fix tower-summary bug

examples/cifar10-convnet.py

@@ -100,8 +100,6 @@ def get_data(train_or_test):
         ds = PrefetchData(ds, 10, 5)
     return ds
 
-
-
 def get_config():
     # prepare dataset
     dataset_train = get_data('train')

tensorpack/dataflow/dataset/visualqa.py

@@ -11,6 +11,12 @@ import json
 
 __all__ = ['VisualQA']
 
+def read_json(fname):
+    f = open(fname)
+    ret = json.load(f)
+    f.close()
+    return ret
+
 # TODO shuffle
 class VisualQA(DataFlow):
     """
@@ -19,12 +25,11 @@ class VisualQA(DataFlow):
     """
     def __init__(self, question_file, annotation_file):
         with timed_operation('Reading VQA JSON file'):
-            qobj = json.load(open(question_file))
+            qobj, aobj = list(map(read_json, [question_file, annotation_file]))
             self.task_type = qobj['task_type']
             self.questions = qobj['questions']
             self._size = len(self.questions)
 
-            aobj = json.load(open(annotation_file))
             self.anno = aobj['annotations']
             assert len(self.anno) == len(self.questions), \
                 "{}!={}".format(len(self.anno), len(self.questions))
@@ -49,7 +54,7 @@ class VisualQA(DataFlow):
         """
         cnt = Counter()
         for anno in self.anno:
-            cnt[anno['multiple_choice_answer']] += 1
+            cnt[anno['multiple_choice_answer'].lower()] += 1
         return [k[0] for k in cnt.most_common(n)]
 
     def get_common_question_words(self, n):

tensorpack/tfutils/sessinit.py

@@ -107,7 +107,6 @@ class SaverRestore(SessionInit):
                 logger.warn("Param {} not found in checkpoint! Will not restore.".format(v.op.name))
         return var_dict
 
-
 class ParamRestore(SessionInit):
     """
     Restore trainable variables from a dictionary.

tensorpack/tfutils/summary.py

@@ -69,7 +69,7 @@ def add_param_summary(summary_lists):
                 for act in actions:
                     perform(p, act)
 
-# TODO use name of cost_var
+# TODO get rid of the cost_var thing...
 def summary_moving_average(cost_var):
     """ Create a MovingAverage op and summary for all variables in
         MOVING_SUMMARY_VARS_KEY, as well as `cost_var`.

tensorpack/train/trainer.py

@@ -137,8 +137,8 @@ class QueueInputTrainer(Trainer):
                             kept_summaries[k] = copy.copy(tf.get_collection(k))
                     logger.info("Graph built for tower {}.".format(i))
             for k in coll_keys:
-                del tf.get_collection(k)[:]
-                tf.get_collection(k).extend(kept_summaries[k])
+                del tf.get_collection_ref(k)[:]
+                tf.get_collection_ref(k).extend(kept_summaries[k])
             grads = QueueInputTrainer._average_grads(grad_list)
             cost_var = cost_var_t0
         else: