updated args

pytorch_lightning/models/trainer.py

@@ -15,6 +15,18 @@ except ModuleNotFoundError:
     APEX_AVAILABLE = False
 
 
+def reduce_distributed_output(output, nb_gpus):
+    for k, v in output.items():
+        # recurse on nested dics
+        if isinstance(output[k], dict):
+            output[k] = reduce_distributed_output(output[k], nb_gpus)
+
+        # reduce only metrics that have the same nb of gpus
+        elif output[k].size(0) == nb_gpus:
+            reduced = torch.mean(output[k])
+            output[k] = reduced
+    return output
+
 class Trainer(TrainerIO):
 
     def __init__(self,
@@ -188,13 +200,20 @@ class Trainer(TrainerIO):
             # RUN VALIDATION STEP
             # -----------------
             output = model(data_batch, batch_i)
-            pdb.set_trace()
+
+            # when DP, we need to aggregate the scalars we received as outputs
+            # use mean as the reduce function
+            if self.data_parallel:
+                output = reduce_distributed_output(output, len(self.gpus))
+
             outputs.append(output)
 
             # batch done
             if self.enable_tqdm and self.prog_bar is not None:
                 self.prog_bar.update(1)
 
+        pdb.set_trace()
+
         # give model a chance to do something with the outputs
         val_results = model.validation_end(outputs)