code: def _draw_domain_tensor(
      self, bijector, data, event_dim, sample_shape=()
  ):
      codomain_event_shape = [
          event_dim
      ] * bijector.inverse_min_event_ndims
      codomain_event_shape = constrain_inverse_shape(
          bijector, codomain_event_shape
      )
      shp = bijector.inverse_event_shape(codomain_event_shape).as_list()
      xs = tf.identity(
          data.draw(domain_tensors(bijector, shape=shp)), name="xs"
      )
  
      return xs
  
imports: import collections
  import functools
  from absl.testing import parameterized
  import hypothesis
  from hypothesis import strategies
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python import bijectors
  from tensorflow_probability.python import util
  from tensorflow_probability.python.bijectors import hypothesis_testlib
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 for calling the BijectorSlicingTest obj's underlying member method code with example usage: obj._draw_domain_tensor(bijector, data, event_dim, sample_shape) and returns: xs