fix imports

Author: Borda

benchmarks/test_sharded_parity.py

@@ -21,10 +21,10 @@
 import torch
 
 from pytorch_lightning import seed_everything, Trainer
-from pytorch_lightning.plugins.ddp_plugin import DDPPlugin
-from pytorch_lightning.plugins.sharded_plugin import DDPShardedPlugin
+from pytorch_lightning.plugins.legacy.ddp_plugin import DDPPlugin
+from pytorch_lightning.plugins.legacy.sharded_plugin import DDPShardedPlugin
 from pytorch_lightning.utilities import _FAIRSCALE_AVAILABLE, _NATIVE_AMP_AVAILABLE
-from tests.backends import DDPLauncher
+from tests.accelerators.legacy import DDPLauncher
 from tests.base.boring_model import BoringModel, RandomDataset
 
 

docs/source/accelerators.rst

@@ -16,7 +16,7 @@ To link up arbitrary hardware, implement your own Accelerator subclass
 
 .. code-block:: python
 
-    from pytorch_lightning.accelerators.accelerator import Accelerator
+    from pytorch_lightning.accelerators.legacy.accelerator import Accelerator
 
         class MyAccelerator(Accelerator):
             def __init__(self, trainer, cluster_environment=None):
@@ -124,59 +124,59 @@ Available Accelerators
 CPU Accelerator
 ===============
 
-.. autoclass:: pytorch_lightning.accelerators.cpu_accelerator.CPUAccelerator
+.. autoclass:: pytorch_lightning.accelerators.legacy.cpu_accelerator.CPUAccelerator
     :noindex:
 
 DDP Accelerator
 ===============
 
-.. autoclass:: pytorch_lightning.accelerators.ddp_accelerator.DDPAccelerator
+.. autoclass:: pytorch_lightning.accelerators.legacy.ddp_accelerator.DDPAccelerator
     :noindex:
 
 DDP2 Accelerator
 ================
 
-.. autoclass:: pytorch_lightning.accelerators.ddp2_accelerator.DDP2Accelerator
+.. autoclass:: pytorch_lightning.accelerators.legacy.ddp2_accelerator.DDP2Accelerator
     :noindex:
 
 DDP CPU HPC Accelerator
 =======================
 
-.. autoclass:: pytorch_lightning.accelerators.ddp_cpu_hpc_accelerator.DDPCPUHPCAccelerator
+.. autoclass:: pytorch_lightning.accelerators.legacy.ddp_cpu_hpc_accelerator.DDPCPUHPCAccelerator
     :noindex:
 
 DDP CPU Spawn Accelerator
 =========================
 
-.. autoclass:: pytorch_lightning.accelerators.ddp_cpu_spawn_accelerator.DDPCPUSpawnAccelerator
+.. autoclass:: pytorch_lightning.accelerators.legacy.ddp_cpu_spawn_accelerator.DDPCPUSpawnAccelerator
     :noindex:
 
 DDP HPC Accelerator
 ===================
 
-.. autoclass:: pytorch_lightning.accelerators.ddp_hpc_accelerator.DDPHPCAccelerator
+.. autoclass:: pytorch_lightning.accelerators.legacy.ddp_hpc_accelerator.DDPHPCAccelerator
     :noindex:
 
 DDP Spawn Accelerator
 =====================
 
-.. autoclass:: pytorch_lightning.accelerators.ddp_spawn_accelerator.DDPSpawnAccelerator
+.. autoclass:: pytorch_lightning.accelerators.legacy.ddp_spawn_accelerator.DDPSpawnAccelerator
     :noindex:
 
 GPU Accelerator
 ===============
 
-.. autoclass:: pytorch_lightning.accelerators.gpu_accelerator.GPUAccelerator
+.. autoclass:: pytorch_lightning.accelerators.legacy.gpu_accelerator.GPUAccelerator
     :noindex:
 
 Horovod Accelerator
 ===================
 
-.. autoclass:: pytorch_lightning.accelerators.horovod_accelerator.HorovodAccelerator
+.. autoclass:: pytorch_lightning.accelerators.legacy.horovod_accelerator.HorovodAccelerator
     :noindex:
 
 TPU Accelerator
 ===============
 
-.. autoclass:: pytorch_lightning.accelerators.tpu_accelerator.TPUAccelerator
+.. autoclass:: pytorch_lightning.accelerators.legacy.tpu_accelerator.TPUAccelerator
     :noindex:

docs/source/multi_gpu.rst

@@ -580,9 +580,9 @@ Below are the possible configurations we support.
 
 Implement Your Own Distributed (DDP) training
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-If you need your own way to init PyTorch DDP you can override :meth:`pytorch_lightning.plugins.ddp_plugin.DDPPlugin.init_ddp_connection`.
+If you need your own way to init PyTorch DDP you can override :meth:`pytorch_lightning.plugins.legacy.ddp_plugin.DDPPlugin.init_ddp_connection`.
 
-If you also need to use your own DDP implementation, override :meth:`pytorch_lightning.plugins.ddp_plugin.DDPPlugin.configure_ddp`.
+If you also need to use your own DDP implementation, override :meth:`pytorch_lightning.plugins.legacy.ddp_plugin.DDPPlugin.configure_ddp`.
 
 
 ----------
@@ -692,7 +692,7 @@ This should be kept within the ``sequential_module`` variable within your ``Ligh
 
 .. code-block:: python
 
-    from pytorch_lightning.plugins.ddp_sequential_plugin import DDPSequentialPlugin
+    from pytorch_lightning.plugins.legacy.ddp_sequential_plugin import DDPSequentialPlugin
     from pytorch_lightning import LightningModule
 
     class MyModel(LightningModule):

docs/source/plugins.rst

@@ -19,16 +19,16 @@ For example, to customize your own DistributedDataParallel you could do somethin
 ApexPlugin
 **********
 
-.. autoclass:: pytorch_lightning.plugins.apex.ApexPlugin
+.. autoclass:: pytorch_lightning.plugins.legacy.apex.ApexPlugin
 
 ***************
 NativeAMPPlugin
 ***************
 
-.. autoclass:: pytorch_lightning.plugins.native_amp.NativeAMPPlugin
+.. autoclass:: pytorch_lightning.plugins.legacy.native_amp.NativeAMPPlugin
 
 *********
 DDPPlugin
 *********
 
-.. autoclass:: pytorch_lightning.plugins.ddp_plugin.DDPPlugin
+.. autoclass:: pytorch_lightning.plugins.legacy.ddp_plugin.DDPPlugin

pl_examples/basic_examples/conv_sequential_example.py

@@ -32,7 +32,7 @@
 from pl_examples import cli_lightning_logo
 from pytorch_lightning import Trainer
 from pytorch_lightning.metrics.functional import accuracy
-from pytorch_lightning.plugins.ddp_sequential_plugin import DDPSequentialPlugin
+from pytorch_lightning.plugins.legacy.ddp_sequential_plugin import DDPSequentialPlugin
 from pytorch_lightning.utilities import _BOLTS_AVAILABLE, _FAIRSCALE_PIPE_AVAILABLE
 
 if _BOLTS_AVAILABLE:

tests/accelerators/legacy/test_ddp.py

@@ -16,7 +16,7 @@
 import pytest
 import torch
 
-from tests.backends import ddp_model, DDPLauncher
+from tests.accelerators.legacy import ddp_model, DDPLauncher
 from tests.utilities.distributed import call_training_script
 
 

tests/trainer/properties/test_get_model.py

@@ -17,7 +17,7 @@
 import torch
 
 from pytorch_lightning import Trainer
-from tests.backends import DDPLauncher
+from tests.accelerators.legacy import DDPLauncher
 from tests.base.boring_model import BoringModel