diff options
| -rw-r--r-- | src/core/NEON/kernels/NEConvolutionKernel.cpp | 8 | ||||
| -rw-r--r-- | src/runtime/CL/functions/CLConvolution.cpp | 5 | ||||
| -rw-r--r-- | src/runtime/NEON/functions/NEConvolution.cpp | 5 | ||||
| -rw-r--r-- | tests/validation/CL/Convolution.cpp | 220 | ||||
| -rw-r--r-- | tests/validation/NEON/Convolution.cpp | 239 | ||||
| -rw-r--r-- | tests/validation/Validation.cpp | 10 | ||||
| -rw-r--r-- | tests/validation/Validation.h | 8 | ||||
| -rw-r--r-- | tests/validation/fixtures/ConvolutionFixture.h | 130 | ||||
| -rw-r--r-- | tests/validation/reference/Convolution.cpp | 8 | ||||
| -rw-r--r-- | tests/validation/reference/Convolution.h | 4 |
10 files changed, 393 insertions, 244 deletions
diff --git a/src/core/NEON/kernels/NEConvolutionKernel.cpp b/src/core/NEON/kernels/NEConvolutionKernel.cpp index 3a4884eb21..7468f58ca5 100644 --- a/src/core/NEON/kernels/NEConvolutionKernel.cpp +++ b/src/core/NEON/kernels/NEConvolutionKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016, 2017 ARM Limited. + * Copyright (c) 2016, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -1522,13 +1522,13 @@ void NEConvolutionRectangleKernel::run(const Window &window, const ThreadInfo &i }; // Run appropriate function - switch(_output->info()->format()) + switch(_output->info()->data_type()) { - case Format::U8: + case DataType::U8: ARM_COMPUTE_ERROR_ON(_func_idx >= func_table_u8.size()); (this->*func_table_u8[_func_idx])(window); break; - case Format::S16: + case DataType::S16: ARM_COMPUTE_ERROR_ON(_func_idx >= func_table_s16.size()); (this->*func_table_s16[_func_idx])(window); break; diff --git a/src/runtime/CL/functions/CLConvolution.cpp b/src/runtime/CL/functions/CLConvolution.cpp index a9b086773c..0131801679 100644 --- a/src/runtime/CL/functions/CLConvolution.cpp +++ b/src/runtime/CL/functions/CLConvolution.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016, 2017 ARM Limited. + * Copyright (c) 2016, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -53,7 +53,8 @@ CLConvolutionSquare<matrix_size>::CLConvolutionSquare(std::shared_ptr<IMemoryMan } template <unsigned int matrix_size> -void CLConvolutionSquare<matrix_size>::configure(ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) +void CLConvolutionSquare<matrix_size>::configure(ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, + uint8_t constant_border_value) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); ARM_COMPUTE_ERROR_ON(conv == nullptr); diff --git a/src/runtime/NEON/functions/NEConvolution.cpp b/src/runtime/NEON/functions/NEConvolution.cpp index f10ffa6d14..b84dfd344c 100644 --- a/src/runtime/NEON/functions/NEConvolution.cpp +++ b/src/runtime/NEON/functions/NEConvolution.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016, 2017 ARM Limited. + * Copyright (c) 2016, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -54,7 +54,8 @@ NEConvolutionSquare<matrix_size>::NEConvolutionSquare(std::shared_ptr<IMemoryMan } template <unsigned int matrix_size> -void NEConvolutionSquare<matrix_size>::configure(ITensor *input, ITensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) +void NEConvolutionSquare<matrix_size>::configure(ITensor *input, ITensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, + uint8_t constant_border_value) { ARM_COMPUTE_ERROR_ON(conv == nullptr); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); diff --git a/tests/validation/CL/Convolution.cpp b/tests/validation/CL/Convolution.cpp index c836edabb8..d6405474e3 100644 --- a/tests/validation/CL/Convolution.cpp +++ b/tests/validation/CL/Convolution.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -43,30 +43,17 @@ namespace validation { namespace { -/* Convolution3x3 */ -constexpr unsigned int filter_size_3x3 = 3; /* Size of the kernel/filter in number of elements. */ -constexpr BorderSize border_size_3x3(filter_size_3x3 / 2); /* Border size of the kernel/filter around its central element. */ - -/* Convolution5x5 */ -constexpr unsigned int filter_size_5x5 = 5; /* Size of the kernel/filter in number of elements. */ -constexpr BorderSize border_size_5x5(filter_size_5x5 / 2); /* Border size of the kernel/filter around its central element. */ - -/* Convolution7x7 */ -constexpr unsigned int filter_size_7x7 = 7; /* Size of the kernel/filter in number of elements. */ -constexpr BorderSize border_size_7x7(filter_size_7x7 / 2); /* Border size of the kernel/filter around its central element. */ - -/* Convolution9x9 */ -constexpr unsigned int filter_size_9x9 = 9; /* Size of the kernel/filter in number of elements. */ -constexpr BorderSize border_size_9x9(filter_size_9x9 / 2); /* Border size of the kernel/filter around its central element. */ } // namespace TEST_SUITE(CL) TEST_SUITE(CustomConvolution) +TEST_SUITE(CustomConvolutionSquare) TEST_SUITE(CustomConvolution3x3) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes()), - shape, data_type, border_mode) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + framework::dataset::make("filter_size", { 3 })), + shape, data_type, border_mode, filter_size) { // Create tensors CLTensor src = create_tensor<CLTensor>(shape, data_type); @@ -75,20 +62,15 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca // Create conv matrix int16_t conv[9]; - // Generate random scale value between 0 and 255. - std::mt19937 gen(library->seed()); - std::uniform_int_distribution<uint8_t> distribution(0, 255); - const uint32_t scale = distribution(gen); - 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, scale, border_mode); + convolution.configure(&src, &dst, conv, 0, border_mode); // Validate valid region - const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_3x3); + 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 @@ -108,29 +90,33 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca } template <typename T> -using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution3x3, T, filter_size_3x3>; +using CLConvolutionFixture = ConvolutionSquareValidationFixture<CLTensor, CLAccessor, CLConvolution3x3, T>; -FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 3 }))) { // Validate output - validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_3x3)); + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 3 }))) { // Validate output - validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_3x3)); + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() /* Custom_Convolution 3x3 */ TEST_SUITE(CustomConvolution5x5) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes()), - shape, data_type, border_mode) + +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + framework::dataset::make("filter_size", { 5 })), + shape, data_type, border_mode, filter_size) { // Create tensors CLTensor src = create_tensor<CLTensor>(shape, data_type); @@ -139,20 +125,15 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca // Create conv matrix int16_t conv[25]; - // Generate random scale value between 0 and 255. - std::mt19937 gen(library->seed()); - std::uniform_int_distribution<uint8_t> distribution(0, 255); - const uint32_t scale = distribution(gen); - 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, scale, border_mode); + convolution.configure(&src, &dst, conv, 0, border_mode); // Validate valid region - const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_5x5); + 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 @@ -172,29 +153,31 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca } template <typename T> -using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution5x5, T, filter_size_5x5>; - -FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", +using CLConvolutionFixture = ConvolutionSquareValidationFixture<CLTensor, CLAccessor, CLConvolution5x5, T>; +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 5 }))) { // Validate output - validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_5x5)); + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 5 }))) { // Validate output - validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_5x5)); + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() /* Custom Convolution 5x5 */ TEST_SUITE(CustomConvolution7x7) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes()), - shape, data_type, border_mode) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + framework::dataset::make("filter_size", { 7 })), + shape, data_type, border_mode, filter_size) { // Create tensors CLTensor src = create_tensor<CLTensor>(shape, data_type); @@ -203,20 +186,15 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca // Create conv matrix int16_t conv[49]; - // Generate random scale value between 0 and 255. - std::mt19937 gen(library->seed()); - std::uniform_int_distribution<uint8_t> distribution(0, 255); - const uint32_t scale = distribution(gen); - 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, scale, border_mode); + convolution.configure(&src, &dst, conv, 0, border_mode); // Validate valid region - const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_7x7); + 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 @@ -236,29 +214,32 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca } template <typename T> -using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution7x7, T, filter_size_7x7>; +using CLConvolutionFixture = ConvolutionSquareValidationFixture<CLTensor, CLAccessor, CLConvolution7x7, T>; -FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 7 }))) { // Validate output - validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_7x7)); + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 7 }))) { // Validate output - validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_7x7)); + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() /* Custom Convolution 7x7 */ TEST_SUITE(CustomConvolution9x9) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes()), - shape, data_type, border_mode) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + framework::dataset::make("filter_size", { 9 })), + shape, data_type, border_mode, filter_size) { // Create tensors CLTensor src = create_tensor<CLTensor>(shape, data_type); @@ -267,20 +248,15 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca // Create conv matrix int16_t conv[81]; - // Generate random scale value between 0 and 255. - std::mt19937 gen(library->seed()); - std::uniform_int_distribution<uint8_t> distribution(0, 255); - const uint32_t scale = distribution(gen); - 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, scale, border_mode); + convolution.configure(&src, &dst, conv, 0, border_mode); // Validate valid region - const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_9x9); + 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 @@ -300,24 +276,98 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca } template <typename T> -using CLConvolutionFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolution9x9, T, filter_size_9x9>; +using CLConvolutionFixture = ConvolutionSquareValidationFixture<CLTensor, CLAccessor, CLConvolution9x9, T>; -FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 9 }))) { // Validate output - validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_9x9)); + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 9 }))) { // Validate output - validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_9x9)); + validate(CLAccessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2))); } TEST_SUITE_END() /* Custom Convolution 9x9 */ +TEST_SUITE_END() /* Custom Convolution Square */ + +TEST_SUITE(CustomConvolutionRectangle) + +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, 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 })), + shape, data_type, border_mode, filter_width, filter_height) +{ + // Create tensors + CLTensor src = create_tensor<CLTensor>(shape, data_type); + CLTensor dst = create_tensor<CLTensor>(shape, data_type); + + // Create conv matrix + int16_t 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, 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 <typename T> +using CLConvolutionFixture = ConvolutionRectangleValidationFixture<CLTensor, CLAccessor, CLConvolutionRectangle, T>; + +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), 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))); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(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() /* Custom Convolution Rectangle */ TEST_SUITE_END() TEST_SUITE_END() } // namespace validation diff --git a/tests/validation/NEON/Convolution.cpp b/tests/validation/NEON/Convolution.cpp index 0fb61dcf0e..5af803010b 100644 --- a/tests/validation/NEON/Convolution.cpp +++ b/tests/validation/NEON/Convolution.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -49,47 +49,17 @@ namespace * while reference performs direct division with scale. */ constexpr AbsoluteTolerance<uint8_t> tolerance_u8(1); - -/* Convolution3x3 */ -constexpr unsigned int filter_size_3x3 = 3; /* Size of the kernel/filter in number of elements. */ -constexpr BorderSize border_size_3x3(filter_size_3x3 / 2); /* Border size of the kernel/filter around its central element. */ - -/* Convolution5x5 */ -constexpr unsigned int filter_size_5x5 = 5; /* Size of the kernel/filter in number of elements. */ -constexpr BorderSize border_size_5x5(filter_size_5x5 / 2); /* Border size of the kernel/filter around its central element. */ - -/* Convolution7x7 */ -constexpr unsigned int filter_size_7x7 = 7; /* Size of the kernel/filter in number of elements. */ -constexpr BorderSize border_size_7x7(filter_size_7x7 / 2); /* Border size of the kernel/filter around its central element. */ - -/* Convolutionx */ -constexpr unsigned int filter_size_9x9 = 9; /* Size of the kernel/filter in number of elements. */ -constexpr BorderSize border_size_9x9(filter_size_9x9 / 2); /* Border size of the kernel/filter around its central element. */ - -/** Create conv matrix with filter size, and fill them with random value - * - * @param[in/out] conv Convolution matrix to be filled with random int16_t - * @param[in] filter_size Filter Size. - */ -void create_conv(int16_t *conv, const unsigned int filter_size) -{ - std::mt19937 gen(library->seed()); - std::uniform_int_distribution<int16_t> distribution_int16(-32768, 32767); - - for(unsigned int i = 0; i < filter_size * filter_size; ++i) - { - conv[i] = distribution_int16(gen); - } -} } // namespace TEST_SUITE(NEON) TEST_SUITE(CustomConvolution) +TEST_SUITE(CustomConvolutionSuqare) TEST_SUITE(CustomConvolution3x3) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes()), - shape, data_type, border_mode) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + framework::dataset::make("filter_size", { 3 })), + shape, data_type, border_mode, filter_size) { // Create tensors Tensor src = create_tensor<Tensor>(shape, data_type); @@ -97,22 +67,16 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca // Create conv matrix int16_t conv[9]; - create_conv(conv, filter_size_3x3); - - // Generate random scale value between 0 and 255. - std::mt19937 gen(library->seed()); - std::uniform_int_distribution<uint8_t> distribution(0, 255); - uint32_t scale = distribution(gen); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function NEConvolution3x3 convolution; - convolution.configure(&src, &dst, conv, scale, border_mode); + convolution.configure(&src, &dst, conv, 0, border_mode); // Validate valid region - const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_3x3); + 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 @@ -132,29 +96,32 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca } template <typename T> -using NEConvolutionFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolution3x3, T, filter_size_3x3>; +using NEConvolutionFixture = ConvolutionSquareValidationFixture<Tensor, Accessor, NEConvolution3x3, T>; -FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 3 }))) { // Validate output - validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_3x3), tolerance_u8); + validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2)), tolerance_u8); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 3 }))) { // Validate output - validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_3x3), tolerance_u8); + validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2)), tolerance_u8); } TEST_SUITE_END() /* Custom Convolution3x3 */ TEST_SUITE(CustomConvolution5x5) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes()), - shape, data_type, border_mode) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + framework::dataset::make("filter_size", { 5 })), + shape, data_type, border_mode, filter_size) { // Create tensors Tensor src = create_tensor<Tensor>(shape, data_type); @@ -162,22 +129,16 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca // Create conv matrix int16_t conv[25]; - create_conv(conv, filter_size_5x5); - - // Generate random scale value between 0 and 255. - std::mt19937 gen(library->seed()); - std::uniform_int_distribution<uint8_t> distribution(0, 255); - uint32_t scale = distribution(gen); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function NEConvolution5x5 convolution; - convolution.configure(&src, &dst, conv, scale, border_mode); + convolution.configure(&src, &dst, conv, 0, border_mode); // Validate valid region - const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_5x5); + 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 @@ -197,29 +158,32 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca } template <typename T> -using NEConvolutionFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolution5x5, T, filter_size_5x5>; +using NEConvolutionFixture = ConvolutionSquareValidationFixture<Tensor, Accessor, NEConvolution5x5, T>; -FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 5 }))) { // Validate output - validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_5x5), tolerance_u8); + validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2)), tolerance_u8); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 5 }))) { // Validate output - validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_5x5), tolerance_u8); + validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2)), tolerance_u8); } TEST_SUITE_END() /* Custom Convolution 5x5 */ TEST_SUITE(CustomConvolution7x7) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes()), - shape, data_type, border_mode) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + framework::dataset::make("filter_size", { 7 })), + shape, data_type, border_mode, filter_size) { // Create tensors Tensor src = create_tensor<Tensor>(shape, data_type); @@ -227,22 +191,16 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca // Create conv matrix int16_t conv[49]; - create_conv(conv, filter_size_7x7); - - // Generate random scale value between 0 and 255. - std::mt19937 gen(library->seed()); - std::uniform_int_distribution<uint8_t> distribution(0, 255); - uint32_t scale = distribution(gen); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function NEConvolution7x7 convolution; - convolution.configure(&src, &dst, conv, scale, border_mode); + convolution.configure(&src, &dst, conv, 0, border_mode); // Validate valid region - const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_7x7); + 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 @@ -262,29 +220,32 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca } template <typename T> -using NEConvolutionFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolution7x7, T, filter_size_7x7>; +using NEConvolutionFixture = ConvolutionSquareValidationFixture<Tensor, Accessor, NEConvolution7x7, T>; -FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 7 }))) { // Validate output - validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_7x7), tolerance_u8); + validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2)), tolerance_u8); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 7 }))) { // Validate output - validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_7x7), tolerance_u8); + validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2)), tolerance_u8); } TEST_SUITE_END() /* Custom Convolution 7x7 */ TEST_SUITE(CustomConvolution9x9) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes()), - shape, data_type, border_mode) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", DataType::U8)), + datasets::BorderModes()), + framework::dataset::make("filter_size", { 9 })), + shape, data_type, border_mode, filter_size) { // Create tensors Tensor src = create_tensor<Tensor>(shape, data_type); @@ -292,22 +253,16 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca // Create conv matrix int16_t conv[81]; - create_conv(conv, filter_size_9x9); - - // Generate random scale value between 0 and 255. - std::mt19937 gen(library->seed()); - std::uniform_int_distribution<uint8_t> distribution(0, 255); - uint32_t scale = distribution(gen); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function NEConvolution9x9 convolution; - convolution.configure(&src, &dst, conv, scale, border_mode); + convolution.configure(&src, &dst, conv, 0, border_mode); // Validate valid region - const ValidRegion dst_valid_region = shape_to_valid_region(shape, (border_mode == BorderMode::UNDEFINED), border_size_9x9); + 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 @@ -327,24 +282,98 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(conca } template <typename T> -using NEConvolutionFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolution9x9, T, filter_size_9x9>; +using NEConvolutionFixture = ConvolutionSquareValidationFixture<Tensor, Accessor, NEConvolution9x9, T>; -FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 9 }))) { // Validate output - validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_9x9), tolerance_u8); + validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2)), tolerance_u8); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", +FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::U8)), - datasets::BorderModes())) + datasets::BorderModes()), + framework::dataset::make("filter_size", { 9 }))) { // Validate output - validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), border_size_9x9), tolerance_u8); + validate(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2)), tolerance_u8); } TEST_SUITE_END() /* Custom Convolution 9x9 */ +TEST_SUITE_END() /* Custom Convolution Square */ + +TEST_SUITE(CustomConvolutionRectangle) + +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, 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 })), + shape, data_type, border_mode, filter_width, filter_height) +{ + // Create tensors + Tensor src = create_tensor<Tensor>(shape, data_type); + Tensor dst = create_tensor<Tensor>(shape, data_type); + + // Create conv matrix + int16_t 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 + NEConvolutionRectangle convolution; + convolution.configure(&src, &dst, conv, 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 <typename T> +using NEConvolutionFixture = ConvolutionRectangleValidationFixture<Tensor, Accessor, NEConvolutionRectangle, T>; + +FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), 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(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2)), tolerance_u8); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(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(Accessor(_target), _reference, shape_to_valid_region(_reference.shape(), (_border_mode == BorderMode::UNDEFINED), BorderSize(_height / 2, _width / 2)), tolerance_u8); +} +TEST_SUITE_END() TEST_SUITE_END() TEST_SUITE_END() } // namespace validation diff --git a/tests/validation/Validation.cpp b/tests/validation/Validation.cpp index ebca1936e7..d01ac12f97 100644 --- a/tests/validation/Validation.cpp +++ b/tests/validation/Validation.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -170,6 +170,14 @@ void validate(const arm_compute::PaddingSize &padding, const arm_compute::Paddin ARM_COMPUTE_EXPECT_EQUAL(padding.left, reference.left, framework::LogLevel::ERRORS); } +void validate(const arm_compute::PaddingSize &padding, const arm_compute::PaddingSize &width_reference, const arm_compute::PaddingSize &height_reference) +{ + ARM_COMPUTE_EXPECT_EQUAL(padding.top, height_reference.top, framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT_EQUAL(padding.right, width_reference.right, framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT_EQUAL(padding.bottom, height_reference.bottom, framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT_EQUAL(padding.left, width_reference.left, framework::LogLevel::ERRORS); +} + void validate(const IAccessor &tensor, const void *reference_value) { ARM_COMPUTE_ASSERT(reference_value != nullptr); diff --git a/tests/validation/Validation.h b/tests/validation/Validation.h index 1f81d38acd..b12d7de97a 100644 --- a/tests/validation/Validation.h +++ b/tests/validation/Validation.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -163,6 +163,12 @@ void validate(const arm_compute::ValidRegion ®ion, const arm_compute::ValidRe */ void validate(const arm_compute::PaddingSize &padding, const arm_compute::PaddingSize &reference); +/** Validate padding. + * + * Padding on all sides has to be the same. + */ +void validate(const arm_compute::PaddingSize &padding, const arm_compute::PaddingSize &width_reference, const arm_compute::PaddingSize &height_reference); + /** Validate tensors. * * - Dimensionality has to be the same. diff --git a/tests/validation/fixtures/ConvolutionFixture.h b/tests/validation/fixtures/ConvolutionFixture.h index 8bf6ea26a8..114d38a21a 100644 --- a/tests/validation/fixtures/ConvolutionFixture.h +++ b/tests/validation/fixtures/ConvolutionFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -41,44 +41,40 @@ namespace test { namespace validation { -template <typename TensorType, typename AccessorType, typename FunctionType, typename T, const unsigned int filter_size> +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> class ConvolutionValidationFixture : public framework::Fixture { -public: +protected: template <typename...> - void setup(TensorShape shape, DataType data_type, BorderMode border_mode) + void setup(TensorShape shape, DataType data_type, BorderMode border_mode, const unsigned int width, const unsigned int height) { std::mt19937 gen(library->seed()); std::uniform_int_distribution<uint8_t> distribution(0, 255); const uint8_t constant_border_value = distribution(gen); - // Generate random scale value between 0 and 255. - const uint32_t scale = distribution(gen); + // Generate random scale value between 1 and 255. + std::uniform_int_distribution<uint8_t> distribution_scale(1, 255); + const uint32_t scale = distribution_scale(gen); - switch(filter_size) - { - case 3: - case 5: - case 7: - case 9: - int16_t conv[filter_size * filter_size]; - create_conv(conv); - - _target = compute_target(shape, data_type, conv, scale, border_mode, constant_border_value); - _reference = compute_reference(shape, data_type, conv, scale, border_mode, constant_border_value); - break; - default: - ARM_COMPUTE_ERROR("Filter Size Not Supported"); - } + ARM_COMPUTE_ERROR_ON(3 != width && 5 != width && 7 != width && 9 != width); + ARM_COMPUTE_ERROR_ON(3 != height && 5 != height && 7 != height && 9 != height); + + int16_t conv[width * height]; + create_conv(conv); + + _width = width; + _height = height; + _target = compute_target(shape, data_type, conv, scale, border_mode, constant_border_value); + _reference = compute_reference(shape, data_type, conv, scale, border_mode, constant_border_value); } -protected: - void create_conv(int16_t *conv) + void + create_conv(int16_t *conv) { std::mt19937 gen(library->seed()); std::uniform_int_distribution<int16_t> distribution_int16(-32768, 32767); - for(unsigned int i = 0; i < filter_size * filter_size; ++i) + for(unsigned int i = 0; i < _width * _height; ++i) { conv[i] = distribution_int16(gen); } @@ -90,6 +86,40 @@ protected: library->fill_tensor_uniform(tensor, i); } + SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) + { + ARM_COMPUTE_ERROR_ON(data_type != DataType::U8); + + // Create reference + SimpleTensor<T> src{ shape, data_type }; + + // Fill reference + fill(src, 0); + + // Compute reference + return reference::convolution<T>(src, conv, scale, border_mode, constant_border_value, _width, _height); + } + + virtual TensorType compute_target(const TensorShape &shape, DataType data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) = 0; + + BorderMode _border_mode{}; + TensorType _target{}; + SimpleTensor<T> _reference{}; + unsigned int _width{}; + unsigned int _height{}; +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ConvolutionSquareValidationFixture : public ConvolutionValidationFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(TensorShape shape, DataType data_type, BorderMode border_mode, const unsigned int width) + { + ConvolutionValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, border_mode, width, width); + } + +protected: TensorType compute_target(const TensorShape &shape, DataType data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) { // Create tensors @@ -111,32 +141,56 @@ protected: ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); // Fill tensors - fill(AccessorType(src), 0); - fill(AccessorType(dst), 1); + this->fill(AccessorType(src), 0); + this->fill(AccessorType(dst), 1); // Compute function convolution.run(); return dst; } +}; - SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ConvolutionRectangleValidationFixture : public ConvolutionValidationFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(TensorShape shape, DataType data_type, BorderMode border_mode, const unsigned int width, const unsigned int height) { - ARM_COMPUTE_ERROR_ON(data_type != DataType::U8); + ConvolutionValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, border_mode, width, height); + } - // Create reference - SimpleTensor<T> src{ shape, data_type }; +protected: + TensorType compute_target(const TensorShape &shape, DataType data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) + { + // Create tensors + TensorType src = create_tensor<TensorType>(shape, data_type); + TensorType dst = create_tensor<TensorType>(shape, data_type); - // Fill reference - fill(src, 0); + // Create and configure function + FunctionType convolution; + convolution.configure(&src, &dst, conv, this->_width, this->_height, scale, border_mode, constant_border_value); - // Compute reference - return reference::convolution<T>(src, conv, scale, border_mode, constant_border_value, filter_size); - } + ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - BorderMode _border_mode{}; - TensorType _target{}; - SimpleTensor<T> _reference{}; + // Allocate tensors + src.allocator()->allocate(); + dst.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensors + this->fill(AccessorType(src), 0); + this->fill(AccessorType(dst), 1); + + // Compute function + convolution.run(); + + return dst; + } }; } // namespace validation } // namespace test diff --git a/tests/validation/reference/Convolution.cpp b/tests/validation/reference/Convolution.cpp index 84be858cfc..777e2df400 100644 --- a/tests/validation/reference/Convolution.cpp +++ b/tests/validation/reference/Convolution.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -35,7 +35,7 @@ namespace validation namespace reference { template <typename T> -SimpleTensor<T> convolution(const SimpleTensor<T> &src, const int16_t *conv, uint32_t scale, BorderMode border_mode, T constant_border_value, const unsigned int filter_size) +SimpleTensor<T> convolution(const SimpleTensor<T> &src, const int16_t *conv, uint32_t scale, BorderMode border_mode, T constant_border_value, const unsigned int width, const unsigned int height) { SimpleTensor<T> dst(src.shape(), src.data_type()); SimpleTensor<int32_t> sum(src.shape(), src.data_type()); @@ -43,7 +43,7 @@ SimpleTensor<T> convolution(const SimpleTensor<T> &src, const int16_t *conv, uin for(int element_idx = 0; element_idx < src.num_elements(); ++element_idx) { const Coordinates id = index2coord(src.shape(), element_idx); - apply_2d_spatial_filter(id, src, sum, TensorShape(filter_size, filter_size), conv, 1, border_mode, constant_border_value); + apply_2d_spatial_filter(id, src, sum, TensorShape(width, height), conv, 1, border_mode, constant_border_value); if(tensor_elem_at<int32_t>(sum, id, border_mode, constant_border_value) < 0) { @@ -63,7 +63,7 @@ SimpleTensor<T> convolution(const SimpleTensor<T> &src, const int16_t *conv, uin } template SimpleTensor<uint8_t> convolution(const SimpleTensor<uint8_t> &src, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value, - const unsigned int filter_size); + const unsigned int widht, const unsigned int height); } // namespace reference } // namespace validation } // namespace test diff --git a/tests/validation/reference/Convolution.h b/tests/validation/reference/Convolution.h index bdaac28ae6..ea9f4e444b 100644 --- a/tests/validation/reference/Convolution.h +++ b/tests/validation/reference/Convolution.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017, 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -35,7 +35,7 @@ namespace validation namespace reference { template <typename T> -SimpleTensor<T> convolution(const SimpleTensor<T> &src, const int16_t *conv, uint32_t scale, BorderMode border_mode, T constant_border_value, const unsigned int filter_size); +SimpleTensor<T> convolution(const SimpleTensor<T> &src, const int16_t *conv, uint32_t scale, BorderMode border_mode, T constant_border_value, const unsigned int width, const unsigned int height); } // namespace reference } // namespace validation } // namespace test |