code: def ensure_high_gt_low(low, high):
      """Returns a value with shape matching `high` and gt broadcastable `low`."""
      new_high = tf.maximum(low + tf.abs(low) * 0.1 + 0.1, high)
      reduce_dims = []
      if tensorshape_util.rank(new_high.shape) > tensorshape_util.rank(
          high.shape
      ):
          reduced_leading_axes = tf.range(
              tensorshape_util.rank(new_high.shape)
              - tensorshape_util.rank(high.shape)
          )
          new_high = tf.math.reduce_max(
              new_high, axis=reduced_leading_axes
          )
      reduce_dims = [
          d
          for d in range(tensorshape_util.rank(high.shape))
          if high.shape[d] < new_high.shape[d]
      ]
      if reduce_dims:
          new_high = tf.math.reduce_max(
              new_high, axis=reduce_dims, keepdims=True
          )
      return new_high
  
imports: import contextlib
  import os
  import re
  import traceback
  import unittest
  import hypothesis
  from hypothesis.extra import numpy
  import hypothesis.strategies
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.util.deferred_tensor import DeferredTensor
label_desc: Use image node_id 34 for calling a global function with example usage: ensure_high_gt_low(low, high) and returns: new_high