class_docstr: Linear module on the second-to-last dimension
  Args:
      d_input (str): input dimension
      d_output (int): output dimension
      bias (bool): use bias
code: def forward(self, x):
      return (
          contract("... u l, v u -> ... v l", x, self.weight)
          + self.bias
      )
  
imports: from torch import nn
  import torch
  import math
  from opt_einsum import contract
label_desc: Use image node_id 2 for calling the TransposedLinear obj's underlying member method code with example usage: obj.forward(x) and returns: unknown