memory.py 文件源码

def init_memory(self, batch_size):
        """
        Returns the memory state for step 0. Used in DNC for the argument to tf.while_loop

        :return: 
        """
        read_weightings = tf.fill([batch_size, self.memory_size, self.num_read_heads], Memory.epsilon)
        write_weighting = tf.fill([batch_size, self.memory_size], Memory.epsilon, name="Write_weighting")
        precedence_weighting = tf.zeros([batch_size, self.memory_size], name="Precedence_weighting")
        m = tf.fill([batch_size, self.memory_size, self.word_size], Memory.epsilon)  # initial memory matrix
        usage_vector = tf.zeros([batch_size, self.memory_size], name="Usage_vector")
        link_matrix = tf.zeros([batch_size, self.memory_size, self.memory_size])
        read_vectors = tf.fill([batch_size, self.num_read_heads, self.word_size], Memory.epsilon)

        return [read_weightings, write_weighting, usage_vector, precedence_weighting, m, link_matrix, read_vectors]