| /* |
| * Copyright (c) 2017-2019 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/CL/CLTensor.h" |
| #include "arm_compute/runtime/CL/CLTensorAllocator.h" |
| #include "arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h" |
| #include "tests/CL/CLAccessor.h" |
| #include "tests/PaddingCalculator.h" |
| #include "tests/datasets/DirectConvolutionLayerDataset.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/DirectConvolutionLayerFixture.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| // COMPMID-517 Investigate the mismatch to see whether it is a real bug |
| RelativeTolerance<half> tolerance_fp16(half(0.2)); /**< Tolerance for floating point tests */ |
| RelativeTolerance<float> tolerance_fp32(0.02f); /**< Tolerance for floating point tests */ |
| constexpr float tolerance_num = 0.07f; /**< Tolerance number */ |
| constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance for quantized tests */ |
| |
| const auto data_strides = combine(framework::dataset::make("StrideX", 1, 3), framework::dataset::make("StrideY", 1, 3)); |
| const auto data_strides_small = combine(framework::dataset::make("StrideX", 1), framework::dataset::make("StrideY", 1)); |
| const auto data_ksize_one = combine(framework::dataset::make("PadX", 0, 1), combine(framework::dataset::make("PadY", 0, 1), framework::dataset::make("KernelSize", 1))); |
| const auto data_ksize_one_small = combine(framework::dataset::make("PadX", 0), combine(framework::dataset::make("PadY", 0), framework::dataset::make("KernelSize", 1))); |
| const auto data_ksize_three = combine(framework::dataset::make("PadX", 0, 2), combine(framework::dataset::make("PadY", 0, 2), framework::dataset::make("KernelSize", 3))); |
| const auto data_ksize_five = combine(framework::dataset::make("PadX", 0, 3), combine(framework::dataset::make("PadY", 0, 3), framework::dataset::make("KernelSize", 5))); |
| const auto data_ksize_nine = combine(framework::dataset::make("PadX", 0, 3), combine(framework::dataset::make("PadY", 0, 3), framework::dataset::make("KernelSize", 9))); |
| const auto data_ksize_nine_small = combine(framework::dataset::make("PadX", 0, 1), combine(framework::dataset::make("PadY", 0, 1), framework::dataset::make("KernelSize", 9))); |
| |
| const auto data_all_kernels = concat(concat(data_ksize_one, data_ksize_three), data_ksize_five); |
| |
| const auto data = combine(datasets::SmallDirectConvolutionShapes(), combine(data_strides, data_all_kernels)); |
| const auto data9x9 = combine(datasets::SmallDirectConvolutionShapes(), combine(data_strides, data_ksize_nine)); |
| const auto data_small = combine(datasets::SmallDirectConvolutionShapes(), combine(data_strides_small, data_ksize_one_small)); |
| const auto data_small9x9 = combine(datasets::SmallDirectConvolutionShapes(), combine(data_strides_small, data_ksize_nine_small)); |
| |
| /** Direct convolution nightly data set. */ |
| const auto data_nightly = combine(data, framework::dataset::make("NumKernels", { 1, 4 })); |
| const auto data_nightly_9x9 = combine(data9x9, framework::dataset::make("NumKernels", { 1, 4 })); |
| /** Direct convolution precommit data set. */ |
| const auto data_precommit = combine(data_small, framework::dataset::make("NumKernels", { 1 })); |
| const auto data_precommit_9x9 = combine(data_small9x9, framework::dataset::make("NumKernels", { 1 })); |
| |
| /** Activation function Dataset*/ |
| const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", |
| { ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) }); |
| } // namespace |
| |
| TEST_SUITE(CL) |
| TEST_SUITE(DirectConvolutionLayer) |
| |
| //TODO(COMPMID-415): Configuration tests? |
| |
| // *INDENT-OFF* |
| // clang-format off |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data type input/weights |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching input feature maps |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Unsupported kernel width |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Non-rectangular weights dimensions |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid weights dimensions |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid stride |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases size |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid biases dimensions |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid output size |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Window shrink |
| TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), |
| }), |
| framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F16), |
| TensorInfo(TensorShape(3U, 3U, 3U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(11U, 11U, 2U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(5U, 3U, 2U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U, 3U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32), |
| })), |
| framework::dataset::make("BiasesInfo",{ TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(3U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| TensorInfo(TensorShape(4U), 1, DataType::F32), |
| })), |
| framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(26U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(25U, 11U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32), |
| })), |
| framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(3, 3, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| PadStrideInfo(1, 1, 0, 0), |
| })), |
| framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) |
| })), |
| framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, false, false, true })), |
| input_info, weights_info, biases_info, output_info, conv_info, act_info, expected) |
| { |
| bool is_valid = bool(CLDirectConvolutionLayer::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), conv_info, act_info)); |
| ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); |
| } |
| // clang-format on |
| // *INDENT-ON* |
| |
| template <typename T> |
| using CLDirectConvolutionLayerFixture = DirectConvolutionValidationFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; |
| template <typename T> |
| using CLDirectConvolutionValidationWithTensorShapesFixture = DirectConvolutionValidationWithTensorShapesFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; |
| |
| TEST_SUITE(Float) |
| TEST_SUITE(FP16) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit, framework::dataset::make("DataType", DataType::F16)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", DataLayout::NCHW))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly, framework::dataset::make("DataType", DataType::F16)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", DataLayout::NCHW))) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge9x9, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly_9x9, framework::dataset::make("DataType", |
| DataType::F16)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", { DataLayout::NHWC }))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmall9x9, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit_9x9, framework::dataset::make("DataType", |
| DataType::F16)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", { DataLayout::NHWC }))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num); |
| } |
| TEST_SUITE_END() // FP16 |
| |
| TEST_SUITE(FP32) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit, framework::dataset::make("DataType", |
| DataType::F32)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly, framework::dataset::make("DataType", DataType::F32)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge9x9, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly_9x9, framework::dataset::make("DataType", |
| DataType::F32)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", { DataLayout::NHWC }))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmall9x9, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit_9x9, framework::dataset::make("DataType", |
| DataType::F32)), |
| ActivationFunctionsDataset), |
| framework::dataset::make("DataLayout", { DataLayout::NHWC }))) |
| { |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| TEST_SUITE_END() // FP32 |
| |
| TEST_SUITE(FP32_CustomDataset) |
| FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionValidationWithTensorShapesFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::DirectConvolutionLayerDataset(), |
| framework::dataset::make("DataType", DataType::F32)), |
| ActivationFunctionsDataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_fp32); |
| } |
| TEST_SUITE_END() // FP32_CustomDataset |
| TEST_SUITE_END() // Float |
| |
| template <typename T> |
| using CLDirectConvolutionLayerQuantizedFixture = DirectConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; |
| template <typename T> |
| using CLDirectConvolutionValidationWithTensorShapesQuantizedFixture = DirectConvolutionValidationWithTensorShapesQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; |
| |
| const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f) |
| }); |
| TEST_SUITE(Quantized) |
| TEST_SUITE(QASYMM8) |
| FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit, framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) })), |
| QuantizedActivationFunctionsDataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunSmall9x9, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(data_precommit_9x9, |
| framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) })), |
| QuantizedActivationFunctionsDataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly, framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) })), |
| QuantizedActivationFunctionsDataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge9x9, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly_9x9, framework::dataset::make("DataType", |
| DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10), QuantizationInfo(1.1f, 10) })), |
| QuantizedActivationFunctionsDataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| |
| TEST_SUITE_END() // QASYMM8 |
| |
| TEST_SUITE(QASYMM8_CustomDataset) |
| FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionValidationWithTensorShapesQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::DirectConvolutionLayerDataset(), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127), QuantizationInfo(1.1f, 10) })), |
| QuantizedActivationFunctionsDataset)) |
| { |
| // Validate output |
| validate(CLAccessor(_target), _reference, tolerance_qasymm8); |
| } |
| TEST_SUITE_END() // QASYMM8_CustomDataset |
| TEST_SUITE_END() // Quantized |
| |
| TEST_SUITE_END() // DirectConvolutionLayer |
| TEST_SUITE_END() // Float |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |