code: def __init__(self, prior=None, batch_shape=torch.Size(), **kwargs):
      super(ConstantMeanGrad, self).__init__()
      self.batch_shape = batch_shape
      self.register_parameter(
          name="constant",
          parameter=torch.nn.Parameter(torch.zeros(*batch_shape, 1)),
      )
      if prior is not None:
          self.register_prior("mean_prior", prior, "constant")
  
imports: import torch
  from .mean import Mean
label_desc: Use image node_id 1 to create a new ConstantMeanGrad object from inherited base classes: Mean with example: obj = ConstantMeanGrad(prior, batch_shape)