summelon

@Derdin-datascience Not work under mirrored strategy

Working on converting model which has FFT layer from Tensorflow 2.X -> OpenVINO IR. To those who need a workaround to successfully convert fft/ifft op., this [white paper](https://www.intel.com/content/dam/www/public/us/en/ai/documents/openvino-and-devcloud-accelerate-cs-image-reconstruction-algorithms-for-mri.pdf) may be...

I guess you guys are using `pytorch-lightning==1.2.1`. Downgrading to 1.1.8 may fix this problem.

I encountered the same bug when I tried to load the segmentation dataset which has a high resolution. When I was saving 4kx4k gt & prediction mask to the sample...

Same here. I converted ViT-H encoder to float16 and used the float32 decoder. The prediction is totally wrong. Do you guys have any work around on this?

+1. Unseen domain + hierarchical objects are a big challenge for current foundation model , e.g., SAM, DINO etc. AFAIF, not only in this repo, the finetuning for such tasks...

Thanks for your solution! I encountered the same problem under TensorRT 10.0.1.6 / 8.6.3. It's worth noting that I tried on TensorRT 8.6.1, and trt did not report any conflict....