tensorflow_backend.py 文件源码

def __init__(self, inputs, outputs, updates=[]):
        if not isinstance(inputs, (list, tuple)):
            raise TypeError('`inputs` to a TensorFlow backend function '
                            'should be a list or tuple.')
        if not isinstance(outputs, (list, tuple)):
            raise TypeError('`outputs` of a TensorFlow backend function '
                            'should be a list or tuple.')
        if not isinstance(updates, (list, tuple)):
            raise TypeError('`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):
            updates_ops = []
            for update in updates:
                if isinstance(update, tuple):
                    p, new_p = update
                    updates_ops.append(tf.assign(p, new_p))
                else:
                    # assumed already an op
                    updates_ops.append(update)
            self.updates_op = tf.group(*updates_ops)