Apply suggestions from code review

Co-authored-by: Rohit Gupta <[email protected]>

Author: Borda

pytorch_lightning/callbacks/model_checkpoint.py

@@ -89,7 +89,7 @@ class ModelCheckpoint(Callback):
         mode: one of {min, max}.
             If ``save_top_k != 0``, the decision to overwrite the current save file is made
             based on either the maximization or the minimization of the monitored quantity.
-            For `val_acc`, this should be `max`, for `val_loss` this should be `min`, etc.
+            For ``'val_acc'``, this should be ``'max'``, for ``'val_loss'`` this should be ``'min'``, etc.
         save_weights_only: if ``True``, then only the model's weights will be
             saved (``model.save_weights(filepath)``), else the full model
             is saved (``model.save(filepath)``).
@@ -110,7 +110,7 @@ class ModelCheckpoint(Callback):
         MisconfigurationException:
             If ``save_top_k`` is neither ``None`` nor more than or equal to ``-1``,
             if ``monitor`` is ``None`` and ``save_top_k`` is none of ``None``, ``-1``, and ``0``, or
-            if ``mode`` is none of ``"min"``, ``"max"``.
+            if ``mode`` is none of ``"min"`` or ``"max"``.
         ValueError:
             If ``trainer.save_checkpoint`` is ``None``.
 

tests/trainer/test_trainer.py

@@ -421,7 +421,7 @@ def test_dp_output_reduce():
 
 
 @pytest.mark.parametrize(
-    ["save_top_k", "save_last", "expected_files"],
+    "save_top_k,save_last,expected_files",
     [
         pytest.param(-1, False, [f"epoch={i}.ckpt" for i in range(5)], id="CASE K=-1  (all)"),
         pytest.param(1, False, {"epoch=4.ckpt"}, id="CASE K=1 (2.5, epoch 4)"),