1 /*
2 * Copyright (c) 2018-2021 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"
25 #include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
26 #include "arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h"
27 #include "arm_compute/runtime/Tensor.h"
28 #include "arm_compute/runtime/TensorAllocator.h"
29 #include "src/cpu/operators/CpuConv2d.h"
30 #include "tests/NEON/Accessor.h"
31 #include "tests/PaddingCalculator.h"
32 #include "tests/datasets/DilatedConvolutionLayerDataset.h"
33 #include "tests/framework/Asserts.h"
34 #include "tests/framework/Macros.h"
35 #include "tests/framework/datasets/Datasets.h"
36 #include "tests/validation/Validation.h"
37 #include "tests/validation/fixtures/ConvolutionLayerFixture.h"
38
39 namespace arm_compute
40 {
41 namespace test
42 {
43 namespace validation
44 {
45 namespace
46 {
47 const AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
48 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
49 const AbsoluteTolerance<float> abs_tolerance_f16(0.3f); /**< Absolute tolerance value for comparing reference's output against implementation's output for DataType::F16 */
50 const RelativeTolerance<half_float::half> rel_tolerance_f16(half_float::half(0.2f)); /**< Relative tolerance value for comparing reference's output against implementation's output for DataType::F16 */
51 constexpr float tolerance_num_f16 = 0.07f; /**< Tolerance number for FP16 */
52 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
53 constexpr AbsoluteTolerance<float> tolerance_qasymm8(0.0); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */
54
55 /** CNN data types */
56 const auto CNNDataTypes = framework::dataset::make("DataType",
57 {
58 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
59 DataType::F16,
60 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
61 DataType::F32,
62 DataType::QASYMM8,
63 });
64 } // namespace
65
66 TEST_SUITE(NEON)
TEST_SUITE(DilatedConvolutionLayer)67 TEST_SUITE(DilatedConvolutionLayer)
68
69 // *INDENT-OFF*
70 // clang-format off
71 DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
72 framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32),
73 TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32),
74 TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32),
75 TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32)
76 }),
77 framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32),
78 TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32),
79 TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32),
80 TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16)
81 })),
82 framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(6U, 6U, 1U), 1, DataType::F32),
83 TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32),
84 TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32),
85 TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32)
86 })),
87 framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0),
88 PadStrideInfo(1, 1, 0, 0),
89 PadStrideInfo(2, 1, 0, 0),
90 PadStrideInfo(3, 2, 1, 0)
91 })),
92 framework::dataset::make("Dilation", { Size2D(1U, 2U),
93 Size2D(2U, 1U),
94 Size2D(2U, 2U),
95 Size2D(3U, 3U)
96 })),
97 framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })),
98 input_info, weights_info, output_info, conv_info, dilation, expected)
99 {
100 ConvolutionMethod is_valid = cpu::CpuConv2d::get_convolution_method(&input_info.clone()->set_is_resizable(false),
101 &weights_info.clone()->set_is_resizable(false),
102 &output_info.clone()->set_is_resizable(false),
103 conv_info, WeightsInfo(), dilation);
104 ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
105 }
106 // clang-format on
107 // *INDENT-ON*
108 TEST_SUITE_END() // DilatedConvolutionLayer
109
110 TEST_SUITE(GEMMDilatedConvolutionLayer)
111
112 template <typename T>
113 using NEGEMMDilatedConvolutionLayerFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolutionLayer, T>;
114
115 TEST_SUITE(Float)
116 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(FP16)117 TEST_SUITE(FP16)
118 FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(),
119 framework::dataset::make("ReshapeWeights", { true })),
120 framework::dataset::make("DataType", DataType::F16)),
121 framework::dataset::make("DataLayout", { DataLayout::NCHW })),
122 framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo())))
123 {
124 // Validate output
125 validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16);
126 }
127 FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(),
128 framework::dataset::make("ReshapeWeights", { true })),
129 framework::dataset::make("DataType", DataType::F16)),
130 framework::dataset::make("DataLayout", { DataLayout::NCHW })),
131 framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo())))
132 {
133 // Validate output
134 validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16);
135 }
136 TEST_SUITE_END() // FP16
137 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
138
TEST_SUITE(FP32)139 TEST_SUITE(FP32)
140 FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(),
141 framework::dataset::make("ReshapeWeights", { true })),
142 framework::dataset::make("DataType", DataType::F32)),
143 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
144 framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo())))
145 {
146 // Validate output
147 validate(Accessor(_target), _reference, tolerance_f32);
148 }
149 FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(),
150 framework::dataset::make("ReshapeWeights", { true })),
151 framework::dataset::make("DataType", DataType::F32)),
152 framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
153 framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo())))
154 {
155 // Validate output
156 validate(Accessor(_target), _reference, tolerance_f32);
157 }
158 TEST_SUITE_END() // FP32
159 TEST_SUITE_END() // Float
160
161 template <typename T>
162 using NEGEMMDilatedConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<Tensor, Accessor, NEGEMMConvolutionLayer, T>;
163
164 TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)165 TEST_SUITE(QASYMM8)
166 FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT,
167 combine(combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(),
168 framework::dataset::make("ReshapeWeights", { true })),
169 framework::dataset::make("DataType", DataType::QASYMM8)),
170 framework::dataset::make("DataLayout", { DataLayout::NCHW })),
171 framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })),
172 framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo())))
173 {
174 // Validate output
175 validate(Accessor(_target), _reference, tolerance_qasymm8);
176 }
177 FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY,
178 combine(combine(combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(),
179 framework::dataset::make("ReshapeWeights", { true })),
180 framework::dataset::make("DataType", DataType::QASYMM8)),
181 framework::dataset::make("DataLayout", { DataLayout::NCHW })),
182 framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })),
183 framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo())))
184 {
185 // Validate output
186 validate(Accessor(_target), _reference, tolerance_qasymm8);
187 }
188 TEST_SUITE_END() // QASYMM8
189 TEST_SUITE_END() // Quantized
190
191 TEST_SUITE_END() // GEMMDilatedConvolutionLayer
192 TEST_SUITE_END() // Neon
193 } // namespace validation
194 } // namespace test
195 } // namespace arm_compute
196