checkpointing

PyTorch/sparseconvnet/legacy/classificationTrainValidate.py

@@ -49,11 +49,11 @@ def ClassificationTrainValidate(model, dataset, p):
         'weightDecay': p['weightDecay'],
         'epoch': 1
     }
-    if os.path.isfile('epoch.pth'):
+    if p['checkPoint'] and os.path.isfile('epoch.pth'):
         optimState['epoch'] = torch.load('epoch.pth') + 1
         print('Restarting at epoch ' +
               str(optimState['epoch']) +
-              ' from model.pickle ..')
+              ' from model.pth ..')
         model = torch.load('model.pth')
 
     print(p)

examples/Assamese_handwriting/VGGplus.py

@@ -35,4 +35,4 @@ print('input spatial size', spatial_size)
 dataset = getIterators(spatial_size, 63, 3)
 scn.ClassificationTrainValidate(
     model, dataset,
-    {'nEpochs': 100, 'initial_LR': 0.1, 'LR_decay': 0.05, 'weightDecay': 1e-4})
+    {'nEpochs': 100, 'initial_LR': 0.1, 'LR_decay': 0.05, 'weightDecay': 1e-4, 'checkPoint': False})