code: def forward(self, input):
      mean = torch.zeros(
          *self.batch_shape, 1, dtype=input.dtype, device=input.device
      )
      if input.shape[:-2] == self.batch_shape:
          return mean.expand(input.shape[:-1])
      else:
          return mean.expand(
              torch.broadcast_shapes(input.shape[:-1], mean.shape)
          )
  
imports: import torch
  from .mean import Mean
label_desc: Use image node_id 2 for calling the ZeroMean obj's underlying member method code with example usage: obj.forward(input) and returns: mean, mean