I am quite new to nvidia-tlt. Currently, I have trained, pruned and retrained the model with the kitti dataset, also am able to do these steps on any datasets with the required kitti format. What I want to do is used a previously trained model on kitti and fine tune it to my own data. The config file have the options pretrained_model_path, resume_model_path and pruned_model_path, So there is no option for the fine-tune in config. If I try to use pretrained_model_path, it throws an exception for the shape. Invalid argument: Incompatible shapes: [6,29484,3] vs. [6,29484,12]
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That error is expected. Technically the pretrained model that we download from ngc comes without final layer which represents the total number of classes and their respective bboxes. Once you train that model with any dataset, then the trained model will be frozen with the top layer. Now, if you want to finetune the same model with different number of classes you will get error related to invalid shapes.
You need to train the model on the new dataset from the beginning.
If you want to finetune the model with different dataset but of the same classes then you can use the previously trained model.
Shaik Ahmad
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Thank you soo much. That's the same as what I understood after few days of trouble. – Muhammad Ahsan Jul 05 '21 at 13:03