for v in tf.global_variables():
if 'global_step' in v.name:
var2.append(v) # 重置global step 调整学习率重新训练
else:
var1.append(v)
var1 = tf.train.Saver(var1)
...
"""Restore Model"""
save_file = tf.train.latest_checkpoint(hparams_at.train_dir)
if save_file:
print(save_file)
step = int(save_file.split('ckpt-')[-1]) + 1
var1.restore(sess, save_file)
sess.run(tf.variables_initializer([model.global_step]))
print("Go on")
else:
step = 0
sess.run(tf.global_variables_initializer())
print("Begin")
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