code: def __init__(self, input_size, batch_shape=torch.Size(), bias=True):
      super().__init__()
      self.register_parameter(
          name="weights",
          parameter=torch.nn.Parameter(
              torch.randn(*batch_shape, input_size, 1)
          ),
      )
      if bias:
          self.register_parameter(
              name="bias",
              parameter=torch.nn.Parameter(
                  torch.randn(*batch_shape, 1)
              ),
          )
      else:
          self.bias = None
  
imports: import torch
  from .mean import Mean
label_desc: Use image node_id 1 to create a new LinearMean object from inherited base classes: Mean with example: obj = LinearMean(input_size, batch_shape, bias)