code: def test_nnet():
      x = vector("x")
      x.tag.test_value = np.r_[1.0, 2.0].astype(config.floatX)
  
      out = sigmoid(x)
      fgraph = FunctionGraph([x], [out])
      compare_jax_and_py(
          fgraph, [get_test_value(i) for i in fgraph.inputs]
      )
  
      out = softplus(x)
      fgraph = FunctionGraph([x], [out])
      compare_jax_and_py(
          fgraph, [get_test_value(i) for i in fgraph.inputs]
      )
  
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 17 for calling a global function with example usage: test_nnet() without return types