Merge branch 'release/1.2-dev' into accelerator-refactor-sharded

Author: SeanNaren

Makefile

@@ -9,6 +9,7 @@ clean:
 	# clean all temp runs
 	rm -rf $(shell find . -name "mlruns")
 	rm -rf $(shell find . -name "lightning_log")
+	rm -rf $(shell find . -name "lightning_logs")
 	rm -rf _ckpt_*
 	rm -rf .mypy_cache
 	rm -rf .pytest_cache

benchmarks/generate_comparison.py

@@ -17,7 +17,7 @@
 import pandas as pd
 
 from benchmarks.test_basic_parity import measure_loops
-from tests.base.models import ParityModuleMNIST, ParityModuleRNN
+from tests.helpers.models import ParityModuleMNIST, ParityModuleRNN
 
 NUM_EPOCHS = 20
 NUM_RUNS = 50

benchmarks/test_basic_parity.py

@@ -20,7 +20,7 @@
 from tqdm import tqdm
 
 from pytorch_lightning import LightningModule, seed_everything, Trainer
-from tests.base.models import ParityModuleMNIST, ParityModuleRNN
+from tests.helpers.models import ParityModuleMNIST, ParityModuleRNN
 
 
 def assert_parity_relative(pl_values, pt_values, norm_by: float = 1, max_diff: float = 0.1):

benchmarks/test_sharded_parity.py

@@ -26,7 +26,7 @@
 from pytorch_lightning.plugins.legacy.sharded_plugin import DDPShardedPlugin
 from pytorch_lightning.utilities import _FAIRSCALE_AVAILABLE, _NATIVE_AMP_AVAILABLE
 from tests.accelerators.legacy import DDPLauncher
-from tests.base.boring_model import BoringModel, RandomDataset
+from tests.helpers.boring_model import BoringModel, RandomDataset
 
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="requires GPU machine")

pl_examples/basic_examples/autoencoder.py

@@ -26,7 +26,7 @@
     from torchvision import transforms
     from torchvision.datasets.mnist import MNIST
 else:
-    from tests.base.datasets import MNIST
+    from tests.helpers.datasets import MNIST
 
 
 class LitAutoEncoder(pl.LightningModule):

pl_examples/basic_examples/backbone_image_classifier.py

@@ -25,7 +25,7 @@
     from torchvision import transforms
     from torchvision.datasets.mnist import MNIST
 else:
-    from tests.base.datasets import MNIST
+    from tests.helpers.datasets import MNIST
 
 
 class Backbone(torch.nn.Module):

pl_examples/basic_examples/dali_image_classifier.py

@@ -29,7 +29,7 @@
     from torchvision import transforms
     from torchvision.datasets.mnist import MNIST
 else:
-    from tests.base.datasets import MNIST
+    from tests.helpers.datasets import MNIST
 
 if _DALI_AVAILABLE:
     from nvidia.dali import __version__ as dali_version

pl_examples/basic_examples/mnist_datamodule.py

@@ -24,7 +24,7 @@
     from torchvision import transforms as transform_lib
     from torchvision.datasets import MNIST
 else:
-    from tests.base.datasets import MNIST
+    from tests.helpers.datasets import MNIST
 
 
 class MNISTDataModule(LightningDataModule):

tests/accelerators/legacy/test_accelerator_connector.py

@@ -25,7 +25,7 @@
 from pytorch_lightning.callbacks import Callback
 from pytorch_lightning.plugins import DDP2Plugin, DDPPlugin, DDPSpawnPlugin, PrecisionPlugin, SingleDevicePlugin
 from pytorch_lightning.plugins.environments import ClusterEnvironment, SLURMEnvironment, TorchElasticEnvironment
-from tests.base.boring_model import BoringModel
+from tests.helpers.boring_model import BoringModel
 
 
 def test_accelerator_choice_cpu(tmpdir):

tests/accelerators/legacy/test_ddp_spawn.py

@@ -14,8 +14,8 @@
 import pytest
 import torch
 
-import tests.base.develop_pipelines as tpipes
-import tests.base.develop_utils as tutils
+import tests.helpers.pipelines as tpipes
+import tests.helpers.utils as tutils
 from pytorch_lightning.callbacks import EarlyStopping
 from pytorch_lightning.core import memory
 from pytorch_lightning.trainer import Trainer