Revise the comments for arguments

fluid/DeepASR/infer.py

@@ -29,22 +29,23 @@ def parse_args():
         '--mean_var',
         type=str,
         default='data/global_mean_var_search26kHr',
-        help='mean var path')
+        help="The path for feature's global mean and variance. "
+        "(default: %(default)s)")
     parser.add_argument(
         '--infer_feature_lst',
         type=str,
         default='data/infer_feature.lst',
-        help='feature list path for inference.')
+        help='The feature list path for inference. (default: %(default)s)')
     parser.add_argument(
         '--infer_label_lst',
         type=str,
         default='data/infer_label.lst',
-        help='label list path for inference.')
+        help='The label list path for inference. (default: %(default)s)')
     parser.add_argument(
         '--model_save_path',
         type=str,
         default='./checkpoints/deep_asr.pass_0.model/',
-        help='directory to save model.')
+        help='The directory for saving model. (default: %(default)s)')
     args = parser.parse_args()
     return args
 
@@ -64,7 +65,7 @@ def split_infer_result(infer_seq, lod):
 
 
 def infer(args):
-    """ Get one batch of feature data and predicts labels for each sample.
+    """ Gets one batch of feature data and predicts labels for each sample.
     """
 
     if not os.path.exists(args.model_save_path):

fluid/DeepASR/train.py

@@ -72,33 +72,34 @@ def parse_args():
         '--mean_var',
         type=str,
         default='data/global_mean_var_search26kHr',
-        help='mean var path')
+        help="The path for feature's global mean and variance. "
+        "(default: %(default)s)")
     parser.add_argument(
         '--train_feature_lst',
         type=str,
         default='data/feature.lst',
-        help='feature list path for training.')
+        help='The feature list path for training. (default: %(default)s)')
     parser.add_argument(
         '--train_label_lst',
         type=str,
         default='data/label.lst',
-        help='label list path for training.')
+        help='The label list path for training. (default: %(default)s)')
     parser.add_argument(
         '--val_feature_lst',
         type=str,
         default='data/val_feature.lst',
-        help='feature list path for validation.')
+        help='The feature list path for validation. (default: %(default)s)')
     parser.add_argument(
         '--val_label_lst',
         type=str,
         default='data/val_label.lst',
-        help='label list path for validation.')
+        help='The label list path for validation. (default: %(default)s)')
     parser.add_argument(
         '--model_save_dir',
         type=str,
         default='./checkpoints',
-        help='directory to save model. Do not save model if set to '
-        '.')
+        help="The directory for saving model. Do not save model if set to "
+        "''. (default: %(default)s)")
     args = parser.parse_args()
     return args
 
@@ -114,8 +115,6 @@ def train(args):
     """train in loop.
     """
 
-    # prediction, avg_cost, accuracy = stacked_lstmp_model(args.hidden_dim, 
-    #    args.proj_dim, args.stacked_num, class_num=1749, args.parallel)
     prediction, avg_cost, accuracy = stacked_lstmp_model(
         hidden_dim=args.hidden_dim,
         proj_dim=args.proj_dim,
@@ -206,7 +205,7 @@ def train(args):
                 sys.stdout.flush()
         # run test
         val_cost, val_acc = test(exe)
-        # save model 
+        # save model
         if args.model_save_dir != '':
             model_path = os.path.join(
                 args.model_save_dir, "deep_asr.pass_" + str(pass_id) + ".model")