hardware setup for default training parameters

SwinTransformer / MIM-Depth-Estimation

This is an official implementation of our CVPR 2023 paper "Revealing the Dark Secrets of Masked Image Modeling" on Depth Estimation.

MIT License

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hardware setup for default training parameters #9

Open nikste opened 1 year ago

nikste commented 1 year ago

hey, thanks for putting this on GitHub. trying to reproduce the kitti results.

I was wondering what the original training hardware setup was (number of GPUs and type)? couldn't find any information in the paper, running it on a 4090 with 24gb ram and batch size 3. default batch size seems to be 24.