Comments (2)
Sorry to hear you are having issues. Perhaps try to change this line in the config
"texture_res": [ 2048, 2048 ],
to "texture_res": [ 512, 512 ],
I haven't tried on a GPU with 6GB memory, but the problems seems to be happening in render.render_uv
where we convert from volumetric textures to 2D textures by rasterizing in texture space. The resolution we are rasterizing at is determined by texture_res
, so perhaps it will work with a lower value, if it is a memory issue you are seeing.
Also, to verify, could you run the simpler examples, say bob.json or spot.json (with reduced batch size) without issues?
Unfortunately, I think 6GB is not sufficient to get high quality results from the current code base. We have only tested the code using 12+GB GPUs
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Thanks @jmunkberg for you response, i am not sure what the reason that aborted after i make this feature run, but i guessed it maybe be i did not update torch(cuda) environment for my downgrade to cuda11.3(including cudnn) to match torch.
But i still have memory issue for nerf_ship this time, but i can share some experience during make module running.
a. The environment must be matched version for cuda(cudnn) <-> torch, for example, cuda_11.3 <-> matched torch.
This maybe is why this abort issue, i maybe forgot to update cuda link and cuda environment.
b. GPU memory.
I use Quadro 3000(6g), i must set the batch to 1 to make this system work, of course, different GPU(type, gefore or Quadro rtx) has different model effect.
If it still can't solve memory issue, maybe jmunkberg's answer is the option.
Regards
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