test-embedding.py 文件源码

def __init__(self, embedding):
        self.sess         = tf.Session()
        self.inputs       = tf.placeholder(tf.float32,
                                           [None, embedding.shape[1]],
                                           name='inputs')
        self.test_vec     = tf.placeholder(tf.float32, [1, embedding.shape[1]],
                                           name='test_vec')
        self.cos_distance = tf.matmul(self.inputs, tf.transpose(self.test_vec))

        #-----------------------------------------------------------------------
        # Compute normalized embedding matrix
        #-----------------------------------------------------------------------
        row_sum    = tf.reduce_sum(tf.square(self.inputs), axis=1,
                                   keep_dims=True)
        norm       = tf.sqrt(row_sum)
        self.normalized = self.inputs / norm
        self.embedding = self.sess.run(self.normalized,
                                       feed_dict={self.inputs: embedding})

    #---------------------------------------------------------------------------