Charlie Parker
Reputation: 5201
Why is pip not letting me install torch==1.9.1+cu111 in a new conda env when I have another conda env that has exactly that version?
When I run the pip install in the new conda env:
(base) brando9~ $ pip install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
Looking in links: https://download.pytorch.org/whl/torch_stable.html
ERROR: Could not find a version that satisfies the requirement torch==1.9.1+cu111 (from versions: 1.11.0, 1.11.0+cpu, 1.11.0+cu102, 1.11.0+cu113, 1.11.0+cu115, 1.11.0+rocm4.3.1, 1.11.0+rocm4.5.2, 1.12.0, 1.12.0+cpu, 1.12.0+cu102, 1.12.0+cu113, 1.12.0+cu116, 1.12.0+rocm5.0, 1.12.0+rocm5.1.1, 1.12.1, 1.12.1+cpu, 1.12.1+cu102, 1.12.1+cu113, 1.12.1+cu116, 1.12.1+rocm5.0, 1.12.1+rocm5.1.1, 1.13.0, 1.13.0+cpu, 1.13.0+cu116, 1.13.0+cu117, 1.13.0+cu117.with.pypi.cudnn, 1.13.0+rocm5.1.1, 1.13.0+rocm5.2, 1.13.1, 1.13.1+cpu, 1.13.1+cu116, 1.13.1+cu117, 1.13.1+cu117.with.pypi.cudnn, 1.13.1+rocm5.1.1, 1.13.1+rocm5.2)
ERROR: No matching distribution found for torch==1.9.1+cu111
the other env with that pytorch version:
(metalearning3.9) [pzy2@vision-submit ~]$ pip list
Package Version Location
---------------------------------- -------------------- ------------------
absl-py 1.0.0
aiohttp 3.8.3
aiosignal 1.3.1
alabaster 0.7.12
anaconda-client 1.9.0
anaconda-project 0.10.1
antlr4-python3-runtime 4.8
anyio 2.2.0
appdirs 1.4.4
argcomplete 2.0.0
argh 0.26.2
argon2-cffi 20.1.0
arrow 0.13.1
asn1crypto 1.4.0
astroid 2.6.6
astropy 4.3.1
asttokens 2.0.7
astunparse 1.6.3
async-generator 1.10
async-timeout 4.0.2
atomicwrites 1.4.0
attrs 21.2.0
autopep8 1.5.7
Babel 2.9.1
backcall 0.2.0
backports.shutil-get-terminal-size 1.0.0
beautifulsoup4 4.10.0
binaryornot 0.4.4
bitarray 2.3.0
bkcharts 0.2
black 19.10b0
bleach 4.0.0
bokeh 2.4.1
boto 2.49.0
Bottleneck 1.3.2
brotlipy 0.7.0
cached-property 1.5.2
cachetools 5.0.0
certifi 2021.10.8
cffi 1.14.6
chardet 4.0.0
charset-normalizer 2.0.4
cherry-rl 0.1.4
click 8.0.3
cloudpickle 2.0.0
clyent 1.2.2
colorama 0.4.4
conda 4.12.0
conda-content-trust 0+unknown
conda-pack 0.6.0
conda-package-handling 1.8.0
conda-token 0.3.0
configparser 5.3.0
contextlib2 0.6.0.post1
cookiecutter 1.7.2
crc32c 2.3
crcmod 1.7
cryptography 3.4.8
cycler 0.10.0
Cython 0.29.24
cytoolz 0.11.0
daal4py 2021.3.0
dask 2021.10.0
debugpy 1.4.1
decorator 5.1.0
defusedxml 0.7.1
diff-match-patch 20200713
dill 0.3.4
distributed 2021.10.0
docker-pycreds 0.4.0
docutils 0.17.1
entrypoints 0.3
et-xmlfile 1.1.0
executing 0.9.1
fairseq 0.12.2 /home/pzy2/fairseq
fastcache 1.1.0
fastcluster 1.2.6
fasteners 0.17.3
filelock 3.3.1
flake8 3.9.2
Flask 1.1.2
flatbuffers 2.0.7
fonttools 4.25.0
frozenlist 1.3.0
fsspec 2021.8.1
gast 0.4.0
gcs-oauth2-boto-plugin 3.0
gevent 21.8.0
gitdb 4.0.9
GitPython 3.1.27
glob2 0.7
gmpy2 2.0.8
google-apitools 0.5.32
google-auth 2.6.3
google-auth-oauthlib 0.4.6
google-pasta 0.2.0
google-reauth 0.1.1
gql 0.2.0
graphql-core 1.1
greenlet 1.1.1
grpcio 1.44.0
gsutil 5.9
gym 0.22.0
gym-notices 0.0.6
h5py 3.3.0
HeapDict 1.0.1
higher 0.2.1
html5lib 1.1
httplib2 0.20.4
huggingface-hub 0.5.1
hydra-core 1.0.7
idna 3.2
imagecodecs 2021.8.26
imageio 2.9.0
imagesize 1.2.0
importlib-metadata 4.12.0
inflection 0.5.1
iniconfig 1.1.1
intervaltree 3.1.0
ipykernel 6.4.1
ipython 7.29.0
ipython-genutils 0.2.0
ipywidgets 7.6.5
isort 5.9.3
itsdangerous 2.0.1
jdcal 1.4.1
jedi 0.18.0
jeepney 0.7.1
Jinja2 2.11.3
jinja2-time 0.2.0
joblib 1.1.0
json5 0.9.6
jsonschema 3.2.0
jupyter 1.0.0
jupyter-client 6.1.12
jupyter-console 6.4.0
jupyter-core 4.8.1
jupyter-server 1.4.1
jupyterlab 3.2.1
jupyterlab-pygments 0.1.2
jupyterlab-server 2.8.2
jupyterlab-widgets 1.0.0
keras 2.10.0
Keras-Preprocessing 1.1.2
keyring 23.1.0
kiwisolver 1.3.1
lark-parser 0.12.0
lazy-object-proxy 1.6.0
learn2learn 0.1.7
libarchive-c 2.9
libclang 14.0.6
littleutils 0.2.2
llvmlite 0.37.0
locket 0.2.1
loguru 0.6.0
lxml 4.6.3
Markdown 3.3.6
MarkupSafe 1.1.1
matplotlib 3.4.3
matplotlib-inline 0.1.2
mccabe 0.6.1
mistune 0.8.4
mkl-fft 1.3.1
mkl-random 1.2.2
mkl-service 2.4.0
mock 4.0.3
monotonic 1.6
more-itertools 8.10.0
mpmath 1.2.1
msgpack 1.0.2
multidict 6.0.2
multipledispatch 0.6.0
munkres 1.1.4
mypy-extensions 0.4.3
nbclassic 0.2.6
nbclient 0.5.3
nbconvert 6.1.0
nbformat 5.1.3
nest-asyncio 1.5.1
networkx 2.6.3
nltk 3.6.5
nose 1.3.7
notebook 6.4.5
numba 0.54.1
numexpr 2.7.3
numpy 1.20.3
numpydoc 1.1.0
nvidia-ml-py3 7.352.0
nvidia-smi 0.1.3
oauth2client 4.1.3
oauthlib 3.2.0
olefile 0.46
omegaconf 2.0.6
opencv-python 4.6.0.66
openpyxl 3.0.9
opt-einsum 3.3.0
ordered-set 4.1.0
packaging 21.0
pandas 1.3.4
pandocfilters 1.4.3
parso 0.8.2
partd 1.2.0
path 16.0.0
pathlib2 2.3.6
pathspec 0.7.0
pathtools 0.1.2
patsy 0.5.2
pep8 1.7.1
pexpect 4.8.0
pickleshare 0.7.5
Pillow 8.4.0
pip 22.2.2
pkginfo 1.7.1
plotly 5.7.0
pluggy 0.13.1
ply 3.11
portalocker 2.5.1
poyo 0.5.0
progressbar2 4.0.0
prometheus-client 0.11.0
promise 2.3
prompt-toolkit 3.0.20
protobuf 3.19.6
psutil 5.8.0
ptyprocess 0.7.0
py 1.10.0
pyasn1 0.4.8
pyasn1-modules 0.2.8
pycodestyle 2.7.0
pycosat 0.6.3
pycparser 2.20
pycurl 7.44.1
pydocstyle 6.1.1
pyerfa 2.0.0
pyflakes 2.3.1
Pygments 2.10.0
pylint 2.9.6
pyls-spyder 0.4.0
pyodbc 4.0.0-unsupported
pyOpenSSL 21.0.0
pyparsing 3.0.4
pyrsistent 0.18.0
PySocks 1.7.1
pytest 6.2.4
python-dateutil 2.8.2
python-lsp-black 1.0.0
python-lsp-jsonrpc 1.0.0
python-lsp-server 1.2.4
python-slugify 5.0.2
python-utils 3.1.0
pytz 2021.3
pyu2f 0.1.5
PyWavelets 1.1.1
pyxdg 0.27
PyYAML 6.0
pyzmq 22.2.1
QDarkStyle 3.0.2
qpth 0.0.15
qstylizer 0.1.10
QtAwesome 1.0.2
qtconsole 5.1.1
QtPy 1.10.0
regex 2021.8.3
requests 2.26.0
requests-oauthlib 1.3.1
retry-decorator 1.1.1
rope 0.19.0
rsa 4.7.2
Rtree 0.9.7
ruamel-yaml-conda 0.15.100
sacrebleu 2.2.0
sacremoses 0.0.49
scikit-image 0.18.3
scikit-learn 0.24.2
scikit-learn-intelex 2021.20210714.170444
scipy 1.7.1
seaborn 0.11.2
SecretStorage 3.3.1
Send2Trash 1.8.0
sentry-sdk 1.5.9
setproctitle 1.2.2
setuptools 58.0.4
shortuuid 1.0.8
simplegeneric 0.8.1
singledispatch 3.7.0
sip 4.19.13
six 1.16.0
sklearn 0.0
smmap 5.0.0
sniffio 1.2.0
snowballstemmer 2.1.0
sorcery 0.2.2
sortedcollections 2.1.0
sortedcontainers 2.4.0
soupsieve 2.2.1
Sphinx 4.2.0
sphinxcontrib-applehelp 1.0.2
sphinxcontrib-devhelp 1.0.2
sphinxcontrib-htmlhelp 2.0.0
sphinxcontrib-jsmath 1.0.1
sphinxcontrib-qthelp 1.0.3
sphinxcontrib-serializinghtml 1.1.5
sphinxcontrib-websupport 1.2.4
spyder 5.1.5
spyder-kernels 2.1.3
SQLAlchemy 1.4.22
statsmodels 0.12.2
subprocess32 3.5.4
sympy 1.9
tables 3.6.1
TBB 0.2
tblib 1.7.0
tensorboard 2.10.1
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
tensorflow-estimator 2.10.0
tensorflow-gpu 2.10.1
tensorflow-io-gcs-filesystem 0.27.0
termcolor 2.0.1
terminado 0.9.4
testpath 0.5.0
text-unidecode 1.3
textdistance 4.2.1
tfrecord 1.14.1
threadpoolctl 2.2.0
three-merge 0.1.1
tifffile 2021.7.2
timm 0.6.11
tinycss 0.4
tokenizers 0.11.6
toml 0.10.2
toolz 0.11.1
torch 1.9.1+cu111
torchaudio 0.9.1
torchmeta 1.8.0
torchtext 0.10.1
torchvision 0.10.1+cu111
tornado 6.1
tqdm 4.62.3
traitlets 5.1.0
transformers 4.18.0
typed-ast 1.4.3
typing-extensions 3.10.0.2
ujson 4.0.2
ultimate-anatome 0.1.1
ultimate-aws-cv-task2vec 0.0.1
unicodecsv 0.14.1
Unidecode 1.2.0
urllib3 1.26.7
wandb 0.13.5
watchdog 2.1.3
wcwidth 0.2.5
webencodings 0.5.1
Werkzeug 2.0.2
wheel 0.37.0
whichcraft 0.6.1
widgetsnbextension 3.5.1
wrapt 1.12.1
wurlitzer 2.1.1
xlrd 2.0.1
XlsxWriter 3.0.1
xlwt 1.3.0
yapf 0.31.0
yarl 1.7.2
zict 2.0.0
zipp 3.6.0
zope.event 4.5.0
zope.interface 5.4.0
WARNING: You are using pip version 22.2.2; however, version 22.3.1 is available.
You should consider upgrading via the '/home/pzy2/miniconda3/envs/metalearning3.9/bin/python -m pip install --upgrade pip' command.
(metalearning3.9) [pzy2@vision-submit ~]$
I asked a related question because I can't install pytorch with cuda with conda, see details here: why does conda install the pytorch CPU version despite me putting explicitly to download the cuda toolkit version?
I think this works:
# -- Install PyTorch sometimes requires more careful versioning due to cuda, ref: official install instruction https://pytorch.org/get-started/previous-versions/
# you need python 3.9 for torch version 1.9.1 to work, due to torchmeta==1.8.0 requirement
if ! python -V 2>&1 | grep -q 'Python 3\.9'; then
echo "Error: Python 3.9 is required!"
exit 1
fi
pip install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
Upvotes: 3
Views: 13839
Answers (2)
Charlie Parker
Reputation: 5201
To install pytorch 1.9.1cu11 you need python 3.9 to be avaiable. Added that to my bash install.sh
# - create conda env
conda create -n metalearning_gpu python=3.9
conda activate metalearning_gpu
## conda remove --name metalearning_gpu --all
# - make sure pip is up to date
which python
pip install --upgrade pip
pip3 install --upgrade pip
which pip
which pip3
# -- Install PyTorch sometimes requires more careful versioning due to cuda, ref: official install instruction https://pytorch.org/get-started/previous-versions/
# you need python 3.9 for torch version 1.9.1 to work, due to torchmeta==1.8.0 requirement
if ! python -V 2>&1 | grep -q 'Python 3\.9'; then
echo "Error: Python 3.9 is required!"
exit 1
fi
pip install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
Upvotes: 1
Kraigolas
Reputation: 5560
From looking at the link you've provided, I can see
cu111/torch-1.9.1%2Bcu111-cp36-cp36m-linux_x86_64.whl
cu111/torch-1.9.1%2Bcu111-cp36-cp36m-win_amd64.whl
cu111/torch-1.9.1%2Bcu111-cp37-cp37m-linux_x86_64.whl
cu111/torch-1.9.1%2Bcu111-cp37-cp37m-win_amd64.whl
cu111/torch-1.9.1%2Bcu111-cp38-cp38-linux_x86_64.whl
cu111/torch-1.9.1%2Bcu111-cp38-cp38-win_amd64.whl
cu111/torch-1.9.1%2Bcu111-cp39-cp39-linux_x86_64.whl
cu111/torch-1.9.1%2Bcu111-cp39-cp39-win_amd64.whl
cp39 means Python version 3.9. Notice there is no support for 3.10 or 3.11. In your new environment, you probably are running a newer version of Python, whereas in the other environment you have Python 3.6, 3.7, 3.8, or 3.9
Upvotes: 3
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