update readme about dorefa

examples/DoReFa-Net/README.md

@@ -13,7 +13,7 @@ It's provided in the format of numpy dictionary, so it should be very easy to po
 
 To use the script. You'll need:
 
-+ [TensorFlow](https://tensorflow.org) >= 0.8
++ [TensorFlow](https://tensorflow.org) >= 0.10
 
 + OpenCV bindings for Python
 

tensorpack/callbacks/inference.py

@@ -131,7 +131,7 @@ class ScalarStats(Inferencer):
     """
     Write some scalar tensor to both stat and summary.
     The output of the given Ops must be a scalar.
-    The value will be averaged over all data points in the dataset.
+    The value will be averaged over all data points in the inference dataflow.
     """
     def __init__(self, names_to_print, prefix='validation'):
         """

tensorpack/train/config.py

@@ -52,7 +52,7 @@ class TrainConfig(object):
         self.step_per_epoch = int(kwargs.pop('step_per_epoch'))
         self.starting_epoch = int(kwargs.pop('starting_epoch', 1))
         self.max_epoch = int(kwargs.pop('max_epoch', 99999))
-        assert self.step_per_epoch > 0 and self.max_epoch > 0
+        assert self.step_per_epoch >= 0 and self.max_epoch > 0
 
         if 'nr_tower' in kwargs or 'tower' in kwargs:
             self.set_tower(**kwargs)