_tolerance_f16, 0);
164 }
165 TEST_SUITE_END() // FP16
166 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
167 TEST_SUITE_END() // Float
168
169 TEST_SUITE_END() // BatchNormalizationLayer
170
171 TEST_SUITE(BatchNormalizationLayerFusion)
172 template <typename T>
173 using NEBatchNormalizationLayerFusionFixture = BatchNormalizationLayerFusionValidationFixture<Tensor, Accessor, NEConvolutionLayer, NEFuseBatchNormalization, T>;
174
175 // *INDENT-OFF*
176 // clang-format off
177 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(
178 framework::dataset::make("Weights", { TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), // Valid
179 TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), // Mismatching data types
180 TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F16), // Mismatching data types
181 TensorInfo(TensorShape(32U, 13U, 2U, 1U), 1, DataType::F32), // Invalid mean/var/beta/gamma shape
182 }),
183 framework::dataset::make("MVBGInfo",{ TensorInfo(TensorShape(2U), 1, DataType::F32),
184 TensorInfo(TensorShape(2U), 1, DataType::F16),
185 TensorInfo(TensorShape(2U), 1, DataType::F32),
186 TensorInfo(TensorShape(5U), 1, DataType::F32),
187 })),
188 framework::dataset::make("Expected", { true, false, false, false})),
189 weights_info, mvbg_info, expected)
190 {
191 const auto &weights_in_info = weights_info;
192 const auto &mean_info = mvbg_info;
193 const auto &var_info = mvbg_info;
194 const auto &fused_weights_info = weights_info;
195 const auto &fused_bias_info = mvbg_info;
196 const auto &conv_bias_info = mvbg_info;
197 const auto &beta_info = mvbg_info;
198 const auto &gamma_info = mvbg_info;
199 bool has_error = bool(NEFuseBatchNormalization::validate(
200 &weights_in_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false),
201 &var_info.clone()->set_is_resizable(false), &fused_weights_info.clone()->set_is_resizable(false),
202 &fused_bias_info.clone()->set_is_resizable(false), &conv_bias_info.clone()->set_is_resizable(false),
203 &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f));
204 ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
205 }
206 // clang-format on
207 // *INDENT-ON*
208
209 TEST_SUITE(Float)
TEST_SUITE(FP32)210 TEST_SUITE(FP32)
211 FIXTURE_DATA_TEST_CASE(RunSmall, NEBatchNormalizationLayerFusionFixture<float>, framework::DatasetMode::PRECOMMIT,
212 combine(combine(combine(datasets::SmallConvolutionLayerDataset(), common_fusion_dataset),
213 framework::dataset::make("DataType", DataType::F32)),
214 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
215 {
216 // Validate output
217 validate(Accessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
218 }
219 TEST_SUITE_END() // FP32
220 TEST_SUITE_END() // Float
221
222 TEST_SUITE_END() // BatchNormalizationLayerFusion
223 TEST_SUITE_END() // Neon
224 } // namespace validation
225 } // namespace test
226 } // namespace arm_compute
227