torch and CUDA version

[Terencedu]

Hi,

Thanks for your great work! There are some problems when I installed the torch environment.
My device is Ubuntu 2204, CUDA 11.3, 4 RTX4090 (40 series need at least CUDA 11.3).
My training setting: v1.0-mini dataset. contracted_coord = False, auxiliary_frame = False, render_h = 45, render_w = 80, input_channel = 16, train only depth.

1. conda install pytorch==1.9.1 torchvision==0.10.1 cudatoolkit=11.3 -c pytorch -c conda-forge
   This is from your repo, but it would install torch of cpu version and torch.cuda.is_available() = False
   

2. conda install pytorch==1.10.0 torchvision==0.11.0 torchaudio==0.10.0 cudatoolkit=11.3 -c pytorch -c conda-forge and
   conda install pytorch==1.10.1 torchvision==0.11.2 torchaudio==0.10.1 cudatoolkit=11.3 -c pytorch -c conda-forge
   These two are from pytorch official website. They are gpu version, but they have the same error.
   

3. pip install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
   This is from pytorch official website. It trained successfully with contracted_coord = True and little warnings, but there is error about CUDA with contracted_coord = False, maybe because it is cu111:
   

4. pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cu113 and conda install pytorch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0 cudatoolkit=11.3 -c pytorch
   They both are from pytorch official website. It seems like training successfully. There are lots of warnings about CUDA, is this torch and cuda version suitable?
   
   
   

5. How to set the config to train model with semantic with 4090(24GB each)? A little accuracy can be sacrificed.

Thanks for your help!