cosmetics

Author: awaelchli

tests/tests_pytorch/callbacks/test_model_summary.py

@@ -41,7 +41,7 @@ def test_model_summary_callback_with_enable_model_summary_true():
     assert model_summary_callback._max_depth == 1
 
 
-def test_custom_model_summary_callback_summarize(tmpdir):
+def test_custom_model_summary_callback_summarize(tmp_path):
     class CustomModelSummary(ModelSummary):
         @staticmethod
         def summarize(
@@ -65,6 +65,6 @@ def summarize(
             assert summary_data[4][1][0] == "train"
 
     model = BoringModel()
-    trainer = Trainer(default_root_dir=tmpdir, callbacks=CustomModelSummary(), max_steps=1)
+    trainer = Trainer(default_root_dir=tmp_path, callbacks=CustomModelSummary(), max_steps=1)
 
     trainer.fit(model)

tests/tests_pytorch/utilities/test_model_summary.py

@@ -327,13 +327,13 @@ def test_empty_model_size(max_depth):
         pytest.param("mps", marks=RunIf(mps=True)),
     ],
 )
-def test_model_size_precision(tmpdir, accelerator):
+def test_model_size_precision(tmp_path, accelerator):
     """Test model size for half and full precision."""
     model = PreCalculatedModel()
 
     # fit model
     trainer = Trainer(
-        default_root_dir=tmpdir, accelerator=accelerator, devices=1, max_steps=1, max_epochs=1, precision=32
+        default_root_dir=tmp_path, accelerator=accelerator, devices=1, max_steps=1, max_epochs=1, precision=32
     )
     trainer.fit(model)
     summary = summarize(model)