| /* |
| * Copyright (c) 2018-2021 Arm Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h" |
| #include "arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h" |
| #include "arm_compute/runtime/Tensor.h" |
| #include "arm_compute/runtime/TensorAllocator.h" |
| #include "src/cpu/operators/CpuConv2d.h" |
| #include "tests/NEON/Accessor.h" |
| #include "tests/PaddingCalculator.h" |
| #include "tests/datasets/DilatedConvolutionLayerDataset.h" |
| #include "tests/framework/Asserts.h" |
| #include "tests/framework/Macros.h" |
| #include "tests/framework/datasets/Datasets.h" |
| #include "tests/validation/Validation.h" |
| #include "tests/validation/fixtures/ConvolutionLayerFixture.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| const AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */ |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| const AbsoluteTolerance<float> abs_tolerance_f16(0.3f); /**< Absolute tolerance value for comparing reference's output against implementation's output for DataType::F16 */ |
| 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 */ |
| constexpr float tolerance_num_f16 = 0.07f; /**< Tolerance number for FP16 */ |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| constexpr AbsoluteTolerance<float> tolerance_qasymm8(0.0); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */ |
| |
| /** CNN data types */ |
| const auto CNNDataTypes = framework::dataset::make("DataType", |
| { |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| DataType::F16, |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| DataType::F32, |
| DataType::QASYMM8, |
| }); |
| } // namespace |
| |
| TEST_SUITE(NEON) |
| TEST_SUITE(DilatedConvolutionLayer) |
| |
| // *INDENT-OFF* |
| // clang-format off |
| DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( |
| framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32), |
| TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32) |
| }), |
| framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32), |
| TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16) |
| })), |
| framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(6U, 6U, 1U), 1, DataType::F32), |
| TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32), |
| TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32) |
| })), |
| framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(2, 1, 0, 0), |
| PadStrideInfo(3, 2, 1, 0) |
| })), |
| framework::dataset::make("Dilation", { Size2D(1U, 2U), |
| Size2D(2U, 1U), |
| Size2D(2U, 2U), |
| Size2D(3U, 3U) |
| })), |
| framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })), |
| input_info, weights_info, output_info, conv_info, dilation, expected) |
| { |
| ConvolutionMethod is_valid = cpu::CpuConv2d::get_convolution_method(&input_info.clone()->set_is_resizable(false), |
| &weights_info.clone()->set_is_resizable(false), |
| &output_info.clone()->set_is_resizable(false), |
| conv_info, WeightsInfo(), dilation); |
| ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); |
| } |
| // clang-format on |
| // *INDENT-ON* |
| TEST_SUITE_END() // DilatedConvolutionLayer |
| |
| TEST_SUITE(GEMMDilatedConvolutionLayer) |
| |
| template <typename T> |
| using NEGEMMDilatedConvolutionLayerFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolutionLayer, T>; |
| |
| TEST_SUITE(Float) |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| TEST_SUITE(FP16) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), |
| framework::dataset::make("ReshapeWeights", { true })), |
| framework::dataset::make("DataType", DataType::F16)), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW })), |
| framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), |
| framework::dataset::make("ReshapeWeights", { true })), |
| framework::dataset::make("DataType", DataType::F16)), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW })), |
| framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16); |
| } |
| TEST_SUITE_END() // FP16 |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| |
| TEST_SUITE(FP32) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), |
| framework::dataset::make("ReshapeWeights", { true })), |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), |
| framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), |
| framework::dataset::make("ReshapeWeights", { true })), |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), |
| framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_f32); |
| } |
| TEST_SUITE_END() // FP32 |
| TEST_SUITE_END() // Float |
| |
| template <typename T> |
| using NEGEMMDilatedConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<Tensor, Accessor, NEGEMMConvolutionLayer, T>; |
| |
| TEST_SUITE(Quantized) |
| TEST_SUITE(QASYMM8) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), |
| framework::dataset::make("ReshapeWeights", { true })), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW })), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), |
| framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, |
| combine(combine(combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), |
| framework::dataset::make("ReshapeWeights", { true })), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW })), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), |
| framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qasymm8); |
| } |
| TEST_SUITE_END() // QASYMM8 |
| TEST_SUITE_END() // Quantized |
| |
| TEST_SUITE_END() // GEMMDilatedConvolutionLayer |
| TEST_SUITE_END() // Neon |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
