code: def testOutputRepeatedLabels(self):
      # This is the reverse operation of generalized traces, to be used for
      # computing symbolic gradients of einsum. Note: this operation is not
      # supported by np.einsum as it's only required for gradients.
      r = np.random.RandomState(0)
      a = r.randn(2, 2)
      s = "a->aa"
      diag_a = np.diag(np.diag(a))
      b = self.evaluate(gen_linalg_ops.einsum([np.diag(a)], s))
      self.assertAllClose(diag_a, b, atol=1e-4, rtol=1e-4)
  
imports: import numpy
  from tensorflow.python.client import session
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_linalg_ops
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import special_math_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import benchmark
  from tensorflow.python.platform import test
label_desc: Use image node_id 14 for calling the EinsumOpTest obj's underlying member method code with example usage: obj.testOutputRepeatedLabels() without return types