code: def testComplexConj(self):
      def f(x):
          return math_ops.conj(x)
  
      x_shape = ()
      x_dtype = dtypes.complex64
      x = constant_op.constant(_random_complex(x_shape, x_dtype))
      analytical, numerical = gradient_checker.compute_gradient(f, [x])
      correct = np.array([[1, 0], [0, -1]])
      self.assertAllEqual(correct, analytical[0])
      self.assertAllClose(correct, numerical[0], rtol=2e-5)
      x = constant_op.constant(_random_complex(x_shape, x_dtype))
      self.assertLess(
          gradient_checker.max_error(
              *gradient_checker.compute_gradient(f, [x])
          ),
          2e-5,
      )
  
imports: import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import custom_gradient
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import sparse_ops
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 10 for calling the GradientCheckerTest obj's underlying member method code with example usage: obj.testComplexConj() and returns: math_ops