Support custom scheduler in deepspeed training (#26831)

Reuse trainer.create_scheduler to create scheduler for deepspeed

src/transformers/integrations/deepspeed.py

@@ -14,7 +14,7 @@
 """
 Integration with Deepspeed
 """
-
+import copy
 import importlib.metadata as importlib_metadata
 import importlib.util
 import weakref
@@ -27,7 +27,6 @@ from ..utils import is_accelerate_available, is_torch_available, logging
 if is_torch_available():
     import torch
 
-    from ..optimization import get_scheduler
 
 logger = logging.get_logger(__name__)
 
@@ -341,12 +340,15 @@ def deepspeed_optim_sched(trainer, hf_deepspeed_config, args, num_training_steps
         if isinstance(optimizer, DummyOptim):
 
             def _lr_scheduler_callable(optimizer):
-                return get_scheduler(
-                    trainer.args.lr_scheduler_type,
-                    optimizer=optimizer,
-                    num_warmup_steps=trainer.args.get_warmup_steps(num_training_steps),
-                    num_training_steps=num_training_steps,
+                # create a shallow copy first, so later modifications do not affect original trainer
+                trainer_copy = copy.copy(trainer)
+                # at the time _lr_scheduler_callable is called, trainer.lr_scheduler has been set
+                # update it to None so that we can re-create a new scheduler
+                trainer_copy.lr_scheduler = None
+                lr_scheduler = trainer_copy.create_scheduler(
+                    num_training_steps=num_training_steps, optimizer=optimizer
                 )
+                return lr_scheduler
 
             lr_scheduler = DummyScheduler(optimizer, lr_scheduler_callable=_lr_scheduler_callable)
         else: