Compute Library
 22.11
InstanceNormalizationLayer.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/InstanceNormalizationLayerFixture.h"
36 
37 namespace arm_compute
38 {
39 namespace test
40 {
41 namespace validation
42 {
43 namespace
44 {
45 /** Tolerance for float operations */
46 AbsoluteTolerance<float> tolerance_f32(0.0015f);
47 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
48 // This precision is chosen based on the precision float16_t can provide
49 // for the decimal numbers between 16 and 32 and decided based on multiple
50 // times of execution of tests. Although, with randomly generated numbers
51 // there is no gaurantee that this tolerance will be always large enough.
52 AbsoluteTolerance<half> tolerance_f16(static_cast<half>(0.015625f));
53 #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
54 } // namespace
55 
56 TEST_SUITE(NEON)
57 TEST_SUITE(InstanceNormalizationLayer)
58 
59 // *INDENT-OFF*
60 // clang-format off
62  framework::dataset::make("InputInfo", { TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32), // Mismatching data type input/output
63  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32), // Mismatching shape input/output
64  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 2, DataType::F32), // Number of Input channels != 1
65  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::S16), // DataType != F32
66  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32, DataLayout::NCHW),
67  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32, DataLayout::NHWC),
68  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
69  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
70  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
71  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32)
72  }),
73  framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F16),
74  TensorInfo(TensorShape(256U, 64U, 32U, 4U), 1, DataType::F32),
75  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
76  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::S16),
77  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32, DataLayout::NCHW),
78  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32, DataLayout::NHWC),
79  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
80  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
81  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
82  TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32)
83  })),
84  framework::dataset::make("Expected", { false, false, false, false, true, true, true, true, true, true })),
86 {
87  bool is_valid = bool(NEInstanceNormalizationLayer::validate(&input_info.clone()->set_is_resizable(false),
88  &output_info.clone()->set_is_resizable(false)
89  ));
91 }
92 // clang-format on
93 // *INDENT-ON*
94 
95 template <typename T>
96 using NEInstanceNormalizationLayerFixture = InstanceNormalizationLayerValidationFixture<Tensor, Accessor, NEInstanceNormalizationLayer, T>;
97 
98 TEST_SUITE(FP32)
100  combine(combine(combine(datasets::Small4DShapes(),
101  framework::dataset::make("DataType", DataType::F32)),
102  framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
103  framework::dataset::make("InPlace", { false, true })))
104 {
105  // Validate output
106  validate(Accessor(_target), _reference, tolerance_f32);
107 }
108 
109 TEST_SUITE_END() // FP32
110 
111 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
112 TEST_SUITE(FP16)
114  combine(combine(combine(datasets::SmallShapes(),
117  framework::dataset::make("InPlace", { false, true })))
118 {
119  // Validate output
120  validate(Accessor(_target), _reference, tolerance_f16);
121 }
122 TEST_SUITE_END() // FP16
123 #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
124 
125 TEST_SUITE_END() // InstanceNormalizationLayer
126 TEST_SUITE_END() // Neon
127 } // namespace validation
128 } // namespace test
129 } // namespace arm_compute
InstanceNormalizationLayerValidationFixture< Tensor, Accessor, NEInstanceNormalizationLayer, T > NEInstanceNormalizationLayerFixture
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.
Copyright (c) 2017-2022 Arm Limited.
1 channel, 1 F16 per channel
static Status validate(const ITensorInfo *input, const ITensorInfo *output, float gamma=1.0f, float beta=0.0f, float epsilon=1e-12f)
Static function to check if given info will lead to a valid configuration of NEInstanceNormalizationL...
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
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)
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.
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
combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)))
Definition: AbsLayer.cpp:65