add xception support

README.md

@@ -17,7 +17,7 @@ $ cd pytorch-cifar100
 ```
 
 ### 2. change cifar100 dataset path in conf/global_settings.py
-```CIFAR100_PATH``` is the path to cifar100 dataset, you can download cifar100 by clicking [here](https://www.cs.toronto.edu/~kriz/cifar-100-python.tar.gz), or download from the offical website [here](https://www.cs.toronto.edu/~kriz/cifar.html). Noet that please download the python version cifar100 dataset.
+```CIFAR100_PATH``` is the path to cifar100 dataset, you can download cifar100 by clicking [here](https://www.cs.toronto.edu/~kriz/cifar-100-python.tar.gz), or download from the offical website [here](https://www.cs.toronto.edu/~kriz/cifar.html). Note that please download the python version cifar100 dataset.
 
 ### 3. run tensorbard
 ```bash
@@ -31,9 +31,17 @@ You need to specify the net you want to train using arg -net
 ```bash
 $ python train.py -net vgg16
 ```
-the supported net args are:
+The supported net args are:
 ```
-vgg16, densenet121, densenet161, densenet201, googlenet, inceptionv3, inceptionv4
+vgg16
+densenet121
+densenet161
+densenet201
+googlenet
+inceptionv3
+inceptionv4
+xception
+resnet101
 ```
 Normally, the weights file with the best accuracy would be written to the disk(default in checkpoint folder).
 

test.py

@@ -48,6 +48,12 @@
     elif args.net == 'inceptionv4':
         from models.inceptionv4 import inceptionv4
         net = inceptionv4().cuda()
+    elif args.net == 'resnet101':
+        from models.resnet import resnet101
+        net = resnet101().cuda()
+    elif args.net == 'xception':
+        from models.xception import xception
+        net = xception().cuda()
     else:
         print('the network name you have entered is not supported yet')
 

train.py

@@ -7,6 +7,7 @@
 """
 
 import os
+import sys
 import argparse
 from datetime import datetime
 
@@ -155,9 +156,16 @@ def main(net_name, checkpoint_path, epochs, milestones):
     elif args.net == 'inceptionv4':
         from models.inceptionv4 import inceptionv4
         net = inceptionv4().cuda()
+    elif args.net == 'resnet101':
+        from models.resnet import resnet101
+        net = resnet101().cuda()
+    elif args.net == 'xception':
+        from models.xception import xception
+        net = xception().cuda()
     else:
         print('the network name you have entered is not supported yet')
-
+        sys.exit()
+
     #data preprocessing:
     transform_train = transforms.Compose([
         transforms.ToPILImage(),