How to set layer-wise learning rate in Tensorflow?

Question

I want different learning layers in different layers just like we do in Caffe. I just want to speed up the training for newly added layers without distorting them. Ex. I have a 6-convy-layer pre-trained model and I want to add a new convy-layer, The Starting 6 layers have a learning speed of 0.00002 and last one of 0.002, How can I do this? Select the correct answer from above options

Answer 1

Just use these two optimizers: var_list2 = [variables from first 6 layers] var_list3 = [the rest of variables] train_op1 = GradientDescentOptimizer(0.00002).minimize(loss, var_list=var_list2) train_op2 = GradientDescentOptimizer(0.0002).minimize(loss, var_list=var_list3) train_op = tf.group(train_op1, train_op2) Go through artificial intelligence online course to get ahead in your career!