code: def __init__(self, model, learning_rate, warmup_steps, weight_decay):
      self.model = model
      self.optimizer = torch.optim.AdamW(
          model.parameters(),
          lr=learning_rate,
          weight_decay=weight_decay,
      )
      self.scheduler = torch.optim.lr_scheduler.LambdaLR(
          self.optimizer,
          lambda steps: min((steps + 1) / warmup_steps, 1),
      )
  
file_path: PARL/parl/algorithms/torch/dt.py
imports: import torch
  import numpy
  import parl
  import time
label_desc: Use image node_id 1 to create a new DecisionTransformer object from inherited base classes: parl with example: obj = DecisionTransformer(model, learning_rate, warmup_steps, weight_decay)