I have used this MATLAB documentation example (https://www.mathworks.com/help/deeplearning/ug/train-network-on-image-and-feature-data.html ) to verify if the original network and trained network obtained using “trainnet” of Deep Learning Toolbox are actually the same. It appears that the original network was not modified, suggesting it must be a copy.
I am attaching the output screenshot of my experimentation below.
To save and access the current state of the network during training you can use the “CheckpointPath” name-value pair in “trainingOptions”. This can be specified in the "options" input argument in "trainnet". You can refer to the below MATLAB links for more details:
- Checkpointpath: https://www.mathworks.com/help/releases/R2024b/deeplearning/ref/trainingoptions.html#:~:text=collapse%20all-,CheckpointPath,-%E2%80%94%20Path%20for
- Options in “trainnet” : https://in.mathworks.com/help/deeplearning/ref/trainnet.html#:~:text=options%20%E2%80%94%20Training%20options
I hope this helps you.
