code: def fix_pert(d):
      peak = tfp_hps.ensure_high_gt_low(d["low"], d["peak"])
      high = tfp_hps.ensure_high_gt_low(peak, d["high"])
      temperature = tfp_hps.ensure_high_gt_low(
          np.zeros(d["temperature"].shape, dtype=np.float32),
          d["temperature"],
      )
      return dict(d, peak=peak, high=high, temperature=temperature)
  
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 6 for calling a global function with example usage: fix_pert(d) and returns: dict