Compute Library
 22.11
NormalizationLayer.cpp
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24 #include "arm_compute/core/Types.h"
28 #include "tests/NEON/Accessor.h"
30 #include "tests/datasets/NormalizationTypesDataset.h"
31 #include "tests/datasets/ShapeDatasets.h"
33 #include "tests/framework/Macros.h"
36 #include "tests/validation/fixtures/NormalizationLayerFixture.h"
37 
38 namespace arm_compute
39 {
40 namespace test
41 {
42 namespace validation
43 {
44 namespace
45 {
46 /** Tolerance for float operations */
47 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
48 constexpr AbsoluteTolerance<float> tolerance_f16(0.1f);
49 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
50 constexpr AbsoluteTolerance<float> tolerance_f32(0.00001f);
51 
52 /** Input data set. */
53 const auto NormalizationDataset = combine(combine(combine(combine(datasets::SmallShapes(), datasets::NormalizationTypes()), framework::dataset::make("NormalizationSize", 3, 9, 2)),
54  framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
55  framework::dataset::make("IsScaled", { true }));
56 const auto NormalizationDatasetFP32 = combine(combine(combine(datasets::NormalizationTypes(), framework::dataset::make("NormalizationSize", 3, 9, 2)),
57  framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
58  framework::dataset::make("IsScaled", { true, false }));
59 } // namespace
60 
61 TEST_SUITE(NEON)
62 TEST_SUITE(NormalizationLayer)
63 
64 // *INDENT-OFF*
65 // clang-format off
66 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
67  framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data type input/output
68  TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching shapes
69  TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Even normalization
70  TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Non implemented IN_MAP_2D
71  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
72  }),
73  framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),
74  TensorInfo(TensorShape(27U, 11U, 2U), 1, DataType::F32),
75  TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
76  TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
77  TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
78  })),
84  })),
85  framework::dataset::make("Expected", { false, false, false, true, true })),
86  input_info, output_info, norm_info, expected)
87 {
88  bool is_valid = bool(NENormalizationLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), norm_info));
90 }
91 // clang-format on
92 // *INDENT-ON*
93 
94 template <typename T>
95 using NENormalizationLayerFixture = NormalizationValidationFixture<Tensor, Accessor, NENormalizationLayer, T>;
96 
97 TEST_SUITE(Float)
98 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
99 TEST_SUITE(FP16)
103 {
104  // Validate output
105  validate(Accessor(_target), _reference, tolerance_f16);
106 }
107 TEST_SUITE_END() // FP16
108 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
109 
110 TEST_SUITE(FP32)
111 FIXTURE_DATA_TEST_CASE(RunSmall, NENormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), NormalizationDatasetFP32),
112  framework::dataset::make("DataType", DataType::F32)),
113  framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
114 {
115  // Validate output
116  validate(Accessor(_target), _reference, tolerance_f32);
117 }
121 {
122  // Validate output
123  validate(Accessor(_target), _reference, tolerance_f32);
124 }
125 TEST_SUITE_END() // FP32
126 TEST_SUITE_END() // Float
127 
128 TEST_SUITE_END() // NormalizationLayer
129 TEST_SUITE_END() // Neon
130 } // namespace validation
131 } // namespace test
132 } // namespace arm_compute
Shape of a tensor.
Definition: TensorShape.h:39
1 channel, 1 F32 per channel
Normalization Layer Information class.
Definition: Types.h:1847
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
RelativeTolerance< half_float::half > tolerance_f16(half_float::half(0.1))
Tolerance value for comparing reference&#39;s output against implementation&#39;s output for DataType::F16...
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
Normalization applied within the same map in 1D region.
TEST_SUITE_END() FIXTURE_DATA_TEST_CASE(RunSmall
[CLActivationLayer Test snippet]
RelativeTolerance< float > tolerance_f32(0.01f)
Tolerance value for comparing reference&#39;s output against implementation&#39;s output for DataType::F32...
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
NormalizationValidationFixture< Tensor, Accessor, NENormalizationLayer, T > NENormalizationLayerFixture
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 NormalizationLayerInfo &norm_info)
Static function to check if given info will lead to a valid configuration of NENormalizationLayer.
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
DataLayout
[DataLayout enum definition]
Definition: Types.h:113
Normalization applied cross maps.
combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)))
Definition: AbsLayer.cpp:65
Normalization applied within the same map in 2D region.