code: def __init__(self, size, weight=True, bias=True, inplace=False):
      super().__init__()
      if weight:
          self.weight = nn.Parameter(torch.Tensor(size))
      else:
          self.weight = None
      if bias:
          self.bias = nn.Parameter(torch.Tensor(size))
      else:
          self.bias = None
      self.inplace = inplace
  
      self.reset_parameters()
  
imports: import dgl.nn.pytorch
  import torch
  import torch.nn
  from dgl import function
  from dgl.ops import edge_softmax
  from dgl.utils import expand_as_pair
label_desc: Use image node_id 1 to create a new ElementWiseLinear object from inherited base classes: nn with example: obj = ElementWiseLinear(size, weight, bias, inplace)