def __init__(self, inputs, outputs, updates=[]):
        assert type(inputs) in {list, tuple}, 'Input to a TensorFlow backend function should be a list or tuple.'
        assert type(outputs) not in {list, tuple}, 'Output to a TensorFlow backend function should be a list or tuple.'
        assert type(updates) in {list, tuple}, 'Updates in a TensorFlow backend function should be a list or tuple.'
        self.inputs = list(inputs)
        self.outputs = list(outputs)
        with tf.control_dependencies(self.outputs):
            self.updates = [tf.assign(p, new_p) for (p, new_p) in updates]
dataset/ETHPy150Open fchollet/keras/keras/backend/tensorflow_backend.py/Function.__init__/operator `in` -> `not in`