Compute Library
 22.11
Tile.cpp
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24 #include "arm_compute/core/Types.h"
28 #include "tests/NEON/Accessor.h"
29 #include "tests/datasets/ShapeDatasets.h"
31 #include "tests/framework/Macros.h"
34 #include "tests/validation/fixtures/TileFixture.h"
35 
36 namespace arm_compute
37 {
38 namespace test
39 {
40 namespace validation
41 {
42 namespace
43 {
44 const auto MultiplesDataset = framework::dataset::make("Multiples", { Multiples{ 3 },
45  Multiples{ 2, 2 },
46  Multiples{ 1, 1, 3, 4 },
47  Multiples{ 2, 1, 2, 2 },
48  Multiples{ 2, 1, 3 },
49  Multiples{ 2, 2, 2 }
50  });
51 } // namespace
52 TEST_SUITE(NEON)
53 TEST_SUITE(Tile)
54 
55 // *INDENT-OFF*
56 // clang-format off
58  framework::dataset::make("InputInfo", { TensorInfo(TensorShape(10, 10), 1, DataType::F32),
59  TensorInfo(TensorShape(10, 10), 1, DataType::F32), // Mismatching shape
60  TensorInfo(TensorShape(10, 10), 1, DataType::F16), // Mismatching type
61  TensorInfo(TensorShape(10, 10), 1, DataType::F32)}), // Wrong multiples
62  framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(10, 20), 1, DataType::F32),
63  TensorInfo(TensorShape(20, 20), 1, DataType::F32),
64  TensorInfo(TensorShape(20, 20), 1, DataType::F32),
65  TensorInfo(TensorShape(10, 20), 1, DataType::F32)})),
66  framework::dataset::make("Multiples",{ Multiples{1, 2}, Multiples{1, 2}, Multiples{0, 1} })),
67  framework::dataset::make("Expected", {true, false, false, false })),
68  input_info, output_info, multiples, expected)
69 {
70  const Status status = NETile::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), multiples);
72 }
73 // clang-format on
74 // *INDENT-ON*
75 
76 template <typename T>
77 using NETileFixture = TileValidationFixture<Tensor, Accessor, NETile, T>;
78 
79 TEST_SUITE(Float)
80 TEST_SUITE(FP16)
81 FIXTURE_DATA_TEST_CASE(RunSmall, NETileFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F16)),
82  MultiplesDataset))
83 {
84  // Validate output
85  validate(Accessor(_target), _reference);
86 }
88 {
89  // Validate output
90  validate(Accessor(_target), _reference);
91 }
92 TEST_SUITE_END() // FP16
93 
94 TEST_SUITE(FP32)
95 FIXTURE_DATA_TEST_CASE(RunSmall, NETileFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)),
96  MultiplesDataset))
97 {
98  // Validate output
99  validate(Accessor(_target), _reference);
100 }
102  MultiplesDataset))
103 {
104  // Validate output
105  validate(Accessor(_target), _reference);
106 }
107 TEST_SUITE_END() // FP32
108 TEST_SUITE_END() // Float
109 
110 TEST_SUITE(Integer)
111 TEST_SUITE(S8)
112 FIXTURE_DATA_TEST_CASE(RunSmall, NETileFixture<int8_t>, framework::DatasetMode::ALL,
113  combine(
114  combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::S8 })),
115  MultiplesDataset))
116 {
117  // Validate output
118  validate(Accessor(_target), _reference);
119 }
120 TEST_SUITE_END() // S8
121 TEST_SUITE_END() // Integer
122 
123 TEST_SUITE(Quantized)
125 FIXTURE_DATA_TEST_CASE(RunSmall, NETileFixture<uint8_t>, framework::DatasetMode::ALL,
126  combine(
127  combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::QASYMM8 })),
128  MultiplesDataset))
129 {
130  // Validate output
131  validate(Accessor(_target), _reference);
132 }
133 TEST_SUITE_END() // QASYMM8
134 TEST_SUITE_END() // Quantized
135 
136 TEST_SUITE_END() // Tile
137 TEST_SUITE_END() // Neon
138 } // namespace validation
139 } // namespace test
140 } // namespace arm_compute
half_float::half half
16-bit floating point type
Definition: Types.h:48
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.
TileValidationFixture< Tensor, Accessor, NETile, T > NETileFixture
Definition: Tile.cpp:77
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]
quantized, asymmetric fixed-point 8-bit number unsigned
validate(CLAccessor(output_state), expected_output)
FIXTURE_DATA_TEST_CASE(RunSmall, CLAbsLayerFixture< half >, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F16)))
Definition: AbsLayer.cpp:50
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Multiples &multiples)
Static function to check if given info will lead to a valid configuration of NETile.
Definition: NETile.cpp:41
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
std::vector< uint32_t > Multiples
Information to produce a tiled version of a Tensor.
Definition: Types.h:456
signed 8-bit number
combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)))
Definition: AbsLayer.cpp:65