[Bugfix] Correct the loss function in RGCN model (#1217)

* upd

* upd

* fix
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

examples/mxnet/rgcn/entity_classify.py

@@ -34,7 +34,7 @@ class EntityClassify(BaseRGCN):
 
     def build_output_layer(self):
         return RelGraphConv(self.h_dim, self.out_dim, self.num_rels, "basis",
-                self.num_bases, activation=partial(F.softmax, axis=1),
+                self.num_bases, activation=None,
                 self_loop=self.use_self_loop)
 
 def main(args):

examples/pytorch/rgcn-hetero/entity_classify.py

@@ -239,7 +239,7 @@ class EntityClassify(nn.Module):
         # h2o
         self.layers.append(RelGraphConvHetero(
             self.h_dim, self.out_dim, self.rel_names, "basis",
-            self.num_bases, activation=partial(F.softmax, dim=1),
+            self.num_bases, activation=None,
             self_loop=self.use_self_loop))
 
     def forward(self):

examples/pytorch/rgcn/entity_classify.py

@@ -39,7 +39,7 @@ class EntityClassify(BaseRGCN):
 
     def build_output_layer(self):
         return RelGraphConv(self.h_dim, self.out_dim, self.num_rels, "basis",
-                self.num_bases, activation=partial(F.softmax, dim=1),
+                self.num_bases, activation=None,
                 self_loop=self.use_self_loop)
 
 def main(args):