Cosmetics.

diff --git a/cnn-svrt.py b/cnn-svrt.py
index 338e145..a6b9cab 100755 (executable)
--- a/cnn-svrt.py
+++ b/cnn-svrt.py
@@ -442,7 +442,7 @@ class vignette_logger():
             )
             self.last_t = t
 
-def save_examplar_vignettes(data_set, nb, name):
+def save_exemplar_vignettes(data_set, nb, name):
     n = torch.randperm(data_set.nb_samples).narrow(0, 0, nb)
 
     for k in range(0, nb):
@@ -493,7 +493,7 @@ for problem_number in map(int, args.problems.split(',')):
 
     model_filename = model.name + '_pb:' + \
                      str(problem_number) + '_ns:' + \
-                     int_to_suffix(args.nb_train_samples) + '.state'
+                     int_to_suffix(args.nb_train_samples) + '.pth'
 
     nb_parameters = 0
     for p in model.parameters(): nb_parameters += p.numel()
@@ -529,8 +529,8 @@ for problem_number in map(int, args.problems.split(',')):
         )
 
         if args.nb_exemplar_vignettes > 0:
-            save_examplar_vignettes(train_set, args.nb_exemplar_vignettes,
-                                    'examplar_{:d}.png'.format(problem_number))
+            save_exemplar_vignettes(train_set, args.nb_exemplar_vignettes,
+                                    'exemplar_{:d}.png'.format(problem_number))
 
         if args.validation_error_threshold > 0.0:
             validation_set = VignetteSet(problem_number,