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def evaluate(tensors):
    if tf.executing_eagerly():
         return tf.contrib.framework.nest.pack_sequence_as(
             tensors,
             [t.numpy() if tf.contrib.framework.is_tensor(t) else t
             for t in tf.contrib.framework.nest.flatten(tensors)])
    with tf.Session() as sess:
        return sess.run(tensors)