code: def test_jax_Composite_singe_output(x, y, x_val, y_val):
      x_s = ps.float64("x")
      y_s = ps.float64("y")
  
      comp_op = Elemwise(
          Composite([x_s, y_s], [x_s + y_s * 2 + ps.exp(x_s - y_s)])
      )
  
      out = comp_op(x, y)
  
      out_fg = FunctionGraph([x, y], [out])
  
      test_input_vals = [
          x_val.astype(config.floatX),
          y_val.astype(config.floatX),
      ]
      _ = compare_jax_and_py(out_fg, test_input_vals)
  
imports: import numpy
  import pytest
  import pytensor.scalar.basic
  import pytensor.tensor
  from pytensor.configdefaults import config
  from pytensor.graph.fg import FunctionGraph
  from pytensor.graph.op import get_test_value
  from pytensor.scalar.basic import Composite
  from pytensor.tensor import as_tensor
  from pytensor.tensor.elemwise import Elemwise
  from pytensor.tensor.math import all
  from pytensor.tensor.math import betaincinv, cosh, erf, erfc, erfcinv, erfcx, erfinv, gammainccinv, gammaincinv, iv, log, log1mexp, polygamma, psi, sigmoid, softplus, tri_gamma
  from pytensor.tensor.type import matrix, scalar, vector
  from tests.link.jax.test_basic import compare_jax_and_py
  from pytensor.link.jax.dispatch import jax_funcify
label_desc: Use image node_id 4 for calling a global function with example usage: test_jax_Composite_singe_output(x, y, x_val, y_val) without return types