code: def testTriangularCDFPeakEqualsLow(self):
      low = np.arange(1.0, 5.0, dtype=self._dtype)
      high = np.arange(7.0, 11.0, dtype=self._dtype)
      peak = low
      tri = self._create_triangular_dist(low, high, peak)
  
      x = self._rng.uniform(low=low, high=high).astype(self._dtype)
  
      tri_cdf = self.evaluate(tri.cdf(self.make_tensor(x)))
      self.assertAllClose(
          self._scipy_triangular(low, high, peak).cdf(x), tri_cdf
      )
  
      tri_log_cdf = self.evaluate(tri.log_cdf(self.make_tensor(x)))
      self.assertAllClose(
          self._scipy_triangular(low, high, peak).logcdf(x), tri_log_cdf
      )
      self.assertAllClose(tri_cdf, np.exp(tri_log_cdf))
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import triangular
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 14 for calling the _TriangularTest obj's underlying member method code with example usage: obj.testTriangularCDFPeakEqualsLow() without return types