triton
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triton-lang
Documentation on triton-lang.org is not versioned
Describe the bug
DriverBase abstract class has the method get_active_torch_device but after installation it is giving the error as
DEVICE = triton.runtime.driver.active.get_active_torch_device()
{
"name": "AttributeError",
"message": "'CudaDriver' object has no attribute 'get_active_torch_device'",
"stack": "---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[16], line 1
----> 1 DEVICE = triton.runtime.driver.active.get_active_torch_device()
2 DEVICE
File /HOME/miniconda3/envs/learn/lib/python3.12/site-packages/triton/runtime/driver.py:24, in LazyProxy.__getattr__(self, name)
22 def __getattr__(self, name):
23 self._initialize_obj()
---> 24 return getattr(self._obj, name)
AttributeError: 'CudaDriver' object has no attribute 'get_active_torch_device'"
}
Environment details
Triton: 3.1.0 GPUs: 4xA100 80G
This means CudaDriver is coming from a older install of triton. Try uninstalling any other triton versions in your system.
This means
CudaDriveris coming from a older install of triton. Try uninstalling any other triton versions in your system.
Hi Peter, thanks for the response I checked and there is only one triton installation, attaching complete environement below
# Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 2_gnu conda-forge
asttokens 3.0.0 pyhd8ed1ab_1 conda-forge
bzip2 1.0.8 h4bc722e_7 conda-forge
ca-certificates 2024.8.30 hbcca054_0 conda-forge
comm 0.2.2 pyhd8ed1ab_1 conda-forge
debugpy 1.8.9 py310hf71b8c6_0 conda-forge
decorator 5.1.1 pyhd8ed1ab_1 conda-forge
exceptiongroup 1.2.2 pyhd8ed1ab_1 conda-forge
executing 2.1.0 pyhd8ed1ab_1 conda-forge
filelock 3.16.1 pypi_0 pypi
fsspec 2024.10.0 pypi_0 pypi
importlib-metadata 8.5.0 pyha770c72_1 conda-forge
ipykernel 6.29.5 pyh3099207_0 conda-forge
ipython 8.30.0 pyh707e725_0 conda-forge
jedi 0.19.2 pyhd8ed1ab_1 conda-forge
jinja2 3.1.4 pypi_0 pypi
jupyter_client 8.6.3 pyhd8ed1ab_1 conda-forge
jupyter_core 5.7.2 pyh31011fe_1 conda-forge
keyutils 1.6.1 h166bdaf_0 conda-forge
krb5 1.21.3 h659f571_0 conda-forge
ld_impl_linux-64 2.43 h712a8e2_2 conda-forge
libedit 3.1.20191231 he28a2e2_2 conda-forge
libffi 3.4.2 h7f98852_5 conda-forge
libgcc 14.2.0 h77fa898_1 conda-forge
libgcc-ng 14.2.0 h69a702a_1 conda-forge
libgomp 14.2.0 h77fa898_1 conda-forge
liblzma 5.6.3 hb9d3cd8_1 conda-forge
libnsl 2.0.1 hd590300_0 conda-forge
libsodium 1.0.20 h4ab18f5_0 conda-forge
libsqlite 3.47.2 hee588c1_0 conda-forge
libstdcxx 14.2.0 hc0a3c3a_1 conda-forge
libstdcxx-ng 14.2.0 h4852527_1 conda-forge
libuuid 2.38.1 h0b41bf4_0 conda-forge
libxcrypt 4.4.36 hd590300_1 conda-forge
libzlib 1.3.1 hb9d3cd8_2 conda-forge
markupsafe 3.0.2 pypi_0 pypi
matplotlib-inline 0.1.7 pyhd8ed1ab_1 conda-forge
mpmath 1.3.0 pypi_0 pypi
ncurses 6.5 he02047a_1 conda-forge
nest-asyncio 1.6.0 pyhd8ed1ab_1 conda-forge
networkx 3.4.2 pypi_0 pypi
nvidia-cublas-cu12 12.4.5.8 pypi_0 pypi
nvidia-cuda-cupti-cu12 12.4.127 pypi_0 pypi
nvidia-cuda-nvrtc-cu12 12.4.127 pypi_0 pypi
nvidia-cuda-runtime-cu12 12.4.127 pypi_0 pypi
nvidia-cudnn-cu12 9.1.0.70 pypi_0 pypi
nvidia-cufft-cu12 11.2.1.3 pypi_0 pypi
nvidia-curand-cu12 10.3.5.147 pypi_0 pypi
nvidia-cusolver-cu12 11.6.1.9 pypi_0 pypi
nvidia-cusparse-cu12 12.3.1.170 pypi_0 pypi
nvidia-nccl-cu12 2.21.5 pypi_0 pypi
nvidia-nvjitlink-cu12 12.4.127 pypi_0 pypi
nvidia-nvtx-cu12 12.4.127 pypi_0 pypi
openssl 3.4.0 hb9d3cd8_0 conda-forge
packaging 24.2 pyhd8ed1ab_2 conda-forge
parso 0.8.4 pyhd8ed1ab_1 conda-forge
pexpect 4.9.0 pyhd8ed1ab_1 conda-forge
pickleshare 0.7.5 pyhd8ed1ab_1004 conda-forge
pip 24.3.1 pyh8b19718_0 conda-forge
platformdirs 4.3.6 pyhd8ed1ab_1 conda-forge
prompt-toolkit 3.0.48 pyha770c72_1 conda-forge
psutil 6.1.0 py310ha75aee5_0 conda-forge
ptyprocess 0.7.0 pyhd8ed1ab_1 conda-forge
pure_eval 0.2.3 pyhd8ed1ab_1 conda-forge
pygments 2.18.0 pyhd8ed1ab_1 conda-forge
python 3.10.16 he725a3c_1_cpython conda-forge
python-dateutil 2.9.0.post0 pyhff2d567_1 conda-forge
python_abi 3.10 5_cp310 conda-forge
pyzmq 26.2.0 py310h71f11fc_3 conda-forge
readline 8.2 h8228510_1 conda-forge
setuptools 75.6.0 pyhff2d567_1 conda-forge
six 1.17.0 pyhd8ed1ab_0 conda-forge
stack_data 0.6.3 pyhd8ed1ab_1 conda-forge
sympy 1.13.1 pypi_0 pypi
tk 8.6.13 noxft_h4845f30_101 conda-forge
torch 2.5.1 pypi_0 pypi
tornado 6.4.2 py310ha75aee5_0 conda-forge
traitlets 5.14.3 pyhd8ed1ab_1 conda-forge
triton 3.1.0 pypi_0 pypi
typing_extensions 4.12.2 pyha770c72_1 conda-forge
tzdata 2024b hc8b5060_0 conda-forge
wcwidth 0.2.13 pyhd8ed1ab_1 conda-forge
wheel 0.45.1 pyhd8ed1ab_1 conda-forge
zeromq 4.3.5 h3b0a872_7 conda-forge
zipp 3.21.0 pyhd8ed1ab_1 conda-forge
Oh I see the issue, get_active_torch_device has been added recently on the main branch and isn't in a released version but the docs on the website were updated to match main. The website should probably have docs from the latest released version instead.
As a workaround you can replace with:
DEVICE = "cuda"
Run into the same issue. Would the team open to PR to make the documentations host on ReadTheDocs so that it's versioned?
3.2.0 still AttributeError: 'CudaDriver' object has no attribute 'get_active_torch_device'
Does anyone have any idea which version works with the tutorials? It looks like building from source doesn’t work either
