Save and restore in CNN
<p>i am beginner in tensorflow and i have one question related to save and restore checkpoint in Convolutional neural networks. I am trying to create CNN to classify faces. My question is:</p>

<p>If is it possible when i add new class in my dataset to make partial training? So i just want to retrain the new class instead to retrain the hole Network. is it possible to restore the weights and bias from previous training and train just the new class ?</p>

<p>i am using for save </p>

<pre><code>saver = tf.train.Saver(tf.all_variables())
save = saver.save(session, "/home/owner//tensorflownew_models.ckpt")

print("Model saved in file: %s" % save)
</code></pre>

<p>Sure. You can use the var_list parameter in tf.train.Optimizer.minimize() to control the weights you want to optimize. If you don't include the variables you restored (or currently have trained,) they shouldn't get changed.</p>

python python-2.7 tensorflow conv-neural-network