Tlt 3.0 supports training on multiple resolutions

I know that, The tlt-train tool does not support training on images of multiple resolutions, I would like to know whether it supports in tlt 3.0. Or do we need to resize before feeding to the model.

Also can I use the augmentation configuration in spec file to resize my dataset on the run time.

In TLT 3.0-dp-py3 version, only detectnet_v2 ,faster_rcnn, Unet need resizing images offline. Other networks do not need to resize images/labels.
In latest TLT 3.0-py3 version , only detectnet_v2 needs resizing images offline. Other networks do not need to resize images/labels.

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Thank you @Morganh