Compute Library
 22.11
BatchConcatenateLayer.cpp
Go to the documentation of this file.
1 /*
2  * Copyright (c) 2019-2020 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
5  *
6  * Permission is hereby granted, free of charge, to any person obtaining a copy
7  * of this software and associated documentation files (the "Software"), to
8  * deal in the Software without restriction, including without limitation the
9  * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10  * sell copies of the Software, and to permit persons to whom the Software is
11  * furnished to do so, subject to the following conditions:
12  *
13  * The above copyright notice and this permission notice shall be included in all
14  * copies or substantial portions of the Software.
15  *
16  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22  * SOFTWARE.
23  */
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/ConcatenateLayerFixture.h"
35 
36 namespace arm_compute
37 {
38 namespace test
39 {
40 namespace validation
41 {
42 TEST_SUITE(NEON)
43 TEST_SUITE(BatchConcatenateLayer)
44 
45 // *INDENT-OFF*
46 // clang-format off
48  framework::dataset::make("InputInfo1", { TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32), // Mismatching data type input/output
49  TensorInfo(TensorShape(20U, 27U, 4U, 4U), 1, DataType::F32), // Mismatching x dimension
50  TensorInfo(TensorShape(23U, 26U, 4U, 3U), 1, DataType::F32), // Mismatching y dim
51  TensorInfo(TensorShape(23U, 27U, 4U, 3U), 1, DataType::F32), // Mismatching z dim
52  TensorInfo(TensorShape(16U, 27U, 3U, 6U), 1, DataType::F32)
53  }),
54  framework::dataset::make("InputInfo2", { TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32),
55  TensorInfo(TensorShape(23U, 27U, 4U, 4U), 1, DataType::F32),
56  TensorInfo(TensorShape(23U, 27U, 4U, 4U), 1, DataType::F32),
57  TensorInfo(TensorShape(23U, 27U, 3U, 3U), 1, DataType::F32),
58  TensorInfo(TensorShape(16U, 27U, 3U, 6U), 1, DataType::F32)
59  })),
60  framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F16),
61  TensorInfo(TensorShape(23U, 12U, 4U, 4U), 1, DataType::F32),
62  TensorInfo(TensorShape(23U, 27U, 4U, 4U), 1, DataType::F32),
63  TensorInfo(TensorShape(23U, 20U, 4U, 3U), 1, DataType::F32),
64  TensorInfo(TensorShape(16U, 27U, 3U, 12U), 1, DataType::F32)
65  })),
66  framework::dataset::make("Expected", { false, false, false, false, true })),
67  input_info1, input_info2, output_info,expected)
68 {
69  std::vector<TensorInfo> inputs_vector_info;
70  inputs_vector_info.emplace_back(std::move(input_info1));
71  inputs_vector_info.emplace_back(std::move(input_info2));
72 
73  std::vector<const ITensorInfo *> inputs_vector_info_raw;
74  inputs_vector_info_raw.reserve(inputs_vector_info.size());
75  for(auto &input : inputs_vector_info)
76  {
77  inputs_vector_info_raw.emplace_back(&input);
78  }
79 
80  bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw, &output_info.clone()->set_is_resizable(false), 3));
82 }
83 // clang-format on
84 // *INDENT-ON*
85 
86 template <typename T>
87 using NEBatchConcatenateLayerFixture = ConcatenateLayerValidationFixture<Tensor, ITensor, Accessor, NEConcatenateLayer, T>;
88 
89 TEST_SUITE(Float)
90 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
91 TEST_SUITE(FP16)
92 FIXTURE_DATA_TEST_CASE(RunSmall, NEBatchConcatenateLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(concat(datasets::Small2DShapes(), datasets::Tiny4DShapes()),
93  framework::dataset::make("DataType",
94  DataType::F16)),
95  framework::dataset::make("Axis", 3)))
96 {
97  // Validate output
98  validate(Accessor(_target), _reference);
99 }
101  DataType::F16)),
102  framework::dataset::make("Axis", 3)))
103 {
104  // Validate output
105  validate(Accessor(_target), _reference);
106 }
108 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
109 
110 TEST_SUITE(FP32)
111 FIXTURE_DATA_TEST_CASE(RunSmall, NEBatchConcatenateLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(concat(datasets::Small3DShapes(), datasets::Tiny4DShapes()),
112  framework::dataset::make("DataType",
113  DataType::F32)),
114  framework::dataset::make("Axis", 3)))
115 {
116  // Validate output
117  validate(Accessor(_target), _reference);
118 }
120  DataType::F32)),
121  framework::dataset::make("Axis", 3)))
122 {
123  // Validate output
124  validate(Accessor(_target), _reference);
125 }
128 
129 TEST_SUITE(Quantized)
131 FIXTURE_DATA_TEST_CASE(RunSmall, NEBatchConcatenateLayerFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(concat(datasets::Small3DShapes(), datasets::Tiny4DShapes()),
132  framework::dataset::make("DataType",
133  DataType::QASYMM8)),
134  framework::dataset::make("Axis", 3)))
135 {
136  // Validate output
137  validate(Accessor(_target), _reference);
138 }
141 FIXTURE_DATA_TEST_CASE(RunSmall, NEBatchConcatenateLayerFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(concat(datasets::Small3DShapes(), datasets::Tiny4DShapes()),
142  framework::dataset::make("DataType",
143  DataType::QASYMM8_SIGNED)),
144  framework::dataset::make("Axis", 3)))
145 {
146  // Validate output
147  validate(Accessor(_target), _reference);
148 }
151 
154 } // namespace validation
155 } // namespace test
156 } // namespace arm_compute
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
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
ConcatenateLayerValidationFixture< Tensor, ITensor, Accessor, NEConcatenateLayer, T > NEBatchConcatenateLayerFixture
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
static Status validate(const std::vector< const ITensorInfo *> &inputs_vector, const ITensorInfo *output, size_t axis)
Static function to check if given info will lead to a valid configuration of NEConcatenateLayer.
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
combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)))
Definition: AbsLayer.cpp:65