/* * 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/functions/CLConvolution.h" #include "arm_compute/runtime/Tensor.h" #include "arm_compute/runtime/TensorAllocator.h" #include "tests/CL/CLAccessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/BorderModeDataset.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/ConvolutionFixture.h" namespace arm_compute { namespace test { namespace validation { TEST_SUITE(CL) TEST_SUITE(CustomConvolution) TEST_SUITE(Square3x3) DATA_TEST_CASE(Configuration, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), datasets::BorderModes()), framework::dataset::make("filter_size", { 3 })), shape, output_data_type, border_mode, filter_size) { // Create tensors CLTensor src = create_tensor(shape, DataType::U8); CLTensor dst = create_tensor(shape, output_data_type); // Create conv matrix std::array conv = { 0 }; ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function CLConvolution3x3 convolution; convolution.configure(&src, &dst, conv.data(), 0, border_mode); // Validate valid region const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), BorderSize(filter_size / 2)); validate(dst.info()->valid_region(), dst_valid_region); // Validate padding PaddingCalculator calculator(shape.x(), 8); calculator.set_border_size(1); calculator.set_border_mode(border_mode); const PaddingSize dst_padding = calculator.required_padding(); calculator.set_accessed_elements(16); calculator.set_access_offset(-1); const PaddingSize src_padding = calculator.required_padding(); validate(src.info()->padding(), src_padding); validate(dst.info()->padding(), dst_padding); } template using CLConvolutionFixture = ConvolutionSquareValidationFixture; TEST_SUITE(U8) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), datasets::BorderModes()), framework::dataset::make("filter_size", { 3 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // U8 TEST_SUITE(S16) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::S16)), datasets::BorderModes()), framework::dataset::make("filter_size", { 3 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // S16 TEST_SUITE_END() // Square 3x3 TEST_SUITE(Square5x5) DATA_TEST_CASE(Configuration, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), datasets::BorderModes()), framework::dataset::make("filter_size", { 5 })), shape, output_data_type, border_mode, filter_size) { // Create tensors CLTensor src = create_tensor(shape, DataType::U8); CLTensor dst = create_tensor(shape, output_data_type); // Create conv matrix std::array conv = { 0 }; ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function CLConvolution5x5 convolution; convolution.configure(&src, &dst, conv.data(), 0, border_mode); // Validate valid region const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), BorderSize(filter_size / 2)); validate(dst.info()->valid_region(), dst_valid_region); // Validate padding PaddingCalculator calculator(shape.x(), 8); calculator.set_border_size(2); calculator.set_border_mode(border_mode); const PaddingSize dst_padding = calculator.required_padding(); calculator.set_accessed_elements(16); calculator.set_access_offset(-2); const PaddingSize src_padding = calculator.required_padding(); validate(src.info()->padding(), src_padding); validate(dst.info()->padding(), dst_padding); } template using CLConvolutionFixture = ConvolutionSquareValidationFixture; TEST_SUITE(U8) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), datasets::BorderModes()), framework::dataset::make("filter_size", { 5 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // U8 TEST_SUITE(S16) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::S16)), datasets::BorderModes()), framework::dataset::make("filter_size", { 5 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // S16 TEST_SUITE_END() // Square5x5 TEST_SUITE(Square7x7) DATA_TEST_CASE(Configuration, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), datasets::BorderModes()), framework::dataset::make("filter_size", { 7 })), shape, output_data_type, border_mode, filter_size) { // Create tensors CLTensor src = create_tensor(shape, DataType::U8); CLTensor dst = create_tensor(shape, output_data_type); // Create conv matrix std::array conv = { 0 }; ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function CLConvolution7x7 convolution; convolution.configure(&src, &dst, conv.data(), 0, border_mode); // Validate valid region const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), BorderSize(filter_size / 2)); validate(dst.info()->valid_region(), dst_valid_region); // Validate padding PaddingCalculator calculator(shape.x(), 8); calculator.set_border_size(3); calculator.set_border_mode(border_mode); const PaddingSize dst_padding = calculator.required_padding(); calculator.set_accessed_elements(16); calculator.set_access_offset(-3); const PaddingSize src_padding = calculator.required_padding(); validate(src.info()->padding(), src_padding); validate(dst.info()->padding(), dst_padding); } template using CLConvolutionFixture = ConvolutionSquareValidationFixture; TEST_SUITE(U8) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), datasets::BorderModes()), framework::dataset::make("filter_size", { 7 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // U8 TEST_SUITE(S16) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::S16)), datasets::BorderModes()), framework::dataset::make("filter_size", { 7 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // S16 TEST_SUITE_END() // Square7x7 TEST_SUITE(Square9x9) DATA_TEST_CASE(Configuration, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), datasets::BorderModes()), framework::dataset::make("filter_size", { 9 })), shape, output_data_type, border_mode, filter_size) { // Create tensors CLTensor src = create_tensor(shape, DataType::U8); CLTensor dst = create_tensor(shape, output_data_type); // Create conv matrix std::array conv = { 0 }; ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function CLConvolution9x9 convolution; convolution.configure(&src, &dst, conv.data(), 0, border_mode); // Validate valid region const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), BorderSize(filter_size / 2)); validate(dst.info()->valid_region(), dst_valid_region); // Validate padding PaddingCalculator calculator(shape.x(), 8); calculator.set_border_size(4); calculator.set_border_mode(border_mode); const PaddingSize dst_padding = calculator.required_padding(); calculator.set_accessed_elements(16); calculator.set_access_offset(-4); const PaddingSize src_padding = calculator.required_padding(); validate(src.info()->padding(), src_padding); validate(dst.info()->padding(), dst_padding); } template using CLConvolutionFixture = ConvolutionSquareValidationFixture; TEST_SUITE(U8) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), datasets::BorderModes()), framework::dataset::make("filter_size", { 9 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // U8 TEST_SUITE(S16) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::S16)), datasets::BorderModes()), framework::dataset::make("filter_size", { 9 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // S16 TEST_SUITE_END() // Square9x9 TEST_SUITE(Rectangle) DATA_TEST_CASE(Configuration, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), datasets::BorderModes()), framework::dataset::make("filter_width", { 3, 5, 7, 9 })), framework::dataset::make("filter_height", { 3, 5, 7, 9 })), shape, output_data_type, border_mode, filter_width, filter_height) { // Create tensors CLTensor src = create_tensor(shape, DataType::U8); CLTensor dst = create_tensor(shape, output_data_type); // Create conv matrix std::vector conv(filter_width * filter_height); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function CLConvolutionRectangle convolution; convolution.configure(&src, &dst, conv.data(), filter_width, filter_height, 1, border_mode); // Validate valid region const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), BorderSize(filter_height / 2, filter_width / 2)); validate(dst.info()->valid_region(), dst_valid_region); // Validate padding PaddingCalculator calculator(shape.x(), 8); calculator.set_border_size(filter_width / 2); calculator.set_border_mode(border_mode); const PaddingSize dst_padding = calculator.required_padding(); calculator.set_accessed_elements(16); calculator.set_access_offset(-(filter_width / 2)); const PaddingSize width_padding = calculator.required_padding(); calculator.set_border_size(filter_height / 2); calculator.set_access_offset(-(filter_height / 2)); const PaddingSize height_padding = calculator.required_padding(); validate(src.info()->padding(), width_padding, height_padding); validate(dst.info()->padding(), dst_padding); } template using CLConvolutionFixture = ConvolutionRectangleValidationFixture; TEST_SUITE(U8) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), datasets::BorderModes()), framework::dataset::make("filter_width", { 3, 5, 7, 9 })), framework::dataset::make("filter_height", { 3, 5, 7, 9 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // U8 TEST_SUITE(S16) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::S16)), datasets::BorderModes()), framework::dataset::make("filter_width", { 3, 5, 7, 9 })), framework::dataset::make("filter_height", { 3, 5, 7, 9 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // S16 TEST_SUITE_END() // Rectangle TEST_SUITE(Separable5x5) template using CLConvolutionFixture = ConvolutionSeparableValidationFixture; TEST_SUITE(U8) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), datasets::BorderModes()), framework::dataset::make("filter_size", { 5 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // U8 TEST_SUITE(S16) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::S16)), datasets::BorderModes()), framework::dataset::make("filter_size", { 5 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // S16 TEST_SUITE_END() // Separable5x5 TEST_SUITE(Separable7x7) template using CLConvolutionFixture = ConvolutionSeparableValidationFixture; TEST_SUITE(U8) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), datasets::BorderModes()), framework::dataset::make("filter_size", { 7 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // U8 TEST_SUITE(S16) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::S16)), datasets::BorderModes()), framework::dataset::make("filter_size", { 7 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // S16 TEST_SUITE_END() // Separable7x7 TEST_SUITE(Separable9x9) template using CLConvolutionFixture = ConvolutionSeparableValidationFixture; TEST_SUITE(U8) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), datasets::BorderModes()), framework::dataset::make("filter_size", { 9 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() // U8 TEST_SUITE(S16) FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::S16)), datasets::BorderModes()), framework::dataset::make("filter_size", { 9 }))) { // Validate output validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() TEST_SUITE_END() // Separable9x9 TEST_SUITE_END() // Custom Convolution TEST_SUITE_END() // CL } // namespace validation } // namespace test } // namespace arm_compute