code: def test_default_event_space_bijector_bijective_and_finite(self):
      batch_shape = [5, 1, 4]
      batch_size = np.prod(batch_shape)
      low = tf.Variable(
          np.linspace(-5.0, 5.0, batch_size).astype(self.dtype),
          shape=(batch_size,) if self.is_static_shape else None,
      )
      dist = uniform.Uniform(low=low, high=30.0, validate_args=True)
      reshape_dist = batch_reshape.BatchReshape(
          dist, batch_shape=batch_shape, validate_args=True
      )
      x = (
          np.linspace(-10.0, 10.0, batch_size)
          .astype(self.dtype)
          .reshape(batch_shape)
      )
      y = (
          np.linspace(5.0, 30 - 1e-4, batch_size)
          .astype(self.dtype)
          .reshape(batch_shape)
      )
  
      self.evaluate(low.initializer)
      bijector_test_util.assert_bijective_and_finite(
          reshape_dist.experimental_default_event_space_bijector(),
          x,
          y,
          eval_func=self.evaluate,
          event_ndims=0,
          rtol=1e-4,
      )
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.distributions import batch_reshape
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.distributions import triangular
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.distributions import wishart
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.util.deferred_tensor import DeferredTensor
label_desc: Use image node_id 18 for calling the _BatchReshapeTest obj's underlying member method code with example usage: obj.test_default_event_space_bijector_bijective_and_finite() without return types