Please provide the following information when requesting support.
• Hardware (T4/V100/Xavier/Nano/etc)
• Network Type (Detectnet_v2/Faster_rcnn/Yolo_v4/LPRnet/Mask_rcnn/Classification/etc) Classification
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here) 5.0.0
• Training spec file(If have, please share here)
• How to reproduce the issue ? (This is for errors. Please share the command line and the detailed log here.)
I tried to use mixed precision training by adding the --use_amp argument but it says argument not found.
There is no update from you for a period, assuming this is not an issue anymore. Hence we are closing this topic. If need further support, please open a new one. Thanks
Yes, in tao_tf2, there is not use_amp in https://github.com/NVIDIA/tao_tensorflow2_backend/blob/main/nvidia_tao_tf2/common/entrypoint/entrypoint.py. In tao_tf1, it is available in https://github.com/NVIDIA/tao_tensorflow1_backend/blob/c7a3926ddddf3911842e057620bceb45bb5303cc/nvidia_tao_tf1/cv/common/entrypoint/entrypoint.py#L106 .
You can run as below.
$ TF_ENABLE_AUTO_MIXED_PRECISION=1 python nvidia_tao_tf2/cv/classification/entrypoint/classification.py trian xxx
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