'Step 2: define weights. In word2vec, it\'s actually the weights that we care about'

def _create_embedding(self):

    with tf.device('/cpu:0'):
        with tf.name_scope('embed'):
            self.embed_matrix = tf.Variable(tf.random_uniform([self.vocab_size, self.embed_size], (-1.0), 1.0), name='embed_matrix')
