TEST_P(Test_Torch_layers, net_normalize)
{
+ if(backend == DNN_BACKEND_CUDA)
+ applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA); /* only L1 and L2 norms are supported */
runTorchNet("net_normalize", "", false, true);
}
TEST_P(Test_Torch_nets, OpenFace_accuracy)
{
-#if defined(INF_ENGINE_RELEASE)
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2018050000)
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD);
#endif
// Reference output values are in range [-0.17212, 0.263492]
// on Myriad problem layer: l4_Pooling - does not use pads_begin
- float l1 = (target == DNN_TARGET_OPENCL_FP16) ? 4e-4 : 1e-5;
- float lInf = (target == DNN_TARGET_OPENCL_FP16) ? 1.5e-3 : 1e-3;
+ float l1 = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 2e-3 : 1e-5;
+ float lInf = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 5e-3 : 1e-3;
Mat outRef = readTorchBlob(_tf("net_openface_output.dat"), true);
normAssert(out, outRef, "", l1, lInf);
}
{
applyTestTag(target == DNN_TARGET_CPU ? "" : CV_TEST_TAG_MEMORY_512MB);
checkBackend();
- if (backend == DNN_BACKEND_INFERENCE_ENGINE ||
- (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16))
- applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16);
+ if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16)
+ throw SkipTestException("");
+ if (backend == DNN_BACKEND_INFERENCE_ENGINE && target != DNN_TARGET_CPU)
+ {
+ if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16);
+ if (target == DNN_TARGET_OPENCL) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL);
+ if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD);
+ throw SkipTestException("");
+ }
Net net;
{