code: def _cumulative_logsumexp(
      x, axis=0, exclusive=False, reverse=False, name=None
  ):
      del name
      axis = int(axis)
      if axis < 0:
          axis = axis + len(x.shape)
      if JAX_MODE:
          op = jax.lax.cumlogsumexp
      else:
          op = np.logaddexp.accumulate
      return _cumop(
          op,
          x,
          axis=axis,
          exclusive=exclusive,
          reverse=reverse,
          initial_value=-np.inf,
      )
  
imports: import collections
  import functools
  import numpy
  import numpy
  from tensorflow_probability.python.internal.backend.numpy import _utils
  from tensorflow_probability.python.internal.backend.numpy.numpy_array import _reverse
  from tensorflow_probability.python.internal.backend.numpy.numpy_array import one_hot
  from tensorflow_probability.python.internal.backend.numpy.ops import _convert_to_tensor
label_desc: Use image node_id 6 for calling a global function with example usage: _cumulative_logsumexp(x, axis, exclusive, reverse, name) and returns: _cumop