From 2d9de0a3fa6ad858e70040124f362799a962bb6a Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Thu, 15 Mar 2018 17:58:20 +0000 Subject: COMPMID-1009 Support 4x4 output tile for Winograd Filter Transform on OpenCL. Change-Id: I68c6453e0f192de659582404f109a89616b9fbb9 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/124811 Tested-by: Jenkins Reviewed-by: Georgios Pinitas Reviewed-by: Gian Marco Iodice --- tests/validation/CL/Winograd.cpp | 37 +++++++++++++++++++++++++------------ 1 file changed, 25 insertions(+), 12 deletions(-) (limited to 'tests/validation/CL/Winograd.cpp') diff --git a/tests/validation/CL/Winograd.cpp b/tests/validation/CL/Winograd.cpp index aa668fa575..07a52f8ebc 100644 --- a/tests/validation/CL/Winograd.cpp +++ b/tests/validation/CL/Winograd.cpp @@ -147,12 +147,12 @@ TEST_SUITE_END() // InputTransform TEST_SUITE(FilterTransform) // *INDENT-OFF* // clang-format off -DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip( +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( framework::dataset::make("InputInfo",{ TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::F16), // F16 not supported TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::QASYMM8), // QASYMM8 not supported TensorInfo(TensorShape(5U, 5U, 5U, 3U), 1, DataType::F32), // Kernel size not supported - TensorInfo(TensorShape(3U, 3U), 1, DataType::F32), // valid + TensorInfo(TensorShape(3U, 3U), 1, DataType::F32), // Output tile not supported TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::F32), // valid TensorInfo(TensorShape(3U, 3U, 37U, 2U), 1, DataType::F32), // valid TensorInfo(TensorShape(3U, 3U, 37U, 22U), 1, DataType::F32) // valid @@ -164,12 +164,21 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip( TensorInfo(TensorShape(1U, 1U, 16U), 1, DataType::F32), TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F32), TensorInfo(TensorShape(2U, 37U, 16U), 1, DataType::F32), - TensorInfo(TensorShape(22U, 37U, 16U), 1, DataType::F32) + TensorInfo(TensorShape(22U, 37U, 36U), 1, DataType::F32) })), - framework::dataset::make("Expected", { false, false, false, true, true, true, true })), - input_info, output_info, expected) + framework::dataset::make("OutputTile", { + Size2D(2U, 2U), + Size2D(2U, 2U), + Size2D(2U, 2U), + Size2D(3U, 3U), + Size2D(2U, 2U), + Size2D(2U, 2U), + Size2D(4U, 4U) + })), + framework::dataset::make("Expected", { false, false, false, false, true, true, true })), + input_info, output_info, output_tile, expected) { - ARM_COMPUTE_EXPECT(bool(CLWinogradFilterTransformKernel::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(bool(CLWinogradFilterTransformKernel::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), output_tile)) == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* @@ -177,13 +186,14 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip( using CLWinogradFilterTransform = CLSynthetizeFunctionWithZeroConstantBorder; using CLWinogradFilterTransformFixture = WinogradFilterTransformValidationFixture; -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallWinogradFilterTransformDataset(), datasets::LargeWinogradFilterTransformDataset()), +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallWinogradFilterTransformDataset(), datasets::LargeWinogradFilterTransformDataset()), + framework::dataset::make("OutputTile", { Size2D(2U, 2U), Size2D(4U, 4U) })), framework::dataset::make("DataType", { DataType::F32 })), - shape_a, is_nchw_format, data_type) + shape_a, is_nchw_format, output_tile, data_type) { ARM_COMPUTE_UNUSED(is_nchw_format); - TensorShape shape_b = compute_winograd_filter_transform_shape(TensorInfo(shape_a, 1, data_type)); + TensorShape shape_b = compute_winograd_filter_transform_shape(TensorInfo(shape_a, 1, data_type), output_tile); // Create tensors CLTensor a = create_tensor(shape_a, data_type); @@ -194,16 +204,19 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::da // Create and configure function CLWinogradFilterTransform winograd_filter_transform; - winograd_filter_transform.configure(&a, &b); + winograd_filter_transform.configure(&a, &b, output_tile); } -FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradFilterTransformFixture, framework::DatasetMode::ALL, combine(datasets::SmallWinogradFilterTransformDataset(), framework::dataset::make("DataType", { DataType::F32 }))) +FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradFilterTransformFixture, framework::DatasetMode::ALL, combine(combine(datasets::SmallWinogradFilterTransformDataset(), framework::dataset::make("OutputTile", { Size2D(2U, 2U), Size2D(4U, 4U) })), + framework::dataset::make("DataType", { DataType::F32 }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradFilterTransformFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeWinogradFilterTransformDataset(), framework::dataset::make("DataType", { DataType::F32 }))) +FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradFilterTransformFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeWinogradFilterTransformDataset(), + framework::dataset::make("OutputTile", { Size2D(2U, 2U), Size2D(4U, 4U) })), + framework::dataset::make("DataType", { DataType::F32 }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); -- cgit v1.2.1