Cosmetics.

[pysvrt.git] / cnn-svrt.py

diff --git a/cnn-svrt.py b/cnn-svrt.py
index 06e58bd..c75b336 100755 (executable)
--- a/cnn-svrt.py
+++ b/cnn-svrt.py
@@ -66,7 +66,7 @@ parser.add_argument('--batch_size',
                     help = 'Mini-batch size')
 
 parser.add_argument('--log_file',
-                    type = str, default = 'cnn-svrt.log',
+                    type = str, default = 'default.log',
                     help = 'Log file name')
 
 parser.add_argument('--compress_vignettes',
@@ -75,7 +75,7 @@ parser.add_argument('--compress_vignettes',
 
 parser.add_argument('--test_loaded_models',
                     action='store_true', default = False,
-                    help = 'Should we compute the test error of models we load')
+                    help = 'Should we compute the test errors of loaded models')
 
 args = parser.parse_args()
 
@@ -88,13 +88,16 @@ print(Fore.RED + 'Logging into ' + args.log_file + Style.RESET_ALL)
 
 def log_string(s):
     global pred_log_t
+
     t = time.time()
 
     if pred_log_t is None:
         elapsed = 'start'
     else:
         elapsed = '+{:.02f}s'.format(t - pred_log_t)
+
     pred_log_t = t
+
     s = Fore.BLUE + time.ctime() + ' ' + Fore.GREEN + elapsed + Style.RESET_ALL + ' ' + s
     log_file.write(s + '\n')
     log_file.flush()
@@ -159,7 +162,7 @@ def train_model(model, train_set):
             loss.backward()
             optimizer.step()
         log_string('train_loss {:d} {:f}'.format(e + 1, acc_loss))
-        dt = (time.time() - t) / (e + 1)
+        dt = (time.time() - start_t) / (e + 1)
         print(Fore.CYAN + 'ETA ' + time.ctime(time.time() + dt * (args.nb_epochs - e)) + Style.RESET_ALL)
 
     return model