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dnn(test): update InferenceEngine tests
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@@ -373,7 +373,7 @@ TEST_P(Test_Caffe_layers, layer_prelu_fc)
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// Reference output values are in range [-0.0001, 10.3906]
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double l1 = (target == DNN_TARGET_MYRIAD) ? 0.005 : 0.0;
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double lInf = (target == DNN_TARGET_MYRIAD) ? 0.021 : 0.0;
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#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2020040000)
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#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2020040000)
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if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL)
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{
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l1 = 0.006f; lInf = 0.05f;
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@@ -1416,6 +1416,14 @@ TEST_P(Test_DLDT_two_inputs, as_backend)
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double l1 = (targetId == DNN_TARGET_OPENCL_FP16 || targetId == DNN_TARGET_MYRIAD) ? 0.06 : 1e-6;
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double lInf = (targetId == DNN_TARGET_OPENCL_FP16 || targetId == DNN_TARGET_MYRIAD) ? 0.3 : 1e-5;
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normAssert(out, ref, "", l1, lInf);
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if (cvtest::debugLevel > 0 || HasFailure())
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{
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std::cout << "input1 scale=" << kScale << " input2 scale=" << kScaleInv << std::endl;
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std::cout << "input1: " << firstInp.size << " " << firstInp.reshape(1, 1) << std::endl;
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std::cout << "input2: " << secondInp.size << " " << secondInp.reshape(1, 1) << std::endl;
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std::cout << "ref: " << ref.reshape(1, 1) << std::endl;
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std::cout << "out: " << out.reshape(1, 1) << std::endl;
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}
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}
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INSTANTIATE_TEST_CASE_P(/*nothing*/, Test_DLDT_two_inputs, Combine(
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