Compute Library
 22.05
L2NormalizeLayer.cpp
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24 #include "arm_compute/core/Types.h"
28 #include "tests/NEON/Accessor.h"
30 #include "tests/datasets/ShapeDatasets.h"
32 #include "tests/framework/Macros.h"
35 #include "tests/validation/fixtures/L2NormalizeLayerFixture.h"
36 
37 namespace arm_compute
38 {
39 namespace test
40 {
41 namespace validation
42 {
43 namespace
44 {
45 /** Tolerance for float operations */
46 RelativeTolerance<float> tolerance_f32(0.00001f);
47 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
48 RelativeTolerance<float> tolerance_f16(0.2f);
49 #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
50 } // namespace
51 
52 TEST_SUITE(NEON)
53 TEST_SUITE(L2NormalizeLayer)
54 
55 // *INDENT-OFF*
56 // clang-format off
58  framework::dataset::make("InputInfo", { TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Mismatching data type input/output
59  TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Mismatching shape input/output
60  TensorInfo(TensorShape(128U, 64U), 2, DataType::F32), // Number of Input channels != 1
61  TensorInfo(TensorShape(128U, 64U), 1, DataType::S16), // DataType != F32
62  TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
63  TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
64  TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
65  TensorInfo(TensorShape(128U, 64U), 1, DataType::F32)
66  }),
67  framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(128U, 64U), 1, DataType::F16),
68  TensorInfo(TensorShape(256U, 64U), 1, DataType::F32),
69  TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
70  TensorInfo(TensorShape(128U, 64U), 1, DataType::S16),
71  TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
72  TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
73  TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
74  TensorInfo(TensorShape(128U, 64U), 1, DataType::F32)
75  })),
76  framework::dataset::make("Axis", {
77  0,
78  0,
79  0,
80  0,
81  static_cast<int>(TensorShape::num_max_dimensions),
82  3,
83  -2,
84  0 })),
85  framework::dataset::make("Expected", { false, false, false, false, true, true, true, true })),
87 {
88  bool is_valid = bool(NEL2NormalizeLayer::validate(&input_info.clone()->set_is_resizable(false),
89  &output_info.clone()->set_is_resizable(false),
90  axis));
92 }
93 // clang-format on
94 // *INDENT-ON*
95 
96 template <typename T>
97 using NEL2NormalizeLayerFixture = L2NormalizeLayerValidationFixture<Tensor, Accessor, NEL2NormalizeLayer, T>;
98 
99 TEST_SUITE(FP32)
100 FIXTURE_DATA_TEST_CASE(RunSmall, NEL2NormalizeLayerFixture<float>, framework::DatasetMode::PRECOMMIT,
101  combine(combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
102  framework::dataset::make("Axis", { -1, 0, 1, 2 })),
103  framework::dataset::make("Epsilon", { 1e-6 })))
104 {
105  // Validate output
106  validate(Accessor(_target), _reference, tolerance_f32);
107 }
108 
111  framework::dataset::make("Axis", { -1, 0, 2 })),
112  framework::dataset::make("Epsilon", { 1e-6 })))
113 {
114  // Validate output
115  validate(Accessor(_target), _reference, tolerance_f32);
116 }
117 TEST_SUITE_END() // FP32
118 
119 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
120 TEST_SUITE(FP16)
123  framework::dataset::make("Axis", { -1, 0, 1, 2 })),
124  framework::dataset::make("Epsilon", { 1e-6 })))
125 {
126  // Validate output
127  validate(Accessor(_target), _reference, tolerance_f16);
128 }
129 
132  framework::dataset::make("Axis", { -1, 0, 2 })),
133  framework::dataset::make("Epsilon", { 1e-6 })))
134 {
135  // Validate output
136  validate(Accessor(_target), _reference, tolerance_f16);
137 }
138 TEST_SUITE_END() // FP16
139 #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
140 
141 TEST_SUITE_END() // L2NormalizeLayer
142 TEST_SUITE_END() // Neon
143 } // namespace validation
144 } // namespace test
145 } // namespace arm_compute
RelativeTolerance< float > tolerance_f32(0.001f)
F32 Tolerance value for comparing reference&#39;s output against implementation&#39;s output for floating poi...
1 channel, 1 F32 per channel
L2NormalizeLayerValidationFixture< Tensor, Accessor, NEL2NormalizeLayer, T > NEL2NormalizeLayerFixture
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]
validate(CLAccessor(output_state), expected_output)
1 channel, 1 S16 per channel
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.
static Status validate(const ITensorInfo *input, const ITensorInfo *output, int axis, float epsilon=1e-6f)
Static function to check if given info will lead to a valid configuration of NEL2NormalizeLayer.
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}))
static constexpr size_t num_max_dimensions
Number of dimensions the tensor has.
Definition: Dimensions.h:46
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
combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)))
Definition: AbsLayer.cpp:65