Update `tests/checkpointing/*.py` to use `devices` instead of `gpus` or `ipus` (#11408)

Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>

tests/checkpointing/test_checkpoint_callback_frequency.py

@@ -115,7 +115,8 @@ def test_top_k_ddp(save_mock, tmpdir, k, epochs, val_check_interval, expected):
         enable_model_summary=False,
         val_check_interval=val_check_interval,
         strategy="ddp",
-        gpus=2,
+        accelerator="gpu",
+        devices=2,
         limit_train_batches=64,
         limit_val_batches=32,
     )

tests/checkpointing/test_legacy_checkpoints.py

@@ -75,9 +75,11 @@ def test_resume_legacy_checkpoints(tmpdir, pl_version: str):
         model = ClassificationModel()
         es = EarlyStopping(monitor="val_acc", mode="max", min_delta=0.005)
         stop = LimitNbEpochs(1)
+
         trainer = Trainer(
             default_root_dir=str(tmpdir),
-            gpus=int(torch.cuda.is_available()),
+            accelerator="auto",
+            devices=1,
             precision=(16 if torch.cuda.is_available() else 32),
             callbacks=[es, stop],
             max_epochs=21,

tests/checkpointing/test_model_checkpoint.py

@@ -396,7 +396,8 @@ def test_model_checkpoint_no_extraneous_invocations(tmpdir):
     model_checkpoint = ModelCheckpointTestInvocations(monitor="early_stop_on", expected_count=num_epochs, save_top_k=-1)
     trainer = Trainer(
         strategy="ddp_spawn",
-        num_processes=2,
+        accelerator="cpu",
+        devices=2,
         default_root_dir=tmpdir,
         callbacks=[model_checkpoint],
         max_epochs=num_epochs,

tests/checkpointing/test_torch_saving.py

@@ -40,7 +40,7 @@ def test_model_torch_save_ddp_cpu(tmpdir):
     model = BoringModel()
     num_epochs = 1
     trainer = Trainer(
-        default_root_dir=tmpdir, max_epochs=num_epochs, strategy="ddp_spawn", num_processes=2, logger=False
+        default_root_dir=tmpdir, max_epochs=num_epochs, strategy="ddp_spawn", accelerator="cpu", devices=2, logger=False
     )
     temp_path = os.path.join(tmpdir, "temp.pt")
     trainer.fit(model)
@@ -55,7 +55,9 @@ def test_model_torch_save_ddp_cuda(tmpdir):
     """Test to ensure torch save does not fail for model and trainer using gpu ddp."""
     model = BoringModel()
     num_epochs = 1
-    trainer = Trainer(default_root_dir=tmpdir, max_epochs=num_epochs, strategy="ddp_spawn", gpus=2)
+    trainer = Trainer(
+        default_root_dir=tmpdir, max_epochs=num_epochs, strategy="ddp_spawn", accelerator="gpu", devices=2
+    )
     temp_path = os.path.join(tmpdir, "temp.pt")
     trainer.fit(model)