為什么 pip 不允許我在新的 conda env 中安裝 torch==1.9.1+cu111 當我有另一個具有該版本的 conda env 時？
[英]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?
問題描述
當我在新的 conda 環境中運行 pip 安裝時：
(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
另一個版本為 pytorch 的環境：
(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 ~]$
我問了一個相關的問題，因為我無法使用 conda 安裝 pytorch 和 cuda，請在此處查看詳細信息： 盡管我明確下載 cuda 工具包版本，為什么 conda 安裝 pytorch CPU 版本？
我認為這有效：
# -- 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
2 個解決方案
解決方案1
2 2023-01-05 19:08:39
通過查看您提供的鏈接，我可以看到
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 表示 Python 版本 3.9。 請注意，不支持 3.10 或 3.11。 在您的新環境中，您可能正在運行更新版本的 Python，而在其他環境中，您運行的是 Python 3.6、3.7、3.8 或 3.9
解決方案2
-1
要安裝 pytorch 1.9.1cu11，您需要 python 3.9 可用。 將其添加到我的 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
適用於anaconda環境的錯誤點子版本。 使用“ conda activate”激活環境時，我該怎么做才能更正點子版本？
[英]Wrong pip version for anaconda's environments. What should I do to correct the pip version when activate a env using `conda activate`?
pycharm 中的 Pip 在 conda env 中安裝包，而不是在項目內的活動 venv 中
[英]Pip in pycharm install packages in conda env and not in active venv inside project
將 Python 包安裝到需要 Pip 的 Conda Env 時出現 ModuleNotFoundError 或 ImportError
[英]ModuleNotFoundError or ImportError When Installing Python Packages to Conda Env That Require Pip
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