code: def beta_binomial_from_beta_binomial(fgraph, node):
      rng, *other_inputs, n, a, b = node.inputs
      n, a, b = broadcast_arrays(n, a, b)
      next_rng, b = beta.make_node(rng, *other_inputs, a, b).outputs
      next_rng, b = binomial.make_node(
          next_rng, *other_inputs, n, b
      ).outputs
      return [next_rng, b]
  
file_path: pytensor/pytensor/tensor/random/rewriting/jax.py
imports: from pytensor.compile import optdb
  from pytensor.graph.rewriting.basic import in2out, node_rewriter
  from pytensor.graph.rewriting.db import SequenceDB
  from pytensor.tensor import abs
  from pytensor.tensor import broadcast_arrays, exp, floor, log, log1p, reciprocal, sqrt
  from pytensor.tensor.basic import MakeVector, cast, ones_like, switch, zeros_like
  from pytensor.tensor.elemwise import DimShuffle
  from pytensor.tensor.random.basic import BetaBinomialRV, GenGammaRV, GeometricRV, HalfNormalRV, InvGammaRV, LogNormalRV, NegBinomialRV, WaldRV, _gamma, beta, binomial, normal, poisson, uniform
  from pytensor.tensor.random.op import RandomVariable
label_desc: Use image node_id 9 for calling a global function with example usage: beta_binomial_from_beta_binomial(fgraph, node) and returns: list