imports

Author: awaelchli

pytorch_lightning/plugins/training_type/__init__.py

@@ -1 +1,5 @@
-from pytorch_lightning.plugins.training_type.training_type_plugin import TrainingTypePlugin
+from pytorch_lightning.plugins.training_type.training_type_plugin import TrainingTypePlugin  # noqa: F401
+from pytorch_lightning.plugins.training_type.parallel import ParallelPlugin  # noqa: F401
+from pytorch_lightning.plugins.training_type.ddp import DDPPlugin  # noqa: F401
+from pytorch_lightning.plugins.training_type.ddp2 import DDP2Plugin  # noqa: F401
+from pytorch_lightning.plugins.training_type.ddp_spawn import DDPSpawnPlugin  # noqa: F401

pytorch_lightning/plugins/training_type/ddp.py

@@ -12,7 +12,7 @@
 from pytorch_lightning.plugins.training_type.parallel import ParallelPlugin
 from pytorch_lightning.cluster_environments.cluster_environment import ClusterEnvironment
 from pytorch_lightning.distributed import LightningDistributed
-from pytorch_lightning.overrides.data_parallel import LightningDistributedDataParallel, unwrap_lightning_module
+from pytorch_lightning.overrides.data_parallel import LightningDistributedDataParallel
 from pytorch_lightning.utilities import _HYDRA_AVAILABLE
 from pytorch_lightning.utilities.distributed import find_free_network_port, rank_zero_only, sync_ddp_if_available
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
@@ -60,7 +60,9 @@ def root_device(self):
     @property
     def lightning_module(self):
         # the model may not be wrapped with DistributedDataParallel if calling this too early
-        return unwrap_lightning_module(self._model)
+        # fixme: uncomment when this class will actually be used
+        # return unwrap_lightning_module(self._model)
+        pass
 
     @property
     def distributed_sampler_kwargs(self):

pytorch_lightning/plugins/training_type/ddp_spawn.py

@@ -10,7 +10,7 @@
 from pytorch_lightning.plugins.training_type.parallel import ParallelPlugin
 from pytorch_lightning.cluster_environments.cluster_environment import ClusterEnvironment
 from pytorch_lightning.distributed.dist import LightningDistributed
-from pytorch_lightning.overrides.data_parallel import LightningDistributedDataParallel, unwrap_lightning_module
+from pytorch_lightning.overrides.data_parallel import LightningDistributedDataParallel
 from pytorch_lightning.utilities.cloud_io import atomic_save, load as pl_load
 from pytorch_lightning.utilities.distributed import find_free_network_port, rank_zero_only
 from pytorch_lightning.utilities.distributed import sync_ddp_if_available, rank_zero_warn
@@ -52,7 +52,9 @@ def root_device(self):
     @property
     def lightning_module(self):
         # the model may not be wrapped with DistributedDataParallel if calling this too early
-        return unwrap_lightning_module(self._model)
+        # fixme: uncomment when this class will actually be used
+        # return unwrap_lightning_module(self._model)
+        pass
 
     @property
     def distributed_sampler_kwargs(self):

pytorch_lightning/plugins/training_type/parallel.py

@@ -4,7 +4,7 @@
 
 import torch
 
-from pytorch_lightning.plugins .training_type.training_type_plugin import TrainingTypePlugin
+from pytorch_lightning.plugins.training_type.training_type_plugin import TrainingTypePlugin
 from pytorch_lightning.cluster_environments import ClusterEnvironment
 from pytorch_lightning.core import LightningModule
 from pytorch_lightning.overrides.data_parallel import LightningDistributedDataParallel