OSError: CUDA_HOME environment variable is not set. Please set it to your CUDA install root.

$ pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html
pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch
Looking in links: https://download.pytorch.org/whl/torch_stable.html
Collecting torch==1.12.1+cu113
  Using cached https://download.pytorch.org/whl/cu113/torch-1.12.1%2Bcu113-cp38-cp38-linux_x86_64.whl (1837.7 MB)
Collecting torchvision==0.13.1+cu113
  Using cached https://download.pytorch.org/whl/cu113/torchvision-0.13.1%2Bcu113-cp38-cp38-linux_x86_64.whl (23.4 MB)
Collecting typing-extensions
  Using cached typing_extensions-4.4.0-py3-none-any.whl (26 kB)
Collecting requests
  Using cached requests-2.28.1-py3-none-any.whl (62 kB)
Collecting pillow!=8.3.*,>=5.3.0
  Using cached Pillow-9.2.0-cp38-cp38-manylinux_2_28_x86_64.whl (3.2 MB)
Collecting numpy
  Using cached numpy-1.23.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.1 MB)
Collecting urllib3<1.27,>=1.21.1
  Using cached urllib3-1.26.12-py2.py3-none-any.whl (140 kB)
Collecting idna<4,>=2.5
  Using cached idna-3.4-py3-none-any.whl (61 kB)
Collecting charset-normalizer<3,>=2
  Using cached charset_normalizer-2.1.1-py3-none-any.whl (39 kB)
Requirement already satisfied: certifi>=2017.4.17 in ./anaconda3/envs/nerfstudio/lib/python3.8/site-packages (from requests->torchvision==0.13.1+cu113) (2022.9.24)
Installing collected packages: urllib3, typing-extensions, pillow, numpy, idna, charset-normalizer, torch, requests, torchvision
Successfully installed charset-normalizer-2.1.1 idna-3.4 numpy-1.23.3 pillow-9.2.0 requests-2.28.1 torch-1.12.1+cu113 torchvision-0.13.1+cu113 typing-extensions-4.4.0 urllib3-1.26.12
Collecting git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch
  Cloning https://github.com/NVlabs/tiny-cuda-nn/ to /tmp/pip-req-build-p95k6ytq
  Running command git clone --filter=blob:none --quiet https://github.com/NVlabs/tiny-cuda-nn/ /tmp/pip-req-build-p95k6ytq
  Resolved https://github.com/NVlabs/tiny-cuda-nn/ to commit 563b626c298a88b5a0c6fb47944c693e9fbd8507
  Running command git submodule update --init --recursive -q
  Preparing metadata (setup.py) ... error
  error: subprocess-exited-with-error

  × python setup.py egg_info did not run successfully.
  │ exit code: 1
  ╰─> [14 lines of output]
      Traceback (most recent call last):
        File "<string>", line 2, in <module>
        File "<pip-setuptools-caller>", line 34, in <module>
        File "/tmp/pip-req-build-p95k6ytq/bindings/torch/setup.py", line 111, in <module>
          ext = CUDAExtension(
        File "/home/kosuke/anaconda3/envs/nerfstudio/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 983, in CUDAExtension
          library_dirs += library_paths(cuda=True)
        File "/home/kosuke/anaconda3/envs/nerfstudio/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1098, in library_paths
          if (not os.path.exists(_join_cuda_home(lib_dir)) and
        File "/home/kosuke/anaconda3/envs/nerfstudio/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 2125, in _join_cuda_home
          raise EnvironmentError('CUDA_HOME environment variable is not set. '
      OSError: CUDA_HOME environment variable is not set. Please set it to your CUDA install root.
      Building PyTorch extension for tiny-cuda-nn version 1.6
      Obtained compute capability 80 from PyTorch
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.

[stevekm]

I think it would be a good idea to at least note in the README that CUDA needs to be installed, and possibly provide some links or docs on various ways to install it. As it stands currently, I was under the impression that the README install guide included everything necessary to run nerfstudio out of the box, including CUDA installation, especially because (confusingly) some of the Python libraries included in the installation have “cuda” in the name.

[stevekm]

Ok, it seems that I was able resolve it with this; https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#conda-installation

$ conda install -c nvidia cuda

which installed CUDA version 11.8.0 into my conda env, and let me install this sucessfully;

$ pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch

which let me run

$ ns-train nerfacto

Maybe we can get cuda put in the conda env installation instructions for nerfstudio?