Fix accelerate init (coqui-ai#116)

trainer/trainer.py

@@ -620,32 +620,28 @@ def init_accelerate(model, optimizer, training_dataloader, scheduler, grad_accum
             _precision = "bf16"
         accelerator = Accelerator(gradient_accumulation_steps=grad_accum_steps, mixed_precision=_precision)
         if isinstance(model, torch.nn.Module):
-            model = accelerator.prepare(model)
+            model = accelerator.prepare_model(model)
 
-        if isinstance(optimizer, torch.optim.Optimizer):
-            optimizer = accelerator.prepare(optimizer)
-        elif isinstance(optimizer, dict):
+        if isinstance(optimizer, dict):
             for key, optim in optimizer.items():
-                optimizer[key] = accelerator.prepare(optim)
+                optimizer[key] = accelerator.prepare_optimizer(optim)
         elif isinstance(optimizer, list):
             for i, optim in enumerate(optimizer):
-                optimizer[i] = accelerator.prepare(optim)
+                optimizer[i] = accelerator.prepare_optimizer(optim)
         elif optimizer is not None:
-            raise ValueError("Optimizer must be a dict, list or torch.optim.Optimizer")
+            optimizer = accelerator.prepare_optimizer(optimizer)
 
         if isinstance(training_dataloader, torch.utils.data.DataLoader):
-            training_dataloader = accelerator.prepare(training_dataloader)
+            training_dataloader = accelerator.prepare_data_loader(training_dataloader)
 
-        if isinstance(scheduler, torch.optim.lr_scheduler._LRScheduler):  # pylint:disable=protected-access
-            scheduler = accelerator.prepare(scheduler)
-        elif isinstance(scheduler, dict):
+        if isinstance(scheduler, dict):
             for key, sched in scheduler.items():
-                scheduler[key] = accelerator.prepare(sched)
+                scheduler[key] = accelerator.prepare_scheduler(sched)
         elif isinstance(scheduler, list):
             for i, sched in enumerate(scheduler):
-                scheduler[i] = accelerator.prepare(sched)
+                scheduler[i] = accelerator.prepare_scheduler(sched)
         elif scheduler is not None:
-            raise ValueError("Scheduler must be a dict, list or torch.optim.lr_scheduler._LRScheduler")
+            scheduler = accelerator.prepare_scheduler(scheduler)
 
         return model, optimizer, training_dataloader, scheduler, accelerator