code: def __init__(
      self,
      params,
      lr=1e-3,
      betas=(0.9, 0.999),
      eps=1e-8,
      weight_decay=0,
      delta=0.1,
      wd_ratio=0.1,
      nesterov=False,
  ):
      defaults = dict(
          lr=lr,
          betas=betas,
          eps=eps,
          weight_decay=weight_decay,
          delta=delta,
          wd_ratio=wd_ratio,
          nesterov=nesterov,
      )
      super(AdamP, self).__init__(params, defaults)
  
file_path: pywick/pywick/optimizers/adamp.py
imports: import torch
  import torch.nn.functional
  from torch.optim.optimizer import Optimizer
  import math
label_desc: Use image node_id 1 to create a new AdamP object from inherited base classes: Optimizer with example: obj = AdamP(params, lr, betas, eps, weight_decay, delta, wd_ratio, nesterov)