李沐d2l 环境安装
安装pytorch 对应李沐d2l 环境安装
- 过程问题
-
- 1 安装问题
- 2 从头检查环境
- 3 CUDA
- 4 测试pytorch
- 5 安装 d2l 软件包
- 6 开始使用d2l
- 7 遗留问题
- 8 已安装的软件包
- 9 问题AttributeError: module 'torch' has no attribute 'plot'
过程问题
1 安装问题
anaconda prompt （anaconda3）base 环境下
WARNING: You are using pip version 21.1.1; however, version 22.0.4 is available.
升级pip
python -m pip install --upgrade pip
未成功
2 从头检查环境
cmd下
python
Python 3.8.5 (default, Sep 3 2020, 21:29:08) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Warning:
This Python interpreter is in a conda environment, but the environment has
not been activated. Libraries may fail to load. To activate this environment
please see https://conda.io/activation
C:\Users\>conda activate
(base) C:\Users\>conda --version
conda 4.9.2
conda安装，输入 conda --version
输入 conda info ，出现info内容则校验成功
conda config --show channels
channels:
- defaults
- (base) C:\Users\>conda config --show channels
channels:
- defaults
(base) C:\Users\>conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
(base) C:\Users\>conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
(base) C:\Users\>conda config --set show_channel_urls yes
(base) C:\Users\>conda config --show channels
channels:
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
- defaults
该步未尝试
~~修改此文件，采用清华源
/.condarc：~
channels:
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
- defaults
default_channels:
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
- https://repo.continuum.io/pkgs/free
- https://repo.continuum.io/pkgs/r
- https://repo.continuum.io/pkgs/pro
3 CUDA
CUDA安装成功
C:\Users\>nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Tue_Sep_15_19:12:04_Pacific_Daylight_Time_2020
Cuda compilation tools, release 11.1, V11.1.74
Build cuda_11.1.relgpu_drvr455TC455_06.29069683_0
4 测试pytorch
测试pytorch
import torch
x = torch.rand(2,3)
print(x)
应该输出的内容
tensor([[0.8159, 0.1670, 0.9336],
[0.9877, 0.6789, 0.2509]])
torch.cuda.is_available()
True
此时，GPU驱动和CUDA可支持pytorch的加速计算。
打开anaconda navigator，点击左边enviroment，然后creat d2l
5 安装 d2l 软件包
进入d2l-zh\pytorch 的cmd里
安装成功以后还需要安装 d2l 软件包，它封装了本书中常用的函数和类。
-U：将所有包升级到最新的可用版本
pip install -U d2l
D:\d2l\d2l-zh\pytorch>pip install -U d2l
6 开始使用d2l
打开anaconda prompt
conda activate d2l
退出输入
conda deactivate
7 遗留问题
paddlepaddle 2.1.0 环境与李沐d2l 环境产生冲突
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
paddlepaddle 2.1.0 requires numpy<=1.19.3,>=1.13; python_version >= "3.5" and platform_system == "Windows", but you have numpy 1.22.2 which is incompatible.
mxnet 1.7.0.post2 requires numpy<1.17.0,>=1.8.2, but you have numpy 1.22.2 which is incompatible.
mxnet 1.7.0.post2 requires requests<2.19.0,>=2.18.4, but you have requests 2.25.1 which is incompatible.
WARNING: You are using pip version 21.1.1; however, version 22.0.4 is available.
You should consider upgrading via the 'D:\Anaconda3\python.exe -m pip install --upgrade pip' command.
Successfully installed d2l-0.17.4 matplotlib-3.4.0 numpy-1.22.2 pandas-1.2.4
pip 的依赖项解析器当前未考虑安装的所有包。此行为是以下依赖项冲突的根源。
paddlepaddle 2.1.0
mxnet 1.7.0
要求包低
incompatible 不匹配
于是：
就重新安装这几个包
pip install 包名 -i 地址
pip install 包名 -i https://pypi.tuna.tsinghua.edu.cn/simple # 清华
8 已安装的软件包
查看已安装的软件包
pip list
pip list
Package Version
---------------------------------- -------------------
alabaster 0.7.12
anaconda-client 1.7.2
anaconda-navigator 1.10.0
anaconda-project 0.8.3
argh 0.26.2
argon2-cffi 20.1.0
asn1crypto 1.4.0
astor 0.8.1
astroid 2.4.2
astropy 4.0.2
async-generator 1.10
atomicwrites 1.4.0
attrs 20.3.0
autopep8 1.5.4
Babel 2.8.1
backcall 0.2.0
backports.functools-lru-cache 1.6.1
backports.shutil-get-terminal-size 1.0.0
backports.tempfile 1.0
backports.weakref 1.0.post1
bcrypt 3.2.0
beautifulsoup4 4.9.3
bitarray 1.6.1
bkcharts 0.2
bleach 3.2.1
bokeh 2.2.3
boto 2.49.0
Bottleneck 1.3.2
brotlipy 0.7.0
certifi 2020.6.20
cffi 1.14.3
chardet 3.0.4
click 7.1.2
cloudpickle 1.6.0
clyent 1.2.2
colorama 0.4.4
comtypes 1.1.7
conda 4.9.2
conda-build 3.20.5
conda-package-handling 1.7.2
conda-verify 3.4.2
contextlib2 0.6.0.post1
cryptography 3.1.1
cycler 0.10.0
Cython 0.29.21
cytoolz 0.11.0
d2l 0.17.4
dask 2.30.0
decorator 4.4.2
defusedxml 0.6.0
diff-match-patch 20200713
distributed 2.30.1
docutils 0.16
entrypoints 0.3
et-xmlfile 1.0.1
fastcache 1.1.0
filelock 3.0.12
flake8 3.8.4
Flask 1.1.2
fsspec 0.8.3
future 0.18.2
gast 0.3.3
gevent 20.9.0
glob2 0.7
graphviz 0.8.4
greenlet 0.4.17
h5py 2.10.0
HeapDict 1.0.1
html5lib 1.1
idna 2.6
imageio 2.9.0
imagesize 1.2.0
importlib-metadata 2.0.0
iniconfig 1.1.1
intervaltree 3.1.0
ipykernel 5.3.4
ipython 7.19.0
ipython-genutils 0.2.0
ipywidgets 7.5.1
isort 5.6.4
itsdangerous 1.1.0
jdcal 1.4.1
jedi 0.17.1
jieba 0.42.1
Jinja2 2.11.2
joblib 0.17.0
json5 0.9.5
jsonschema 3.2.0
jupyter 1.0.0
jupyter-client 6.1.7
jupyter-console 6.2.0
jupyter-core 4.6.3
jupyterlab 2.2.6
jupyterlab-pygments 0.1.2
jupyterlab-server 1.2.0
keyring 21.4.0
kiwisolver 1.3.0
lazy-object-proxy 1.4.3
libarchive-c 2.9
llvmlite 0.34.0
locket 0.2.0
lxml 4.6.1
MarkupSafe 1.1.1
matplotlib 3.4.0
mccabe 0.6.1
menuinst 1.4.16
mistune 0.8.4
mkl-fft 1.2.0
mkl-random 1.1.1
mkl-service 2.3.0
mock 4.0.2
more-itertools 8.6.0
mpmath 1.1.0
msgpack 1.0.0
multipledispatch 0.6.0
mxnet 1.7.0.post2
navigator-updater 0.2.1
nbclient 0.5.1
nbconvert 6.0.7
nbformat 5.0.8
nest-asyncio 1.4.2
networkx 2.5
nltk 3.5
nose 1.3.7
notebook 6.1.4
numba 0.51.2
numexpr 2.7.1
numpy 1.22.2
numpydoc 1.1.0
olefile 0.46
openpyxl 3.0.5
packaging 20.4
paddlepaddle 2.1.0
pandas 1.2.4
pandocfilters 1.4.3
paramiko 2.7.2
parso 0.7.0
partd 1.1.0
path 15.0.0
pathlib2 2.3.5
pathtools 0.1.2
patsy 0.5.1
pep8 1.7.1
pexpect 4.8.0
pickleshare 0.7.5
Pillow 8.0.1
pip 21.1.1
pkginfo 1.6.1
pluggy 0.13.1
ply 3.11
prometheus-client 0.8.0
prompt-toolkit 3.0.8
protobuf 3.17.2
psutil 5.7.2
py 1.9.0
pycodestyle 2.6.0
pycosat 0.6.3
pycparser 2.20
pycurl 7.43.0.6
pydocstyle 5.1.1
pyflakes 2.2.0
Pygments 2.7.2
pylint 2.6.0
PyNaCl 1.4.0
pyodbc 4.0.0-unsupported
pyOpenSSL 19.1.0
pyparsing 2.4.7
pyreadline 2.1
pyrsistent 0.17.3
PySocks 1.7.1
pytest 0.0.0
python-dateutil 2.8.1
python-jsonrpc-server 0.4.0
python-language-server 0.35.1
pytz 2020.1
PyWavelets 1.1.1
pywin32 227
pywin32-ctypes 0.2.0
pywinpty 0.5.7
PyYAML 5.3.1
pyzmq 19.0.2
QDarkStyle 2.8.1
QtAwesome 1.0.1
qtconsole 4.7.7
QtPy 1.9.0
regex 2020.10.15
requests 2.25.1
rope 0.18.0
Rtree 0.9.4
ruamel-yaml 0.15.87
scikit-image 0.17.2
scikit-learn 0.24.2
scipy 1.5.2
seaborn 0.11.0
Send2Trash 1.5.0
setuptools 50.3.1.post20201107
simplegeneric 0.8.1
singledispatch 3.4.0.3
sip 4.19.13
six 1.15.0
snowballstemmer 2.0.0
sortedcollections 1.2.1
sortedcontainers 2.2.2
soupsieve 2.0.1
Sphinx 3.2.1
sphinxcontrib-applehelp 1.0.2
sphinxcontrib-devhelp 1.0.2
sphinxcontrib-htmlhelp 1.0.3
sphinxcontrib-jsmath 1.0.1
sphinxcontrib-qthelp 1.0.3
sphinxcontrib-serializinghtml 1.1.4
sphinxcontrib-websupport 1.2.4
spyder 4.1.5
spyder-kernels 1.9.4
SQLAlchemy 1.3.20
statsmodels 0.12.0
sympy 1.6.2
tables 3.6.1
tblib 1.7.0
tensorboardX 2.2
terminado 0.9.1
testpath 0.4.4
threadpoolctl 2.1.0
tifffile 2020.10.1
toml 0.10.1
toolz 0.11.1
torch 1.8.1+cu111
torchaudio 0.8.1
torchtext 0.4.0
torchvision 0.9.1+cu111
tornado 6.0.4
tqdm 4.50.2
traitlets 5.0.5
typing-extensions 3.7.4.3
ujson 4.0.1
unicodecsv 0.14.1
urllib3 1.22
watchdog 0.10.3
wcwidth 0.2.5
webencodings 0.5.1
Werkzeug 1.0.1
wheel 0.35.1
widgetsnbextension 3.5.1
win-inet-pton 1.1.0
win-unicode-console 0.5
wincertstore 0.2
wrapt 1.11.2
xlrd 1.2.0
XlsxWriter 1.3.7
xlwings 0.20.8
xlwt 1.3.0
xmltodict 0.12.0
yapf 0.30.0
zict 2.0.0
zipp 3.4.0
zope.event 4.5.0
zope.interface 5.1.2
WARNING: You are using pip version 21.1.1; however, version 22.0.4 is available.
You should consider upgrading via the 'D:\Anaconda3\python.exe -m pip install --upgrade pip' command.
1链接: link.
pip 工具 _ Python 包管理工具常用命令及镜像地址
9 问题AttributeError: module ‘torch’ has no attribute ‘plot’
在linear-regression中
该步中
再次使用numpy进行可视化
x = np.arange(-7, 7, 0.01)
均值和标准差对
params = [(0, 1), (0, 2), (3, 1)]
d2l.plot(x, [normal(x, mu, sigma) for mu, sigma in params], xlabel='x',
ylabel='p(x)', figsize=(4.5, 2.5),
legend=[f'mean {mu}, std {sigma}' for mu, sigma in params])
产生如下错误
AttributeError Traceback (most recent call last)
<ipython-input-13-f717769c2c17> in <module>
4 # 均值和标准差对
5 params = [(0, 1), (0, 2), (3, 1)]
----> 6 d2l.plot(x, [normal(x, mu, sigma) for mu, sigma in params], xlabel='x',
7 ylabel='p(x)', figsize=(4.5, 2.5),
8 legend=[f'mean {mu}, std {sigma}' for mu, sigma in params])
AttributeError: module 'torch' has no attribute 'plot'
按上述步骤从头重新配置环境后解决问题。
注意jupyter notebook（anaconda3）中可以直接启动http://localhost:8888/
若需要jupyter打开的目录是D盘：
首先打开cmd输入命令 cd /d D:
cd /d D:
jupyter notebook
即可