From a8aef2916379402e241d9f2c5e0faf3f99c860f7 Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Mon, 14 May 2018 14:21:39 +0100 Subject: COMPMID-792 - Re-enabled Winograd on NEON in all graph examples. Since now the input transform can be multi-threaded, I re-ebaled Winograd in all graph examples Change-Id: I39ef78243bb47fdae135e18dcae2102af0675b3b Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/131048 Reviewed-by: Anthony Barbier Tested-by: Jenkins --- tests/validation/NEON/ConvolutionLayer.cpp | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) (limited to 'tests/validation/NEON/ConvolutionLayer.cpp') diff --git a/tests/validation/NEON/ConvolutionLayer.cpp b/tests/validation/NEON/ConvolutionLayer.cpp index 4f59345f6c..330480e4d8 100644 --- a/tests/validation/NEON/ConvolutionLayer.cpp +++ b/tests/validation/NEON/ConvolutionLayer.cpp @@ -78,12 +78,12 @@ TEST_SUITE(NEON) TEST_SUITE(ConvolutionLayer) DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32, 0), - TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(23U, 27U, 32U, 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(3U, 3U, 5U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 32U, 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) })), @@ -97,7 +97,7 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z PadStrideInfo(2, 1, 0, 0), PadStrideInfo(3, 2, 1, 0) })), - framework::dataset::make("Expected", { ConvolutionMethod::WINOGRAD, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })), + framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })), input_info, weights_info, output_info, conv_info, expected) { ConvolutionMethod is_valid = NEConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(false), -- cgit v1.2.1