How to initialize a network using .caffemodel, .solverstate? Thank you.

[ayeshasGithub]

Could any please show me how to initialize a deep network using .caffemodel or .solverstate?

Thanks
Ayesha

[amalF]

Hello @ayeshasGithub

To resume from a snapshot :
caffe train -gpu all -solver my_model/solver.prototxt -snapshot my_model/my_model_iter_6000.solverstate 2>&1 | tee log/my_model.log

To use weights of a trained model

caffe train -gpu all -solver my_model/solver.prototxt -weights my_model/bvlc_reference_caffenet.caffemodel 2>&1 | tee -a log/my_model.log

Hope it helps
cheers

[ayeshasGithub]

Thanks so much amal, but I need those commands in python. Do you know how I can do it in python?

[amalF]

In your train.py, you can use solver.net.copy_from(pretrained_model) to restore a trained model and solver.restore(previous_state) to restore previous solver state.

You can find an example here : https://github.com/rbgirshick/py-faster-rcnn/blob/master/lib/fast_rcnn/train.py

Hope it helps
Cheers

[ayeshasGithub]

Nice of you amal, thank you so much, that definitely should help, thanks a lot

[pratikds]

Hello,

Do I need to keep the same old learning rate in solver file while resuming the training via snapshot or I need to change the base_lr where it had left of?

Cheers

[shaibagon]

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