[Need Help] Cannot use DL checkpoint model to predict?
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I tried to use models saved in path specified by 'CheckpointPath' parameter during training by Deep Learning Toolbox, I got following error:
Error using DAGNetwork/calculatePredict>predictSingle (line 112)
Input parameter has the wrong class.
Error in DAGNetwork/calculatePredict (line 13)
Y = predictSingle( ...
Error in DAGNetwork/predict (line 125)
Y = this.calculatePredict( ...
The detector after training can be used without problem.
Did I miss something? Are the checkpoint models of same class as final detector itself?
Thanks
2 commentaires
Guillaume PERRIN
le 29 Mar 2020
Modifié(e) : Guillaume PERRIN
le 29 Mar 2020
Hi, indeed checkpoints that are associated to some DAGNetwork architectures cannot be used to make predictions. As an example, those who contain batchNorm layers. See https://fr.mathworks.com/matlabcentral/answers/423588-how-to-classify-with-dag-network-from-checkpoint or https://fr.mathworks.com/matlabcentral/answers/451383-issue-with-batch-normalization-layer-of-saved-cnn#answer_366855.
For a workaround, you can still retrain from your checkpoint during 1 epoch, with a minimalist training set, at a very low learning rate.
Best,
Guillaume
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