upd (#2097)

docs/source/api/python/dgl.ops.rst

@@ -15,7 +15,7 @@ It *fuses* two steps into one kernel.
 
 1. Computes messages by add/sub/mul/div source node and edge features,
    or copy node features to edges.
-2. Aggregate the messages by sum/max/min as the features on destination nodes.
+2. Aggregate the messages by sum/max/min/mean as the features on destination nodes.
 
 Our implementation supports tensors on CPU/GPU in PyTorch/MXNet/Tensorflow
 as input. All operators are equipped with autograd (computing the input gradients
@@ -100,12 +100,18 @@ graph.
     u_sub_e_min
     u_mul_e_min
     u_div_e_min
+    u_add_e_mean
+    u_sub_e_mean
+    u_mul_e_mean
+    u_div_e_mean
     copy_u_sum
     copy_e_sum
     copy_u_max
     copy_e_max
     copy_u_min
     copy_e_min 
+    copy_u_mean
+    copy_e_mean
 
 GSDDMM functions
 ----------------