docstr: This method is used to transpose the other operand for linear function.
  For example:
      input = torch.rand(3, 4)
      m1 = torch.rand(3, 5)
      m2 = torch.rand(5, 4)
      original_output = torch.addmm(input, m1, m2)
      # To keep the computation graph consistent with the origin computation graph, we need to transpose the m2
      # before we call the linear function.
      new_output = torch.linear(m1, m2.transpose(0, 1)) + input
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code: def transpose_other_operand_for_linear(self, other_proxy):
      """
      This method is used to transpose the other operand for linear function.
      For example:
          input = torch.rand(3, 4)
          m1 = torch.rand(3, 5)
          m2 = torch.rand(5, 4)
          original_output = torch.addmm(input, m1, m2)
          # To keep the computation graph consistent with the origin computation graph, we need to transpose the m2
          # before we call the linear function.
          new_output = torch.linear(m1, m2.transpose(0, 1)) + input
      """
      node_kind = "call_function"
      node_target = torch.transpose
      node_args = (other_proxy, 0, 1)
      node_kwargs = {}
      transpose_proxy = self.tracer.create_proxy(
          node_kind, node_target, node_args, node_kwargs
      )
      return transpose_proxy
  
file_path: ColossalAI/colossalai/fx/tracer/bias_addition_patch/patched_bias_addition_function/addmm.py
imports: import torch
  from ...registry import bias_addition_function, bias_addition_method
  from .bias_addition_function import LinearBasedBiasFunc
label_desc: Use image node_id 2 for calling the Addmm obj's underlying member method code with example usage: obj.transpose_other_operand_for_linear(other_proxy) and returns: transpose_proxy