change some model url

examples/OpenAIGym/README.md

@@ -13,7 +13,7 @@ The pre-trained models are all trained with 4 GPUs for about 2 days.
 
 ### To run a pretrained Atari model for 100 episodes:
 
-1. Download models from [model zoo](https://drive.google.com/open?id=0B9IPQTvr2BBkS0VhX0xmS1c5aFk)
+1. Download models from [model zoo](https://goo.gl/9yIol2)
 2. `ENV=Breakout-v0; ./run-atari.py --load "$ENV".tfmodel --env "$ENV" --episode 100 --output output_dir`
 
 Models are available for the following gym atari environments (click links for videos on gym):

examples/ResNet/README.md

@@ -3,7 +3,7 @@
 
 Training code of pre-activation ResNet on ImageNet. It follows the setup in
 [fb.resnet.torch](https://github.com/facebook/fb.resnet.torch) and gets similar performance (with much fewer lines of code).
-Models can be [downloaded here](https://drive.google.com/open?id=0B9IPQTvr2BBkTXBlZmh1cmlnQ0k).
+Models can be [downloaded here](https://goo.gl/6XjK9V).
 
 | Model              | Top 5 Error | Top 1 Error |
 |:-------------------|-------------|------------:|
@@ -16,7 +16,7 @@ Models can be [downloaded here](https://drive.google.com/open?id=0B9IPQTvr2BBkTX
 
 ## load-resnet.py
 
-A script to convert and run ImageNet-ResNet{50,101,152} Caffe models [released by Kaiming](https://github.com/KaimingHe/deep-residual-networks).
+This script only converts and runs ImageNet-ResNet{50,101,152} Caffe models [released by Kaiming](https://github.com/KaimingHe/deep-residual-networks).
 
 Example usage:
 ```bash

tensorpack/train/base.py

@@ -152,6 +152,7 @@ class Trainer(object):
                                 return
                             self.run_step() # implemented by subclass
                             callbacks.trigger_step()   # not useful?
+                    # trigger epoch outside the timing region.
                     self.trigger_epoch()
             except StopTraining:
                 logger.info("Training was stopped.")