thingtalk.py 文件源码

def value_transition(self, curr_state, next_symbols, batch_size):
        first_value_token = self.num_functions + self.num_begin_tokens + self.num_control_tokens
        num_value_tokens = self.output_size - first_value_token
        with tf.name_scope('grammar_transition'):
            adjusted_next_symbols = tf.where(next_symbols >= self.num_control_tokens, next_symbols + (first_value_token - self.num_control_tokens), next_symbols)

            assert1 = tf.Assert(tf.reduce_all(tf.logical_and(next_symbols < num_value_tokens, next_symbols >= 0)), [curr_state, next_symbols])
            with tf.control_dependencies([assert1]):
                transitions = tf.gather(tf.constant(self.transition_matrix), curr_state)
            assert transitions.get_shape()[1:] == (self.output_size,)

            indices = tf.stack((tf.range(0, batch_size), adjusted_next_symbols), axis=1)
            next_state = tf.gather_nd(transitions, indices)

            assert2 = tf.Assert(tf.reduce_all(next_state >= 0), [curr_state, adjusted_next_symbols, next_state])
            with tf.control_dependencies([assert2]):
                return tf.identity(next_state)