code: def _makeTridiagonalMatrix(self, superdiag, maindiag, subdiag):
      super_pad = [[0, 0], [0, 1], [1, 0]]
      sub_pad = [[0, 0], [1, 0], [0, 1]]
  
      super_part = array_ops.pad(
          array_ops.matrix_diag(superdiag), super_pad
      )
      main_part = array_ops.matrix_diag(maindiag)
      sub_part = array_ops.pad(array_ops.matrix_diag(subdiag), sub_pad)
      return super_part + main_part + sub_part
  
imports: import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops.linalg import linalg_impl
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 4 for calling the TridiagonalMatMulOpsTest obj's underlying member method code with example usage: obj._makeTridiagonalMatrix(superdiag, maindiag, subdiag) and returns: unknown