support group convolution layer with mkldnn.

paddle/fluid/operators/conv_mkldnn_op.cc

@@ -302,8 +302,7 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
     bool fuse_relu = ctx.Attr<bool>("fuse_relu");
     int groups = ctx.Attr<int>("groups");
 
-    // TODO(pzelazko-intel) add support for group convolution and dilation
-    PADDLE_ENFORCE(groups == 1, "group convolution is not implemented yet");
+    // TODO: add support for dilation
     PADDLE_ENFORCE(
         dilations.size() == 2 && dilations[0] == 1 && dilations[1] == 1,
         "dilation in convolution is not implemented yet");
@@ -314,6 +313,19 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
     std::vector<int> src_tz = paddle::framework::vectorize2int(input->dims());
     std::vector<int> weights_tz =
         paddle::framework::vectorize2int(filter->dims());
+    int g = std::max(groups, 1);
+    if (g > 1) {
+      int o = weights_tz[0];
+      int i = weights_tz[1];
+      int h = weights_tz[2];
+      int w = weights_tz[3];
+      weights_tz.resize(5);
+      weights_tz[0] = g;
+      weights_tz[1] = o / g;
+      weights_tz[2] = i;
+      weights_tz[3] = h;
+      weights_tz[4] = w;
+    }
     std::vector<int> dst_tz = paddle::framework::vectorize2int(output->dims());
 
     // Get unique name for storing MKLDNN primitives
@@ -327,7 +339,8 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
     auto user_src_md = platform::MKLDNNMemDesc(
         {src_tz}, platform::MKLDNNGetDataType<T>(), input->format());
     auto user_weights_md = platform::MKLDNNMemDesc(
-        {weights_tz}, platform::MKLDNNGetDataType<T>(), filter->format());
+        {weights_tz}, platform::MKLDNNGetDataType<T>(),
+        (g == 1) ? filter->format() : mkldnn::memory::format::goihw);
 
     /* create memory descriptor for convolution without specified format
      * ('any') which lets a primitive (convolution in this case) choose
@@ -340,7 +353,8 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
     auto src_md = platform::MKLDNNMemDesc(
         src_tz, platform::MKLDNNGetDataType<T>(), chosen_memory_format);
     auto weights_md = platform::MKLDNNMemDesc(
-        weights_tz, platform::MKLDNNGetDataType<T>(), chosen_memory_format);
+        weights_tz, platform::MKLDNNGetDataType<T>(),
+        (g == 1) ? chosen_memory_format : mkldnn::memory::format::goihw);
     std::vector<int> bias_tz;  // TODO(mgallus): avoid empty vector creation.
                                // Currently used whenever bias is != nullptr.
     auto dst_md = platform::MKLDNNMemDesc(