code: def __init__(
      self,
      params,
      lr=required,
      momentum=0,
      dampening=0,
      weight_decay=0,
      nesterov=False,
      eps=1e-8,
      delta=0.1,
      wd_ratio=0.1,
  ):
      defaults = dict(
          lr=lr,
          momentum=momentum,
          dampening=dampening,
          weight_decay=weight_decay,
          nesterov=nesterov,
          eps=eps,
          delta=delta,
          wd_ratio=wd_ratio,
      )
      super(SGDP, self).__init__(params, defaults)
  
file_path: pytorch-image-models/timm/optim/sgdp.py
imports: import torch
  import torch.nn.functional
  from torch.optim.optimizer import Optimizer, required
  import math
  from .adamp import projection
label_desc: Use image node_id 1 to create a new SGDP object from inherited base classes: Optimizer with example: obj = SGDP(params, lr, momentum, dampening, weight_decay, nesterov, eps, delta, wd_ratio)