Compute Library
 21.11
BatchNormalizationLayer.cpp
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24 #include "arm_compute/core/Types.h"
30 #include "tests/CL/CLAccessor.h"
32 #include "tests/datasets/LargeConvolutionLayerDataset.h"
33 #include "tests/datasets/RandomBatchNormalizationLayerDataset.h"
34 #include "tests/datasets/SmallConvolutionLayerDataset.h"
36 #include "tests/framework/Macros.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 constexpr AbsoluteTolerance<float> tolerance_f16(0.02f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
54 const auto act_infos = framework::dataset::make("ActivationInfo",
55 {
58  ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
59 });
60 
61 const auto common_fusion_dataset = combine(combine(combine(framework::dataset::make("UseBias",
62 { false, true }),
63 framework::dataset::make("UseBeta", { false, true })),
64 framework::dataset::make("UseGamma", { false, true })),
65 framework::dataset::make("Epsilon", { 0.001f }));
66 
67 } // namespace
68 
69 TEST_SUITE(CL)
70 TEST_SUITE(BatchNormalizationLayer)
71 
72 template <typename T>
73 using CLBatchNormalizationLayerFixture = BatchNormalizationLayerValidationFixture<CLTensor, CLAccessor, CLBatchNormalizationLayer, T>;
74 
75 // *INDENT-OFF*
76 // clang-format off
78  framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
79  TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Window shrink
80  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types
81  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types
82  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Invalid mean/var/beta/gamma shape
83  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Unsupported fused activation
84  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Fused activation's a < b
85  }),
86  framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
87  TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
88  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
89  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
90  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
91  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
92  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
93  })),
101  })),
109  })),
110  framework::dataset::make("Expected", { true, false, false, false, false, false, false})),
112 {
113  const auto &mean_info = mvbg_info;
114  const auto &var_info = mvbg_info;
115  const auto &beta_info = mvbg_info;
116  const auto &gamma_info = mvbg_info;
117  bool has_error = bool(CLBatchNormalizationLayer::validate(&input_info.clone()->set_is_resizable(false), (output_info.total_size() == 0) ? nullptr : &output_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false), &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f, act_info));
119 }
120 // clang-format on
121 // *INDENT-ON*
122 
123 TEST_SUITE(Float)
124 TEST_SUITE(FP32)
125 FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallRandomBatchNormalizationLayerDataset(),
126  combine(framework::dataset::make("UseBeta", { false, true }), framework::dataset::make("UseGamma", { false, true }))),
127  act_infos),
130 {
131  // Validate output
132  validate(CLAccessor(_target), _reference, abs_tolerance_f32, 0);
133 }
134 TEST_SUITE_END() //FP32
135 
136 TEST_SUITE(FP16)
137 FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallRandomBatchNormalizationLayerDataset(),
138  combine(framework::dataset::make("UseBeta", { false, true }), framework::dataset::make("UseGamma", { false, true }))),
139  framework::dataset::make("ActivationInfo",
143 {
144  // Validate output
145  validate(CLAccessor(_target), _reference, tolerance_f16, 0);
146 }
147 TEST_SUITE_END() // FP16
148 TEST_SUITE_END() // Float
149 
150 TEST_SUITE_END() // BatchNormalizationLayer
151 
152 TEST_SUITE(BatchNormalizationLayerFusion)
153 // *INDENT-OFF*
154 // clang-format off
156  framework::dataset::make("Weights", { TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), // Valid
157  TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), // Mismatching data types
158  TensorInfo(TensorShape(32U, 13U, 2U, 1U), 1, DataType::F32), // Invalid mean/var/beta/gamma shape
159  }),
163  })),
164  framework::dataset::make("Expected", { true, false, false})),
166 {
167  const auto &weights_in_info = weights_info;
168  const auto &mean_info = mvbg_info;
169  const auto &var_info = mvbg_info;
171  const auto &fused_bias_info = mvbg_info;
172  const auto &conv_bias_info = mvbg_info;
173  const auto &beta_info = mvbg_info;
174  const auto &gamma_info = mvbg_info;
176  &weights_in_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false),
177  &var_info.clone()->set_is_resizable(false), &fused_weights_info.clone()->set_is_resizable(false),
178  &fused_bias_info.clone()->set_is_resizable(false), &conv_bias_info.clone()->set_is_resizable(false),
179  &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f));
181 }
182 // clang-format on
183 // *INDENT-ON*
184 template <typename T>
185 using CLBatchNormalizationLayerFusionFixture = BatchNormalizationLayerFusionValidationFixture<CLTensor, CLAccessor, CLConvolutionLayer, CLFuseBatchNormalization, T>;
186 
187 TEST_SUITE(Float)
188 TEST_SUITE(FP32)
190  combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(), common_fusion_dataset),
191  framework::dataset::make("DataType", DataType::F32)),
192  framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
193 {
194  // Validate output
195  validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
196 }
198  combine(combine(combine(datasets::SmallConvolutionLayerDataset(), common_fusion_dataset),
201 {
202  // Validate output
203  validate(CLAccessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
204 }
205 TEST_SUITE_END() // FP32
206 TEST_SUITE_END() // Float
207 
208 TEST_SUITE_END() // BatchNormalizationLayerFusion
209 TEST_SUITE_END() // CL
210 } // namespace validation
211 } // namespace test
212 } // namespace arm_compute
Shape of a tensor.
Definition: TensorShape.h:39
BatchNormalizationLayerValidationFixture< CLTensor, CLAccessor, CLBatchNormalizationLayer, T > CLBatchNormalizationLayerFixture
half_float::half half
16-bit floating point type
Definition: Types.h:48
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.
Activation Layer Information class.
Definition: Types.h:1509
static Status validate(const ITensorInfo *input_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var, const ITensorInfo *fused_weights, const ITensorInfo *fused_bias, const ITensorInfo *input_bias=nullptr, const ITensorInfo *bn_beta=nullptr, const ITensorInfo *bn_gamma=nullptr, float epsilon=0.001f, FuseBatchNormalizationType fbn_type=FuseBatchNormalizationType::CONVOLUTION)
Static function to check if given info will lead to a valid configuration of CLFuseBatchNormalization...
Copyright (c) 2017-2021 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)
DatasetMode
Possible dataset modes.
Definition: DatasetModes.h:40
TEST_SUITE_END() FIXTURE_DATA_TEST_CASE(RunSmall
[CLActivationLayer Test snippet]
Accessor implementation for CLTensor objects.
Definition: CLAccessor.h:36
TEST_SUITE(U8_to_S8) FIXTURE_DATA_TEST_CASE(RunSmall
validate(CLAccessor(output_state), expected_output)
Num samples, channels, height, width.
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
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *mean, const ITensorInfo *var, const ITensorInfo *beta=nullptr, const ITensorInfo *gamma=nullptr, float epsilon=0.001f, ActivationLayerInfo act_info=ActivationLayerInfo())
Static function to check if given info will lead to a valid configuration of CLBatchNormalizationLaye...
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}))
DataType
Available data types.
Definition: Types.h:79
constexpr float abs_tolerance_f32(0.0001f)
F32 Absolute tolerance value for comparing reference&#39;s output against implementation&#39;s output for flo...
DataLayout
[DataLayout enum definition]
Definition: Types.h:113
BatchNormalizationLayerFusionValidationFixture< CLTensor, CLAccessor, CLConvolutionLayer, CLFuseBatchNormalization, T > CLBatchNormalizationLayerFusionFixture
combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)))
Definition: AbsLayer.cpp:65