Compute Library
 23.08
ElementwiseRsqrtLayer.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/ElementwiseUnaryFixture.h"
36 
37 namespace arm_compute
38 {
39 namespace test
40 {
41 namespace validation
42 {
43 namespace
44 {
45 RelativeTolerance<float> tolerance_fp32(0.000001f);
46 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
47 RelativeTolerance<float> tolerance_fp16(0.01f);
48 #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
49 #if defined(__aarch64__)
50 constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(0);
51 constexpr AbsoluteTolerance<int8_t> tolerance_qasymm8_signed(0);
52 #else // #if !defined(__aarch64__)
53 constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); // There is difference of 1, because quantizing in reference uses round policy "TO_NEAREST_UP", where the armv7a neon kernel uses "TO_ZERO"
54 constexpr AbsoluteTolerance<int8_t> tolerance_qasymm8_signed(1);
55 #endif // #if !defined(__aarch64__)
56 } // namespace
57 TEST_SUITE(NEON)
58 TEST_SUITE(RsqrtLayer)
59 
60 // Test test cases will execute the function with dynamic-stated shapes
61 // Since other elementwise unary operations share the same kernel, this tests are added only here.
62 // Also, only FP32 is tested since data type doesn't/shouldn't matter with dynamic shapes.
63 TEST_SUITE(DynamicShape)
64 TEST_SUITE(FP32)
65 
66 template <typename T>
67 using CpuRsqrtDynamicShapeFixture = RsqrtDynamicShapeValidationFixture<Tensor, Accessor, NERsqrtLayer, T>;
68 
70  DataType::F32)))
71 {
72  // Validate output
73  validate(Accessor(_target), _reference, tolerance_fp32);
74 }
75 
76 TEST_SUITE_END() // FP32
77 TEST_SUITE_END() // DynamicShape
78 
79 template <typename T>
80 using NERsqrtLayerFixture = RsqrtValidationFixture<Tensor, Accessor, NERsqrtLayer, T>;
81 
82 template <typename T>
83 using NERsqrtLayerQuantizedFixture = RsqrtQuantizedValidationFixture<Tensor, Accessor, NERsqrtLayer, T>;
84 
85 TEST_SUITE(Float)
86 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
87 TEST_SUITE(FP16)
88 FIXTURE_DATA_TEST_CASE(RunSmall, NERsqrtLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), framework::dataset::make("DataType",
89  DataType::F16)))
90 {
91  // Validate output
92  validate(Accessor(_target), _reference, tolerance_fp16);
93 }
94 FIXTURE_DATA_TEST_CASE(RunLarge, NERsqrtLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), framework::dataset::make("DataType",
95  DataType::F16)))
96 {
97  // Validate output
98  validate(Accessor(_target), _reference, tolerance_fp16);
99 }
100 
101 TEST_SUITE_END() // FP16
102 #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
103 
104 TEST_SUITE(FP32)
105 FIXTURE_DATA_TEST_CASE(RunSmall, NERsqrtLayerFixture<float>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), framework::dataset::make("DataType",
106  DataType::F32)))
107 {
108  // Validate output
109  validate(Accessor(_target), _reference, tolerance_fp32);
110 }
111 
112 TEST_SUITE_END() // FP32
113 TEST_SUITE_END() // Float
114 
115 TEST_SUITE(Quantized)
116 TEST_SUITE(QASYMM8)
118  datasets::SmallShapes(),
119  framework::dataset::make("DataType", DataType::QASYMM8)),
120  framework::dataset::make("InputQInfo", { QuantizationInfo(20, 0) })),
121  framework::dataset::make("OutputQInfo", { QuantizationInfo(0.5, 10) })))
122 {
123  // Validate output
124  validate(Accessor(_target), _reference, tolerance_qasymm8);
125 }
126 TEST_SUITE_END() // QASYMM8
127 
128 TEST_SUITE(QASYMM8_SIGNED)
130  datasets::SmallShapes(),
131  framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
132  framework::dataset::make("InputQInfo", { QuantizationInfo(25, -128) })),
133  framework::dataset::make("OutputQInfo", { QuantizationInfo(0.1, -7) })))
134 {
135  // Validate output
136  validate(Accessor(_target), _reference, tolerance_qasymm8_signed);
137 }
138 TEST_SUITE_END() // QASYMM8_SIGNED
139 TEST_SUITE_END() // Quantized
140 
141 TEST_SUITE_END() // RsqrtLayer
142 TEST_SUITE_END() // Neon
143 } // namespace validation
144 } // namespace test
145 } // namespace arm_compute
Datasets.h
arm_compute::test::validation::TEST_SUITE_END
TEST_SUITE_END() FIXTURE_DATA_TEST_CASE(RunSmall
[CLActivationLayer Test snippet]
Definition: DequantizationLayer.cpp:111
PaddingCalculator.h
arm_compute::test::validation::FIXTURE_DATA_TEST_CASE
FIXTURE_DATA_TEST_CASE(RunSmall, CLAbsLayerFixture< half >, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F16)))
Definition: AbsLayer.cpp:50
arm_compute::QuantizationInfo
Quantization information.
Definition: QuantizationInfo.h:68
arm_compute::test::validation::combine
combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)))
Definition: AbsLayer.cpp:65
Types.h
arm_compute::test::Accessor
Accessor implementation for Tensor objects.
Definition: Accessor.h:35
arm_compute::test::validation::CpuRsqrtDynamicShapeFixture
RsqrtDynamicShapeValidationFixture< Tensor, Accessor, NERsqrtLayer, T > CpuRsqrtDynamicShapeFixture
Definition: ElementwiseRsqrtLayer.cpp:67
arm_compute::test::validation::tolerance_fp16
const AbsoluteTolerance< half > tolerance_fp16(half(0.1f))
arm_compute::test::validation::NERsqrtLayerQuantizedFixture
RsqrtQuantizedValidationFixture< Tensor, Accessor, NERsqrtLayer, T > NERsqrtLayerQuantizedFixture
Definition: ElementwiseRsqrtLayer.cpp:83
arm_compute::test::validation::validate
validate(CLAccessor(output_state), expected_output)
TensorAllocator.h
NEElementwiseUnaryLayer.h
arm_compute::test::framework::DatasetMode::ALL
@ ALL
arm_compute::test::framework::DatasetMode::NIGHTLY
@ NIGHTLY
Asserts.h
Accessor.h
Macros.h
arm_compute::test::framework::DatasetMode::PRECOMMIT
@ PRECOMMIT
Tensor.h
arm_compute::test::framework::dataset::make
std::enable_if< is_container< T >::value, ContainerDataset< T > >::type make(std::string name, T &&values)
Helper function to create a ContainerDataset.
Definition: ContainerDataset.h:160
Validation.h
arm_compute
Copyright (c) 2017-2023 Arm Limited.
Definition: introduction.dox:24
arm_compute::test::validation::TEST_SUITE
TEST_SUITE(QASYMM8_to_F32) FIXTURE_DATA_TEST_CASE(RunSmall
arm_compute::DataType::F16
@ F16
16-bit floating-point number
arm_compute::NEElementwiseUnaryLayer
Basic function to perform unary elementwise operations.
Definition: NEElementwiseUnaryLayer.h:39
arm_compute::test::validation::tolerance_qasymm8_signed
constexpr AbsoluteTolerance< int8_t > tolerance_qasymm8_signed
Definition: Scale.cpp:548
arm_compute::DataType::F32
@ F32
32-bit floating-point number
arm_compute::Tensor
Basic implementation of the tensor interface.
Definition: Tensor.h:37
arm_compute::test::validation::tolerance_fp32
RelativeTolerance< float > tolerance_fp32(0.001f)
Tolerance value for comparing reference's output against implementation's output for FP32 data types.
arm_compute::test::framework::DatasetMode
DatasetMode
Possible dataset modes.
Definition: DatasetModes.h:40
arm_compute::DataType
DataType
Available data types.
Definition: CoreTypes.h:82