diff --git a/GNNGraphs/src/gnngraph.jl b/GNNGraphs/src/gnngraph.jl
index 64fd32aad..a9af576e2 100644
--- a/GNNGraphs/src/gnngraph.jl
+++ b/GNNGraphs/src/gnngraph.jl
@@ -209,10 +209,10 @@ function GNNGraph(g::GNNGraph; ndata = g.ndata, edata = g.edata, gdata = g.gdata
     else
         graph = g.graph
     end
-    GNNGraph(graph,
-             g.num_nodes, g.num_edges, g.num_graphs,
-             g.graph_indicator,
-             ndata, edata, gdata)
+    return GNNGraph(graph,
+                g.num_nodes, g.num_edges, g.num_graphs,
+                g.graph_indicator,
+                ndata, edata, gdata)
 end
 
 """
diff --git a/GNNlib/src/layers/conv.jl b/GNNlib/src/layers/conv.jl
index 50b5b34aa..3a5c543a1 100644
--- a/GNNlib/src/layers/conv.jl
+++ b/GNNlib/src/layers/conv.jl
@@ -74,7 +74,7 @@ end
 # when we also have edge_weight we need to convert the graph to COO
 function gcn_conv(l, g::GNNGraph{<:ADJMAT_T}, x, edge_weight::EW, norm_fn::F, conv_weight::CW) where 
         {EW <: Union{Nothing, AbstractVector}, CW<:Union{Nothing,AbstractMatrix}, F} 
-    g = GNNGraph(edge_index(g)...; g.num_nodes)  # convert to COO
+    g = GNNGraph(g, graph_type = :coo)
     return gcn_conv(l, g, x, edge_weight, norm_fn, conv_weight)
 end
 
@@ -449,9 +449,10 @@ function sgc_conv(l, g::GNNGraph, x::AbstractMatrix{T},
     return (x .+ l.bias)
 end
 
+# when we also have edge_weight we need to convert the graph to COO
 function sgc_conv(l, g::GNNGraph{<:ADJMAT_T}, x::AbstractMatrix,
                      edge_weight::AbstractVector)
-    g = GNNGraph(edge_index(g)...; g.num_nodes)
+    g = GNNGraph(g; graph_type=:coo)
     return sgc_conv(l, g, x, edge_weight)
 end
 
@@ -542,9 +543,10 @@ function sg_conv(l, g::GNNGraph, x::AbstractMatrix{T},
     return (x .+ l.bias)
 end
 
+# when we also have edge_weight we need to convert the graph to COO
 function sg_conv(l, g::GNNGraph{<:ADJMAT_T}, x::AbstractMatrix,
                      edge_weight::AbstractVector)
-    g = GNNGraph(edge_index(g)...; g.num_nodes)
+    g = GNNGraph(g; graph_type=:coo)
     return sg_conv(l, g, x, edge_weight)
 end
 
@@ -684,9 +686,10 @@ function tag_conv(l, g::GNNGraph, x::AbstractMatrix{T},
     return (sum_total .+ l.bias)
 end
 
+# when we also have edge_weight we need to convert the graph to COO
 function tag_conv(l, g::GNNGraph{<:ADJMAT_T}, x::AbstractMatrix,
                      edge_weight::AbstractVector)
-    g = GNNGraph(edge_index(g)...; g.num_nodes)
+    g = GNNGraph(g; graph_type = :coo)
     return l(g, x, edge_weight)
 end