fix train-atari py3 compatbility

README.md

@@ -9,7 +9,7 @@ You can actually train them and reproduce the performance... not just to see how
 + [InceptionV3 on ImageNet](examples/Inception/inceptionv3.py)
 + [Fully-convolutional Network for Holistically-Nested Edge Detection](examples/HED)
 + [Spatial Transformer Networks on MNIST addition](examples/SpatialTransformer)
-+ [Deep Convolutional Generative Adversarial Networks](examples/GAN)
++ [Generative Adversarial Networks & Image to Image Translation](examples/GAN)
 + [DQN variants on Atari games](examples/Atari2600)
 + [Asynchronous Advantage Actor-Critic(A3C) with demos on OpenAI Gym](examples/OpenAIGym)
 + [char-rnn language model](examples/char-rnn)

examples/OpenAIGym/train-atari.py

@@ -240,11 +240,11 @@ if __name__ == '__main__':
         if args.gpu:
             nr_gpu = get_nr_gpu()
             if nr_gpu > 1:
-                predict_tower = range(nr_gpu)[-nr_gpu/2:]
+                predict_tower = range(nr_gpu)[-nr_gpu//2:]
             else:
                 predict_tower = [0]
             PREDICTOR_THREAD = len(predict_tower) * PREDICTOR_THREAD_PER_GPU
-            train_tower = range(nr_gpu)[:-nr_gpu/2] or [0]
+            train_tower = range(nr_gpu)[:-nr_gpu//2] or [0]
             logger.info("[BA3C] Train on gpu {} and infer on gpu {}".format(
                 ','.join(map(str, train_tower)), ','.join(map(str, predict_tower))))
         else:

opt-requirements.txt

@@ -2,7 +2,6 @@ pillow
 scipy
 nltk
 h5py
-pyzmq
 tornado; python_version < '3.0'
 lmdb
 matplotlib

requirements.txt

@@ -4,4 +4,5 @@ termcolor
 tqdm>4.6.1
 msgpack-python
 msgpack-numpy
+pyzmq
 subprocess32; python_version < '3.0'