change to python2 shebang

README.md

@@ -9,8 +9,8 @@ You can actually train them and reproduce the performance... not just to see how
 + [ResNet for Cifar10 classification](examples/ResNet)
 + [Fully-convolutional Network for Holistically-Nested Edge Detection](examples/HED)
 + [Spatial Transformer Networks on MNIST addition](examples/SpatialTransformer)
-+ [Double-DQN plays Atari games](examples/Atari2600)
-+ [Batch-A3C plays Atari games with demos on OpenAI Gym](examples/OpenAIGym)
++ [Double DQN plays Atari games](examples/Atari2600)
++ [Asynchronous Advantage Actor-Critic(A3C) with demos on OpenAI Gym Atari games](examples/OpenAIGym)
 + [char-rnn language model](examples/char-rnn)
 
 ## Features:

examples/Atari2600/DQN.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: utf-8 -*-
 # File: DQN.py
 # Author: Yuxin Wu <ppwwyyxxc@gmail.com>
@@ -160,8 +160,7 @@ def get_config():
         dataset=dataset_train,
         optimizer=tf.train.AdamOptimizer(lr, epsilon=1e-3),
         callbacks=Callbacks([
-            StatPrinter(),
-            ModelSaver(),
+            StatPrinter(), ModelSaver(),
             ScheduledHyperParamSetter('learning_rate',
                 [(150, 4e-4), (250, 1e-4), (350, 5e-5)]),
             RunOp(lambda: M.update_target_param()),

examples/Atari2600/README.md

 ![breakout](breakout.jpg)
 
+[video demo](https://youtu.be/o21mddZtE5Y)
+
 Reproduce the following reinforcement learning methods:
 
 + Nature-DQN in:
@@ -18,16 +20,11 @@ Claimed performance in the paper can be reproduced, on several games I've tested
 DQN typically took 2 days of training to reach a score of 400 on breakout game.
 My Batch-A3C implementation only took <2 hours.
 Both were trained on one GPU with an extra GPU for simulation.
-<!--
-   -This is probably the fastest RL trainer you'd find.
-	 -->
 
 The x-axis is the number of iterations, not wall time.
 Iteration speed on Tesla M40 is about 9.7it/s for B-A3C.
 D-DQN is faster at the beginning but will converge to 12it/s due of exploration annealing.
 
-A demo trained with Double-DQN on breakout is available at [youtube](https://youtu.be/o21mddZtE5Y).
-
 ## How to use
 
 Download [atari roms](https://github.com/openai/atari-py/tree/master/atari_py/atari_roms) to
@@ -40,7 +37,7 @@ To train:
 
 To visualize the agent:
 ```
-./DQN.py --rom breakout.bin --task play --load pretrained.model
+./DQN.py --rom breakout.bin --task play --load trained.model
 ```
 
 A3C code and models for Atari games in OpenAI Gym are released in [examples/OpenAIGym](../OpenAIGym)

examples/OpenAIGym/README.md

-# A3C Code and models for my Gym submissions on Atari games.
+### A3C code and models for my Gym submissions on Atari games
 
 ### To train on an Atari game:
 
@@ -7,7 +7,7 @@
 ### To run a pretrained Atari model for 100 episodes:
 
 1. Download models from [model zoo](https://drive.google.com/open?id=0B9IPQTvr2BBkS0VhX0xmS1c5aFk)
-2. `ENV=Breakout-v0; ./run-atari.py --load "$ENV".tfmodel --env "$ENV"`
+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):
 
@@ -64,3 +64,5 @@ Note that atari game settings in gym are quite different from DeepMind papers, s
 + In gym, inputs are RGB instead of greyscale.
 + In gym, an episode is limited to 10000 steps.
 + The action space also seems to be different.
+
+Also see the DQN implementation [here](../Atari2600)

examples/OpenAIGym/run-atari.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: utf-8 -*-
 # File: run-atari.py
 # Author: Yuxin Wu <ppwwyyxxc@gmail.com>
@@ -61,25 +61,26 @@ class Model(ModelDesc):
         policy = self._get_NN_prediction(state)
         self.logits = tf.nn.softmax(policy, name='logits')
 
-def run_submission(cfg):
-    dirname = 'gym-submit'
-    player = get_player(dumpdir=dirname)
+def run_submission(cfg, output, nr):
+    player = get_player(dumpdir=output)
     predfunc = get_predict_func(cfg)
-    for k in range(100):
+    for k in range(nr):
         if k != 0:
             player.restart_episode()
         score = play_one_episode(player, predfunc)
         print("Total:", score)
 
-def do_submit():
-    dirname = 'gym-submit'
-    gym.upload(dirname, api_key='xxx')
+def do_submit(output):
+    gym.upload(output, api_key='xxx')
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.') # nargs='*' in multi mode
     parser.add_argument('--load', help='load model', required=True)
-    parser.add_argument('--env', help='env', required=True)
+    parser.add_argument('--env', help='environment name', required=True)
+    parser.add_argument('--episode', help='number of episodes to run',
+            type=int, default=100)
+    parser.add_argument('--output', help='output directory', default='gym-submit')
     args = parser.parse_args()
 
     ENV_NAME = args.env
@@ -95,4 +96,4 @@ if __name__ == '__main__':
             session_init=SaverRestore(args.load),
             input_var_names=['state'],
             output_var_names=['logits'])
-    run_submission(cfg)
+    run_submission(cfg, args.output, args.episode)

examples/OpenAIGym/train-atari.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: utf-8 -*-
 # File: train-atari.py
 # Author: Yuxin Wu <ppwwyyxxc@gmail.com>

examples/README.md

@@ -4,9 +4,9 @@
 Training examples with __reproducible__ and meaningful performance.
 
 + [An illustrative mnist example with explanation of the framework](mnist-convnet.py)
-+ [A tiny SVHN ConvNet with 97.5% accuracy](svhn-digit-convnet.py)
++ [A tiny SVHN ConvNet with 97.8% accuracy](svhn-digit-convnet.py)
 + [Inception-BN with 71% accuracy](Inception/inception-bn.py)
-+ [InceptionV3 with 74.5% accuracy (similar to the official code)](Inception/inceptionv3.py)
++ [InceptionV3 with 74% accuracy (similar to the official code)](Inception/inceptionv3.py)
 + [DoReFa-Net: binary / low-bitwidth CNN on ImageNet](DoReFa-Net)
 + [ResNet for Cifar10 and SVHN](ResNet)
 + [Holistically-Nested Edge Detection](HED)

examples/load-alexnet.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: load-alexnet.py
 # Author: Yuxin Wu <ppwwyyxxc@gmail.com>
@@ -15,7 +15,7 @@ from tensorpack.dataflow.dataset import ILSVRCMeta
 
 """
 Usage:
-    python2 -m tensorpack.utils.loadcaffe PATH/TO/CAFFE/{deploy.prototxt,bvlc_alexnet.caffemodel} alexnet.npy
+    python -m tensorpack.utils.loadcaffe PATH/TO/CAFFE/{deploy.prototxt,bvlc_alexnet.caffemodel} alexnet.npy
     ./load-alexnet.py --load alexnet.npy --input cat.png
 """
 

examples/load-vgg16.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: load-vgg16.py
 # Author: Yuxin Wu <ppwwyyxxc@gmail.com>
@@ -23,7 +23,7 @@ from tensorpack.dataflow.dataset import ILSVRCMeta
 
 """
 Usage:
-    python2 -m tensorpack.utils.loadcaffe PATH/TO/VGG/{VGG_ILSVRC_16_layers_deploy.prototxt,VGG_ILSVRC_16_layers.caffemodel} vgg16.npy
+    python -m tensorpack.utils.loadcaffe PATH/TO/VGG/{VGG_ILSVRC_16_layers_deploy.prototxt,VGG_ILSVRC_16_layers.caffemodel} vgg16.npy
     ./load-vgg16.py --load vgg16.npy --input cat.png
 """
 

scripts/dump-model-params.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: dump-model-params.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

scripts/dump-train-config.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: dump_train_config.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

scripts/imgclassify.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: imgclassify.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

scripts/plot-point.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: utf-8 -*-
 
 """

tensorpack/RL/expreplay.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: utf-8 -*-
 # File: expreplay.py
 # Author: Yuxin Wu <ppwwyyxxc@gmail.com>

tensorpack/RL/simulator.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: utf-8 -*-
 # File: simulator.py
 # Author: Yuxin Wu <ppwwyyxxc@gmail.com>

tensorpack/callbacks/param.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: param.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
@@ -144,6 +144,9 @@ class HumanHyperParamSetter(HyperParamSetter):
             self.file_name, self.param.readable_name))
 
     def _get_value_to_set(self):
+        # ignore if no such file exists
+        if not os.path.isfile(self.file_name):
+            return None
         try:
             with open(self.file_name) as f:
                 lines = f.readlines()
@@ -152,9 +155,9 @@ class HumanHyperParamSetter(HyperParamSetter):
             ret = dic[self.param.readable_name]
             return ret
         except:
-            #logger.warn(
-                #"Cannot find {} in {}".format(
-                    #self.param.readable_name, self.file_name))
+            logger.warn(
+                "Cannot find {} in {}".format(
+                    self.param.readable_name, self.file_name))
             return None
 
 class ScheduledHyperParamSetter(HyperParamSetter):

tensorpack/dataflow/base.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: base.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/dataflow/dataset/cifar.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: cifar.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/dataflow/dataset/mnist.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: mnist.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/dataflow/dataset/svhn.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: svhn.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/dataflow/imgaug/_test.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: _test.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/models/_test.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: _test.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/models/batch_norm.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: batch_norm.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/models/conv2d.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: conv2d.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/models/fc.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: fc.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/models/image_sample.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: image_sample.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/models/model_desc.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: model_desc.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/models/nonlin.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: nonlin.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/models/pool.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: pool.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/tfutils/common.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: common.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/tfutils/gradproc.py

-#!/usr/bin/env python2
+#!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 # File: gradproc.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>

tensorpack/train/base.py

@@ -126,7 +126,7 @@ class Trainer(object):
                 for self.epoch_num in range(
                         self.config.starting_epoch, self.config.max_epoch+1):
                     with timed_operation(
-                        'Epoch {}, global_step={}'.format(
+                        'Epoch {} (global_step {})'.format(
                             self.epoch_num, self.global_step + self.config.step_per_epoch)):
                         for step in tqdm.trange(
                                 self.config.step_per_epoch,

tensorpack/utils/timer.py

@@ -42,7 +42,7 @@ def timed_operation(msg, log_start=False):
         logger.info('Start {} ...'.format(msg))
     start = time.time()
     yield
-    logger.info('{} finished, time={:.2f}sec.'.format(
+    logger.info('{} finished, time:{:.2f}sec.'.format(
         msg, time.time() - start))
 
 _TOTAL_TIMER_DATA = defaultdict(StatCounter)

tensorpack/utils/viz.py

 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 # File: viz.py
-# Author: Yuxin Wu <ppwwyyxxc@gmail.com>
+# Credit: zxytim
 
 import numpy as np