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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def generate_np(self, x_val, **kwargs):
 """ Facilitates testing this attack. """

    _, feedable, _feedable_types, hash_key = self.construct_variables(kwargs)

    if hash_key not in self.graphs:
      with tf.variable_scope(None, 'attack_%d' % len(self.graphs)):
        # x is a special placeholder we always want to have
        with tf.device('/gpu:0'):
          x = tf.placeholder(tf.float32, shape=x_val.shape, name='x')

        inputs, outputs = self.generate(x, **kwargs)

        from runner import RunnerMultiGPU
        runner = RunnerMultiGPU(inputs, outputs, sess=self.sess)
        self.graphs[hash_key] = runner

    runner = self.graphs[hash_key]
    feed_dict = {'x': x_val}
    for name in feedable:
      feed_dict[name] = feedable[name]
    fvals = runner.run(feed_dict)
    while not runner.is_finished():
      fvals = runner.run()

    return fvals['adv_x']