vars = tf.global_variables()
net_var = [var for var in vars if 'bi-lstm_secondLayer' not in var.name and 'word_embedding1s' not in var.name
and 'proj_secondLayer' not in var.name
]
saver_pre = tf.train.Saver(net_var)
saver_pre.restore(self.sess, tf.train.latest_checkpoint(self.config.dir_model_storepath_pre))
'''
with tf.variable_scope('bi-lstm',reuse=True):
fwk=tf.get_variable('bidirectional_rnn/fw/lstm_cell/kernel')
fwb=tf.get_variable('bidirectional_rnn/fw/lstm_cell/bias')
bwk = tf.get_variable('bidirectional_rnn/bw/lstm_cell/kernel')
bwb = tf.get_variable('bidirectional_rnn/bw/lstm_cell/bias')
saver_pre= tf.train.Saver({'words/_word_embeddings':self._word_embeddings,
'bi-lstm/bidirectional_rnn/fw/lstm_cell/kernel':fwk,
'bi-lstm/bidirectional_rnn/fw/lstm_cell/bias':fwb,
'bi-lstm/bidirectional_rnn/bw/lstm_cell/kernel':bwk,
'bi-lstm/bidirectional_rnn/bw/lstm_cell/bias':bwb})
for x in tf.trainable_variables():
print(x.name)
#mysaver = tf.train.import_meta_graph(self.config.dir_model_storepath_pre_graph)
saver_pre.restore(self.sess, tf.train.latest_checkpoint(self.config.dir_model_storepath_pre))
'''