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rapidsai / cuml

cuML - RAPIDS Machine Learning Library
https://docs.rapids.ai/api/cuml/stable/
Apache License 2.0
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Getting error in Cuml installation #5237

Closed Kowsher closed 1 year ago

Kowsher commented 1 year ago

I am following the instruction of https://rapids.ai/pip.html#install When I'm running !pip install cuml-cu11 --extra-index-url=https://pypi.ngc.nvidia.com in colab getting this error Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/, https://pypi.ngc.nvidia.com/ Collecting cuml-cu11 Using cached cuml_cu11-23.2.0.tar.gz (6.5 kB) error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully. │ exit code: 1 ╰─> See above for output.

note: This error originates from a subprocess, and is likely not a problem with pip. Preparing metadata (setup.py) ... error 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.

beckernick commented 1 year ago

Starting in 23.02, RAPIDS pip packages use a new index URL: https://pypi.nvidia.com. You can install with pip install cuml-cu11 --extra-index-url=https://pypi.nvidia.com.

If you still see the old URL on https://rapids.ai/pip.html#install you may be looking at a cached version on your browser.

Closing as answered, but please feel free to reopen if you have any issues.

plehman2000 commented 1 year ago

Hello, I'm receiving the same error. Both the cu11 and cu12 versions of the command pip install cuml-cu11 --extra-index-url=https://pypi.nvidia.com do not work and yield the error note: This error originates from a subprocess, and is likely not a problem with pip. error: metadata-generation-failed

ermaxinc commented 1 year ago

Same error

vyasr commented 1 year ago

@plehman2000 @ermaxinc could you include the full traceback (ideally in an attached file so that the GH thread doesn't explode :slightly_smiling_face:)? Are you also seeing the same Using cached cuml_cu11-23.2.0.tar.gz (6.5 kB) in the original error message? If so, you may need to do a pip install --no-cache-dir.

ermaxinc commented 1 year ago

@vyasr 

PS G:\Python\Boosty_V3> python --version
Python 3.10.5
PS G:\Python\Boosty_V3> pip install cuml-cu11 --extra-index-url=https://pypi.nvidia.com --no-cache-dir                                                                                                       
Looking in indexes: https://pypi.org/simple, https://pypi.nvidia.com
Collecting cuml-cu11
  Downloading cuml-cu11-23.6.0.tar.gz (6.8 kB)
  Preparing metadata (setup.py) ... error
  error: subprocess-exited-with-error

  × python setup.py egg_info did not run successfully.
  │ exit code: 1
  ╰─> [16 lines of output]
      Traceback (most recent call last):
        File "<string>", line 2, in <module>
        File "<pip-setuptools-caller>", line 34, in <module>
        File "C:\Users\user\AppData\Local\Temp\pip-install-nxtn50fa\cuml-cu11_9a521611ce1046eebf6aec7624b06565\setup.py", line 137, in <module>
          raise RuntimeError(open("ERROR.txt", "r").read())
      RuntimeError:
      ###########################################################################################
      The package you are trying to install is only a placeholder project on PyPI.org repository.
      This package is hosted on NVIDIA Python Package Index.

      This package can be installed as:
  $ pip install --extra-index-url https://pypi.nvidia.com cuml-cu11
  ```
  ###########################################################################################

  [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.



PS. PyCharm latest version
vyasr commented 1 year ago

Ah that looks like you are on Windows, is that right? Unfortunately cuml isn't supported on Windows.

bdice commented 1 year ago

RAPIDS supported platforms are listed here: https://docs.rapids.ai/install#system-req

Windows users can try the provided instructions for WSL2, but RAPIDS does not produce native Windows packages.

vyasr commented 1 year ago

Going to close this as resolved again for now, but please reopen if needed.

jena-shreyas commented 1 year ago

I'm trying to install cuML on a Linux system, but I get the same error as mentioned above.

(dinov2) [jenas@beluga3 dinov2]$ pip install --extra-index-url https://download.pytorch.org/whl/cu117 --extra-index-url https://pypi.nvidia.com cuml-cu11
Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cu117, https://pypi.nvidia.com
Looking in links: /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/avx512, /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/avx2, /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/generic, /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/generic
Collecting cuml-cu11
  Using cached cuml-cu11-23.6.0.tar.gz (6.8 kB)
  Preparing metadata (setup.py) ... error
  error: subprocess-exited-with-error

  × python setup.py egg_info did not run successfully.
  │ exit code: 1
  ╰─> [16 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-install-x0qpxtmz/cuml-cu11_436e7571d2b440ce8339f1c5e9b054b1/setup.py", line 137, in <module>
          raise RuntimeError(open("ERROR.txt", "r").read())
      RuntimeError:
      ###########################################################################################
      The package you are trying to install is only a placeholder project on PyPI.org repository.
      This package is hosted on NVIDIA Python Package Index.

      This package can be installed as:
  $ pip install --extra-index-url https://pypi.nvidia.com cuml-cu11
  ```
  ###########################################################################################

  [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.

chaoer commented 1 year ago

hi, @vyasr

I have tried the command pip install cuml-cu11 --extra-index-url=https://pypi.nvidia.com ; but network errors still exist.

And when i try to open 'https://pypi.nvidia.com' directly in browser, it returns only a 'AccessDenied' page.

So, is there any other way to install it?

pingumen96 commented 1 year ago

Hello, the error is still there, I'm on Ubuntu 22.04

$ pip install --extra-index-url https://pypi.nvidia.com cudf-cu12
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com, https://pypi.nvidia.com
Collecting cudf-cu12
  Downloading cudf-cu12-23.8.0.tar.gz (6.8 kB)
  Preparing metadata (setup.py) ... error
  error: subprocess-exited-with-error

  × python setup.py egg_info did not run successfully.
  │ exit code: 1
  ╰─> [16 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-install-ktxk516p/cudf-cu12_e8ca359c76df488cb8ee1376ebd020c1/setup.py", line 137, in <module>
          raise RuntimeError(open("ERROR.txt", "r").read())
      RuntimeError:
      ###########################################################################################
      The package you are trying to install is only a placeholder project on PyPI.org repository.
      This package is hosted on NVIDIA Python Package Index.

      This package can be installed as:
  $ pip install --extra-index-url https://pypi.nvidia.com cudf-cu12
  ```
  ###########################################################################################

  [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.

bdice commented 1 year ago

@chaoer @pingumen96 Can you please provide your OS and version (if not already mentioned), Python version, pip version, output of pip list, and output of nvidia-smi? This will help us make sure you're using a supported OS (Linux or WSL2), supported Python version (3.9 or 3.10 as of this writing), recent version of pip, and compatible CUDA 11 or CUDA 12 version.

The installation guide https://docs.rapids.ai/install also provides conda packages and Docker image instructions, as well as some troubleshooting information for pip packages.

pingumen96 commented 1 year ago

@chaoer @pingumen96 Can you please provide your OS and version (if not already mentioned), Python version, pip version, output of pip list, and output of nvidia-smi? This will help us make sure you're using a supported OS (Linux or WSL2), supported Python version (3.9 or 3.10 as of this writing), recent version of pip, and compatible CUDA 11 or CUDA 12 version.

The installation guide https://docs.rapids.ai/install also provides conda packages and Docker image instructions, as well as some troubleshooting information for pip packages.

OS: Ubuntu 22.04.3 LTS Python version: 3.11 (it's possible that this is the problem, I see now) pip version: 23.1.2 pip list output:

Package                      Version
---------------------------- ---------------
absl-py                      2.0.0
accelerate                   0.21.0
addict                       2.4.0
aenum                        3.1.15
aiofiles                     23.2.1
aiohttp                      3.8.5
aiosignal                    1.3.1
altair                       5.1.1
antlr4-python3-runtime       4.9.3
anyio                        3.7.1
astunparse                   1.6.3
async-timeout                4.0.3
attrs                        23.1.0
basicsr                      1.4.2
beautifulsoup4               4.12.2
blendmodes                   2022
blinker                      1.6.2
boltons                      23.0.0
brotlipy                     0.7.0
cachetools                   5.3.1
certifi                      2023.7.22
cffi                         1.15.1
charset-normalizer           2.0.4
clean-fid                    0.1.35
click                        8.1.7
clip                         1.0
cmake                        3.27.5
colorama                     0.4.6
conda                        23.7.4
conda-content-trust          0.1.3
conda-libmamba-solver        23.5.0
conda-package-handling       2.1.0
conda_package_streaming      0.8.0
contourpy                    1.1.1
cryptography                 39.0.1
cycler                       0.11.0
deprecation                  2.1.0
einops                       0.4.1
facexlib                     0.3.0
fastapi                      0.94.0
ffmpy                        0.3.1
filelock                     3.12.4
filterpy                     1.4.5
Flask                        2.3.3
flatbuffers                  23.5.26
fonttools                    4.42.1
frozenlist                   1.4.0
fsspec                       2023.9.2
ftfy                         6.1.1
future                       0.18.3
gast                         0.4.0
gdown                        4.7.1
gfpgan                       1.3.8
gitdb                        4.0.10
GitPython                    3.1.32
google-auth                  2.23.0
google-auth-oauthlib         1.0.0
google-pasta                 0.2.0
gradio                       3.41.2
gradio_client                0.5.0
grpcio                       1.58.0
h11                          0.12.0
h5py                         3.9.0
httpcore                     0.15.0
httpx                        0.24.1
huggingface-hub              0.17.2
idna                         3.4
imageio                      2.31.4
importlib-metadata           6.8.0
importlib-resources          6.1.0
inflection                   0.5.1
itsdangerous                 2.1.2
Jinja2                       3.1.2
joblib                       1.3.2
jsonmerge                    1.8.0
jsonpatch                    1.32
jsonpointer                  2.1
jsonschema                   4.19.1
jsonschema-specifications    2023.7.1
keras                        2.13.1
kiwisolver                   1.4.5
kornia                       0.6.7
lark                         1.1.2
lazy_loader                  0.3
libclang                     16.0.6
libmambapy                   1.4.1
lightning-utilities          0.9.0
lit                          17.0.1
llvmlite                     0.41.0
lmdb                         1.4.1
lpips                        0.1.4
Markdown                     3.4.4
MarkupSafe                   2.1.3
matplotlib                   3.8.0
mpmath                       1.3.0
multidict                    6.0.4
networkx                     3.1
numba                        0.58.0
numpy                        1.23.5
nvidia-cublas-cu11           11.11.3.6
nvidia-cublas-cu12           12.2.5.6
nvidia-cuda-nvrtc-cu12       12.2.140
nvidia-cuda-runtime-cu12     12.2.140
nvidia-cudnn-cu11            8.6.0.163
nvidia-cudnn-cu12            8.9.4.25
nvidia-pyindex               1.0.9
oauthlib                     3.2.2
omegaconf                    2.2.3
open-clip-torch              2.20.0
openai                       0.28.1
opencv-python                4.8.0.76
opencv-python-headless       4.8.0.76
opt-einsum                   3.3.0
orjson                       3.9.7
packaging                    23.0
pandas                       2.1.1
piexif                       1.1.3
Pillow                       9.5.0
pip                          23.1.2
platformdirs                 3.10.0
pluggy                       1.0.0
protobuf                     3.20.0
psutil                       5.9.5
pyasn1                       0.5.0
pyasn1-modules               0.3.0
pycosat                      0.6.4
pycparser                    2.21
pydantic                     1.10.12
pydub                        0.25.1
pygame                       2.5.2
pyOpenSSL                    23.0.0
pyparsing                    3.1.1
PySocks                      1.7.1
pytesseract                  0.3.10
python-dateutil              2.8.2
python-decouple              3.8
python-multipart             0.0.6
pytorch-lightning            1.9.4
pytz                         2023.3.post1
PyWavelets                   1.4.1
PyYAML                       6.0.1
realesrgan                   0.3.0
referencing                  0.30.2
regex                        2023.8.8
requests                     2.29.0
requests-oauthlib            1.3.1
resize-right                 0.0.2
rpds-py                      0.10.3
rsa                          4.9
ruamel.yaml                  0.17.21
safetensors                  0.3.1
scikit-image                 0.21.0
scikit-learn                 1.3.1
scipy                        1.11.2
semantic-version             2.10.0
sentencepiece                0.1.99
setuptools                   67.8.0
six                          1.16.0
smmap                        5.0.1
sniffio                      1.3.0
soupsieve                    2.5
starlette                    0.26.1
sympy                        1.12
tb-nightly                   2.15.0a20230925
tenacity                     8.2.3
tensorboard                  2.13.0
tensorboard-data-server      0.7.1
tensorflow                   2.13.0
tensorflow-estimator         2.13.0
tensorflow-io-gcs-filesystem 0.34.0
tensorrt                     8.6.1.post1
tensorrt-bindings            8.6.1
tensorrt-libs                8.6.1
termcolor                    2.3.0
tesseract                    0.1.3
threadpoolctl                3.2.0
tifffile                     2023.9.18
tiktoken                     0.5.1
timm                         0.9.2
tokenizers                   0.13.3
tomesd                       0.1.3
tomli                        2.0.1
toolz                        0.12.0
torch                        2.0.1+cu118
torchdiffeq                  0.2.3
torchmetrics                 1.2.0
torchsde                     0.2.5
torchvision                  0.15.2+cu118
tqdm                         4.65.0
trampoline                   0.1.2
transformers                 4.30.2
triton                       2.0.0
typing_extensions            4.5.0
tzdata                       2023.3
urllib3                      1.26.16
uvicorn                      0.23.2
wcwidth                      0.2.6
websockets                   11.0.3
Werkzeug                     2.3.7
wheel                        0.38.4
wrapt                        1.15.0
yapf                         0.40.2
yarl                         1.9.2
zipp                         3.17.0
zstandard                    0.19.0

nvidia-smi output:

+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.104.05             Driver Version: 535.104.05   CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA GeForce RTX 2080 ...    Off | 00000000:01:00.0  On |                  N/A |
|  0%   61C    P0              57W / 250W |   4501MiB /  8192MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|    0   N/A  N/A      1544      G   /usr/lib/xorg/Xorg                         1361MiB |
|    0   N/A  N/A      1827      G   /usr/bin/gnome-shell                        375MiB |
|    0   N/A  N/A      2547      G   ...2938967,15047306651023814721,262144      256MiB |
|    0   N/A  N/A      2945      G   ...sion,SpareRendererForSitePerProcess      236MiB |
|    0   N/A  N/A      3950      C   python                                     2184MiB |
+---------------------------------------------------------------------------------------+
beckernick commented 1 year ago

Thanks for the info, and it look like the problem is clear! (We don't currently provide Python 3.11 wheels).

Are you able to use Python 3.9 or 3.10? If not, would love to learn more about how you selected Python 3.11.

pingumen96 commented 1 year ago

Thanks for the info, and it look like the problem is clear! (We don't currently provide Python 3.11 wheels).

Are you able to use Python 3.9 or 3.10? If not, would love to learn more about how you selected Python 3.11.

Yes, I've been able to install the libs using Python 3.10. I was using the default version of Python that is present on Ubuntu 22.04 and I was pretty sure it was the 3.10. So thank you very much for the support

chaoer commented 1 year ago

@chaoer @pingumen96 Can you please provide your OS and version (if not already mentioned), Python version, pip version, output of pip list, and output of nvidia-smi? This will help us make sure you're using a supported OS (Linux or WSL2), supported Python version (3.9 or 3.10 as of this writing), recent version of pip, and compatible CUDA 11 or CUDA 12 version.

The installation guide https://docs.rapids.ai/install also provides conda packages and Docker image instructions, as well as some troubleshooting information for pip packages.

I have checked the python version. It's 3.9.18. Is there any other advice?

OS Version (with lsb_release -a ): 

Distributor ID: Ubuntu
Description:    Ubuntu 20.04.6 LTS
Release:        20.04
Codename:       focal

Python list ( with conda list ):

# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                        main    defaults
_openmp_mutex             5.1                       1_gnu    defaults
addict                    2.4.0                    pypi_0    pypi
antlr-python-runtime      4.9.3              pyhd8ed1ab_1    conda-forge
asttokens                 2.4.0              pyhd8ed1ab_0    conda-forge
backcall                  0.2.0              pyh9f0ad1d_0    conda-forge
backports                 1.0                pyhd8ed1ab_3    conda-forge
backports.functools_lru_cache 1.6.5              pyhd8ed1ab_0    conda-forge
blas                      1.0                         mkl    defaults
bottleneck                1.3.5            py39h7deecbd_0    defaults
brotlipy                  0.7.0           py39h27cfd23_1003    defaults
bzip2                     1.0.8                h7b6447c_0    defaults
ca-certificates           2023.08.22           h06a4308_0    defaults
certifi                   2023.7.22        py39h06a4308_0    defaults
cffi                      1.15.1           py39h5eee18b_3    defaults
charset-normalizer        2.0.4              pyhd3eb1b0_0    defaults
cloudpickle               2.2.1                    pypi_0    pypi
comm                      0.1.4              pyhd8ed1ab_0    conda-forge
contourpy                 1.1.1                    pypi_0    pypi
cryptography              41.0.3           py39hdda0065_0    defaults
cuda-cudart               11.7.99                       0    nvidia
cuda-cupti                11.7.101                      0    nvidia
cuda-libraries            11.7.1                        0    nvidia
cuda-nvrtc                11.7.99                       0    nvidia
cuda-nvtx                 11.7.91                       0    nvidia
cuda-runtime              11.7.1                        0    nvidia
cycler                    0.11.0                   pypi_0    pypi
dataclasses               0.8                pyh6d0b6a4_7    defaults
debugpy                   1.6.7            py39h6a678d5_0    defaults
decorator                 5.1.1              pyhd8ed1ab_0    conda-forge
entrypoints               0.4                pyhd8ed1ab_0    conda-forge
exceptiongroup            1.1.3              pyhd8ed1ab_0    conda-forge
executing                 1.2.0              pyhd8ed1ab_0    conda-forge
ffmpeg                    4.2.2                h20bf706_0    defaults
filelock                  3.9.0            py39h06a4308_0    defaults
fonttools                 4.42.1                   pypi_0    pypi
freetype                  2.12.1               h4a9f257_0    defaults
fvcore                    0.1.5.post20221221    pyhd8ed1ab_0    conda-forge
giflib                    5.2.1                h5eee18b_3    defaults
gmp                       6.2.1                h295c915_3    defaults
gnutls                    3.6.15               he1e5248_0    defaults
idna                      3.4              py39h06a4308_0    defaults
importlib-metadata        6.8.0                    pypi_0    pypi
importlib-resources       6.1.0                    pypi_0    pypi
intel-openmp              2023.1.0         hdb19cb5_46305    defaults
iopath                    0.1.9              pyhd8ed1ab_0    conda-forge
ipykernel                 6.25.2             pyh2140261_0    conda-forge
ipython                   8.15.0             pyh0d859eb_0    conda-forge
jedi                      0.19.0             pyhd8ed1ab_0    conda-forge
jinja2                    3.1.2            py39h06a4308_0    defaults
jpeg                      9e                   h5eee18b_1    defaults
jupyter_client            7.3.4              pyhd8ed1ab_0    conda-forge
jupyter_core              4.12.0           py39hf3d152e_0    conda-forge
kiwisolver                1.4.5                    pypi_0    pypi
lame                      3.100                h7b6447c_0    defaults
lcms2                     2.12                 h3be6417_0    defaults
ld_impl_linux-64          2.38                 h1181459_1    defaults
lerc                      3.0                  h295c915_0    defaults
libcublas                 11.10.3.66                    0    nvidia
libcufft                  10.7.2.124           h4fbf590_0    nvidia
libcufile                 1.7.2.10                      0    nvidia
libcurand                 10.3.3.141                    0    nvidia
libcusolver               11.4.0.1                      0    nvidia
libcusparse               11.7.4.91                     0    nvidia
libdeflate                1.17                 h5eee18b_0    defaults
libffi                    3.4.4                h6a678d5_0    defaults
libgcc-ng                 11.2.0               h1234567_1    defaults
libgomp                   11.2.0               h1234567_1    defaults
libidn2                   2.3.4                h5eee18b_0    defaults
libnpp                    11.7.4.75                     0    nvidia
libnvjpeg                 11.8.0.2                      0    nvidia
libopus                   1.3.1                h7b6447c_0    defaults
libpng                    1.6.39               h5eee18b_0    defaults
libsodium                 1.0.18               h36c2ea0_1    conda-forge
libstdcxx-ng              11.2.0               h1234567_1    defaults
libtasn1                  4.19.0               h5eee18b_0    defaults
libtiff                   4.5.1                h6a678d5_0    defaults
libunistring              0.9.10               h27cfd23_0    defaults
libvpx                    1.7.0                h439df22_0    defaults
libwebp                   1.3.2                h11a3e52_0    defaults
libwebp-base              1.3.2                h5eee18b_0    defaults
lz4-c                     1.9.4                h6a678d5_0    defaults
markupsafe                2.1.1            py39h7f8727e_0    defaults
matplotlib                3.8.0                    pypi_0    pypi
matplotlib-inline         0.1.6              pyhd8ed1ab_0    conda-forge
mkl                       2023.1.0         h213fc3f_46343    defaults
mkl-service               2.4.0            py39h5eee18b_1    defaults
mkl_fft                   1.3.8            py39h5eee18b_0    defaults
mkl_random                1.2.4            py39hdb19cb5_0    defaults
mmcls                     0.25.0                   pypi_0    pypi
mmcv-full                 1.5.0                    pypi_0    pypi
mmsegmentation            0.27.0                   pypi_0    pypi
mpmath                    1.3.0            py39h06a4308_0    defaults
mypy-extensions           1.0.0                    pypi_0    pypi
ncurses                   6.4                  h6a678d5_0    defaults
nest-asyncio              1.5.6              pyhd8ed1ab_0    conda-forge
nettle                    3.7.3                hbbd107a_1    defaults
networkx                  3.1              py39h06a4308_0    defaults
numexpr                   2.8.4            py39hc78ab66_1    defaults
numpy                     1.25.2           py39h5f9d8c6_0    defaults
numpy-base                1.25.2           py39hb5e798b_0    defaults
omegaconf                 2.3.0              pyhd8ed1ab_0    conda-forge
opencv-python             4.8.0.76                 pypi_0    pypi
openh264                  2.1.1                h4ff587b_0    defaults
openssl                   3.0.11               h7f8727e_2    defaults
packaging                 23.1             py39h06a4308_0    defaults
pandas                    2.0.3            py39h1128e8f_0    defaults
parso                     0.8.3              pyhd8ed1ab_0    conda-forge
pexpect                   4.8.0              pyh1a96a4e_2    conda-forge
pickleshare               0.7.5                   py_1003    conda-forge
pillow                    9.4.0            py39h6a678d5_1    defaults
pip                       23.2.1           py39h06a4308_0    defaults
platformdirs              3.10.0                   pypi_0    pypi
portalocker               2.3.0            py39h06a4308_1    defaults
prettytable               3.9.0                    pypi_0    pypi
prompt-toolkit            3.0.39             pyha770c72_0    conda-forge
prompt_toolkit            3.0.39               hd8ed1ab_0    conda-forge
psutil                    5.9.0            py39h5eee18b_0    defaults
ptyprocess                0.7.0              pyhd3deb0d_0    conda-forge
pure_eval                 0.2.2              pyhd8ed1ab_0    conda-forge
pycparser                 2.21               pyhd3eb1b0_0    defaults
pygments                  2.16.1             pyhd8ed1ab_0    conda-forge
pyopenssl                 23.2.0           py39h06a4308_0    defaults
pyparsing                 3.1.1                    pypi_0    pypi
pyre-extensions           0.0.23                   pypi_0    pypi
pysocks                   1.7.1            py39h06a4308_0    defaults
python                    3.9.18               h955ad1f_0    defaults
python-dateutil           2.8.2              pyhd8ed1ab_0    conda-forge
python-tzdata             2023.3             pyhd3eb1b0_0    defaults
python_abi                3.9                      2_cp39    conda-forge
pytorch                   2.0.0           py3.9_cuda11.7_cudnn8.5.0_0    pytorch
pytorch-cuda              11.7                 h778d358_5    pytorch
pytorch-mutex             1.0                        cuda    pytorch
pytz                      2023.3.post1     py39h06a4308_0    defaults
pyyaml                    6.0              py39h5eee18b_1    defaults
pyzmq                     25.1.0           py39h6a678d5_0    defaults
readline                  8.2                  h5eee18b_0    defaults
requests                  2.31.0           py39h06a4308_0    defaults
setuptools                68.0.0           py39h06a4308_0    defaults
six                       1.16.0             pyh6c4a22f_0    conda-forge
sqlite                    3.41.2               h5eee18b_0    defaults
stack_data                0.6.2              pyhd8ed1ab_0    conda-forge
submitit                  1.4.6                    pypi_0    pypi
sympy                     1.12               pyh04b8f61_3    conda-forge
tabulate                  0.8.10           py39h06a4308_0    defaults
tbb                       2021.8.0             hdb19cb5_0    defaults
termcolor                 2.1.0            py39h06a4308_0    defaults
tk                        8.6.12               h1ccaba5_0    defaults
tomli                     2.0.1                    pypi_0    pypi
torchmetrics              0.10.3             pyhd8ed1ab_0    conda-forge
torchtriton               2.0.0                      py39    pytorch
torchvision               0.15.0               py39_cu117    pytorch
tornado                   6.1              py39hb9d737c_3    conda-forge
tqdm                      4.65.0           py39hb070fc8_0    defaults
traitlets                 5.10.0             pyhd8ed1ab_0    conda-forge
typing-inspect            0.9.0                    pypi_0    pypi
typing_extensions         4.7.1            py39h06a4308_0    defaults
tzdata                    2023c                h04d1e81_0    defaults
urllib3                   1.26.16          py39h06a4308_0    defaults
wcwidth                   0.2.6              pyhd8ed1ab_0    conda-forge
wheel                     0.38.4           py39h06a4308_0    defaults
x264                      1!157.20191217       h7b6447c_0    defaults
xformers                  0.0.18                   pypi_0    pypi
xz                        5.4.2                h5eee18b_0    defaults
yacs                      0.1.6              pyhd3eb1b0_1    defaults
yaml                      0.2.5                h7b6447c_0    defaults
yapf                      0.40.1                   pypi_0    pypi
zeromq                    4.3.4                h9c3ff4c_1    conda-forge
zipp                      3.17.0                   pypi_0    pypi
zlib                      1.2.13               h5eee18b_0    defaults
zstd                      1.5.5                hc292b87_0    defaults

NVIDIA output：

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 520.61.05    Driver Version: 520.61.05    CUDA Version: 11.8     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla V100-SXM2...  Off  | 00000000:2D:00.0 Off |                    0 |
| N/A   46C    P0    73W / 300W |  28395MiB / 32768MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  Tesla V100-SXM2...  Off  | 00000000:32:00.0 Off |                    0 |
| N/A   47C    P0    70W / 300W |  28411MiB / 32768MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   2  Tesla V100-SXM2...  Off  | 00000000:5B:00.0 Off |                    0 |
| N/A   48C    P0    86W / 300W |  28459MiB / 32768MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   3  Tesla V100-SXM2...  Off  | 00000000:5F:00.0 Off |                    0 |
| N/A   45C    P0    69W / 300W |  29639MiB / 32768MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   4  Tesla V100-SXM2...  Off  | 00000000:B5:00.0 Off |                    0 |
| N/A   49C    P0    68W / 300W |  28431MiB / 32768MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   5  Tesla V100-SXM2...  Off  | 00000000:BE:00.0 Off |                    0 |
| N/A   45C    P0    69W / 300W |  29399MiB / 32768MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   6  Tesla V100-SXM2...  Off  | 00000000:DF:00.0 Off |                    0 |
| N/A   49C    P0    74W / 300W |  29659MiB / 32768MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   7  Tesla V100-SXM2...  Off  | 00000000:E7:00.0 Off |                    0 |
| N/A   49C    P0    72W / 300W |  29635MiB / 32768MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
bdice commented 1 year ago

@chaoer It seems like your environment (Python 3.9 / CUDA 11.8 / Ubuntu 20.04) should be supported by current RAPIDS versions. I didn't see a traceback with the errors you saw from your comment above, though you mentioned network errors. You might be able to try using conda packages or Docker containers. Feel free to join the RAPIDS Slack (https://rapids.ai/slack-invite) and message there if you'd like to diagnose this together in more detail.

chaoer commented 1 year ago

@bdice thanks for your help. It's indeed a network error, as I successfully installed it on another server with different network settings.

babaduke7 commented 11 months ago

Hello everyone,

I have the same issue, I am trying to install RAPIDS on google colab, I checked and I'm using the T4 GPU (I tried with other GPUs as well) image

My python version seems to be OK image

But I am still getting this error, can someone help me please ? tempsnip

Sorry to bother but I really can't find to problem on my own

Thank you for your attention.

oferw-xpz commented 11 months ago

Hi guys,

Same over here.... cuml librry used to work up untill few days ago and now it breaks. Any help or idea would be appreciated.

  1. attempt to install: image

  2. Python and os: image

  3. !nvidia-smi: image

Thanks for any help,

-Ofer

raydouglass commented 11 months ago

Apologies for the issues installing cuml! We are in the middle of releasing RAPIDS v23.12 (including cuml) and things aren't quite working just yet! You can use v23.10 in the meantime.

I have the same issue, I am trying to install RAPIDS on google colab, I checked and I'm using the T4 GPU (I tried with other GPUs as well)

@babaduke7 https://github.com/rapidsai-community/rapidsai-csp-utils/pull/84 should fix this issue for you by using v23.10. Please try again!

Same over here.... cuml librry used to work up untill few days ago and now it breaks. Any help or idea would be appreciated.

@oferw-xpz You can try using v23.10 like pip install --no-cache-dir --extra-index-url https://pypi.nvidia.com 'cuml-cu11==23.10.*'

oferw-xpz commented 11 months ago

Many thanks... works like a charm 🙏

On Mon, Dec 11, 2023 at 10:44 PM babaduke7 @.***> wrote:

thank you, it worked for me

— Reply to this email directly, view it on GitHub https://github.com/rapidsai/cuml/issues/5237#issuecomment-1850859016, or unsubscribe https://github.com/notifications/unsubscribe-auth/BCWQHDTPWK2YF6DAQXGE7GLYI5WCZAVCNFSM6AAAAAAU623QOKVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTQNJQHA2TSMBRGY . You are receiving this because you were mentioned.Message ID: @.***>

Bersk91 commented 10 months ago

Sorry to reopen, but was not sure where to ask. I am having issues with the installation of cuml, but from what I understand it might be related to my environment installation versions, so I wanted to confirm if upgrading is the only thing I could do.

Environment details: Python 3.8.10 (from the university, so it is hard for me to make the upgrade as I have to request it) Linux dl-machine 5.4.0-146-generic #163-Ubuntu SMP Fri Mar 17 18:26:02 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux NVIDIA-SMI 525.85.12 Driver Version: 525.85.12 CUDA Version: 12.0

Is Python 3.8 only supported for cudf-cu11?

Thanks in advance

bdice commented 10 months ago

@Bersk91 Python 3.8 support was dropped in RAPIDS 23.06. https://docs.rapids.ai/notices/rsn0029/

RAPIDS currently supports Python 3.9 and 3.10. Please consult https://docs.rapids.ai/install for the latest installation information, system requirements, and platform support.

Sometimes it is possible to install a conda environment that you control on university HPC clusters, such as into a home directory. That could allow you to get a newer Python version. This guide is a little outdated but covers the main ideas: https://rabernat.medium.com/custom-conda-environments-for-data-science-on-hpc-clusters-32d58c63aa95 I searched online for "installing conda on hpc cluster" and found several more guides. Hope that helps.

alif-munim commented 9 months ago

Hello everyone,

I'm still facing this issue on a Linux system despite trying both Python 3.9 and Python 3.10

$ pip install --no-cache-dir --extra-index-url https://pypi.nvidia.com 'cuml-cu11==23.10.*'
Defaulting to user installation because normal site-packages is not writeable
Looking in indexes: https://pypi.org/simple, https://pypi.nvidia.com
Looking in links: /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo2020/avx2, /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/avx2, /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo2020/generic, /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/gentoo/generic, /cvmfs/soft.computecanada.ca/custom/python/wheelhouse/generic
Collecting cuml-cu11==23.10.*
  Downloading cuml-cu11-23.10.0.tar.gz (6.8 kB)
  Preparing metadata (setup.py) ... error
  error: subprocess-exited-with-error

  × python setup.py egg_info did not run successfully.
  │ exit code: 1
  ╰─> [16 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-install-p4a44k3u/cuml-cu11_409cf69ac8f24629a1ad58b782afdc08/setup.py", line 137, in <module>
          raise RuntimeError(open("ERROR.txt", "r").read())
      RuntimeError:
      ###########################################################################################
      The package you are trying to install is only a placeholder project on PyPI.org repository.
      This package is hosted on NVIDIA Python Package Index.

      This package can be installed as:
  $ pip install --no-cache-dir --extra-index-url https://pypi.nvidia.com cuml-cu11
  ```
  ###########################################################################################

  [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.


Here is the output from nvidia-smi:

$ nvidia-smi
+---------------------------------------------------------------------------------------+ | NVIDIA-SMI 530.30.02 Driver Version: 530.30.02 CUDA Version: 12.1 | |-----------------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+======================+======================| | 0 Tesla V100-SXM2-32GB On | 00000000:18:00.0 Off | 0 | | N/A 33C P0 41W / 300W| 3MiB / 32768MiB | 0% Default | | | | N/A | +-----------------------------------------+----------------------+----------------------+ | 1 Tesla V100-SXM2-32GB On | 00000000:3B:00.0 Off | 0 | | N/A 33C P0 41W / 300W| 3MiB / 32768MiB | 0% Default | | | | N/A | +-----------------------------------------+----------------------+----------------------+ | 2 Tesla V100-SXM2-32GB On | 00000000:86:00.0 Off | 0 | | N/A 35C P0 41W / 300W| 3MiB / 32768MiB | 0% Default | | | | N/A | +-----------------------------------------+----------------------+----------------------+ | 3 Tesla V100-SXM2-32GB On | 00000000:AF:00.0 Off | 0 | | N/A 35C P0 42W / 300W| 3MiB / 32768MiB | 0% Default | | | | N/A | +-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=======================================================================================| | No running processes found | +---------------------------------------------------------------------------------------+

bdice commented 9 months ago

@alif-munim Can you share the output of each of these commands? I'm interested in getting to the bottom of this, so we can better troubleshoot user issues like this in the future.

  1. python -VV (extra verbosity about your Python version and build)
  2. pip -V (get the pip version)
  3. uname -a (to get kernel/CPU information)
  4. ldconfig -V (to get your system's glibc version)
  5. cat /etc/os-release (or cat /etc/lsb-release or some similar source of information about your OS version)
luccachiang commented 7 months ago

According to PyPI https://pypi.org/project/cuml-cu11/#history, it has a requirement python >= 3.9. In one conda env, I successfully installed it with python 3.10.14. However, in another with python 3.8.18 I failed.

VictorWylde commented 6 months ago

In order to install cuml_cu11-23.4.1, enter “https://pypi.nvidia.com”, then you need download and install the following installation packages in order. If there are other errors, continue downloading and installing:

-ptxcompiler-cu11-0.8.1. post1 -cubinlinker cu11-0.3.0.post2 -rmm-cu11-23.4.1 -cudf_cu11-23.4.1 -dask_cudf_cu11-23.4.1 -pylibraft_cu11-23.4.1 -ucx_py_cu11-0.31.1 -raft_dask_cu11-23.4.1 -cuml_cu11-23.4.1

gunjanmimo commented 4 months ago

I updated my python 3.8 to 3.9, and the problem was solved!

esmnralican commented 4 weeks ago

I am working on Windows and want to download dinov2. But I after executed this code "pip install --extra-index-url https://pypi.nvidia.com/ cuml-cu11" , I am getting this error:

The installation of cuml-cu11 for version 24.8.0 failed. 

  This is a special placeholder package which downloads a real wheel package
  from https://pypi.nvidia.com/. If https://pypi.nvidia.com/ is not reachable, we
  cannot download the real wheel file to install.

  You might try installing this package via

$ pip install --extra-index-url https://pypi.nvidia.com/ cuml-cu11

  Here is some debug information about your platform to include in any bug
  report:

  Python Version: CPython 3.9.17
  Operating System: Windows 10
  CPU Architecture: AMD64
  Driver Version: 516.01
  CUDA Version: 11.7

Is it possible to work in Windows with DINO?

vyasr commented 3 weeks ago

No, unfortunately we do not support Windows. Our recommended approach for Windows use is via WSL. You can find information on supported platforms here.