class_docstr: Test by comparing TruncatedNormals with wide bounds and unbounded Normal.
    
class_docstr_tok: ["Test","by","comparing","TruncatedNormals","with","wide","bounds","and","unbounded","Normal","."]
code: def testEntropy(self, loc, scale):
      truncated_dist, normal_dist = self.constructDists(loc, scale)
      self.assertAllClose(
          self.evaluate(truncated_dist.entropy()),
          self.evaluate(normal_dist.entropy()),
          rtol=1e-6,
          atol=1e-6,
      )
  
imports: import itertools
  import unittest
  from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import truncated_normal
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 2 for calling the TruncatedNormalTestCompareWithNormal obj's underlying member method code with example usage: obj.testEntropy(loc, scale) without return types