Save intermediate model in matlab while training a deep learning model and resume training from that stage later

Hi,

I am training a 3 pipeline deep learning model in matlab which takes a lot of time to train. I need to store intermediate variable values while training, stop the training process and then resume training at a later point from the stage at which the training was stopped previously. Does Matlab have any options to do this? Any help in this regard would be highly appreciated.

Thanks in Advance

Answer 1

[Mahesh Taparia]

Hi

You can set the checkpoint path in trainingOptions as suggested in the above answer. The trained weights will be saved into the specified path as a mat file. To resume the training process, you can load those weights in the net variable and start the training process. For example, you can refer this documentation.

Hope it will help!

Answer 2

[yanqi liu]

sir，may be use CheckpointPath，such as

options = trainingOptions('sgdm', ...
    'MaxEpochs', 5, ...
    'MiniBatchSize', 1, ...
    'InitialLearnRate', 1e-3, ...
    'CheckpointPath', tempdir);