code: def is_1pexp(t, only_process_constants=True):
      """
  
      Returns
      -------
      object
          If 't' is of the form (1+exp(x)), return (False, x).
          Else return None.
  
      """
      if t.owner and t.owner.op == tensor.add:
          scalars, scalar_inputs, nonconsts = opt.scalarconsts_rest(
              t.owner.inputs,
              only_process_constants=only_process_constants,
          )
          # scalar_inputs are potentially dimshuffled and filled with scalars
          if len(nonconsts) == 1:
              maybe_exp = nonconsts[0]
              if maybe_exp.owner and maybe_exp.owner.op == tensor.exp:
                  # Verify that the constant terms sum to 1.
                  if scalars:
                      scal_sum = scalars[0]
                      for s in scalars[1:]:
                          scal_sum = scal_sum + s
                      if np.allclose(scal_sum, 1):
                          return False, maybe_exp.owner.inputs[0]
                  # Before 7987b51 there used to be a bug where *any* constant
                  # was considered as if it was equal to 1, and thus this
                  # function would incorrectly identify it as (1 + exp(x)).
                  if config.warn.identify_1pexp_bug:
                      warnings.warn(
                          "Although your current code is fine, please note that "
                          "Theano versions prior to 0.5 (more specifically, "
                          "prior to commit 7987b51 on 2011-12-18) may have "
                          "yielded an incorrect result. To remove this warning, "
                          "either set the `warn.identify_1pexp_bug` config "
                          "option to False, or `warn.ignore_bug_before` to at "
                          "least '0.4.1'."
                      )
      return None
  
imports: from __future__ import absolute_import, print_function, division
  import warnings
  import numpy
  import theano
  from theano import config, gof, printing, scalar
  from theano.compat import imap
  from theano.printing import pprint
  from theano.tensor import basic
  from theano.tensor import elemwise, opt, NotScalarConstantError
  from theano.tensor.type import values_eq_approx_remove_inf
  from theano.gof.opt import copy_stack_trace
label_desc: Use image node_id 6 for calling a global function with example usage: is_1pexp(t, only_process_constants) and returns: None, False,  maybe_exp