code: def test_grad(self, shp, k_, sorted):
      ndim = len(shp)
      for axis in range(-ndim, ndim):
          if isinstance(k_, str):
              k = eval(k_.replace("n", str(shp[axis])))
          else:
              k = k_
  
          if k == 0:
              continue
  
          # make input away from undefined gradient (where some inputs are equal)
          xval = gen_unique_vector(
              reduce(int.__mul__, shp), dtype=pytensor.config.floatX
          ).reshape(shp)
          utt.verify_grad(
              lambda x: topk(x, k, axis=axis, sorted=sorted),
              [xval],
              eps=1e-2,
          )
  
imports: from functools import reduce
  from itertools import chain, product
  import numpy
  import pytest
  import pytensor
  from pytensor.compile.mode import Mode
  from pytensor.tensor.sort import ArgSortOp, SortOp, TopKOp, argsort, argtopk, sort, topk, topk_and_argtopk
  from pytensor.tensor.type import dmatrix, dvector, float_dtypes, integer_dtypes, lscalar, matrix, scalar, tensor, vector
  from tests import unittest_tools
label_desc: Use image node_id 10 for calling the TestTopK obj's underlying member method code with example usage: obj.test_grad(shp, k_, sorted) without return types