Compute Library
 21.02
DequantizationLayer.cpp
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24 #include "arm_compute/core/Types.h"
28 #include "tests/NEON/Accessor.h"
30 #include "tests/datasets/DatatypeDataset.h"
31 #include "tests/datasets/ShapeDatasets.h"
33 #include "tests/framework/Macros.h"
36 #include "tests/validation/fixtures/DequantizationLayerFixture.h"
37 
38 namespace arm_compute
39 {
40 namespace test
41 {
42 namespace validation
43 {
44 namespace
45 {
46 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
47 const auto data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32 });
48 #else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
49 const auto data_types = framework::dataset::make("DataType", { DataType::F32 });
50 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
51 
52 const auto dataset_quant_f32 = combine(combine(combine(datasets::SmallShapes(), datasets::QuantizedTypes()),
54  framework::dataset::make("DataLayout", { DataLayout::NCHW }));
55 const auto dataset_quant_f16 = combine(combine(combine(datasets::SmallShapes(), datasets::QuantizedTypes()),
57  framework::dataset::make("DataLayout", { DataLayout::NCHW }));
58 const auto dataset_quant_asymm_signed_f32 = combine(combine(combine(datasets::SmallShapes(),
59  framework::dataset::make("QuantizedTypes", { DataType::QASYMM8_SIGNED })),
61  framework::dataset::make("DataLayout", { DataLayout::NCHW }));
62 const auto dataset_quant_asymm_signed_f16 = combine(combine(combine(datasets::SmallShapes(),
63  framework::dataset::make("QuantizedTypes", { DataType::QASYMM8_SIGNED })),
65  framework::dataset::make("DataLayout", { DataLayout::NCHW }));
66 const auto dataset_quant_per_channel_f32 = combine(combine(combine(datasets::SmallShapes(), datasets::QuantizedPerChannelTypes()),
69 const auto dataset_quant_per_channel_f16 = combine(combine(combine(datasets::SmallShapes(), datasets::QuantizedPerChannelTypes()),
72 const auto dataset_quant_nightly_f32 = combine(combine(combine(datasets::LargeShapes(), datasets::QuantizedTypes()),
74  framework::dataset::make("DataLayout", { DataLayout::NCHW }));
75 const auto dataset_quant_nightly_f16 = combine(combine(combine(datasets::LargeShapes(), datasets::QuantizedTypes()),
77  framework::dataset::make("DataLayout", { DataLayout::NCHW }));
78 const auto dataset_quant_per_channel_nightly_f32 = combine(combine(combine(datasets::LargeShapes(), datasets::QuantizedPerChannelTypes()),
81 const auto dataset_quant_per_channel_nightly_f16 = combine(combine(combine(datasets::LargeShapes(), datasets::QuantizedPerChannelTypes()),
84 
85 const auto dataset_precommit_f16 = concat(concat(dataset_quant_f16, dataset_quant_per_channel_f16), dataset_quant_asymm_signed_f16);
86 const auto dataset_precommit_f32 = concat(concat(dataset_quant_f32, dataset_quant_per_channel_f32), dataset_quant_asymm_signed_f32);
87 const auto dataset_nightly_f16 = concat(dataset_quant_f16, dataset_quant_per_channel_f16);
88 const auto dataset_nightly_f32 = concat(dataset_quant_f32, dataset_quant_per_channel_f32);
89 
90 } // namespace
91 
92 TEST_SUITE(NEON)
93 TEST_SUITE(DequantizationLayer)
94 
95 // *INDENT-OFF*
96 // clang-format off
97 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(
98  framework::dataset::make("InputInfo", { TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), // Wrong input data type
99  TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Wrong output data type
100  TensorInfo(TensorShape(16U, 16U, 2U, 5U), 1, DataType::QASYMM8), // Missmatching shapes
101  TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Valid
102  TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Valid
103  TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::QASYMM8_SIGNED), // Valid
104  }),
105  framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32),
106  TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8),
107  TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32),
108  TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::F32),
109  TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32),
110  TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32),
111  })),
112  framework::dataset::make("Expected", { false, false, false, true, true, true })),
114 {
115  ARM_COMPUTE_EXPECT(bool(NEDequantizationLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS);
116 }
117 // clang-format on
118 // *INDENT-ON*
119 
120 template <typename T>
121 using NEDequantizationLayerFixture = DequantizationValidationFixture<Tensor, Accessor, NEDequantizationLayer, T>;
122 
123 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
124 TEST_SUITE(FP16)
126 {
127  // Validate output
128  validate(Accessor(_target), _reference);
129 }
131 {
132  // Validate output
133  validate(Accessor(_target), _reference);
134 }
135 TEST_SUITE_END() // FP16
136 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
137 
138 TEST_SUITE(FP32)
139 FIXTURE_DATA_TEST_CASE(RunSmall, NEDequantizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, dataset_precommit_f32)
140 {
141  // Validate output
142  validate(Accessor(_target), _reference);
143 }
145 {
146  // Validate output
147  validate(Accessor(_target), _reference);
148 }
149 TEST_SUITE_END() // FP32
150 
151 TEST_SUITE_END() // DequantizationLayer
152 TEST_SUITE_END() // Neon
153 } // namespace validation
154 } // namespace test
155 } // namespace arm_compute
Shape of a tensor.
Definition: TensorShape.h:39
1 channel, 1 U8 per channel
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) 2017-2021 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)
Accessor implementation for Tensor objects.
Definition: Accessor.h:35
DatasetMode
Possible dataset modes.
Definition: DatasetModes.h:40
static Status validate(const ITensorInfo *input, const ITensorInfo *output)
Static function to check if given info will lead to a valid configuration of NEDequantizationLayer.
TEST_SUITE_END() FIXTURE_DATA_TEST_CASE(RunSmall
[CLActivationLayer Test snippet]
quantized, asymmetric fixed-point 8-bit number unsigned
TEST_SUITE(U8_to_S8) FIXTURE_DATA_TEST_CASE(RunSmall
validate(CLAccessor(output_state), expected_output)
DequantizationValidationFixture< Tensor, Accessor, NEDequantizationLayer, T > NEDequantizationLayerFixture
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:45
JoinDataset< T, U > concat(T &&dataset1, U &&dataset2)
Helper function to create a JoinDataset.
Definition: JoinDataset.h:160
quantized, asymmetric fixed-point 8-bit number signed
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}))
combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)))
Definition: AbsLayer.cpp:65