Fixing a small issue in trainer logging (Lightning-AI#1563)

* The epoch was being logged to metrics, which isn't read, rather than to current_metrics.

* Updated the tests to account for the epoch arriving at the logger.

Author: guydav

pytorch_lightning/trainer/logging.py

@@ -68,7 +68,7 @@ def log_metrics(self, metrics, grad_norm_dic, step=None):
             step = scalar_metrics.pop("step")
         else:
             # added metrics by Lightning for convenience
-            metrics['epoch'] = self.current_epoch
+            scalar_metrics['epoch'] = self.current_epoch
             step = step if step is not None else self.global_step
         # log actual metrics
         if self.proc_rank == 0 and self.logger is not None:

tests/loggers/test_all.py

@@ -62,9 +62,9 @@ def log_metrics(self, metrics, step):
     trainer.test()
 
     log_metric_names = [(s, sorted(m.keys())) for s, m in logger.history]
-    assert log_metric_names == [(0, ['val_acc', 'val_loss']),
-                                (0, ['train_some_val']),
-                                (1, ['test_acc', 'test_loss'])]
+    assert log_metric_names == [(0, ['epoch', 'val_acc', 'val_loss']),
+                                (0, ['epoch', 'train_some_val']),
+                                (1, ['epoch', 'test_acc', 'test_loss'])]
 
 
 @pytest.mark.parametrize("logger_class", [