code: def testGammaLogPDFBoundary(self):
      # When concentration = 1, we have an exponential distribution. Check that at
      # 0 we have finite log prob.
      rate = np.array([0.1, 0.5, 1.0, 2.0, 5.0, 10.0], dtype=np.float32)
      gamma = gamma_lib.Gamma(concentration=1.0, rate=rate)
      log_pdf = gamma.log_prob(0.0)
      self.assertAllClose(np.log(rate), self.evaluate(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 tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops.distributions import gamma
  from tensorflow.python.ops.distributions import kullback_leibler
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 3 for calling the GammaTest obj's underlying member method code with example usage: obj.testGammaLogPDFBoundary() without return types