code: def __init__(
      self,
      model,
      optimizer="Adam",
      lr=1e-3,
      weight_decay=0.0,
      betas=(0.9, 0.999),
      momentum=0.9,
  ):
      super().__init__(
          model, optimizer, lr, weight_decay, betas, momentum
      )
  
      """Class for ERM Algorithm.
  
          :param model: Networks used for training. `model` type expected is torch.nn.Sequential(featurizer, classifier) where featurizer and classifier are of type torch.nn.Module.
          :param optimizer: Optimization algorithm used for training. Currently supports "Adam" and "SGD".
          :param lr: learning rate for ERM
          :param weight_decay: Value of weight decay for optimizer
          :param betas: Adam configuration parameters (beta1, beta2), exponential decay rate for the first moment and second-moment estimates, respectively.
          :param momentum: Value of momentum for SGD optimzer
          :returns: an instance of PredictionAlgorithm class
  
          """
  
imports: import torch
  from torch.nn import functional
  from dowhy.causal_prediction.algorithms.base_algorithm import PredictionAlgorithm
label_desc: Use image node_id 1 to create a new ERM object from inherited base classes: PredictionAlgorithm with example: obj = ERM(model, optimizer, lr, weight_decay, betas, momentum)