Modify nGraph's ConvolutionBackpropData and GroupConvolution

modules/dnn/src/layers/convolution_layer.cpp

@@ -544,6 +544,12 @@ public:
         const int group = inpCn / inpGroupCn;
 
         std::vector<size_t> kernel_shape = getShape<size_t>(blobs[0]);
+        if (group != 1)
+        {
+            kernel_shape[0] /= group;
+            kernel_shape.insert(kernel_shape.begin(), group);
+        }
+
         auto ieWeights = std::make_shared<ngraph::op::Constant>(ngraph::element::f32, kernel_shape, blobs[0].data);
         if (fusedWeights)
         {
@@ -566,14 +572,12 @@ public:
 
         std::shared_ptr<ngraph::Node> conv_node;
         if (group != 1) {
-            conv_node = std::make_shared<ngraph::op::GroupConvolution>(
+            conv_node = std::make_shared<ngraph::op::v1::GroupConvolution>(
                                 ieInpNode, ieWeights,
                                 ngraph::Strides(strides),
-                                ngraph::Strides(dilations),
                                 ngraph::CoordinateDiff(std::vector<std::ptrdiff_t>(pads_begin.begin(), pads_begin.end())),
                                 ngraph::CoordinateDiff(std::vector<std::ptrdiff_t>(pads_end.begin(),   pads_end.end())),
-                                ngraph::Strides{},
-                                group,
+                                ngraph::Strides(dilations),
                                 pad_type);
         } else {
             conv_node = std::make_shared<ngraph::op::v1::Convolution>(
@@ -2037,37 +2041,29 @@ public:
             Mat newWeights = blobs[0].reshape(1, inpCn);
             transpose(weightsMat, newWeights);
         }
-        size_t batch = ieInpNode->get_shape()[0];
-        std::vector<size_t> out_shape = {batch, (size_t)numOutput};
         std::vector<size_t> paddings_end;
-        std::vector<size_t> inpShape = ieInpNode->get_shape();
         if (padMode.empty())
         {
             for (int i = 0; i < pads_end.size(); i++) {
-                out_shape.push_back(strides[i] * (inpShape[2 + i] - 1) +
-                                    kernel_size[i] - pads_begin[i] - pads_end[i] + adjust_pads[i]);
                 paddings_end.push_back(pads_end[i] - adjust_pads[i]);
             }
         }
         else if (padMode == "SAME")
         {
             for (int i = 0; i < pads_begin.size(); i++) {
-                out_shape.push_back(strides[i] * (inpShape[2 + i] - 1) + 1 + adjust_pads[i]);
                 paddings_end.push_back(kernel_size[i] - pads_begin[i] - 1 - adjust_pads[i]);
             }
         } else {
             paddings_end = pads_end;
         }
 
-        auto deconv = std::make_shared<ngraph::op::ConvolutionBackpropData>(
-                          ngraph::Shape{out_shape},
-                          ieWeights,
+        auto deconv = std::make_shared<ngraph::op::v1::ConvolutionBackpropData>(
                           ieInpNode,
+                          ieWeights,
                           ngraph::Strides(strides),
-                          ngraph::Strides(dilations),
                           ngraph::CoordinateDiff(std::vector<std::ptrdiff_t>(pads_begin.begin(), pads_begin.end())),
                           ngraph::CoordinateDiff(std::vector<std::ptrdiff_t>(paddings_end.begin(), paddings_end.end())),
-                          (strides.size() == 2 ? ngraph::Strides{1, 1} : ngraph::Strides{1, 1, 1}));
+                          ngraph::Strides(dilations));
         if (hasBias() || fusedBias)
         {
             std::vector<size_t> shape(deconv->get_shape().size(), 1);