Lidar_AI_Solution
Lidar_AI_Solution copied to clipboard
Exporting PTQ model on my custom bevfusion trained weights
Thank you for the amazing work. I was able to setup the BEVFusion inference using the model files given in the readme. I want to use this pipeline for BEVFusion trained on my dataset, so as per the Quantization README,
- Run the export scripts for each module with the checkpoint as my checkpoint that I get from BEVFusion training pipeline
- Run
qat/ptq.pywith the dataset changed to my custom dataset
TLDR
Can I directly use my BEVFusion weights trained on my dataset in the quantisation flow mentioned in this repo with the change in the qat/ptq.py file to use my custom dataset
same question, same failure Need an answer, the same.
Seems like the qat/ptq.py is written for the resnet50 backbone. So I think even for custom dataset, as long as the model architecture doesn't change, the script should work as is (except for the change in the dataloaders)