当 conda 尚不支持时，如何在 Windows 上安装最新的
时间：2023-03-03
本文介绍了当 conda 尚不支持时，如何在 Windows 上安装最新的 Tensorflow(此处:2.2)?的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我在 Windows 8.1 上有 conda 4.8.3 和 Python 3.7.4.
I have conda 4.8.3 and Python 3.7.4 on Windows 8.1.
我在 conda 环境中安装了 tf 2.0.0.如何升级到 2.2.x?
I have tf 2.0.0 installed in a conda environment. How do I upgrade to 2.2.x?
或者，我如何在 conda 环境中安装 2.2.x?
Or, how do I just install 2.2.x in a conda environment?
编辑 1:pip install --upgrade tensorflow 说:要求已经是最新的:d:anaconda3envs f2libsite-packages (2.1.0) 中的 tensorflow
Edit 1: pip install --upgrade tensorflow says: Requirement already up-to-date: tensorflow in d:anaconda3envs f2libsite-packages (2.1.0)
但是tf版本还是2.0.
but tf version is still 2.0.
编辑 2:conda install tensorflow==2.2.0 说:
Edit 2: conda install tensorflow==2.2.0 says:
PackagesNotFoundError: The following packages are not available from current channels:
- 张量流==2.2.0
我确实有一些运气 这里.
编辑 3:
(tf2) D:
aydevcovid-19>conda list -n tf2
# packages in environment at D:Anaconda3envs f2:
#
# Name Version Build Channel
_anaconda_depends 2019.03 py37_0
_ipyw_jlab_nb_ext_conf 0.1.0 py37_0
_tflow_select 2.3.0 mkl
absl-py 0.9.0 pypi_0 pypi
alabaster 0.7.12 py37_0
anaconda custom py37_1
anaconda-client 1.7.2 py37_0
anaconda-navigator 1.9.7 py37_0
anaconda-project 0.8.3 py_0
asn1crypto 1.0.1 py37_0
astor 0.8.1 pypi_0 pypi
astroid 2.3.1 py37_0
astropy 3.2.1 py37he774522_0
atomicwrites 1.3.0 py37_1
attrs 19.2.0 py_0
babel 2.7.0 py_0
backcall 0.1.0 py37_0
backports 1.0 py_2
backports.functools_lru_cache 1.5 py_2
backports.os 0.1.1 py37_0
backports.shutil_get_terminal_size 1.0.0 py37_2
backports.tempfile 1.0 py_1
backports.weakref 1.0.post1 py_1
beautifulsoup4 4.8.0 py37_0
bitarray 1.0.1 py37he774522_0
bkcharts 0.2 py37_0
blas 1.0 mkl
bleach 3.1.0 py37_0
blosc 1.16.3 h7bd577a_0
bokeh 1.3.4 py37_0
boto 2.49.0 py37_0
bottleneck 1.2.1 py37h452e1ab_1
bzip2 1.0.8 he774522_0
ca-certificates 2020.1.1 0
cachetools 4.0.0 pypi_0 pypi
certifi 2019.9.11 py37_0
cffi 1.12.3 py37h7a1dbc1_0
chardet 3.0.4 py37_1003
click 7.0 py37_0
cloudpickle 1.2.2 py_0
clyent 1.2.2 py37_1
colorama 0.4.1 py37_0
comtypes 1.1.7 py37_0
conda-package-handling 1.6.0 py37h62dcd97_0
conda-verify 3.4.2 py_1
console_shortcut 0.1.1 3
contextlib2 0.6.0 py_0
cryptography 2.7 py37h7a1dbc1_0
curl 7.65.3 h2a8f88b_0
cycler 0.10.0 py37_0
cython 0.29.13 py37ha925a31_0
cytoolz 0.10.0 py37he774522_0
dask 2.5.2 py_0
dask-core 2.5.2 py_0
decorator 4.4.0 py37_1
defusedxml 0.6.0 py_0
dill 0.3.1.1 pypi_0 pypi
distributed 2.5.2 py_0
docutils 0.15.2 py37_0
entrypoints 0.3 py37_0
et_xmlfile 1.0.1 py37_0
fastcache 1.1.0 py37he774522_0
filelock 3.0.12 py_0
flask 1.1.1 py_0
freetype 2.9.1 ha9979f8_1
fsspec 0.5.2 py_0
future 0.17.1 py37_0
gast 0.2.2 pypi_0 pypi
get_terminal_size 1.0.0 h38e98db_0
gevent 1.4.0 py37he774522_0
glob2 0.7 py_0
google-auth 1.11.0 pypi_0 pypi
google-auth-oauthlib 0.4.1 pypi_0 pypi
google-pasta 0.1.8 py_0
googleapis-common-protos 1.51.0 pypi_0 pypi
greenlet 0.4.15 py37hfa6e2cd_0
grpcio 1.26.0 pypi_0 pypi
h5py 2.9.0 py37h5e291fa_0
hdf5 1.10.4 h7ebc959_0
heapdict 1.0.1 py_0
html5lib 1.0.1 py37_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha66f8fd_1
idna 2.8 py37_0
imageio 2.6.0 py37_0
imagesize 1.1.0 py37_0
importlib_metadata 0.23 py37_0
intel-openmp 2019.4 245
ipykernel 5.1.2 py37h39e3cac_0
ipython 7.8.0 py37h39e3cac_0
ipython_genutils 0.2.0 py37_0
ipywidgets 7.5.1 py_0
isort 4.3.21 py37_0
itsdangerous 1.1.0 py37_0
jdcal 1.4.1 py_0
jedi 0.15.1 py37_0
jinja2 2.10.3 py_0
joblib 0.13.2 py37_0
jpeg 9b hb83a4c4_2
json5 0.8.5 py_0
jsonschema 3.0.2 py37_0
jupyter 1.0.0 py37_7
jupyter_client 5.3.3 py37_1
jupyter_console 6.0.0 py37_0
jupyter_core 4.5.0 py_0
jupyterlab 1.1.4 pyhf63ae98_0
jupyterlab_server 1.0.6 py_0
keras 2.3.1 py37h21ff451_0 conda-forge
keras-applications 1.0.8 py_0
keras-preprocessing 1.1.0 py_1
keyring 18.0.0 py37_0
kiwisolver 1.1.0 py37ha925a31_0
krb5 1.16.1 hc04afaa_7
lazy-object-proxy 1.4.2 py37he774522_0
libarchive 3.3.3 h0643e63_5
libcurl 7.65.3 h2a8f88b_0
libgpuarray 0.7.6 hfa6e2cd_0
libiconv 1.15 h1df5818_7
liblief 0.9.0 ha925a31_2
libmklml 2019.0.5 0
libpng 1.6.37 h2a8f88b_0
libprotobuf 3.11.2 h7bd577a_0
libpython 2.1 py37_0
libsodium 1.0.16 h9d3ae62_0
libssh2 1.8.2 h7a1dbc1_0
libtiff 4.0.10 hb898794_2
libxml2 2.9.9 h464c3ec_0
libxslt 1.1.33 h579f668_0
llvmlite 0.29.0 py37ha925a31_0
locket 0.2.0 py37_1
lxml 4.4.1 py37h1350720_0
lz4-c 1.8.1.2 h2fa13f4_0
lzo 2.10 h6df0209_2
m2w64-binutils 2.25.1 5
m2w64-bzip2 1.0.6 6
m2w64-crt-git 5.0.0.4636.2595836 2
m2w64-gcc 5.3.0 6
m2w64-gcc-ada 5.3.0 6
m2w64-gcc-fortran 5.3.0 6
m2w64-gcc-libgfortran 5.3.0 6
m2w64-gcc-libs 5.3.0 7
m2w64-gcc-libs-core 5.3.0 7
m2w64-gcc-objc 5.3.0 6
m2w64-gmp 6.1.0 2
m2w64-headers-git 5.0.0.4636.c0ad18a 2
m2w64-isl 0.16.1 2
m2w64-libiconv 1.14 6
m2w64-libmangle-git 5.0.0.4509.2e5a9a2 2
m2w64-libwinpthread-git 5.0.0.4634.697f757 2
m2w64-make 4.1.2351.a80a8b8 2
m2w64-mpc 1.0.3 3
m2w64-mpfr 3.1.4 4
m2w64-pkg-config 0.29.1 2
m2w64-toolchain 5.3.0 7
m2w64-tools-git 5.0.0.4592.90b8472 2
m2w64-windows-default-manifest 6.4 3
m2w64-winpthreads-git 5.0.0.4634.697f757 2
m2w64-zlib 1.2.8 10
mako 1.1.0 py_0
markdown 3.1.1 py37_0
markupsafe 1.1.1 py37he774522_0
matplotlib 3.1.1 py37hc8f65d3_0
mccabe 0.6.1 py37_1
menuinst 1.4.16 py37he774522_0
mistune 0.8.4 py37he774522_0
mkl 2019.4 245
mkl-service 2.3.0 py37hb782905_0
mkl_fft 1.0.14 py37h14836fe_0
mkl_random 1.1.0 py37h675688f_0
mock 3.0.5 py37_0
more-itertools 7.2.0 py37_0
mpmath 1.1.0 py37_0
msgpack-python 0.6.1 py37h74a9793_1
msys2-conda-epoch 20160418 1
multipledispatch 0.6.0 py37_0
navigator-updater 0.2.1 py37_0
nbconvert 5.6.0 py37_1
nbformat 4.4.0 py37_0
networkx 2.3 py_0
nltk 3.4.5 py37_0
nose 1.3.7 py37_2
notebook 6.0.1 py37_0
numba 0.45.1 py37hf9181ef_0
numexpr 2.7.0 py37hdce8814_0
numpy 1.16.5 py37h19fb1c0_0
numpy-base 1.16.5 py37hc3f5095_0
numpydoc 0.9.1 py_0
oauthlib 3.1.0 pypi_0 pypi
olefile 0.46 py37_0
openpyxl 3.0.0 py_0
openssl 1.1.1d he774522_3
opt_einsum 3.1.0 py_0
packaging 19.2 py_0
pandas 0.25.1 pypi_0 pypi
pandoc 2.2.3.2 0
pandocfilters 1.4.2 py37_1
parso 0.5.1 py_0
partd 1.0.0 py_0
path.py 12.0.1 py_0
pathlib2 2.3.5 py37_0
patsy 0.5.1 py37_0
pep8 1.7.1 py37_0
pickleshare 0.7.5 py37_0
pillow 6.2.0 py37hdc69c19_0
pip 20.0.2 pypi_0 pypi
pkginfo 1.5.0.1 py37_0
pluggy 0.13.0 py37_0
ply 3.11 py37_0
powershell_shortcut 0.0.1 2
prometheus_client 0.7.1 py_0
promise 2.3 pypi_0 pypi
prompt_toolkit 2.0.10 py_0
protobuf 3.11.2 pypi_0 pypi
psutil 5.6.3 py37he774522_0
py 1.8.0 py37_0
py-lief 0.9.0 py37ha925a31_2
pyasn1 0.4.8 pypi_0 pypi
pyasn1-modules 0.2.8 pypi_0 pypi
pycodestyle 2.5.0 py37_0
pycosat 0.6.3 py37hfa6e2cd_0
pycparser 2.19 py37_0
pycrypto 2.6.1 py37hfa6e2cd_9
pycurl 7.43.0.3 py37h7a1dbc1_0
pyflakes 2.1.1 py37_0
pygments 2.4.2 py_0
pygpu 0.7.6 py37h452e1ab_0
pylint 2.4.2 py37_0
pyodbc 4.0.27 py37ha925a31_0
pyopenssl 19.0.0 py37_0
pyparsing 2.4.2 py_0
pyqt 5.9.2 py37h6538335_2
pyreadline 2.1 py37_1
pyrsistent 0.15.4 py37he774522_0
pysocks 1.7.1 py37_0
pytables 3.5.2 py37h1da0976_1
pytest 5.2.1 py37_0
pytest-arraydiff 0.3 py37h39e3cac_0
pytest-astropy 0.5.0 py37_0
pytest-doctestplus 0.4.0 py_0
pytest-openfiles 0.4.0 py_0
pytest-remotedata 0.3.2 py37_0
python 3.7.4 h5263a28_0
python-dateutil 2.8.0 py37_0
python-libarchive-c 2.8 py37_13
pytz 2019.3 py_0
pywavelets 1.0.3 py37h8c2d366_1
pywin32 223 py37hfa6e2cd_1
pywinpty 0.5.5 py37_1000
pyyaml 5.1.2 py37he774522_0
pyzmq 18.1.0 py37ha925a31_0
qt 5.9.7 vc14h73c81de_0
qtawesome 0.6.0 py_0
qtconsole 4.5.5 py_0
qtpy 1.9.0 py_0
requests 2.22.0 py37_0
requests-oauthlib 1.3.0 pypi_0 pypi
rope 0.14.0 py_0
rsa 4.0 pypi_0 pypi
ruamel_yaml 0.15.46 py37hfa6e2cd_0
scikit-image 0.15.0 py37ha925a31_0
scikit-learn 0.21.3 py37h6288b17_0
scipy 1.4.1 pypi_0 pypi
seaborn 0.9.0 py37_0
send2trash 1.5.0 py37_0
setuptools 41.4.0 py37_0
simplegeneric 0.8.1 py37_2
singledispatch 3.4.0.3 py37_0
sip 4.19.8 py37h6538335_0
six 1.12.0 py37_0
sklearn 0.0 pypi_0 pypi
snappy 1.1.7 h777316e_3
snowballstemmer 2.0.0 py_0
sortedcollections 1.1.2 py37_0
sortedcontainers 2.1.0 py37_0
soupsieve 1.9.3 py37_0
sphinx 2.2.0 py_0
sphinxcontrib 1.0 py37_1
sphinxcontrib-applehelp 1.0.1 py_0
sphinxcontrib-devhelp 1.0.1 py_0
sphinxcontrib-htmlhelp 1.0.2 py_0
sphinxcontrib-jsmath 1.0.1 py_0
sphinxcontrib-qthelp 1.0.2 py_0
sphinxcontrib-serializinghtml 1.1.3 py_0
sphinxcontrib-websupport 1.1.2 py_0
spyder 3.3.6 py37_0
spyder-kernels 0.5.2 py37_0
sqlalchemy 1.3.9 py37he774522_0
sqlite 3.30.0 he774522_0
statsmodels 0.10.1 py37h8c2d366_0
sympy 1.4 py37_0
tbb 2019.4 h74a9793_0
tblib 1.4.0 py_0
tensorboard 2.1.0 pypi_0 pypi
tensorflow 2.1.0 pypi_0 pypi
tensorflow-base 2.0.0 mkl_py37hd1d5974_0
tensorflow-datasets 2.0.0 pypi_0 pypi
tensorflow-estimator 2.1.0 pypi_0 pypi
tensorflow-metadata 0.21.1 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
terminado 0.8.2 py37_0
testpath 0.4.2 py37_0
theano 1.0.4 py37_0
tk 8.6.8 hfa6e2cd_0
toolz 0.10.0 py_0
tornado 6.0.3 py37he774522_0
tqdm 4.36.1 py_0
traitlets 4.3.3 py37_0
unicodecsv 0.14.1 py37_0
urllib3 1.24.2 py37_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_0
wcwidth 0.1.7 py37_0
webencodings 0.5.1 py37_1
werkzeug 0.16.0 py_0
wheel 0.33.6 py37_0
widgetsnbextension 3.5.1 py37_0
win_inet_pton 1.1.0 py37_0
win_unicode_console 0.5 py37_0
wincertstore 0.2 py37_0
winpty 0.4.3 4
wrapt 1.11.2 py37he774522_0
xlrd 1.2.0 py37_0
xlsxwriter 1.2.1 py_0
xlwings 0.15.10 py37_0
xlwt 1.3.0 py37_0
xz 5.2.4 h2fa13f4_4
yaml 0.1.7 hc54c509_2
zeromq 4.3.1 h33f27b4_3
zict 1.0.0 py_0
zipp 0.6.0 py_0
zlib 1.2.11 h62dcd97_3
zstd 1.3.7 h508b16e_0
推荐答案
有两种方法
1.安装到虚拟环境中
pip TensorFlow
virtualenv --system-site-packages -p python3 ./venv
那么你需要激活你的新环境
then you need to activate your new environment
pip install --upgrade pip
pip list # show packages installed within the virtual environment
this command for quit
deactivate # don't exit until you're done using TensorFlow
we finish by installing tensor
pip install --upgrade tensorflow
2.在您的系统中安装
python3 --version
pip3 --version
virtualenv --version
Ubuntu
sudo apt update
sudo apt install python3-dev python3-pip
sudo pip3 install -U virtualenv # system-wide install
然后
pip3 install --user --upgrade tensorflow # install in $HOME
这篇关于当 conda 尚不支持时，如何在 Windows 上安装最新的 Tensorflow(此处:2.2)?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持html5模板网！
相关文章
使用 python 解析非常大的 xml 文件时出现问题Troubles while parsing with python very large xml file(使用 python 解析非常大的 xml 文件时出现问题)- 使用 Python 2 在 XML 中按属性查找所有节点Find all nodes by attribute in XML using Python 2(使用 Python 2 在 XML 中按属性查找所有节点)
- Python - 如何解析 xml 响应并将元素值存储在变量中Python - How to parse xml response and store a elements value in a variable?(Python - 如何解析 xml 响应并将元素值存储在变量中?)
- 如何在 Python 中获取 XML 标记值How to get XML tag value in Python(如何在 Python 中获取 XML 标记值)
- 如何使用 ElementTree 正确解析 utf-8 xml?How to correctly parse utf-8 xml with ElementTree?(如何使用 ElementTree 正确解析 utf-8 xml?)
- 将 XML 从 URL 解析为 python 对象Parse XML from URL into python object(将 XML 从 URL 解析为 python 对象)
最新文章
- CondaHTTPError: HTTP 000 CONNECTION FAILED for url <ht
- 安装 Keras 后 Anaconda 提示卡住/关闭
- Conda 和 Visual Studio 代码调试
- 构建期间在 Dockerfile 中激活和切换 Anaconda 环境
- 查看 conda 交易的历史记录?
- 如何将文件夹添加到给定 Anaconda 环境的搜索路径
- 使用 Numba 时如何并行化此 Python for 循环
- 在 docker 中激活 conda 环境
- 在 Windows 上通过批处理调度 Python 脚本(使用 Ana
- 带有 Pandas 的 PyInstaller 创建超过 500 MB 的 exe