code: def testGradientThroughRate(self):
      log_rate = tf.Variable(3.0)
      dist = poisson_lib.Poisson(log_rate=log_rate, validate_args=True)
      with tf.GradientTape() as tape:
          loss = -dist.log_prob([1.0, 2.0, 4.0])
      grad = tape.gradient(loss, dist.trainable_variables)
      self.assertLen(grad, 1)
      self.assertAllNotNone(grad)
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import implementation_selection
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 5 for calling the PoissonLogRateTest obj's underlying member method code with example usage: obj.testGradientThroughRate() without return types