code: def testLogProb(self):
      dist = self._make_pixel_cnn()
      images = self._make_fake_images()
      h = self._make_fake_conditional()
  
      self.evaluate([v.initializer for v in dist.network.weights])
      log_prob_values = self.evaluate(
          dist.log_prob(images, conditional_input=h)
      )
  
      self.assertAllEqual(self.batch_shape, log_prob_values.shape)
      prob = tf.exp(log_prob_values)
      prob_ = self.evaluate(prob)
      self.assertAllInRange(prob_, 0.0, 1.0)
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import pixel_cnn
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import tf_keras
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 10 for calling the PixelCnnTest obj's underlying member method code with example usage: obj.testLogProb() without return types