code: def testLogCDF(self, loc, scale, low, high):
      test_x = list(np.float32(np.random.uniform(low, high, 10)))
      test_x += [
          low,
          high,
          low + 100 * EPSILON,
          low - EPSILON,
          high + EPSILON,
          high - EPSILON,
          low - 100.0,
          high + 100.0,
      ]
  
      tf_dist, sp_dist = self.constructDists(
          loc, scale, low, high, validate_args=False
      )
  
      tf_log_cdf = self.evaluate(tf_dist.log_cdf(test_x))
      sp_log_cdf = sp_dist.logcdf(test_x)
      self.assertAllClose(tf_log_cdf, sp_log_cdf, rtol=1e-4, atol=1e-4)
  
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 6 for calling the TruncatedNormalTestCompareWithScipy obj's underlying member method code with example usage: obj.testLogCDF(loc, scale, low, high) without return types