need nott bcast_param

fluid/neural_machine_translation/transformer/train.py

@@ -404,7 +404,6 @@ def train_loop(exe, train_progm, dev_count, sum_cost, avg_cost, lr_scheduler,
                 feed_dict[sum_cost.name + "@GRAD"] = 1. / total_num_token
             outs = train_exe.run(fetch_list=[sum_cost.name, token_num.name],
                                  feed=feed_list)
-            train_exe.bcast_params()
             sum_cost_val, token_num_val = np.array(outs[0]), np.array(outs[1])
             total_sum_cost = sum_cost_val.sum(
             )  # sum the cost from multi-devices