code: def forward(self, input):
      batch_shape = torch.broadcast_shapes(
          self.batch_shape, input.shape[:-2]
      )
      mean = (
          self.constant.unsqueeze(-1)
          .expand(*batch_shape, input.size(-2), input.size(-1) + 1)
          .contiguous()
      )
      mean[..., 1:] = 0
      return mean
  
imports: import torch
  from .mean import Mean
label_desc: Use image node_id 2 for calling the ConstantMeanGrad obj's underlying member method code with example usage: obj.forward(input) and returns: mean