Deduplicate tests

Author: carmocca

.azure-pipelines/gpu-tests.yml

@@ -108,6 +108,8 @@ jobs:
         bash pl_examples/run_examples.sh --trainer.gpus=1
         bash pl_examples/run_examples.sh --trainer.gpus=2 --trainer.accelerator=ddp
         bash pl_examples/run_examples.sh --trainer.gpus=2 --trainer.accelerator=ddp --trainer.precision=16
+        bash pl_examples/run_examples.sh --trainer.gpus=2 --trainer.accelerator=dp
+        bash pl_examples/run_examples.sh --trainer.gpus=2 --trainer.accelerator=dp --trainer.precision=16
       env:
         PL_USE_MOCKED_MNIST: "1"
       displayName: 'Testing: examples'

pl_examples/test_examples.py

@@ -11,70 +11,27 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
-import importlib
-import platform
 from unittest import mock
 
 import pytest
-import torch
 
 from pl_examples import _DALI_AVAILABLE
+from tests.helpers.runif import RunIf
 
 ARGS_DEFAULT = (
     "--trainer.default_root_dir %(tmpdir)s "
     "--trainer.max_epochs 1 "
     "--trainer.limit_train_batches 2 "
     "--trainer.limit_val_batches 2 "
+    "--trainer.limit_test_batches 2 "
+    "--trainer.limit_predict_batches 2 "
     "--data.batch_size 32 "
 )
 ARGS_GPU = ARGS_DEFAULT + "--trainer.gpus 1 "
-ARGS_DP = ARGS_DEFAULT + "--trainer.gpus 2 --trainer.accelerator dp "
-ARGS_AMP = "--trainer.precision 16 "
-
-
-@pytest.mark.parametrize(
-    "import_cli",
-    [
-        "pl_examples.basic_examples.simple_image_classifier",
-        "pl_examples.basic_examples.backbone_image_classifier",
-        "pl_examples.basic_examples.autoencoder",
-    ],
-)
-@pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
-@pytest.mark.parametrize("cli_args", [ARGS_DP, ARGS_DP + ARGS_AMP])
-def test_examples_dp(tmpdir, import_cli, cli_args):
-
-    module = importlib.import_module(import_cli)
-    # update the temp dir
-    cli_args = cli_args % {"tmpdir": tmpdir}
-
-    with mock.patch("argparse._sys.argv", ["any.py"] + cli_args.strip().split()):
-        module.cli_main()
-
-
-@pytest.mark.parametrize(
-    "import_cli",
-    [
-        "pl_examples.basic_examples.simple_image_classifier",
-        "pl_examples.basic_examples.backbone_image_classifier",
-        "pl_examples.basic_examples.autoencoder",
-    ],
-)
-@pytest.mark.parametrize("cli_args", [ARGS_DEFAULT])
-def test_examples_cpu(tmpdir, import_cli, cli_args):
-
-    module = importlib.import_module(import_cli)
-    # update the temp dir
-    cli_args = cli_args % {"tmpdir": tmpdir}
-
-    with mock.patch("argparse._sys.argv", ["any.py"] + cli_args.strip().split()):
-        module.cli_main()
 
 
 @pytest.mark.skipif(not _DALI_AVAILABLE, reason="Nvidia DALI required")
-@pytest.mark.skipif(not torch.cuda.is_available(), reason="test requires GPU machine")
-@pytest.mark.skipif(platform.system() != "Linux", reason="Only applies to Linux platform.")
+@RunIf(min_gpus=1, skip_windows=True)
 @pytest.mark.parametrize("cli_args", [ARGS_GPU])
 def test_examples_mnist_dali(tmpdir, cli_args):
     from pl_examples.basic_examples.dali_image_classifier import cli_main