diff --git a/pytorch_lightning/trainer/connectors/callback_connector.py b/pytorch_lightning/trainer/connectors/callback_connector.py
index 75cd74b307..2b14a229ce 100644
--- a/pytorch_lightning/trainer/connectors/callback_connector.py
+++ b/pytorch_lightning/trainer/connectors/callback_connector.py
@@ -153,8 +153,8 @@ class CallbackConnector:
         model_callbacks = model.configure_callbacks()
         if not model_callbacks:
             return
-        model_callback_types = set(type(c) for c in model_callbacks)
-        trainer_callback_types = set(type(c) for c in trainer.callbacks)
+        model_callback_types = {type(c) for c in model_callbacks}
+        trainer_callback_types = {type(c) for c in trainer.callbacks}
         override_types = model_callback_types.intersection(trainer_callback_types)
         if override_types:
             rank_zero_info(
diff --git a/pytorch_lightning/utilities/argparse.py b/pytorch_lightning/utilities/argparse.py
index b6bc30b8ea..aebbcb41ac 100644
--- a/pytorch_lightning/utilities/argparse.py
+++ b/pytorch_lightning/utilities/argparse.py
@@ -46,7 +46,7 @@ def from_argparse_args(cls, args: Union[Namespace, ArgumentParser], **kwargs):
 
     # we only want to pass in valid Trainer args, the rest may be user specific
     valid_kwargs = inspect.signature(cls.__init__).parameters
-    trainer_kwargs = dict((name, params[name]) for name in valid_kwargs if name in params)
+    trainer_kwargs = {name: params[name] for name in valid_kwargs if name in params}
     trainer_kwargs.update(**kwargs)
 
     return cls(**trainer_kwargs)
diff --git a/tests/checkpointing/test_model_checkpoint.py b/tests/checkpointing/test_model_checkpoint.py
index 8e2e52b55e..23e63d3883 100644
--- a/tests/checkpointing/test_model_checkpoint.py
+++ b/tests/checkpointing/test_model_checkpoint.py
@@ -823,7 +823,7 @@ def test_model_checkpoint_topk_all(tmpdir):
     assert checkpoint_callback.best_model_path == tmpdir / "epoch=2.ckpt"
     assert checkpoint_callback.best_model_score == epochs - 1
     assert len(os.listdir(tmpdir)) == len(checkpoint_callback.best_k_models) == epochs
-    assert set(checkpoint_callback.best_k_models.keys()) == set(str(tmpdir / f"epoch={i}.ckpt") for i in range(epochs))
+    assert set(checkpoint_callback.best_k_models.keys()) == {str(tmpdir / f"epoch={i}.ckpt") for i in range(epochs)}
     assert checkpoint_callback.kth_best_model_path == tmpdir / 'epoch=0.ckpt'
 
 
@@ -1275,7 +1275,8 @@ def test_ckpt_version_after_rerun_new_trainer(tmpdir):
         assert {Path(f).name for f in mc.best_k_models} == expected
 
     # check created ckpts
-    assert set(f.basename for f in tmpdir.listdir()) == {
+    actual = {f.basename for f in tmpdir.listdir()}
+    assert actual == {
         "epoch=0.ckpt",
         "epoch=1.ckpt",
         "epoch=0-v1.ckpt",