code: def concat_and_multiply(weights, *args):
      cat_state = np.hstack(args + (np.ones((args[0].shape[0], 1)),))
      return np.dot(cat_state, weights)
  
file_path: autograd/examples/rnn.py
imports: from __future__ import absolute_import
  from __future__ import print_function
  from builtins import range
  import autograd.numpy
  import autograd.numpy.random
  from autograd import grad
  from autograd.scipy.special import logsumexp
  from os.path import dirname, join
  from autograd.misc.optimizers import adam
label_desc: Use image node_id 2 for calling a global function with example usage: concat_and_multiply(weights) and returns: np