Optimization for 8GB #3
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Remove invalid line that was attempting to reassign radar_pcd.points with incorrect arguments (radar_pcd, lidar_pcd). This line would cause the data patch generation to fail.
Created UpPoinTr_lowmem.yaml with reduced batch size (16→2) and gradient accumulation (4 steps) to enable training on GPUs with ~8GB VRAM. This config prevents CUDA out of memory errors while maintaining effective batch size of 8. Users can copy this config to UpPoinTr/cfgs/ColoRadar_models/ and train with: python main.py --config cfgs/ColoRadar_models/UpPoinTr_lowmem.yaml
Remove leading space before 'bnmscheduler' on line 16 that was causing YAML parser error.
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