fix pep8 style in examples/

examples/Atari2600/DQN.py

@@ -62,6 +62,8 @@ def get_player(viz=False, train=False):
         pl = PreventStuckPlayer(pl, 30, 1)
     pl = LimitLengthPlayer(pl, 30000)
     return pl
+
+
 common.get_player = get_player  # so that eval functions in common can use the player
 
 
@@ -92,9 +94,9 @@ class Model(ModelDesc):
                  .Conv2D('conv3', out_channel=64, kernel_shape=3)
 
                  # the original arch
-                 #.Conv2D('conv0', image, out_channel=32, kernel_shape=8, stride=4)
-                 #.Conv2D('conv1', out_channel=64, kernel_shape=4, stride=2)
-                 #.Conv2D('conv2', out_channel=64, kernel_shape=3)
+                 # .Conv2D('conv0', image, out_channel=32, kernel_shape=8, stride=4)
+                 # .Conv2D('conv1', out_channel=64, kernel_shape=4, stride=2)
+                 # .Conv2D('conv2', out_channel=64, kernel_shape=3)
 
                  .FullyConnected('fc0', 512, nl=LeakyReLU)())
         if METHOD != 'Dueling':
@@ -180,8 +182,8 @@ def get_config():
             RunOp(lambda: M.update_target_param()),
             dataset_train,
             PeriodicCallback(Evaluator(EVAL_EPISODE, ['state'], ['Qvalue']), 3),
-            #HumanHyperParamSetter('learning_rate', 'hyper.txt'),
-            #HumanHyperParamSetter(ObjAttrParam(dataset_train, 'exploration'), 'hyper.txt'),
+            # HumanHyperParamSetter('learning_rate', 'hyper.txt'),
+            # HumanHyperParamSetter(ObjAttrParam(dataset_train, 'exploration'), 'hyper.txt'),
         ]),
         # save memory for multiprocess evaluator
         session_config=get_default_sess_config(0.6),
@@ -189,6 +191,7 @@ def get_config():
         step_per_epoch=STEP_PER_EPOCH,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/Atari2600/atari.py

@@ -166,9 +166,9 @@ class AtariPlayer(RLEnvironment):
             self.restart_episode()
         return (r, isOver)
 
+
 if __name__ == '__main__':
     import sys
-    import time
 
     def benchmark():
         a = AtariPlayer(sys.argv[1], viz=False, height_range=(28, -8))
@@ -189,7 +189,7 @@ if __name__ == '__main__':
         import threading
         import multiprocessing
         for k in range(3):
-            #th = multiprocessing.Process(target=benchmark)
+            # th = multiprocessing.Process(target=benchmark)
             th = threading.Thread(target=benchmark)
             th.start()
             time.sleep(0.02)
@@ -201,8 +201,8 @@ if __name__ == '__main__':
         rng = get_rng(num)
         import time
         while True:
-            #im = a.grab_image()
-            #cv2.imshow(a.romname, im)
+            # im = a.grab_image()
+            # cv2.imshow(a.romname, im)
             act = rng.choice(range(num))
             print(act)
             r, o = a.action(act)

examples/ConvolutionalPoseMachines/load-cpm.py

@@ -113,6 +113,7 @@ def run_test(model_path, img_file):
     viz = colorize(im, hm)
     cv2.imwrite("output.jpg", viz)
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--load', required=True, help='.npy model file')

examples/DisturbLabel/mnist-disturb.py

@@ -22,8 +22,9 @@ def get_data():
     dataset_train = BatchData(DisturbLabel(dataset.Mnist('train'), args.prob), 128)
     dataset_test = BatchData(dataset.Mnist('test'), 256, remainder=True)
     return dataset_train, dataset_test
-mnist_example.get_data = get_data
 
+
+mnist_example.get_data = get_data
 IMAGE_SIZE = 28
 
 
@@ -54,6 +55,7 @@ class Model(mnist_example.Model):
 
         self.cost = tf.add_n([wd_cost, cost], name='cost')
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/DisturbLabel/svhn-disturb.py

@@ -15,18 +15,19 @@ from disturb import DisturbLabel
 import imp
 
 svhn_example = imp.load_source('svhn_example',
-        os.path.join(os.path.dirname(__file__), '..', 'svhn-digit-convnet.py')))
-Model=svhn_example.Model
-get_config=svhn_example.get_config
+                               os.path.join(os.path.dirname(__file__), '..', 'svhn-digit-convnet.py'))
+Model = svhn_example.Model
+get_config = svhn_example.get_config
+
 
 def get_data():
-    d1=dataset.SVHNDigit('train')
-    d2=dataset.SVHNDigit('extra')
-    data_train=RandomMixData([d1, d2])
-    data_train=DisturbLabel(data_train, args.prob)
-    data_test=dataset.SVHNDigit('test')
+    d1 = dataset.SVHNDigit('train')
+    d2 = dataset.SVHNDigit('extra')
+    data_train = RandomMixData([d1, d2])
+    data_train = DisturbLabel(data_train, args.prob)
+    data_test = dataset.SVHNDigit('test')
 
-    augmentors=[
+    augmentors = [
         imgaug.Resize((40, 40)),
         imgaug.Brightness(30),
         imgaug.Contrast((0.5, 1.5)),
@@ -35,18 +36,20 @@ def get_data():
     data_train = BatchData(data_train, 128)
     data_train = PrefetchData(data_train, 5, 5)
 
-    augmentors = [ imgaug.Resize((40, 40)) ]
+    augmentors = [imgaug.Resize((40, 40))]
     data_test = AugmentImageComponent(data_test, augmentors)
     data_test = BatchData(data_test, 128, remainder=True)
     return data_train, data_test
 
+
 svhn_example.get_data = get_data
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='a gpu to use')
     parser.add_argument('--load', help='load model')
-    parser.add_argument('--prob', help='disturb prob', type=float, required=True)
+    parser.add_argument('--prob', help='disturb prob',
+                        type=float, required=True)
     args = parser.parse_args()
 
     if args.gpu:

examples/DoReFa-Net/alexnet-dorefa.py

@@ -290,6 +290,7 @@ def run_image(model, sess_init, inputs):
         print(f + ":")
         print(list(zip(names, prob[ret])))
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='the physical ids of GPUs to use')

examples/DoReFa-Net/svhn-digit-dorefa.py

@@ -140,8 +140,8 @@ def get_config():
         imgaug.Brightness(30),
         imgaug.Contrast((0.5, 1.5)),
         # imgaug.GaussianDeform(  # this is slow but helpful. only use it when you have lots of cpus
-        #[(0.2, 0.2), (0.2, 0.8), (0.8,0.8), (0.8,0.2)],
-        #(40,40), 0.2, 3),
+        # [(0.2, 0.2), (0.2, 0.8), (0.8,0.8), (0.8,0.2)],
+        # (40,40), 0.2, 3),
     ]
     data_train = AugmentImageComponent(data_train, augmentors)
     data_train = BatchData(data_train, 128)
@@ -173,6 +173,7 @@ def get_config():
         max_epoch=200,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='the GPU to use')

examples/GAN/DCGAN-CelebA.py

@@ -134,6 +134,7 @@ def sample(model_path):
         o = o[:, :, :, ::-1]
         viz = next(build_patch_list(o, nr_row=10, nr_col=10, viz=True))
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/GAN/Image2Image.py

@@ -22,7 +22,8 @@ from GAN import GANTrainer, build_GAN_losses
 To train:
     ./Image2Image.py --data /path/to/datadir --mode {AtoB,BtoA}
     # datadir should contain jpg images of shpae 2s x s, formed by A and B
-    # you can download some data from the original authors: https://people.eecs.berkeley.edu/~tinghuiz/projects/pix2pix/datasets/
+    # you can download some data from the original authors:
+    # https://people.eecs.berkeley.edu/~tinghuiz/projects/pix2pix/datasets/
     # training visualization will appear be in tensorboard
 
 Speed:
@@ -193,7 +194,8 @@ def sample(datadir, model_path):
     pred = SimpleDatasetPredictor(pred, ds)
     for o in pred.get_result():
         o = o[0][:, :, :, ::-1]
-        viz = next(build_patch_list(o, nr_row=3, nr_col=2, viz=True))
+        next(build_patch_list(o, nr_row=3, nr_col=2, viz=True))
+
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()

examples/GAN/InfoGAN-mnist.py

@@ -134,6 +134,7 @@ def sample(model_path):
         viz = cv2.resize(viz, (800, 800))
         interactive_imshow(viz)
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/HED/hed.py

@@ -206,6 +206,7 @@ def run(model_path, image_path, output):
         pred = outputs[5][0]
         cv2.imwrite(output, pred * 255)
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/Inception/inception-bn.py

@@ -165,7 +165,7 @@ def get_config():
             InferenceRunner(dataset_val, [
                 ClassificationError('wrong-top1', 'val-top1-error'),
                 ClassificationError('wrong-top5', 'val-top5-error')]),
-            #HumanHyperParamSetter('learning_rate', 'hyper-googlenet.txt')
+            # HumanHyperParamSetter('learning_rate', 'hyper-googlenet.txt')
             ScheduledHyperParamSetter('learning_rate',
                                       [(8, 0.03), (14, 0.02), (17, 5e-3),
                                        (19, 3e-3), (24, 1e-3), (26, 2e-4),
@@ -177,6 +177,7 @@ def get_config():
         max_epoch=80,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/Inception/inceptionv3.py

@@ -19,7 +19,8 @@ import multiprocessing
 InceptionV3 on ILSVRC12.
 See "Rethinking the Inception Architecture for Computer Vision", arxiv:1512.00567
 
-This config follows the official inceptionv3 setup (https://github.com/tensorflow/models/tree/master/inception/inception)
+This config follows the official inceptionv3 setup
+(https://github.com/tensorflow/models/tree/master/inception/inception)
 with much much fewer lines of code.
 It reaches 74% single-crop validation accuracy,
 and has the same running speed as the official code.
@@ -284,6 +285,7 @@ def get_config():
         max_epoch=100,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/OpenAIGym/run-atari.py

@@ -15,6 +15,7 @@ import six
 
 from tensorpack import *
 from tensorpack.RL import *
+from common import play_one_episode
 
 IMAGE_SIZE = (84, 84)
 FRAME_HISTORY = 4
@@ -24,8 +25,6 @@ IMAGE_SHAPE3 = IMAGE_SIZE + (CHANNEL,)
 NUM_ACTIONS = None
 ENV_NAME = None
 
-from common import play_one_episode
-
 
 def get_player(dumpdir=None):
     pl = GymEnv(ENV_NAME, dumpdir=dumpdir, auto_restart=False)
@@ -82,6 +81,7 @@ def run_submission(cfg, output, nr):
 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.')

examples/OpenAIGym/train-atari.py

@@ -62,6 +62,8 @@ def get_player(viz=False, train=False, dumpdir=None):
         pl = PreventStuckPlayer(pl, 30, 1)
     pl = LimitLengthPlayer(pl, 40000)
     return pl
+
+
 common.get_player = get_player
 
 
@@ -220,6 +222,7 @@ def get_config():
         max_epoch=1000,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/ResNet/cifar10-resnet.py

@@ -153,6 +153,7 @@ def get_config():
         max_epoch=400,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/ResNet/imagenet-resnet.py

@@ -159,9 +159,9 @@ def get_data(train_or_test):
                  imgaug.Saturation(0.4),
                  imgaug.Lighting(0.1,
                                  eigval=[0.2175, 0.0188, 0.0045],
-                                 eigvec=[[-0.5675,  0.7192,  0.4009],
+                                 eigvec=[[-0.5675, 0.7192, 0.4009],
                                          [-0.5808, -0.0045, -0.8140],
-                                         [-0.5836, -0.6948,  0.4203]]
+                                         [-0.5836, -0.6948, 0.4203]]
                                  )]),
             imgaug.Clip(),
             imgaug.Flip(horiz=True),
@@ -221,6 +221,7 @@ def eval_on_ILSVRC12(model_file, data_dir):
     print("Top1 Error: {}".format(acc1.ratio))
     print("Top5 Error: {}".format(acc5.ratio))
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/ResNet/load-resnet.py

@@ -95,10 +95,10 @@ class Model(ModelDesc):
 
 def get_inference_augmentor():
     # load ResNet mean from Kaiming:
-    #from tensorpack.utils.loadcaffe import get_caffe_pb
-    #obj = get_caffe_pb().BlobProto()
+    # from tensorpack.utils.loadcaffe import get_caffe_pb
+    # obj = get_caffe_pb().BlobProto()
     # obj.ParseFromString(open('ResNet_mean.binaryproto').read())
-    #pp_mean_224 = np.array(obj.data).reshape(3, 224, 224).transpose(1,2,0)
+    # pp_mean_224 = np.array(obj.data).reshape(3, 224, 224).transpose(1,2,0)
 
     meta = ILSVRCMeta()
     pp_mean = meta.get_per_pixel_mean()
@@ -194,6 +194,7 @@ def name_conversion(caffe_layer_name):
         int(layer_group) - 2, layer_block, layer_type) + tf_name
     return tf_name
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/ResNet/svhn-resnet.py

@@ -83,6 +83,7 @@ def get_config():
         max_epoch=500,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/SpatialTransformer/mnist-addition.py

@@ -167,6 +167,7 @@ def get_config():
         max_epoch=500,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/TIMIT/create-lmdb.py

@@ -15,8 +15,12 @@ from tensorpack.utils.stats import OnlineMoments
 import bob.ap
 
 CHARSET = set(string.ascii_lowercase + ' ')
-PHONEME_LIST = "aa,ae,ah,ao,aw,ax,ax-h,axr,ay,b,bcl,ch,d,dcl,dh,dx,eh,el,em,en,eng,epi,er,ey,f,g,gcl,h#,hh,hv,ih,ix,iy,jh,k,kcl,l,m,n,ng,nx,ow,oy,p,pau,pcl,q,r,s,sh,t,tcl,th,uh,uw,ux,v,w,y,z,zh".split(
-    ',')
+PHONEME_LIST = [
+    'aa', 'ae', 'ah', 'ao', 'aw', 'ax', 'ax-h', 'axr', 'ay', 'b', 'bcl', 'ch', 'd', 'dcl', 'dh',
+    'dx', 'eh', 'el', 'em', 'en', 'eng', 'epi', 'er', 'ey', 'f', 'g', 'gcl', 'h#', 'hh', 'hv', 'ih',
+    'ix', 'iy', 'jh', 'k', 'kcl', 'l', 'm', 'n', 'ng', 'nx', 'ow', 'oy', 'p', 'pau', 'pcl', 'q', 'r',
+    's', 'sh', 't', 'tcl', 'th', 'uh', 'uw', 'ux', 'v', 'w', 'y', 'z', 'zh']
+
 PHONEME_DIC = {v: k for k, v in enumerate(PHONEME_LIST)}
 WORD_DIC = {v: k for k, v in enumerate(string.ascii_lowercase + ' ')}
 
@@ -110,6 +114,7 @@ def compute_mean_std(db, fname):
     with open(fname, 'wb') as f:
         f.write(serialize.dumps([o.mean, o.std]))
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     subparsers = parser.add_subparsers(title='command', dest='command')

examples/TIMIT/train-timit.py

@@ -109,6 +109,7 @@ def get_config(ds_train, ds_test):
         max_epoch=70,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/char-rnn/char-rnn.py

@@ -161,6 +161,7 @@ def sample(path, start, length):
             ret += c
         print(ret)
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/cifar-convnet.py

@@ -136,6 +136,7 @@ def get_config(cifar_classnum):
         max_epoch=150,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/load-alexnet.py

@@ -74,6 +74,7 @@ def run_test(path, input):
     meta = ILSVRCMeta().get_synset_words_1000()
     print("Top10 class names:", [meta[k] for k in ret])
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/load-vgg16.py

@@ -17,7 +17,8 @@ from tensorpack.dataflow.dataset import ILSVRCMeta
 
 """
 Usage:
-    python -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
 """
 
@@ -84,6 +85,7 @@ def run_test(path, input):
     meta = ILSVRCMeta().get_synset_words_1000()
     print("Top10 class names:", [meta[k] for k in ret])
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/mnist-convnet.py

@@ -129,6 +129,7 @@ def get_config():
         max_epoch=100,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/svhn-digit-convnet.py

@@ -111,6 +111,7 @@ def get_config():
         max_epoch=350,
     )
 
+
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')

examples/tox.ini

+[flake8]
+max-line-length = 120
+ignore = F403,F401,F405,F841