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Error in [conda install xformers -c xformers/label/dev] #1084
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good heart people help help me😢 |
Any specific reason you need the |
hi, thanks for reply. I want to train [StableSR] project, and it needs pytorch1.12.1+cuda11.7 . StableSR Official recommended use [conda install xformers -c xformers/label/dev] to install xformers, but i failed. I also tried [pip install xformers==0.0.16/0.0.16rc425], |
I don't know off the top of my head, but PyTorch 1.12 is quite ancient, I don't know if any of our current packages is still compatible with that. I'd say that your best bet is to just ask conda to find out for you: if you ask it to install |
BTW I ran that command and it looks like xFormers 0.0.22 should work for you. |
Very lucky to have your help! I'll try again later! |
🐛 Bug
Command
conda install xformers -c xformers/label/dev
To Reproduce
Steps to reproduce the behavior:
1.conda install xformers -c xformers/label/dev
2.Collecting package metadata (current_repodata.json): failed
3.An unexpected error has occurred. Conda has prepared the above report.
Collecting package metadata (current_repodata.json): failed
/home/test/anaconda3/bin/conda install xformers -c xformers/label/dev
environment variables:
CIO_TEST=
CONDA_DEFAULT_ENV=try
CONDA_EXE=/home/test/anaconda3/bin/conda
CONDA_PREFIX=/home/test/anaconda3/envs/try
CONDA_PREFIX_1=/home/test/anaconda3
CONDA_PREFIX_2=/home/test/anaconda3/envs/stablesr1
CONDA_PROMPT_MODIFIER=(try)
CONDA_PYTHON_EXE=/home/test/anaconda3/bin/python
CONDA_ROOT=/home/test/anaconda3
CONDA_SHLVL=3
CURL_CA_BUNDLE=
LD_LIBRARY_PATH=/usr/local/ffmpeg/lib/
LD_PRELOAD=
PATH=/home/test/.local/bin:/home/test/.cargo/bin:/home/test/anaconda3/envs/
try/bin:/usr/local/ffmpeg/bin:/home/test/anaconda3/bin:/home/test/anac
onda3/condabin:/data/anaconda3/bin:/usr/local/cuda-
11.7/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:
/usr/games:/usr/local/games:/snap/bin
REQUESTS_CA_BUNDLE=
SSL_CERT_FILE=
populated config files : /home/test/.condarc
conda version : 23.3.1
conda-build version : 3.24.0
python version : 3.10.9.final.0
virtual packages : __archspec=1=x86_64
__cuda=11.7=0
__glibc=2.31=0
__linux=5.15.0=0
__unix=0=0
base environment : /home/test/anaconda3 (writable)
conda av data dir : /home/test/anaconda3/etc/conda
conda av metadata url : None
channel URLs : https://conda.anaconda.org/xformers/label/dev/linux-64
https://conda.anaconda.org/xformers/label/dev/noarch
https://repo.anaconda.com/pkgs/main/linux-64
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/r/linux-64
https://repo.anaconda.com/pkgs/r/noarch
package cache : /home/test/anaconda3/pkgs
/home/test/.conda/pkgs
envs directories : /home/test/anaconda3/envs
/home/test/.conda/envs
platform : linux-64
user-agent : conda/23.3.1 requests/2.31.0 CPython/3.10.9 Linux/5.15.0-101-generic ubuntu/20.04.2 glibc/2.31
UID:GID : 1000:1000
netrc file : /home/test/.netrc
offline mode : False
An unexpected error has occurred. Conda has prepared the above report.
Expected behavior
install successfullyEnvironment
Please copy and paste the output from the
environment collection script from PyTorch
(or fill out the checklist below manually).
You can run the script with:
# For security purposes, please check the contents of collect_env.py before running it. python -m torch.utils.collect_env
conda
,pip
, source):othersCollecting environment information...
PyTorch version: 1.12.1+cu102
Is debug build: False
CUDA used to build PyTorch: 10.2
ROCM used to build PyTorch: N/A
OS: Ubuntu 20.04.2 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: version 3.25.0
Libc version: glibc-2.31
Python version: 3.9.19 (main, May 6 2024, 19:43:03) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 11.7.64
GPU models and configuration:
GPU 0: NVIDIA GeForce RTX 3090
GPU 1: NVIDIA GeForce RTX 3090
GPU 2: NVIDIA GeForce RTX 3090
GPU 3: NVIDIA GeForce RTX 3090
Nvidia driver version: 515.48.07
cuDNN version: Probably one of the following:
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn.so.8
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_adv_train.so.8
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8
/usr/local/cuda-11.7/targets/x86_64-linux/lib/libcudnn_ops_train.so.8
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Versions of relevant libraries:
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.23.1
[pip3] open-clip-torch==2.0.2
[pip3] pytorch-lightning==1.4.2
[pip3] pytorch-metric-learning==1.7.3
[pip3] torch==1.12.1
[pip3] torchmetrics==0.6.0
[pip3] torchvision==0.13.1
[conda] blas 1.0 mkl
[conda] cudatoolkit 11.3.1 h2bc3f7f_2
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] mkl 2021.4.0 h06a4308_640
[conda] mkl-service 2.4.0 py39h7f8727e_0
[conda] mkl_fft 1.3.1 py39hd3c417c_0
[conda] mkl_random 1.2.2 py39h51133e4_0
[conda] numpy 1.23.1 py39h6c91a56_0
[conda] numpy-base 1.23.1 py39ha15fc14_0
[conda] open-clip-torch 2.0.2 pypi_0 pypi
[conda] pytorch-lightning 1.4.2 pypi_0 pypi
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torch 1.12.1 pypi_0 pypi
[conda] torchmetrics 0.6.0 pypi_0 pypi
[conda] torchvision 0.13.1 py39_cu113 pytorch
Additional context
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