code: def test_accuracy(self):
      # Test all approximations are working (cutoff points are -37, 18, 33.3)
      x_test = np.array([-40.0, -17.5, 17.5, 18.5, 40.0])
      y_th = pt.softplus(x_test).eval()
      y_np = np.log1p(np.exp(x_test))
      np.testing.assert_allclose(y_th, y_np, rtol=10e-10)
  
imports: import warnings
  import numpy
  import pytest
  from pytensor.gradient import verify_grad
  from pytensor.scalar import ScalarLoop
  from pytensor.tensor.elemwise import Elemwise
  from functools import partial
  import scipy.special
  import scipy.stats
  from pytensor import function, grad
  from pytensor import tensor
  from pytensor.compile.mode import get_default_mode
  from pytensor.configdefaults import config
  from pytensor.tensor import gammaincc, inplace, vector
  from tests import unittest_tools
  from tests.tensor.utils import _good_broadcast_unary_chi2sf, _good_broadcast_unary_normal, _good_broadcast_unary_normal_float, _good_broadcast_unary_normal_float_no_complex, _good_broadcast_unary_normal_float_no_complex_small_neg_range, _good_broadcast_unary_normal_no_complex, _grad_broadcast_unary_0_2_no_complex, _grad_broadcast_unary_abs1_no_complex, _grad_broadcast_unary_normal, _grad_broadcast_unary_normal_small_neg_range, check_floatX, copymod, integers_ranged, makeBroadcastTester, random_ranged, upcast_int8_nfunc
label_desc: Use image node_id 2 for calling the TestSoftplus obj's underlying member method code with example usage: obj.test_accuracy() without return types