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dnn(test): skip checks only for unstable tests

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but execute tested functions in Layer_Test_Halide/Convolution.Accuracy
This commit is contained in:
Alexander Alekhin 2018-07-25 16:53:37 +03:00
parent 74cf48b5d7
commit dd8701c1a0
1 changed files with 11 additions and 5 deletions
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16
modules/dnn/test/test_halide_layers.cpp
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@ -16,7 +16,7 @@ using namespace cv;
using namespace cv::dnn; using namespace cv::dnn;
using namespace testing; using namespace testing;
static void test(Mat& input, Net& net, Backend backendId, Target targetId) static void test(Mat& input, Net& net, Backend backendId, Target targetId, bool skipCheck = false)
{ {
DNNTestLayer::checkBackend(backendId, targetId); DNNTestLayer::checkBackend(backendId, targetId);
randu(input, -1.0f, 1.0f); randu(input, -1.0f, 1.0f);
@ -29,16 +29,19 @@ static void test(Mat& input, Net& net, Backend backendId, Target targetId)
net.setPreferableTarget(targetId); net.setPreferableTarget(targetId);
Mat outputHalide = net.forward().clone(); Mat outputHalide = net.forward().clone();
if (skipCheck)
return;
double l1, lInf; double l1, lInf;
DNNTestLayer::getDefaultThresholds(backendId, targetId, &l1, &lInf); DNNTestLayer::getDefaultThresholds(backendId, targetId, &l1, &lInf);
normAssert(outputDefault, outputHalide, "", l1, lInf); normAssert(outputDefault, outputHalide, "", l1, lInf);
} }
static void test(LayerParams& params, Mat& input, Backend backendId, Target targetId) static void test(LayerParams& params, Mat& input, Backend backendId, Target targetId, bool skipCheck = false)
{ {
Net net; Net net;
net.addLayerToPrev(params.name, params.type, params); net.addLayerToPrev(params.name, params.type, params);
test(input, net, backendId, targetId); test(input, net, backendId, targetId, skipCheck);
} }
static testing::internal::ParamGenerator<tuple<Backend, Target> > dnnBackendsAndTargetsWithHalide() static testing::internal::ParamGenerator<tuple<Backend, Target> > dnnBackendsAndTargetsWithHalide()
@ -107,10 +110,11 @@ TEST_P(Convolution, Accuracy)
if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_MYRIAD) if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_MYRIAD)
throw SkipTestException(""); throw SkipTestException("");
bool skipCheck = false;
if (cvtest::skipUnstableTests && backendId == DNN_BACKEND_OPENCV && if (cvtest::skipUnstableTests && backendId == DNN_BACKEND_OPENCV &&
(targetId == DNN_TARGET_OPENCL || targetId == DNN_TARGET_OPENCL_FP16) && (targetId == DNN_TARGET_OPENCL || targetId == DNN_TARGET_OPENCL_FP16) &&
kernel == Size(3, 1) && stride == Size(1, 1) && pad == Size(0, 1)) kernel == Size(3, 1) && stride == Size(1, 1) && pad == Size(0, 1))
throw SkipTestException("Skip unstable test"); skipCheck = true;
int sz[] = {outChannels, inChannels / group, kernel.height, kernel.width}; int sz[] = {outChannels, inChannels / group, kernel.height, kernel.width};
Mat weights(4, &sz[0], CV_32F); Mat weights(4, &sz[0], CV_32F);
@ -139,7 +143,9 @@ TEST_P(Convolution, Accuracy)
} }
int inpSz[] = {1, inChannels, inSize.height, inSize.width}; int inpSz[] = {1, inChannels, inSize.height, inSize.width};
Mat input(4, &inpSz[0], CV_32F); Mat input(4, &inpSz[0], CV_32F);
test(lp, input, backendId, targetId); test(lp, input, backendId, targetId, skipCheck);
if (skipCheck)
throw SkipTestException("Skip checks in unstable test");
} }
INSTANTIATE_TEST_CASE_P(Layer_Test_Halide, Convolution, Combine( INSTANTIATE_TEST_CASE_P(Layer_Test_Halide, Convolution, Combine(