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dnn(test): update InferenceEngine tests
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@@ -39,12 +39,13 @@ static void test(Mat& input, Net& net, Backend backendId, Target targetId, bool
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l1 = default_l1;
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if (lInf == 0.0)
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lInf = default_lInf;
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#if 0
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std::cout << "l1=" << l1 << " lInf=" << lInf << std::endl;
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std::cout << outputDefault.reshape(1, outputDefault.total()).t() << std::endl;
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std::cout << outputHalide.reshape(1, outputDefault.total()).t() << std::endl;
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#endif
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normAssert(outputDefault, outputHalide, "", l1, lInf);
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if (cvtest::debugLevel > 0 || testing::Test::HasFailure())
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{
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std::cout << "l1=" << l1 << " lInf=" << lInf << std::endl;
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std::cout << outputDefault.reshape(1, outputDefault.total()).t() << std::endl;
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std::cout << outputHalide.reshape(1, outputDefault.total()).t() << std::endl;
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}
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}
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static void test(LayerParams& params, Mat& input, Backend backendId, Target targetId, bool skipCheck = false, double l1 = 0.0, double lInf = 0.0)
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@@ -795,6 +796,16 @@ TEST_P(Eltwise, Accuracy)
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Backend backendId = get<0>(get<4>(GetParam()));
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Target targetId = get<1>(get<4>(GetParam()));
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#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000)
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// accuracy
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if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && targetId == DNN_TARGET_OPENCL &&
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inSize == Vec3i(1, 4, 5) && op == "sum" && numConv == 1 && !weighted)
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applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
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if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && targetId == DNN_TARGET_OPENCL &&
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inSize == Vec3i(2, 8, 6) && op == "sum" && numConv == 1 && !weighted)
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applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
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#endif
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#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LE(2018050000)
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if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && targetId == DNN_TARGET_MYRIAD &&
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inSize == Vec3i(1, 4, 5))
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