| /* |
| * Copyright (c) 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/Helpers.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/runtime/NEON/functions/NEConv3D.h" |
| #include "arm_compute/runtime/Tensor.h" |
| #include "arm_compute/runtime/TensorAllocator.h" |
| #include "tests/NEON/Accessor.h" |
| #include "tests/PaddingCalculator.h" |
| #include "tests/datasets/ShapeDatasets.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/DirectConvolution3DFixture.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| const RelativeTolerance<half_float::half> rel_tolerance_f16(half_float::half(0.2f)); /**< Relative tolerance value for FP16 types */ |
| const AbsoluteTolerance<float> abs_tolerance_f16(0.2f); /**< Absolute tolerance for FP16 types */ |
| constexpr float tolerance_num = 0.07f; /**< Tolerance number for the FP16 implementation */ |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| constexpr AbsoluteTolerance<float> tolerance_fp32(0.001f); /**< Tolerance for floating point tests */ |
| constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance for quantized tests */ |
| |
| /** Activation function Dataset*/ |
| const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) |
| }); |
| |
| const auto data_precommit = combine(combine(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip( |
| datasets::SmallDirectConv3DShapes(), |
| framework::dataset::make("StrideX", { 1, 5, 8 })), |
| framework::dataset::make("StrideY", { 1, 2, 3 })), |
| framework::dataset::make("StrideZ", { 1, 2, 1 })), |
| framework::dataset::make("PadX", { 0, 1, 2 })), |
| framework::dataset::make("PadY", { 0, 2, 1 })), |
| framework::dataset::make("PadZ", { 0, 3, 5 })), |
| framework::dataset::make("KernelWidth", { 3, 5, 9 })), |
| framework::dataset::make("KernelHeight", { 2, 1, 3 })), |
| framework::dataset::make("KernelDepth", { 1, 2, 3 })), |
| framework::dataset::make("NumKernels", { 2, 3, 8 })), |
| framework::dataset::make("HasBias", { true, false })), |
| ActivationFunctionsDataset); |
| } // namespace |
| |
| TEST_SUITE(NEON) |
| TEST_SUITE(Convolution3D) |
| |
| // *INDENT-OFF* |
| // clang-format off |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( |
| framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Mismatching data type input/weights |
| TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Mismatching input feature maps |
| TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid weights dimensions |
| TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NHWC), // Invalid data layout |
| TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid biases size |
| TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid biases dimensions |
| TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid output size |
| TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::U32, DataLayout::NDHWC), // Invalid data type |
| }), |
| framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F16), |
| TensorInfo(TensorShape(4U, 3U, 3U, 3U, 3U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U, 3U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::U32), |
| })), |
| framework::dataset::make("BiasesInfo",{ TensorInfo(TensorShape(4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(3U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U, 2U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(4U), 1U, DataType::F32), |
| })), |
| framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(26U, 11U, 4U), 1U, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::U32), |
| })), |
| framework::dataset::make("Expected", { false, false, false, false, false, false, false, false})), |
| input_info, weights_info, biases_info, output_info, expected) |
| { |
| const Conv3dInfo conv3d_info(Size3D(1, 1, 1), Padding3D(0, 0, 0), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false); |
| bool is_valid = bool(NEConv3D::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv3d_info)); |
| ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); |
| } |
| // clang-format on |
| // *INDENT-ON* |
| |
| template <typename T> |
| using NEDirectConvolution3DFixture = DirectConvolution3DValidationFixture<Tensor, Accessor, NEConv3D, T>; |
| |
| TEST_SUITE(Float) |
| TEST_SUITE(FP32) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(data_precommit, |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("DataLayout", { DataLayout::NDHWC }))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_fp32); |
| } |
| TEST_SUITE_END() // FP32 |
| |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| TEST_SUITE(FP16) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(data_precommit, |
| framework::dataset::make("DataType", DataType::F16)), |
| framework::dataset::make("DataLayout", { DataLayout::NDHWC }))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_f16); |
| } |
| TEST_SUITE_END() // FP16 |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| |
| TEST_SUITE_END() // Float |
| |
| template <typename T> |
| using NEDirectConvolution3DQuantizedFixture = DirectConvolution3DValidationQuantizedFixture<Tensor, Accessor, NEConv3D, T>; |
| |
| TEST_SUITE(Quantized) |
| TEST_SUITE(QASYMM8) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(combine(combine(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(7U, 5U, 3U, 13U, 3U), |
| TensorShape(15U, 7U, 11U, 7U), |
| TensorShape(19U, 5U, 16U, 4U), |
| TensorShape(13U, 5U, 17U, 2U) |
| }), |
| framework::dataset::make("StrideX", { 1, 3, 2, 1 })), |
| framework::dataset::make("StrideY", { 2, 1, 3, 1 })), |
| framework::dataset::make("StrideZ", { 3, 2, 1, 1 })), |
| framework::dataset::make("PadX", { 0, 2, 1, 0 })), |
| framework::dataset::make("PadY", { 1, 0, 2, 0 })), |
| framework::dataset::make("PadZ", { 2, 1, 0, 0 })), |
| framework::dataset::make("KernelWidth", { 3, 7, 5, 1 })), |
| framework::dataset::make("KernelHeight", { 5, 3, 7, 1 })), |
| framework::dataset::make("KernelDepth", { 7, 5, 3, 1 })), |
| framework::dataset::make("NumKernels", { 5, 3, 1, 11 })), |
| framework::dataset::make("HasBias", { true, true, true, false })), |
| framework::dataset::make("Activation", ActivationLayerInfo())), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("DataLayout", DataLayout::NDHWC)), |
| framework::dataset::make("SrcQuantizationInfo", QuantizationInfo(0.1f, 10))), |
| framework::dataset::make("WeightsQuantizationInfo", QuantizationInfo(0.3f, 20))), |
| framework::dataset::make("DstQuantizationInfo", QuantizationInfo(0.2f, 5)))) |
| { |
| validate(Accessor(_target), _reference, tolerance_qasymm8); |
| } |
| |
| TEST_SUITE_END() // QASYMM8 |
| |
| TEST_SUITE(QASYMM8_SIGNED) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(combine(combine(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputShape", { TensorShape(7U, 5U, 3U, 13U, 3U), |
| TensorShape(15U, 7U, 11U, 7U), |
| TensorShape(19U, 5U, 16U, 4U), |
| TensorShape(13U, 5U, 17U, 2U) |
| }), |
| framework::dataset::make("StrideX", { 1, 3, 2, 1 })), |
| framework::dataset::make("StrideY", { 2, 1, 3, 1 })), |
| framework::dataset::make("StrideZ", { 3, 2, 1, 1 })), |
| framework::dataset::make("PadX", { 0, 2, 1, 0 })), |
| framework::dataset::make("PadY", { 1, 0, 2, 0 })), |
| framework::dataset::make("PadZ", { 2, 1, 0, 0 })), |
| framework::dataset::make("KernelWidth", { 3, 7, 5, 1 })), |
| framework::dataset::make("KernelHeight", { 5, 3, 7, 1 })), |
| framework::dataset::make("KernelDepth", { 7, 5, 3, 1 })), |
| framework::dataset::make("NumKernels", { 5, 3, 1, 11 })), |
| framework::dataset::make("HasBias", { true, true, true, false })), |
| framework::dataset::make("Activation", ActivationLayerInfo())), |
| framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), |
| framework::dataset::make("DataLayout", DataLayout::NDHWC)), |
| framework::dataset::make("SrcQuantizationInfo", QuantizationInfo(0.1f, 10))), |
| framework::dataset::make("WeightsQuantizationInfo", QuantizationInfo(0.3f, 20))), |
| framework::dataset::make("DstQuantizationInfo", QuantizationInfo(0.2f, 5)))) |
| { |
| validate(Accessor(_target), _reference, tolerance_qasymm8); |
| } |
| |
| TEST_SUITE_END() // QASYMM8_SIGNED |
| TEST_SUITE_END() // Quantized |
| |
| TEST_SUITE_END() // Convolution3D |
| TEST_SUITE_END() // Neon |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |