fix test - reduce metric

tests/trainer/logging_tests/test_train_loop_logging_1_0.py

@@ -862,19 +862,18 @@ def test_metric_are_properly_reduced(tmpdir):
     class TestingModel(BoringModel):
         def __init__(self, *args, **kwargs):
             super().__init__()
-            self.train_acc = pl.metrics.Accuracy()
             self.val_acc = pl.metrics.Accuracy()
 
         def training_step(self, batch, batch_idx):
-            self.train_acc(torch.rand(1, 3, device=self.device), torch.randint(0, 2, (1,), device=self.device))
-            self.log('train_acc', self.train_acc, on_step=True, on_epoch=True)
-            return super().training_step(batch, batch_idx)
+            output = super().training_step(batch, batch_idx)
+            self.log("train_loss", output["loss"])
+            return output
 
         def validation_step(self, batch, batch_idx):
-            preds = torch.tensor(0, device=self.device)
-            targets = torch.tensor(1, device=self.device)
+            preds = torch.tensor([[0.9, 0.1]], device=self.device)
+            targets = torch.tensor([1], device=self.device)
             if batch_idx < 8:
-                targets = preds
+                preds = torch.tensor([[0.1, 0.9]], device=self.device)
             self.val_acc(preds, targets)
             self.log('val_acc', self.val_acc, on_step=True, on_epoch=True)
             return super().validation_step(batch, batch_idx)
@@ -899,4 +898,4 @@ def validation_step(self, batch, batch_idx):
     trainer.fit(model)
 
     assert trainer.callback_metrics["val_acc"] == 8 / 32.
-    assert "train_acc" in trainer.callback_metrics
+    assert "train_loss" in trainer.callback_metrics