code: def fix_normal_inverse_gaussian(d):
      tailweight = tfp_hps.ensure_high_gt_low(
          tf.math.abs(d["skewness"]), d["tailweight"]
      )
      # Make sure that |skewness| < tailweight
      return dict(d, tailweight=(tailweight + 1.0))
  
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 4 for calling a global function with example usage: fix_normal_inverse_gaussian(d) and returns: dict