From 2213d4b334567d0cb7f283090d42b5fb1b70f66b Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Fri, 27 Apr 2018 10:39:06 +0100 Subject: COMPMID-1096 - Add fast_math flag to CLConvolutionLayer COMPMID-1103 - CLWinogradConvolutionLayer mismatches Change-Id: Iceaa9482a1790ec39d2720c220261aaea8043978 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/129398 Tested-by: Jenkins Reviewed-by: Giorgio Arena Reviewed-by: Georgios Pinitas --- tests/validation/CL/ConvolutionLayer.cpp | 102 ++++++++++++++++++++----------- 1 file changed, 65 insertions(+), 37 deletions(-) (limited to 'tests/validation/CL/ConvolutionLayer.cpp') diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp index 8685e5bbc7..a2b55a8555 100644 --- a/tests/validation/CL/ConvolutionLayer.cpp +++ b/tests/validation/CL/ConvolutionLayer.cpp @@ -73,44 +73,72 @@ const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo TEST_SUITE(CL) TEST_SUITE(ConvolutionLayer) -DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( - framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0), - TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0), - TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0), - TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0) - }), - framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0), - TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0) - })), - framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0), - TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0), - TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0), - TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32, 0) - })), - framework::dataset::make("ConvInfo", { PadStrideInfo(1, 2, 1, 1), - PadStrideInfo(1, 2, 1, 1), - PadStrideInfo(1, 1, 0, 0), - PadStrideInfo(2, 1, 0, 0), - PadStrideInfo(3, 2, 1, 0) - })), - framework::dataset::make("GpuTarget", { GPUTarget::BIFROST, - GPUTarget::MIDGARD, - GPUTarget::G71, - GPUTarget::MIDGARD, - GPUTarget::BIFROST - })), - - framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })), - input_info, weights_info, output_info, conv_info, gpu_target, expected) +DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0), + TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0) + }), + framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0), + TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0), + TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0), + TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0) + })), + framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0), + TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0), + TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32, 0), + TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32, 0) + })), + framework::dataset::make("ConvInfo", { PadStrideInfo(1, 2, 1, 1), + PadStrideInfo(1, 2, 1, 1), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(2, 1, 0, 0), + PadStrideInfo(3, 2, 1, 0), + PadStrideInfo(1, 1, 2, 2), + PadStrideInfo(1, 1, 2, 2) + })), + framework::dataset::make("GpuTarget", { GPUTarget::BIFROST, + GPUTarget::MIDGARD, + GPUTarget::G71, + GPUTarget::MIDGARD, + GPUTarget::BIFROST, + GPUTarget::BIFROST, + GPUTarget::BIFROST + })), + framework::dataset::make("Dilation", { - ConvolutionMethod is_valid = CLConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(false), - &weights_info.clone()->set_is_resizable(false), - &output_info.clone()->set_is_resizable(false), conv_info, WeightsInfo(), ActivationLayerInfo(), gpu_target); + Size2D(1U, 1U), + Size2D(1U, 1U), + Size2D(1U, 1U), + Size2D(1U, 1U), + Size2D(1U, 1U), + Size2D(1U, 1U), + Size2D(2U, 1U), +})), +framework::dataset::make("EnableFastMath", { false, false, false, false, false, true, true })), +framework::dataset::make("Expected", +{ + ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, +})), +input_info, weights_info, output_info, conv_info, gpu_target, dilation, enable_fast_math, expected) +{ + ConvolutionMethod is_valid = CLConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(true), + &weights_info.clone()->set_is_resizable(true), + &output_info.clone()->set_is_resizable(true), conv_info, + WeightsInfo(), + ActivationLayerInfo(), + gpu_target, + dilation, + enable_fast_math); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } TEST_SUITE_END() -- cgit v1.2.1