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 constructDists(self, loc, scale, validate_args=True):
      truncated_dist = truncated_normal.TruncatedNormal(
          loc=loc,
          scale=scale,
          low=loc - (10.0 * scale),
          high=loc + (10.0 * scale),
          validate_args=validate_args,
      )
      normal_dist = normal.Normal(loc=loc, scale=scale)
      return truncated_dist, normal_dist
  
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 1 for calling the TruncatedNormalTestCompareWithNormal obj's underlying member method code with example usage: obj.constructDists(loc, scale, validate_args) and returns: truncated_dist,  normal_dist