NameError: name '_C' is not defined

Describe the bug A clear and concise description of what the bug is. I run following command:

docker run --gpus '"device=1"' -v /home/fakhriddin/patata/PersonalFakhriddin/nerf/split_allview_new:/workspace/ --rm -it dromni/nerfstudio:0.1.10 ns-train instant-ngp --data /data/nerfstudio/poster

And then it shows this error

Traceback (most recent call last):
  File "/home/user/.local/bin/ns-train", line 5, in <module>
    from scripts.train import entrypoint
  File "/home/user/nerfstudio/scripts/train.py", line 50, in <module>
    from nerfstudio.configs.method_configs import AnnotatedBaseConfigUnion
  File "/home/user/nerfstudio/nerfstudio/configs/method_configs.py", line 39, in <module>
    from nerfstudio.field_components.temporal_distortions import TemporalDistortionKind
  File "/home/user/nerfstudio/nerfstudio/field_components/__init__.py", line 17, in <module>
    from .encodings import Encoding, ScalingAndOffset
  File "/home/user/nerfstudio/nerfstudio/field_components/encodings.py", line 34, in <module>
    import tinycudann as tcnn
  File "/home/user/.local/lib/python3.8/site-packages/tinycudann/__init__.py", line 9, in <module>
    from tinycudann.modules import free_temporary_memory, NetworkWithInputEncoding, Network, Encoding
  File "/home/user/.local/lib/python3.8/site-packages/tinycudann/modules.py", line 33, in <module>
    if _C is None:
NameError: name '_C' is not defined

How to solve this issue? I pulled docker image with versions 0.1.13 and 0.1.10. I also tried to build Docker image but the same error Other parameters:

NVIDIA-SMI 520.61.05    Driver Version: 520.61.05    CUDA Version: 11.8 
Distributor ID: Ubuntu
Description:    Ubuntu 22.04.1 LTS
Release:        22.04
Codename:       jammy

[KtechB]

I had this issue when I use Docker , and tried pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch --force-reinstall but not solved. So, I tried use tiny-cuda-nn of older version. Then it worked well.

pip install git+https://github.com/NVlabs/tiny-cuda-nn.git@v1.5#subdirectory=bindings/torch --force-reinstall

[mabl]

The problem here is that nerfstudio hard-codes the CUDA architecture version in the Docker skript (TCNN_CUDA_ARCHITECTURES). When run on a GPU with lower than the default 8.5 architecture, a bug in tiny-cuda-nn is triggered in a code path that is supposed to tell you, that no backend for your architecture has been found.

Try either removing the environmental variable definition or lower the the architecture to match your hardware.