1 /*
2 * Copyright (c) 2017-2020 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> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
55 #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
56 const auto act_infos = framework::dataset::make("ActivationInfo",
57 {
58 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
59 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
60 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
61 });
62 const auto common_fusion_dataset = combine(combine(combine(framework::dataset::make("UseBias", { false, true }),
63 framework::dataset::make("UseBeta", { false, true })),
64 framework::dataset::make("UseGamma", { false, true })),
65 framework::dataset::make("Epsilon", { 0.001f }));
66 } // namespace
67
68 TEST_SUITE(NEON)
69 TEST_SUITE(BatchNormalizationLayer)
70
71 template <typename T>
72 using NEBatchNormalizationLayerFixture = BatchNormalizationLayerValidationFixture<Tensor, Accessor, NEBatchNormalizationLayer, T>;
73
74 // *INDENT-OFF*
75 // clang-format off
76 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
77 framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
78 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types
79 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types
80 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Invalid mean/var/beta/gamma shape
81 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Fused activation's a < b
82 }),
83 framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
84 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
85 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
86 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
87 TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
88 })),
89 framework::dataset::make("MVBGInfo",{ TensorInfo(TensorShape(2U), 1, DataType::F32),
90 TensorInfo(TensorShape(2U), 1, DataType::F16),
91 TensorInfo(TensorShape(2U), 1, DataType::F32),
92 TensorInfo(TensorShape(5U), 1, DataType::F32),
93 TensorInfo(TensorShape(2U), 1, DataType::F32),
94 })),
95 framework::dataset::make("ActivationLayerInfo",{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
96 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
97 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
98 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f),
99 ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 2.f, 6.f),
100 })),
101 framework::dataset::make("Expected", { true, false, false, false, false})),
102 input_info, output_info, mvbg_info, act_info, expected)
103 {
104 const auto &mean_info = mvbg_info;
105 const auto &var_info = mvbg_info;
106 const auto &beta_info = mvbg_info;
107 const auto &gamma_info = mvbg_info;
108 bool has_error = bool(NEBatchNormalizationLayer::validate(
109 &input_info.clone()->set_is_resizable(false), output_info.total_size() ? &output_info.clone()->set_is_resizable(false) : nullptr,
110 &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false),
111 &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f, act_info));
112 ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
113 }
114 // clang-format on
115 // *INDENT-ON*
116
117 TEST_SUITE(Float)
TEST_SUITE(FP32)118 TEST_SUITE(FP32)
119 FIXTURE_DATA_TEST_CASE(RandomSmall, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallRandomBatchNormalizationLayerDataset(),
120 combine(framework::dataset::make("UseBeta", { false, true }),
121 framework::dataset::make("UseGamma", { false, true }))),
122 act_infos),
123 framework::dataset::make("DataType", DataType::F32)),
124 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
125 {
126 // Validate output
127 validate(Accessor(_target), _reference, abs_tolerance_f32, 0);
128 }
129 FIXTURE_DATA_TEST_CASE(RandomLarge, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeRandomBatchNormalizationLayerDataset(),
130 combine(framework::dataset::make("UseBeta", { false, true }),
131 framework::dataset::make("UseGamma", { false, true }))),
132 act_infos),
133 framework::dataset::make("DataType", DataType::F32)),
134 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
135 {
136 // Validate output
137 validate(Accessor(_target), _reference, abs_tolerance_f32, 0);
138 }
139 TEST_SUITE_END() // F32
140
141 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(FP16)142 TEST_SUITE(FP16)
143 FIXTURE_DATA_TEST_CASE(RandomSmall, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallRandomBatchNormalizationLayerDataset(),
144 combine(framework::dataset::make("UseBeta", { false, true }),
145 framework::dataset::make("UseGamma", { false, true }))),
146 framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
147 framework::dataset::make("DataType", DataType::F16)),
148 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
149 {
150 // Validate output
151 validate(Accessor(_target), _reference, tolerance_f16, 0);
152 }
153
154 FIXTURE_DATA_TEST_CASE(RandomLarge, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::LargeRandomBatchNormalizationLayerDataset(),
155 combine(framework::dataset::make("UseBeta", { false, true }),
156 framework::dataset::make("UseGamma", { false, true }))),
157 framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
158 framework::dataset::make("DataType", DataType::F16)),
159 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
160 {
161 // Validate output
162 validate(Accessor(_target), _reference, tolerance_f16, 0);
163 }
164 TEST_SUITE_END() // FP16
165 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
166 TEST_SUITE_END() // Float
167
168 TEST_SUITE_END() // BatchNormalizationLayer
169
170 TEST_SUITE(BatchNormalizationLayerFusion)
171 template <typename T>
172 using NEBatchNormalizationLayerFusionFixture = BatchNormalizationLayerFusionValidationFixture<Tensor, Accessor, NEConvolutionLayer, NEFuseBatchNormalization, T>;
173
174 // *INDENT-OFF*
175 // clang-format off
176 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(
177 framework::dataset::make("Weights", { TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), // Valid
178 TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), // Mismatching data types
179 TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F16), // Mismatching data types
180 TensorInfo(TensorShape(32U, 13U, 2U, 1U), 1, DataType::F32), // Invalid mean/var/beta/gamma shape
181 }),
182 framework::dataset::make("MVBGInfo",{ TensorInfo(TensorShape(2U), 1, DataType::F32),
183 TensorInfo(TensorShape(2U), 1, DataType::F16),
184 TensorInfo(TensorShape(2U), 1, DataType::F32),
185 TensorInfo(TensorShape(5U), 1, DataType::F32),
186 })),
187 framework::dataset::make("Expected", { true, false, false, false})),
188 weights_info, mvbg_info, expected)
189 {
190 const auto &weights_in_info = weights_info;
191 const auto &mean_info = mvbg_info;
192 const auto &var_info = mvbg_info;
193 const auto &fused_weights_info = weights_info;
194 const auto &fused_bias_info = mvbg_info;
195 const auto &conv_bias_info = mvbg_info;
196 const auto &beta_info = mvbg_info;
197 const auto &gamma_info = mvbg_info;
198 bool has_error = bool(NEFuseBatchNormalization::validate(
199 &weights_in_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false),
200 &var_info.clone()->set_is_resizable(false), &fused_weights_info.clone()->set_is_resizable(false),
201 &fused_bias_info.clone()->set_is_resizable(false), &conv_bias_info.clone()->set_is_resizable(false),
202 &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f));
203 ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
204 }
205 // clang-format on
206 // *INDENT-ON*
207
208 TEST_SUITE(Float)
TEST_SUITE(FP32)209 TEST_SUITE(FP32)
210 FIXTURE_DATA_TEST_CASE(RunSmall, NEBatchNormalizationLayerFusionFixture<float>, framework::DatasetMode::PRECOMMIT,
211 combine(combine(combine(datasets::SmallConvolutionLayerDataset(), common_fusion_dataset),
212 framework::dataset::make("DataType", DataType::F32)),
213 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
214 {
215 // Validate output
216 validate(Accessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
217 }
218 TEST_SUITE_END() // FP32
219 TEST_SUITE_END() // Float
220
221 TEST_SUITE_END() // BatchNormalizationLayerFusion
222 TEST_SUITE_END() // NEON
223 } // namespace validation
224 } // namespace test
225 } // namespace arm_compute
226