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CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' Building PyTorch extension for tiny-cuda-nn version 1.7 #237
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I'm having this same issue |
similar issue, I'm using WSL2 with Ubuntu 20.04 error is
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same issue |
same here, anyone found a solution? |
I meet same issue and have solved it. If you ensure that you have install cuda driver and the version of cuda and torch are matched, and your cuda install path is under CUDA_HOME, then it maybe because your machine has no GPU cards ... This sounds a little stupid but it's really my situation. I build the environment on my lab's cluster login node rather than my own machine. On the cluster's login node, there are no GPU cards and only when you launch an experiment task, will the GPU resources that you request be aligned to your experiment. So, I meet this error on the login node where no GPU card available but it goes very smoothly when I launch a test environment with 1 GPU aligned to it. Hope my reply can help someone in similar situation as me. |
my machine have GPU below is nvidia-smi output, still facing the same issue. +-----------------------------------------------------------------------------+ |
You have to specify the TCNN_CUDA_ARCHITECTURE as shown in this line of code:
Also note that any GPU-related commands such as torch.cuda.is_available() cannot be executed when building an image. https://discuss.huggingface.co/t/how-to-deal-with-no-gpu-during-docker-build-time/28544/4 |
This is an example of my Dockerfile where i've set the CUDA architecture
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pip install --global-option="--no-networks" git+https://github.com/NVlabs/tiny-cuda-nn#subdirectory=bindings/torch imageio_download_bin freeimage
Error is
ARNING: Implying --no-binary=:all: due to the presence of --build-option / --global-option / --install-option. Consider using --config-settings for more flexibility.
DEPRECATION: --no-binary currently disables reading from the cache of locally built wheels. In the future --no-binary will not influence the wheel cache. pip 23.1 will enforce this behaviour change. A possible replacement is to use the --no-cache-dir option. You can use the flag --use-feature=no-binary-enable-wheel-cache to test the upcoming behaviour. Discussion can be found at pypa/pip#11453
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-lh3mplh3
Running command git clone --quiet https://github.com/NVlabs/tiny-cuda-nn /tmp/pip-req-build-lh3mplh3
Resolved https://github.com/NVlabs/tiny-cuda-nn to commit 14053e9
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
╰─> [8 lines of output]
Traceback (most recent call last):
File "", line 36, in
File "", line 34, in
File "/tmp/pip-req-build-lh3mplh3/bindings/torch/setup.py", line 30, in
raise EnvironmentError("Unknown compute capability. Specify the target compute capabilities in the TCNN_CUDA_ARCHITECTURES environment variable or install PyTorch with the CUDA backend to detect it automatically.")
OSError: Unknown compute capability. Specify the target compute capabilities in the TCNN_CUDA_ARCHITECTURES environment variable or install PyTorch with the CUDA backend to detect it automatically.
No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda'
Building PyTorch extension for tiny-cuda-nn version 1.7
[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.
how could I solve it
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