*): Make code run on python3.

README.md

@@ -33,7 +33,7 @@ bash launch/run_train.sh
 ```
 To test:
 ```
-python test --input_path path/to/img
+python test.py --input_path path/to/img
 ```
 
 ## Citation

data/dataset_aus.py

@@ -34,9 +34,9 @@ def __getitem__(self, index):
             real_cond = self._get_cond_by_id(sample_id)
 
             if real_img is None:
-                print 'error reading image %s, skipping sample' % sample_id
+                print('error reading image %s, skipping sample' % sample_id)
             if real_cond is None:
-                print 'error reading aus %s, skipping sample' % sample_id
+                print('error reading aus %s, skipping sample' % sample_id)
 
         desired_cond = self._generate_random_cond()
 
@@ -92,11 +92,11 @@ def _create_transform(self):
 
     def _read_ids(self, file_path):
         ids = np.loadtxt(file_path, delimiter='\t', dtype=np.str)
-        return [id[:-4] for id in ids]
+        return [str.encode(id[:-4]) for id in ids]
 
     def _read_conds(self, file_path):
         with open(file_path, 'rb') as f:
-            return pickle.load(f)
+            return pickle.load(f, encoding='bytes')
 
     def _get_cond_by_id(self, id):
         if id in self._conds:

launch/run_train.sh

@@ -1,6 +1,6 @@
 #!/usr/bin/env bash
 
 python train.py \
---data_dir path/to/dataset/ \
+--data_dir sample_dataset \
 --name experiment_1 \
 --batch_size 25 \

models/models.py

@@ -90,13 +90,13 @@ def _load_optimizer(self, optimizer, optimizer_label, epoch_label):
             load_path), 'Weights file not found. Have you trained a model!? We are not providing one' % load_path
 
         optimizer.load_state_dict(torch.load(load_path))
-        print 'loaded optimizer: %s' % load_path
+        print('loaded optimizer: %s' % load_path)
 
     def _save_network(self, network, network_label, epoch_label):
         save_filename = 'net_epoch_%s_id_%s.pth' % (epoch_label, network_label)
         save_path = os.path.join(self._save_dir, save_filename)
         torch.save(network.state_dict(), save_path)
-        print 'saved net: %s' % save_path
+        print('saved net: %s' % save_path)
 
     def _load_network(self, network, network_label, epoch_label):
         load_filename = 'net_epoch_%s_id_%s.pth' % (epoch_label, network_label)
@@ -105,7 +105,7 @@ def _load_network(self, network, network_label, epoch_label):
             load_path), 'Weights file not found. Have you trained a model!? We are not providing one' % load_path
 
         network.load_state_dict(torch.load(load_path))
-        print 'loaded net: %s' % load_path
+        print('loaded net: %s' % load_path)
 
     def update_learning_rate(self):
         pass

networks/networks.py

@@ -17,7 +17,7 @@ def get_by_name(network_name, *args, **kwargs):
         else:
             raise ValueError("Network %s not recognized." % network_name)
 
-        print "Network %s was created" % network_name
+        print("Network %s was created" % network_name)
 
         return network