Rename special to standalone (#10779)

Author: carmocca

.azure-pipelines/gpu-tests.yml

@@ -72,10 +72,10 @@ jobs:
       displayName: 'Testing: standard'
 
     - bash: |
-        bash tests/special_tests.sh
+        bash tests/standalone_tests.sh
       env:
         PL_USE_MOCKED_MNIST: "1"
-      displayName: 'Testing: special'
+      displayName: 'Testing: standalone'
 
     - bash: |
         python -m coverage report

tests/accelerators/test_accelerator_connector.py

@@ -323,8 +323,8 @@ def on_fit_start(self, trainer, pl_module):
         trainer.fit(model)
 
 
-@RunIf(special=True)
-def test_accelerator_choice_ddp_cpu_and_plugin(tmpdir):
+@RunIf(skip_windows=True, standalone=True)
+def test_accelerator_choice_ddp_cpu_and_strategy(tmpdir):
     """Test that accelerator="ddp_cpu" can work together with an instance of DDPPlugin."""
     _test_accelerator_choice_ddp_cpu_and_plugin(tmpdir, ddp_plugin_class=DDPPlugin)
 

tests/accelerators/test_ddp.py

@@ -108,7 +108,7 @@ def setup(self, stage: Optional[str] = None) -> None:
         trainer.fit(model)
 
 
-@RunIf(min_gpus=2, min_torch="1.8.1", special=True)
+@RunIf(min_gpus=2, min_torch="1.8.1", standalone=True)
 @pytest.mark.parametrize("precision", (16, 32))
 def test_ddp_wrapper(tmpdir, precision):
     """Test parameters to ignore are carried over for DDP."""

tests/accelerators/test_multi_nodes_gpu.py

@@ -31,7 +31,7 @@
 # TODO(Borda): When multi-node tests are re-enabled (.github/workflows/ci_test-mnodes.yml)
 # use an environment variable `PL_RUNNING_MULTINODE_TESTS` and set `RunIf(multinode=True)`
 @pytest.mark.skip("Multi-node testing is currently disabled")
-@RunIf(special=True)
+@RunIf(standalone=True)
 def test_logging_sync_dist_true_ddp(tmpdir):
     """Tests to ensure that the sync_dist flag works with CPU (should just return the original value)"""
     fake_result = 1
@@ -68,7 +68,7 @@ def validation_step(self, batch, batch_idx):
 # TODO(Borda): When multi-node tests are re-enabled (.github/workflows/ci_test-mnodes.yml)
 # use an environment variable `PL_RUNNING_MULTINODE_TESTS` and set `RunIf(multinode=True)`
 @pytest.mark.skip("Multi-node testing is currently disabled")
-@RunIf(special=True)
+@RunIf(standalone=True)
 def test__validation_step__log(tmpdir):
     """Tests that validation_step can log."""
 

tests/callbacks/test_pruning.py

@@ -160,7 +160,7 @@ def test_pruning_callback(
     )
 
 
-@RunIf(special=True, min_gpus=2)
+@RunIf(standalone=True, min_gpus=2)
 @pytest.mark.parametrize("parameters_to_prune", (False, True))
 @pytest.mark.parametrize("use_global_unstructured", (False, True))
 def test_pruning_callback_ddp(tmpdir, parameters_to_prune, use_global_unstructured):

tests/callbacks/test_stochastic_weight_avg.py

@@ -138,7 +138,7 @@ def train_with_swa(
     assert trainer.lightning_module == model
 
 
-@RunIf(min_gpus=2, special=True)
+@RunIf(min_gpus=2, standalone=True)
 def test_swa_callback_ddp(tmpdir):
     train_with_swa(tmpdir, strategy="ddp", gpus=2)
 

tests/callbacks/test_tqdm_progress_bar.py

@@ -521,7 +521,7 @@ def test_tqdm_progress_bar_can_be_pickled():
     pickle.dumps(bar)
 
 
-@RunIf(min_gpus=2, special=True)
+@RunIf(min_gpus=2, standalone=True)
 @pytest.mark.parametrize(
     ["total_train_samples", "train_batch_size", "total_val_samples", "val_batch_size", "val_check_interval"],
     [(8, 4, 2, 1, 0.2), (8, 4, 2, 1, 0.5)],

tests/checkpointing/test_checkpoint_callback_frequency.py

@@ -87,7 +87,7 @@ def training_step(self, batch, batch_idx):
 
 
 @mock.patch("torch.save")
-@RunIf(special=True, min_gpus=2)
+@RunIf(standalone=True, min_gpus=2)
 @pytest.mark.parametrize(["k", "epochs", "val_check_interval", "expected"], [(1, 1, 1.0, 1), (2, 2, 0.3, 4)])
 def test_top_k_ddp(save_mock, tmpdir, k, epochs, val_check_interval, expected):
     class TestModel(BoringModel):

tests/conftest.py

@@ -159,13 +159,13 @@ def single_process_pg():
 
 
 def pytest_collection_modifyitems(items):
-    if os.getenv("PL_RUNNING_SPECIAL_TESTS", "0") != "1":
+    if os.getenv("PL_RUN_STANDALONE_TESTS", "0") != "1":
         return
-    # filter out non-special tests
+    # filter out non-standalone tests
     items[:] = [
         item
         for item in items
         for marker in item.own_markers
-        # has `@RunIf(special=True)`
-        if marker.name == "skipif" and marker.kwargs.get("special")
+        # has `@RunIf(standalone=True)`
+        if marker.name == "skipif" and marker.kwargs.get("standalone")
     ]

tests/core/test_metric_result_integration.py

@@ -482,7 +482,7 @@ def test_result_collection_reload_1_gpu_ddp(tmpdir):
     result_collection_reload(default_root_dir=tmpdir, strategy="ddp", gpus=1)
 
 
-@RunIf(min_gpus=2, special=True)
+@RunIf(min_gpus=2, standalone=True)
 @mock.patch.dict(os.environ, {"PL_FAULT_TOLERANT_TRAINING": "1"})
 @pytest.mark.skipif(not _TORCH_GREATER_EQUAL_1_7, reason="Requires at least PyTorch 1.7")
 def test_result_collection_reload_2_gpus(tmpdir):