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Enable Eltwise layer with different numbers of inputs channels

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This commit is contained in:
Dmitry Kurtaev
2019-10-18 18:51:52 +03:00
parent 9255df44d0
commit adbd613660
4 changed files with 181 additions and 49 deletions
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modules/dnn/test/test_layers.cpp
+56
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@@ -1488,4 +1488,60 @@ TEST(Layer_Test_Convolution, relu_fusion)
normAssert(input, output);
}
typedef testing::TestWithParam<tuple<bool, tuple<Backend, Target> > > Layer_Test_Eltwise_unequal;
TEST_P(Layer_Test_Eltwise_unequal, Accuracy)
{
bool weighted = get<0>(GetParam());
int backendId = get<0>(get<1>(GetParam()));
int targetId = get<1>(get<1>(GetParam()));
if (backendId == DNN_BACKEND_OPENCV && targetId == DNN_TARGET_OPENCL_FP16)
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16);
Net net;
LayerParams lp;
lp.type = "Eltwise";
lp.name = "testLayer";
const int inpShapes[][4] = {{1, 4, 2, 2}, {1, 5, 2, 2}, {1, 3, 2, 2}};
std::vector<String> inpNames(3);
std::vector<Mat> inputs(3);
size_t numValues = 0;
std::vector<float> weights(3, 1);
if (weighted)
{
for (int i = 0; i < inputs.size(); ++i)
randu(Mat(1, 1, CV_32F, &weights[i]), -1, 1);
lp.set("coeff", DictValue::arrayReal<float*>(&weights[0], weights.size()));
}
int eltwiseId = net.addLayer(lp.name, lp.type, lp);
for (int i = 0; i < inputs.size(); ++i)
{
inputs[i].create(4, inpShapes[i], CV_32F);
numValues = std::max(numValues, inputs[i].total());
randu(inputs[i], 0, 255);
inpNames[i] = format("input_%d", i);
net.connect(0, i, eltwiseId, i);
}
Mat ref(1, numValues, CV_32F, Scalar(0));
net.setInputsNames(inpNames);
for (int i = 0; i < inputs.size(); ++i)
{
net.setInput(inputs[i], inpNames[i]);
ref.colRange(0, inputs[i].total()) += weights[i] * inputs[i].reshape(1, 1);
}
net.setPreferableBackend(backendId);
net.setPreferableTarget(targetId);
Mat out = net.forward();
normAssert(out.reshape(1, 1), ref);
}
INSTANTIATE_TEST_CASE_P(/**/, Layer_Test_Eltwise_unequal, Combine(
testing::Bool(),
dnnBackendsAndTargets()
));
}} // namespace