decouple returns from each step (#307)

* decoupled training metrics from logging metrics * decoupled validation metrics from log metrics * updated docs * updated docs * updated docs * Fixed test * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master * merged master
2026-09-09 11:32:07 +08:00 · 2019-10-05 13:35:20 -04:00
parent 8f5a06bfb8
commit 6cc3f1757f
9 changed files with 193 additions and 248 deletions
@@ -129,7 +129,8 @@ Dictionary or OrderedDict
 | key  | value  | is required |
 |---|---|---|
 |  loss | tensor scalar  | Y |
-|  progress | Dict for progress bar display. Must have only tensors  | N |
+|  progress_bar | Dict for progress bar display. Must have only tensors  | N |
+|  log | Dict of metrics to add to logger. Must have only tensors (no images, etc)  | N |


 **Example**
@@ -144,7 +145,8 @@ def training_step(self, batch, batch_nb):
    
    output = {
        'loss': loss, # required
-        'progress': {'training_loss': loss} # optional (MUST ALL BE TENSORS)
+        'progress_bar': {'training_loss': loss}, # optional (MUST ALL BE TENSORS)
+        'log': {'training_loss': loss} # optional (MUST ALL BE TENSORS)
    }
    
    # return a dict
@@ -161,6 +163,9 @@ def training_step(self, batch, batch_nb, optimizer_idx):
        # do training_step with decoder    
 ```    

+You can also return a -1 instead of a dict to stop the current loop. This is useful if you want to
+break out of the current training epoch early.
+
 --- 
 ### train_dataloader 

@@ -263,7 +268,7 @@ The dict you return here will be available in the `validation_end` method.

 | Return  | description  | optional |
 |---|---|---|   
-|  dict | Dict or OrderedDict with metrics to display in progress bar. All keys must be tensors. | Y |
+|  dict | Dict or OrderedDict - passed to the validation_end step | N |

 **Example**

@@ -327,9 +332,12 @@ The outputs here are strictly for the progress bar. If you don't need to display

 **Return**   

-| Return  | description  | optional |
-|---|---|---|   
-|  dict | Dict of OrderedDict with metrics to display in progress bar | Y |
+Dictionary or OrderedDict   
+
+| key  | value  | is required |
+|---|---|---|
+|  progress_bar | Dict for progress bar display. Must have only tensors  | N |
+|  log | Dict of metrics to add to logger. Must have only tensors (no images, etc)  | N |

 **Example**

@@ -351,7 +359,13 @@ def validation_end(self, outputs):
    val_loss_mean /= len(outputs)
    val_acc_mean /= len(outputs)
    tqdm_dict = {'val_loss': val_loss_mean.item(), 'val_acc': val_acc_mean.item()}
-    return tqdm_dict
+       
+    # show val_loss and val_acc in progress bar but only log val_loss
+    results = {
+        'progress_bar': tqdm_dict,
+        'log': {'val_loss': val_loss_mean.item()}
+    }
+    return results
 ```

 With multiple dataloaders, `outputs` will be a list of lists. The outer list contains
@@ -377,7 +391,13 @@ def validation_end(self, outputs):
    val_loss_mean /= i
    val_acc_mean /= i
    tqdm_dict = {'val_loss': val_loss_mean.item(), 'val_acc': val_acc_mean.item()}
-    return tqdm_dict
+    
+    # show val_loss and val_acc in progress bar but only log val_loss
+    results = {
+        'progress_bar': tqdm_dict,
+        'log': {'val_loss': val_loss_mean.item()}
+    }
+    return results
 ```

 ### test_step
@@ -490,7 +510,13 @@ def test_end(self, outputs):
    test_loss_mean /= len(outputs)
    test_acc_mean /= len(outputs)
    tqdm_dict = {'test_loss': test_loss_mean.item(), 'test_acc': test_acc_mean.item()}
-    return tqdm_dict
+    
+    # show test_loss and test_acc in progress bar but only log test_loss
+    results = {
+        'progress_bar': tqdm_dict,
+        'log': {'test_loss': val_loss_mean.item()}
+    }
+    return results
 ```

 With multiple dataloaders, `outputs` will be a list of lists. The outer list contains
@@ -516,7 +542,13 @@ def test_end(self, outputs):
    test_loss_mean /= i 
    test_acc_mean /= i
    tqdm_dict = {'test_loss': test_loss_mean.item(), 'test_acc': test_acc_mean.item()}
-    return tqdm_dict
+    
+    # show test_loss and test_acc in progress bar but only log test_loss
+    results = {
+        'progress_bar': tqdm_dict,
+        'log': {'test_loss': val_loss_mean.item()}
+    }
+    return results
 ```

 ---