class_docstr: Tests correctness of the cumsum bijector.
class_docstr_tok: ["Tests","correctness","of","the","cumsum","bijector","."]
docstr: Helper for `testJacobian`.
docstr_tok: ["Helper","for","`","testJacobian","`","."]
code: def _checkEqualTheoreticalFldj(self, x):
      """Helper for `testJacobian`."""
      event_ndims = len(x.shape) - 1
      self.assertGreaterEqual(event_ndims, 1)
  
      bijector = cumsum.Cumsum(axis=-event_ndims, validate_args=True)
      fldj = bijector.forward_log_det_jacobian(
          self._build_tensor(x), event_ndims=event_ndims
      )
      fldj_theoretical = bijector_test_util.get_fldj_theoretical(
          bijector, x, event_ndims=event_ndims
      )
      fldj_, fldj_theoretical_ = self.evaluate([fldj, fldj_theoretical])
      self.assertAllEqual(np.zeros_like(fldj_), fldj_)
      self.assertAllClose(
          np.zeros_like(fldj_theoretical_), fldj_theoretical_
      )
  
file_path: probability/tensorflow_probability/python/bijectors/cumsum_test.py
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import cumsum
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 6 for calling the _CumsumBijectorTest obj's underlying member method code with example usage: obj._checkEqualTheoreticalFldj(x) without return types