code: def nn_predict(inputs, t, params):
      for W, b in params:
          outputs = np.dot(inputs, W) + b
          inputs = np.maximum(0, outputs)
      return outputs
  
file_path: autograd/examples/ode_net.py
imports: from __future__ import absolute_import
  from __future__ import print_function
  import matplotlib.pyplot
  import numpy
  import autograd.numpy
  from autograd import grad
  from autograd.scipy.integrate import odeint
  from autograd.builtins import tuple
  from autograd.misc.optimizers import adam
  import autograd.numpy.random
label_desc: Use image node_id 2 for calling a global function with example usage: nn_predict(inputs, t, params) and returns: outputs