Turn on download by default

main.py

@@ -41,10 +41,10 @@
     transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)),
 ])
 
-trainset = torchvision.datasets.CIFAR10(root='./data', train=True, download=False, transform=transform_train)
+trainset = torchvision.datasets.CIFAR10(root='./data', train=True, download=True, transform=transform_train)
 trainloader = torch.utils.data.DataLoader(trainset, batch_size=128, shuffle=True, num_workers=2)
 
-testset = torchvision.datasets.CIFAR10(root='./data', train=False, download=False, transform=transform_test)
+testset = torchvision.datasets.CIFAR10(root='./data', train=False, download=True, transform=transform_test)
 testloader = torch.utils.data.DataLoader(testset, batch_size=100, shuffle=False, num_workers=2)
 
 classes = ('plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck')
@@ -65,7 +65,8 @@
     # net = GoogLeNet()
     # net = DenseNet121()
     # net = ResNeXt29_2x64d()
-    net = MobileNet()
+    # net = MobileNet()
+    net = DPN26()
 
 if use_cuda:
     net.cuda()

models/__init__.py

@@ -1,4 +1,5 @@
 from .vgg import *
+from .dpn import *
 from .lenet import *
 from .resnet import *
 from .resnext import *

utils.py

@@ -45,7 +45,7 @@ def init_params(net):
 _, term_width = os.popen('stty size', 'r').read().split()
 term_width = int(term_width)
 
-TOTAL_BAR_LENGTH = 86.
+TOTAL_BAR_LENGTH = 65.
 last_time = time.time()
 begin_time = last_time
 def progress_bar(current, total, msg=None):
@@ -81,7 +81,7 @@ def progress_bar(current, total, msg=None):
         sys.stdout.write(' ')
 
     # Go back to the center of the bar.
-    for i in range(term_width-int(TOTAL_BAR_LENGTH/2)):
+    for i in range(term_width-int(TOTAL_BAR_LENGTH/2)+2):
         sys.stdout.write('\b')
     sys.stdout.write(' %d/%d ' % (current+1, total))