code: def fix_bates(d):
      total_count = tf.math.maximum(
          tf.math.minimum(
              d["total_count"],
              tfd.bates.BATES_TOTAL_COUNT_STABILITY_LIMITS[  # pylint: disable=protected-access
                  d["total_count"].dtype
              ],
          ),
          1.0,
      )
      high = tfp_hps.ensure_high_gt_low(d["low"], d["high"])
      return dict(d, total_count=total_count, high=high)
  
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 10 for calling a global function with example usage: fix_bates(d) and returns: dict