Hi,
I am training a UNet3D model with MRI data, and the images and the model itself are quite large. To fit into the 24GB VRAM available to me I need to decrease the input image size significantly. I was wondering how much VRAM I would need to use the original image size, but I obviously can’t just try to run it as I will very quickly get an OOM error.
So as a solution I was wondering if there was a way to compute how much VRAM the model’s computation graph and the loaded data will need (taking into account the batch size)?