update docs

tensorpack/callbacks/param.py

@@ -140,8 +140,8 @@ class HyperParamSetter(Callback):
         """
         ret = self._get_value_to_set()
         if ret is not None and ret != self.last_value:
-            logger.info("{} at epoch {} will change to {:.8f}".format(
-                self.param.readable_name, self.epoch_num + 1, ret))
+            logger.info("After epoch {}, {} will change to {:.8f}".format(
+                self.epoch_num, self.param.readable_name, ret))
         self.last_value = ret
         return ret
 

tensorpack/train/base.py

@@ -95,7 +95,11 @@ class Trainer(object):
     @property
     def epoch_num(self):
         """
-        The number of epochs that have finished.
+        The number of the currently ongoing epoch.
+
+        An epoch is defined to cover the moment before calling `before_epoch` until after calling `trigger_epoch`.
+        i.e., in the `trigger_epoch` of epoch 3, `self.epoch_num` is 3.
+        If you need use `self.epoch_num` in your callback, you'll need to know this.
         """
         if self._epoch_num is not None:
             # has started training