code: def testGradsAtIdenticalInputsAreNotNaN(self):
      k = exponential_curve.ExponentialCurve(
          concentration=1.0, rate=1.0
      )
      x = tf.constant(np.arange(3 * 5, dtype=np.float32).reshape(15, 1))
  
      grads = [
          gradient.value_and_gradient(lambda x: k.apply(x, x)[i], x)[
              1
          ]  # pylint: disable=cell-var-from-loop
          for i in range(3)
      ]
  
      self.assertAllNotNan(self.evaluate(grads))
  
file_path: probability/tensorflow_probability/python/math/psd_kernels/exponential_curve_test.py
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math.psd_kernels import exponential_curve
label_desc: Use image node_id 6 for calling the ExponentialCurveTest obj's underlying member method code with example usage: obj.testGradsAtIdenticalInputsAreNotNaN() without return types