Loss keys (#387)

* any key in logs or progress bar is a candidate for callback metric

* any key in logs or progress bar is a candidate for callback metric

docs/LightningModule/RequiredTrainerInterface.md

@@ -318,12 +318,10 @@ The ```dataset_idx``` corresponds to the order of datasets returned in ```val_da
 ``` {.python}
 def validation_end(self, outputs)
 ```   
-If you didn't define a validation_step, this won't be called.       
-
-Called at the end of the validation loop with the outputs of validation_step.
+If you didn't define a validation_step, this won't be called. Called at the end of the validation loop with the outputs of validation_step.
 
 The outputs here are strictly for the progress bar. If you don't need to display anything, don't return anything.    
-
+Any keys present in 'log', 'progress_bar' or the rest of the dictionary are available for callbacks to access.
 **Params**    
 
 | Param  | description  |

pytorch_lightning/trainer/trainer.py

@@ -1364,6 +1364,10 @@ class Trainer(TrainerIOMixin):
             if self.use_dp or self.use_ddp2:
                 loss = reduce_distributed_output(loss, self.num_gpus)
 
+        # use every metric passed in as a candidate for callback
+        callback_metrics.update(progress_bar_metrics)
+        callback_metrics.update(log_metrics)
+
         return loss, progress_bar_metrics, log_metrics, callback_metrics
 
     def __clip_gradients(self):