code: def increment_log_probs(
      draw, batch_shape=None, enable_vars=False, validate_args=True
  ):
      """Strategy for drawing `IncrementLogProb` distributions.
  
      Args:
        draw: Hypothesis strategy sampler supplied by `@hps.composite`.
        batch_shape: An optional `TensorShape`.  The batch shape of the resulting
          `IncrementLogProb` distribution.
        enable_vars: TODO(b/181859346): Make this `True` all the time and put
          variable initialization in slicing_test.  If `False`, the returned
          parameters are all `tf.Tensor`s and not {`tf.Variable`,
          `tfp.util.DeferredTensor` `tfp.util.TransformedVariable`}
        validate_args: Python `bool`; whether to enable runtime assertions.
  
      Returns:
        dists: A strategy for drawing `IncrementLogProb` distributions with the
          specified `batch_shape` (or an arbitrary one if omitted).
      """
      if batch_shape is None:
          batch_shape = draw(tfp_hps.shapes(min_ndims=0, max_side=4))
  
      log_prob_value = draw(
          tfp_hps.maybe_variable(
              tfp_hps.constrained_tensors(
                  tfp_hps.identity_fn,
                  tensorshape_util.as_list(batch_shape),
              ),
              enable_vars=enable_vars,
          )
      )
  
      if draw(hps.booleans()):
          return tfed.IncrementLogProb(
              log_prob_value, validate_args=validate_args
          )
      else:
          return tfed.IncrementLogProb(
              lambda v: v,
              validate_args=validate_args,
              log_prob_increment_kwargs={"v": log_prob_value},
          )
  
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 25 for calling a global function with example usage: increment_log_probs(draw, batch_shape, enable_vars, validate_args) and returns: tfed, tfed