code: def test_event_space_bijector_fldj(self):
      # Also test forward log det jacobian for the default event space
      # bijector in the same setting, for completeness.
      sub_d = relaxed_onehot_categorical.ExpRelaxedOneHotCategorical(
          logits=[0.0, 0.0, 0.0], temperature=[0.01, 0.01, 0.01, 0.01]
      )
      d = masked.Masked(sub_d, validity_mask=False, validate_args=True)
      bij = d.experimental_default_event_space_bijector()
      fldj = bij.forward_log_det_jacobian(tf.zeros(shape=[4, 2]))
      self.assertAllEqual(fldj, tf.zeros_like(fldj))
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import log_prob_ratio
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import masked
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import relaxed_onehot_categorical
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 4 for calling the MaskedTest obj's underlying member method code with example usage: obj.test_event_space_bijector_fldj() without return types