Compute Library
 22.11
ROIPoolingLayer.cpp
Go to the documentation of this file.
1 /*
2  * Copyright (c) 2021 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/Globals.h"
29 #include "tests/NEON/Accessor.h"
30 #include "tests/datasets/ROIDataset.h"
31 #include "tests/datasets/ShapeDatasets.h"
32 #include "tests/framework/Macros.h"
35 #include "tests/validation/fixtures/ROIPoolingLayerFixture.h"
36 
37 namespace arm_compute
38 {
39 namespace test
40 {
41 namespace validation
42 {
43 namespace
44 {
45 RelativeTolerance<float> relative_tolerance_f32(0.01f);
46 AbsoluteTolerance<float> absolute_tolerance_f32(0.001f);
47 
48 constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1);
49 } // end namespace
50 
51 TEST_SUITE(NEON)
52 TEST_SUITE(RoiPooling)
53 
54 // *INDENT-OFF*
55 // clang-format off
57  framework::dataset::make("InputInfo", { TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Successful test
58  TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::QASYMM8), // Successful test (quantized)
59  TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Incorrect rois type
60  TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching data type input/output
61  TensorInfo(TensorShape(250U, 128U, 2U), 1, DataType::F32), // Mismatching depth size input/output
62  TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching number of rois and output batch size
63  TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Invalid number of values per ROIS
64  TensorInfo(TensorShape(250U, 128U, 3U), 1, DataType::F32), // Mismatching height and width input/output
65 
66  }),
67  framework::dataset::make("RoisInfo", { TensorInfo(TensorShape(5, 4U), 1, DataType::U16),
68  TensorInfo(TensorShape(5, 4U), 1, DataType::U16),
69  TensorInfo(TensorShape(5, 4U), 1, DataType::F16),
70  TensorInfo(TensorShape(5, 4U), 1, DataType::U16),
71  TensorInfo(TensorShape(5, 4U), 1, DataType::U16),
72  TensorInfo(TensorShape(5, 10U), 1, DataType::U16),
73  TensorInfo(TensorShape(4, 4U), 1, DataType::U16),
74  TensorInfo(TensorShape(5, 4U), 1, DataType::U16),
75  })),
76  framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32),
77  TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::QASYMM8),
78  TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32),
79  TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F16),
80  TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32),
81  TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32),
82  TensorInfo(TensorShape(7U, 7U, 3U, 4U), 1, DataType::F32),
83  TensorInfo(TensorShape(5U, 5U, 3U, 4U), 1, DataType::F32),
84  })),
85  framework::dataset::make("PoolInfo", { ROIPoolingLayerInfo(7U, 7U, 1./8),
86  ROIPoolingLayerInfo(7U, 7U, 1./8),
87  ROIPoolingLayerInfo(7U, 7U, 1./8),
88  ROIPoolingLayerInfo(7U, 7U, 1./8),
89  ROIPoolingLayerInfo(7U, 7U, 1./8),
90  ROIPoolingLayerInfo(7U, 7U, 1./8),
91  ROIPoolingLayerInfo(7U, 7U, 1./8),
92  ROIPoolingLayerInfo(7U, 7U, 1./8),
93  })),
94  framework::dataset::make("Expected", { true, true, false, false, false, false, false })),
95  input_info, rois_info, output_info, pool_info, expected)
96 {
97  ARM_COMPUTE_EXPECT(bool(NEROIPoolingLayer::validate(&input_info.clone()->set_is_resizable(true), &rois_info.clone()->set_is_resizable(true), &output_info.clone()->set_is_resizable(true), pool_info)) == expected, framework::LogLevel::ERRORS);
98 }
99 // clang-format on
100 // *INDENT-ON*
101 
102 using NEROIPoolingLayerFloatFixture = ROIPoolingLayerFixture<Tensor, Accessor, NEROIPoolingLayer, float>;
103 
104 TEST_SUITE(Float)
105 FIXTURE_DATA_TEST_CASE(SmallROIPoolingLayerFloat, NEROIPoolingLayerFloatFixture, framework::DatasetMode::ALL,
106  framework::dataset::combine(framework::dataset::combine(datasets::SmallROIDataset(),
107  framework::dataset::make("DataType", { DataType::F32 })),
108  framework::dataset::make("DataLayout", { DataLayout::NCHW })))
109 {
110  // Validate output
111  validate(Accessor(_target), _reference, relative_tolerance_f32, .02f, absolute_tolerance_f32);
112 }
113 
114 TEST_SUITE_END() // Float test suite end
115 
116 // Begin quantized tests
117 TEST_SUITE(Quantized)
118 template <typename T>
119 using NEROIPoolingLayerQuantizedFixture = ROIPoolingLayerQuantizedFixture<Tensor, Accessor, NEROIPoolingLayer, T>;
120 
122 
123 FIXTURE_DATA_TEST_CASE(Small, NEROIPoolingLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL,
124  combine(combine(combine(combine(datasets::SmallROIDataset(),
125  framework::dataset::make("DataType", { DataType::QASYMM8 })),
126  framework::dataset::make("DataLayout", { DataLayout::NCHW })),
127  framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 127) })),
128  framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(2.f / 255.f, 120) })))
129 {
130  // Validate output
131  validate(Accessor(_target), _reference, tolerance_qasymm8);
132 }
133 
134 TEST_SUITE_END() // end qasymm8 tests
135 TEST_SUITE_END() // end quantized tests
136 
137 TEST_SUITE_END() // RoiPooling
138 TEST_SUITE_END() // NEON
139 
140 } // validation end
141 } // test namespace end
142 } // arm_compute namespace end
static Status validate(const ITensorInfo *input, const ITensorInfo *rois, const ITensorInfo *output, const ROIPoolingLayerInfo &pool_info)
Static function to check if given info will lead to a valid configuration of NEROIPoolingLayerKernel...
1 channel, 1 F32 per channel
ARM_COMPUTE_EXPECT(has_error==expected, framework::LogLevel::ERRORS)
ROIPoolingLayerFixture< Tensor, Accessor, NEROIPoolingLayer, float > NEROIPoolingLayerFloatFixture
1 channel, 1 U16 per channel
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
Quantization information.
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)
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
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