add batch norm

eda/esmm/Model_pipline/train.py

@@ -36,7 +36,7 @@ tf.app.flags.DEFINE_float("ctr_task_wgt", 0.5, "loss weight of ctr task")
 tf.app.flags.DEFINE_string("optimizer", 'Adam', "optimizer type {Adam, Adagrad, GD, Momentum}")
 tf.app.flags.DEFINE_string("deep_layers", '256,128,64', "deep layers")
 tf.app.flags.DEFINE_string("dropout", '0.5,0.5,0.5', "dropout rate")
-tf.app.flags.DEFINE_boolean("batch_norm", False, "perform batch normaization (True or False)")
+tf.app.flags.DEFINE_boolean("batch_norm", True, "perform batch normaization (True or False)")
 tf.app.flags.DEFINE_float("batch_norm_decay", 0.9, "decay for the moving average(recommend trying decay=0.9)")
 tf.app.flags.DEFINE_string("hdfs_dir", '', "hdfs dir")
 tf.app.flags.DEFINE_string("local_dir", '', "local dir")