Enable torch DataParallel for multi-GPU (#602)

* add data para

* add doc

* Update docstring

* format

federatedscope/core/configs/cfg_training.py

@@ -32,6 +32,7 @@ def extend_training_cfg(cfg):
 
     cfg.train.local_update_steps = 1
     cfg.train.batch_or_epoch = 'batch'
+    cfg.train.data_para_dids = []  # `torch.nn.DataParallel` devices
 
     cfg.train.optimizer = CN(new_allowed=True)
     cfg.train.optimizer.type = 'SGD'

federatedscope/core/trainers/torch_trainer.py

@@ -98,6 +98,8 @@ def evaluate(self, target_data_split_name="test"):
         return self.ctx.eval_metrics
 
     def register_default_hooks_train(self):
+        self.register_hook_in_train(self._hook_on_data_parallel_init,
+                                    "on_fit_start")
         self.register_hook_in_train(self._hook_on_fit_start_init,
                                     "on_fit_start")
         self.register_hook_in_train(
@@ -118,6 +120,8 @@ def register_default_hooks_train(self):
         self.register_hook_in_train(self._hook_on_fit_end, "on_fit_end")
 
     def register_default_hooks_ft(self):
+        self.register_hook_in_ft(self._hook_on_data_parallel_init,
+                                 "on_fit_start")
         self.register_hook_in_ft(self._hook_on_fit_start_init, "on_fit_start")
         self.register_hook_in_ft(self._hook_on_fit_start_calculate_model_size,
                                  "on_fit_start")
@@ -137,6 +141,8 @@ def register_default_hooks_ft(self):
 
     def register_default_hooks_eval(self):
         # test/val
+        self.register_hook_in_eval(self._hook_on_data_parallel_init,
+                                   "on_fit_start")
         self.register_hook_in_eval(self._hook_on_fit_start_init,
                                    "on_fit_start")
         self.register_hook_in_eval(self._hook_on_epoch_start, "on_epoch_start")
@@ -147,6 +153,26 @@ def register_default_hooks_eval(self):
         self.register_hook_in_eval(self._hook_on_batch_end, "on_batch_end")
         self.register_hook_in_eval(self._hook_on_fit_end, "on_fit_end")
 
+    def _hook_on_data_parallel_init(self, ctx):
+        """
+        Note:
+          The modified attributes and according operations are shown below,
+           further modifications should be made to `ctx.model` other object:
+            ==================================  ===========================
+            Attribute                           Operation
+            ==================================  ===========================
+            ``ctx.model``                       Wrap ``nn.Module` to \
+            `nn.DataParallel`
+            ==================================  ===========================
+        """
+        if isinstance(ctx.model, torch.nn.DataParallel):
+            return
+
+        if len(ctx.cfg.train.data_para_dids):
+            ctx.model = \
+                torch.nn.DataParallel(ctx.model,
+                                      device_ids=ctx.cfg.train.data_para_dids)
+
     def _hook_on_fit_start_init(self, ctx):
         """
         Note: