code: def _halton_sequence(i, max_bits=MAX_HALTON_SEQUENCE_BITS):
      bit_masks = 2 ** tf.range(max_bits, dtype=i.dtype)
      return tf.einsum(
          "i,i->", tf.math.mod((i + 1) // bit_masks, 2), 0.5 / bit_masks
      )
  
imports: import collections
  import functools
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import broadcast_util
  from tensorflow_probability.python.internal import distribute_lib
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import unnest
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.mcmc import kernel
  from tensorflow_probability.python.mcmc import simple_step_size_adaptation
  from tensorflow_probability.python.mcmc import transformed_kernel
  from tensorflow_probability.python.mcmc.internal import util
  from tensorflow.python.util import nest
label_desc: Use image node_id 14 for calling a global function with example usage: _halton_sequence(i, max_bits) and returns: tf