more fixes on old usage of add_moving_summary (#805)

examples/HED/hed.py

@@ -115,7 +115,7 @@ class Model(ModelDesc):
 
             add_param_summary(('.*/W', ['histogram']))   # monitor W
             total_cost = tf.add_n(costs, name='cost')
-            add_moving_summary(*(costs + [wrong, total_cost]))
+            add_moving_summary(wrong, total_cost, *costs)
             return total_cost
 
     def optimizer(self):

examples/ImageNetModels/inception-bn.py

@@ -96,7 +96,7 @@ class Model(ModelDesc):
         loss3 = tf.reduce_mean(loss3, name='loss3')
 
         cost = tf.add_n([loss3, 0.3 * loss2, 0.3 * loss1], name='weighted_cost')
-        add_moving_summary([cost, loss1, loss2, loss3])
+        add_moving_summary(cost, loss1, loss2, loss3)
 
         def prediction_incorrect(logits, label, topk, name):
             return tf.cast(tf.logical_not(tf.nn.in_top_k(logits, label, topk)), tf.float32, name=name)

tensorpack/tfutils/summary.py

@@ -196,7 +196,6 @@ def add_param_summary(*summary_lists, **kwargs):
                     add_tensor_summary(p, actions, name=name, collections=collections)
 
 
-# TODO: collection for the summary op
 def add_moving_summary(*args, **kwargs):
     """
     Summarize the moving average for scalar tensors.
@@ -228,6 +227,10 @@ def add_moving_summary(*args, **kwargs):
         logger.warn("add_moving_summary() called under reuse=True scope, ignored.")
         return []
 
+    if len(args) == 1 and isinstance(args[0], (list, tuple)):
+        logger.warn("add_moving_summary() takes positional args instead of an iterable of tensors!")
+        args = args[0]
+
     for x in args:
         assert isinstance(x, (tf.Tensor, tf.Variable)), x
         assert x.get_shape().ndims == 0, \