TypeError: LARC is not an Optimizer

optimizer  = torch.optim.SGD(
    model.parameters(),
    lr=args.learning_rate,
    momentum=0.9,
    weight_decay=1e-6,
)
optimizer = LARC(optimizer=optimizer, trust_coefficient=0.001, clip=False)
scheduler = WarmupLinearSchedule(
    optimizer,
    warmup_steps=args.warmup_proportion * num_train_optimization_steps,
    t_total=num_train_optimization_steps,
)    

Traceback (most recent call last):
  File "train.py", line 774, in <module>
    main()
  File "train.py", line 482, in main
    t_total=num_train_optimization_steps,
  File "/mnt/lustre/chenzhiyuan/anaconda3/envs/pt1.5/lib/python3.7/site-packages/pytorch_transformers/optimization.py", line 56, in __init__
    super(WarmupLinearSchedule, self).__init__(optimizer, self.lr_lambda, last_epoch=last_epoch)
  File "/mnt/lustre/chenzhiyuan/anaconda3/envs/pt1.5/lib/python3.7/site-packages/torch/optim/lr_scheduler.py", line 189, in __init__
    super(LambdaLR, self).__init__(optimizer, last_epoch)
  File "/mnt/lustre/chenzhiyuan/anaconda3/envs/pt1.5/lib/python3.7/site-packages/torch/optim/lr_scheduler.py", line 31, in __init__
    type(optimizer).__name__))
TypeError: LARC is not an Optimizer

Start at the optimizer and scheduler setup shown in train.py, then inspect how LARC is passed to WarmupLinearSchedule. Reproduce the TypeError with the provided snippet and determine whether the scheduler can accept LARC; done means the setup initializes without this error and the relevant behavior is covered by a test.