Added fix for other size
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@@ -1008,8 +1008,8 @@ INSTANTIATE_TEST_CASE_P(/**/, Layer_Test_Convolution_DLDT,
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// net.save('/path/to/caffemodel')
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//
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// 3. Convert using ModelOptimizer.
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typedef testing::TestWithParam<tuple<int, int, Target> > Test_DLDT_two_inputs;
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TEST_P(Test_DLDT_two_inputs, as_IR)
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typedef testing::TestWithParam<tuple<int, int, Target, std::vector<int> > > Test_DLDT_two_inputs_3dim;
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TEST_P(Test_DLDT_two_inputs_3dim, as_IR)
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{
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int firstInpType = get<0>(GetParam());
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int secondInpType = get<1>(GetParam());
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@@ -1021,9 +1021,9 @@ TEST_P(Test_DLDT_two_inputs, as_IR)
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#endif
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Net net = readNet(_tf("net_two_inputs.xml"), _tf("net_two_inputs.bin"));
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int inpSize[] = {1, 2, 3};
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Mat firstInp(3, &inpSize[0], firstInpType);
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Mat secondInp(3, &inpSize[0], secondInpType);
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std::vector<int> inpSize = get<3>(GetParam());
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Mat firstInp(3, inpSize.data(), firstInpType);
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Mat secondInp(3, inpSize.data(), secondInpType);
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randu(firstInp, 0, 255);
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randu(secondInp, 0, 255);
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@@ -1046,6 +1046,15 @@ TEST_P(Test_DLDT_two_inputs, as_IR)
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}
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}
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std::vector< std::vector<int> > list_sizes{ {1, 2, 3}, {3, 2, 1}, {5, 5, 5}, {13, 7, 11} };
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INSTANTIATE_TEST_CASE_P(/*nothing*/, Test_DLDT_two_inputs_3dim, Combine(
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Values(CV_8U, CV_32F), Values(CV_8U, CV_32F),
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testing::ValuesIn(getAvailableTargets(DNN_BACKEND_INFERENCE_ENGINE)),
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testing::ValuesIn(list_sizes)
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));
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typedef testing::TestWithParam<tuple<int, int, Target> > Test_DLDT_two_inputs;
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TEST_P(Test_DLDT_two_inputs, as_backend)
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{
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static const float kScale = 0.5f;
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