Add fairscale install msg for Sharded Plugins (#7213)

docs/source/advanced/multi_gpu.rst

@@ -675,7 +675,7 @@ To use Sharded Training, you need to first install FairScale using the command b
 .. code-block:: python
 
     # train using Sharded DDP
-    trainer = Trainer(accelerator='ddp', plugins='ddp_sharded')
+    trainer = Trainer(plugins='ddp_sharded')
 
 Sharded Training can work across all DDP variants by adding the additional ``--plugins ddp_sharded`` flag.
 

pytorch_lightning/plugins/training_type/sharded.py

@@ -21,6 +21,7 @@ from pytorch_lightning.core.optimizer import is_lightning_optimizer
 from pytorch_lightning.plugins.training_type.ddp import DDPPlugin
 from pytorch_lightning.trainer.states import TrainerState
 from pytorch_lightning.utilities import _FAIRSCALE_AVAILABLE, _FAIRSCALE_OSS_FP16_BROADCAST_AVAILABLE, rank_zero_only
+from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
 if _FAIRSCALE_AVAILABLE:
     from fairscale.nn.data_parallel.sharded_ddp import ShardedDataParallel
@@ -85,6 +86,11 @@ class DDPShardedPlugin(DDPPlugin):
 
     @property
     def lightning_module(self) -> LightningModule:
+        if not _FAIRSCALE_AVAILABLE:  # pragma: no cover
+            raise MisconfigurationException(
+                "`DDPShardedPlugin` requires `fairscale` to be installed."
+                " Install it by running `pip install fairscale`."
+            )
         return unwrap_lightning_module_sharded(self._model)
 
     def pre_backward(self, closure_loss: torch.Tensor, should_accumulate: bool, optimizer: Optimizer, opt_idx: int):

pytorch_lightning/plugins/training_type/sharded_spawn.py

@@ -21,6 +21,7 @@ from pytorch_lightning.plugins.precision.sharded_native_amp import ShardedNative
 from pytorch_lightning.plugins.training_type.ddp_spawn import DDPSpawnPlugin
 from pytorch_lightning.trainer.states import TrainerState
 from pytorch_lightning.utilities import _FAIRSCALE_AVAILABLE, rank_zero_only
+from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
 if _FAIRSCALE_AVAILABLE:
     from fairscale.nn.data_parallel.sharded_ddp import ShardedDataParallel
@@ -71,6 +72,11 @@ class DDPSpawnShardedPlugin(DDPSpawnPlugin):
 
     @property
     def lightning_module(self) -> LightningModule:
+        if not _FAIRSCALE_AVAILABLE:  # pragma: no cover
+            raise MisconfigurationException(
+                "`DDPSpawnShardedPlugin` requires `fairscale` to be installed."
+                " Install it by running `pip install fairscale`."
+            )
         return unwrap_lightning_module_sharded(self._model)
 
     def pre_backward(self, closure_loss: torch.Tensor, should_accumulate: bool, optimizer: Optimizer, opt_idx: int):