How can i use torch.optim.lr_scheduler.MultiStepLR with Trainer?

Beginners
3

here is how i create it:

from torch import nn
from transformers import Trainer

class custom_optimizer(Trainer):
  def create_optimizer(self):
    optimizer = AdamW(model.parameters(),
                  lr = 2e-7
                )
    return self.optimizer

from torch.optim.lr_scheduler import MultiStepLR
class custom_scheduler(Trainer):
  def create_scheduler(self, num_training_steps):
    scheduler = MultiStepLR(optimizer, milestones=[1,5], gamma=0.5)
    return self.scheduler

and my trainer looks like this:

from transformers import Trainer, AdamW

trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=small_train_dataset,
    eval_dataset=small_eval_dataset,
    compute_metrics=compute_metrics,
    callbacks=[EarlyStoppingCallback(early_stopping_patience=3)],
    optimizers = (custom_optimizer(model).create_optimizer(), custom_scheduler(model).create_scheduler(total_steps))
)

trainer.train()

But this is giving me an error:

NameError: name 'optimizer' is not defined

Can you please help me to resolve this issue?