From 66cbafb26261fbf091b799d1e5d0600fb08ee513 Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Thu, 23 Aug 2018 14:51:00 +0100 Subject: COMPMID-1246 Fix NEON mobilenet NCHW Change-Id: I1dd6df9bd4a96cb7cbacce939a89c3a7ccee71c8 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/145397 Tested-by: Jenkins Reviewed-by: Anthony Barbier --- .../validation/NEON/DepthwiseConvolutionLayer.cpp | 28 +++++++++++----------- 1 file changed, 14 insertions(+), 14 deletions(-) (limited to 'tests/validation/NEON/DepthwiseConvolutionLayer.cpp') diff --git a/tests/validation/NEON/DepthwiseConvolutionLayer.cpp b/tests/validation/NEON/DepthwiseConvolutionLayer.cpp index 6b3411b965..fe7bba365a 100644 --- a/tests/validation/NEON/DepthwiseConvolutionLayer.cpp +++ b/tests/validation/NEON/DepthwiseConvolutionLayer.cpp @@ -61,27 +61,27 @@ DATA_TEST_CASE(Validate3x3, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip TensorInfo(TensorShape(32U, 18U, 3U), 1, DataType::F32), // Mismatching input feature maps TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32), // Unsupported weights dimensions TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32), // Mismatching depth multiplier - TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32), // Invalid stride + TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::QASYMM8), // Invalid stride TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32), // Invalid biases size TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32), // Invalid biases dimensions TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32), // Invalid output size - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Window shrink + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), }), - framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F16), - TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(5U, 5U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32), + framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F16), + TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(5U, 5U, 2U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::QASYMM8), + TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F32), })), framework::dataset::make("BiasesInfo", { TensorInfo(TensorShape(2U), 1, DataType::F32), TensorInfo(TensorShape(2U), 1, DataType::F32), TensorInfo(TensorShape(2U), 1, DataType::F32), TensorInfo(TensorShape(2U), 1, DataType::F32), - TensorInfo(TensorShape(2U), 1, DataType::F32), + TensorInfo(TensorShape(2U), 1, DataType::S32), TensorInfo(TensorShape(4U), 1, DataType::F32), TensorInfo(TensorShape(2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(2U), 1, DataType::F32), @@ -91,7 +91,7 @@ DATA_TEST_CASE(Validate3x3, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32), TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32), TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::QASYMM8), TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32), TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32), @@ -117,7 +117,7 @@ DATA_TEST_CASE(Validate3x3, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip 1, 1, })), - framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, false })), + framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, true })), input_info, weights_info, biases_info, output_info, conv_info, depth_multiplier, expected) { bool is_valid = bool(NEDepthwiseConvolutionLayer3x3::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, depth_multiplier)); -- cgit v1.2.1