code: def make_node(self, a, s=None):
      a = T.as_tensor_variable(a)
      if a.ndim < 2:
          raise TypeError(
              "%s: input must have dimension > 2, with first dimension batches"
              % self.__class__.__name__
          )
  
      if s is None:
          s = a.shape[1:]
          s = T.as_tensor_variable(s)
      else:
          s = T.as_tensor_variable(s)
          if s.dtype not in T.integer_dtypes:
              raise TypeError(
                  "%s: length of the transformed axis must be"
                  " of type integer" % self.__class__.__name__
              )
      return gof.Apply(self, [a, s], [self.output_type(a)()])
  
imports: from __future__ import absolute_import, print_function, division
  import numpy
  from theano import gof
  import theano.tensor
  from theano.gradient import DisconnectedType
label_desc: Use image node_id 2 for calling the RFFTOp obj's underlying member method code with example usage: obj.make_node(a, s) and returns: gof