code: def fix_truncated_normal(params):
      new_params = dict(
          params,
          high=tfp_hps.ensure_high_gt_low(
              params["low"], params["high"]
          ),
      )
      max_low = params["loc"] + 5 * params["scale"]
      min_high = params["loc"] - 5 * params["scale"]
      new_params["high"] = tfp_hps.ensure_high_gt_low(
          min_high, new_params["high"]
      )
      new_params["low"] = tfp_hps.ensure_low_lt_high(
          new_params["low"], max_low
      )
      return new_params
  
imports: import collections
  import functools
  import inspect
  from absl import logging
  import hypothesis
  from hypothesis import strategies
  import numpy
  import six
  import tensorflow.compat.v2
  from tensorflow_probability.python import distributions
  from tensorflow_probability.python import util
  from tensorflow_probability.python.bijectors import ascending
  from tensorflow_probability.python.bijectors import hypothesis_testlib
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.experimental import distributions
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import tensorshape_util
label_desc: Use image node_id 8 for calling a global function with example usage: fix_truncated_normal(params) and returns: new_params