code: def forward(self, input):
      bw = self.weight
      ba = input
      bw = bw - bw.mean()
  
      if self.scale.item() == 0.0:
          self.reset_scale(input)
  
      bw = BinaryQuantize().apply(bw)
      bw = bw * self.scale
      if self.binary_act:
          ba = BinaryQuantize().apply(ba)
      output = F.linear(ba, bw)
      return output
  
imports: import dgl
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Function
  from torch.nn import Parameter
  from torch.nn.modules.utils import _single
label_desc: Use image node_id 3 for calling the BiLinearLSR obj's underlying member method code with example usage: obj.forward(input) and returns: output