WIP: Fix non-tensor scalar result aggregation

pytorch_lightning/core/step_result.py

@@ -118,12 +118,16 @@ def log(
         sync_dist_op: Union[Any, str] = 'mean',
         sync_dist_group: Optional[Any] = None,
     ):
+
         # no metrics should be logged with graphs
         if not enable_graph and isinstance(value, torch.Tensor):
             value = value.detach()
 
+        if not isinstance(value, (torch.Tensor, numbers.Number)):
+            value = torch.tensor(value, device=self.device)
+
         # sync across ddp
-        if sync_dist and isinstance(value, (torch.Tensor, numbers.Number)):
+        if sync_dist:
             value = sync_ddp_if_available(value, group=sync_dist_group, reduce_op=sync_dist_op)
 
         if 'meta' not in self:

tests/base/model_train_steps.py

@@ -56,7 +56,10 @@ def training_step_result_obj(self, batch, batch_idx, optimizer_idx=None):
 
         result = TrainResult(loss_val)
         result.log('some_val', log_val * log_val, prog_bar=True, logger=False)
+        assert isinstance(result.some_val, torch.Tensor)
         result.log('train_some_val', log_val * log_val)
+        assert isinstance(result.train_some_val, torch.Tensor)
+        result.log('epoch_some_val', log_val * log_val, on_step=False, on_epoch=True)
         return result
 
     def training_step__inf_loss(self, batch, batch_idx, optimizer_idx=None):

tests/core/test_results.py

@@ -244,3 +244,4 @@ def test_result_retrieve_last_logged_item():
     assert result['epoch_a'] == 5.
     assert result['step_a'] == 5.
     assert result['a'] == 5.
+    assert isinstance(result.a, torch.Tensor)