Comments (2)
Hi,
thanks a lot for your interest!
The reason for this memory pool is to make the rasterizer compatible with complex pytorch pipelines (e.g., running multiple forwards and preserving the context before one backup is run). To do this, we need to keep the internal state of the rasterizer around. Our internal state consists of multiple buffers. We were wary of how pytorch would handle 20+ resize operations of large buffers, that is why we compressed it into 3 memory pools and then deconstruct them into the buffers ourselves. It might very well be overkill, we never tried without it.
Hth,
Bernhard
from gaussian-splatting.
Thanks for the information!
from gaussian-splatting.
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