code: def testExponentialLogPDF(self):
      batch_size = 6
      lam = constant_op.constant([2.0] * batch_size)
      lam_v = 2.0
      x = np.array([2.5, 2.5, 4.0, 0.1, 1.0, 2.0], dtype=np.float32)
      exponential = exponential_lib.Exponential(rate=lam)
  
      log_pdf = exponential.log_prob(x)
      self.assertEqual(log_pdf.get_shape(), (6,))
  
      pdf = exponential.prob(x)
      self.assertEqual(pdf.get_shape(), (6,))
  
      if not stats:
          return
      expected_log_pdf = stats.expon.logpdf(x, scale=1 / lam_v)
      self.assertAllClose(self.evaluate(log_pdf), expected_log_pdf)
      self.assertAllClose(self.evaluate(pdf), np.exp(expected_log_pdf))
  
imports: import importlib
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops.distributions import exponential
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 1 for calling the ExponentialTest obj's underlying member method code with example usage: obj.testExponentialLogPDF() without return types