updated conv bn fuse pass to make it compatible with latest batch_norm op (#31272)

paddle/fluid/framework/ir/graph_pattern_detector.cc

@@ -790,27 +790,31 @@ PDNode *patterns::ConvBN::operator()(paddle::framework::ir::PDNode *conv_input,
   auto *bn_scale_var = pattern->NewNode(bn_scale_repr())
                            ->AsInput()
                            ->assert_is_persistable_var()
-                           ->assert_is_op_input("batch_norm", "Scale");
+                           ->assert_is_op_input("batch_norm", "Scale")
+                           ->assert_has_n_outputs(1);
   // BN Bias
   auto *bn_bias_var = pattern->NewNode(bn_bias_repr())
                           ->AsInput()
                           ->assert_is_persistable_var()
-                          ->assert_is_op_input("batch_norm", "Bias");
+                          ->assert_is_op_input("batch_norm", "Bias")
+                          ->assert_has_n_outputs(1);
   // BN Mean
   auto *bn_mean_var = pattern->NewNode(bn_mean_repr())
                           ->AsInput()
                           ->assert_is_persistable_var()
-                          ->assert_is_op_input("batch_norm", "Mean");
+                          ->assert_is_op_input("batch_norm", "Mean")
+                          ->assert_has_n_outputs(1);
   // BN Variance
   auto *bn_variance_var = pattern->NewNode(bn_variance_repr())
                               ->AsInput()
                               ->assert_is_persistable_var()
-                              ->assert_is_op_input("batch_norm", "Variance");
+                              ->assert_is_op_input("batch_norm", "Variance")
+                              ->assert_has_n_outputs(1);
 
   // BN output
   auto *bn_out_var = pattern->NewNode(bn_out_repr())
                          ->AsOutput()
-                         ->assert_is_op_output("batch_norm");
+                         ->assert_is_op_output("batch_norm", "Y");
 
   auto *bn_mean_out_var = pattern->NewNode(bn_mean_out_repr())
                               ->AsOutput()