技术标签: 机器学习
Windows python是3.9版本的,先安装试试,看看会有什么问题?
Downloading pip-21.0.1-py3-none-any.whl (1.5 MB)
|████████████████████████████████| 1.5 MB 91 kB/s
Installing collected packages: pip
WARNING: The scripts pip.exe, pip3.8.exe and pip3.exe are installed in 'C:\Users\dev\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
Successfully installed pip-21.0.1
WARNING: You are using pip version 20.2.3; however, version 21.0.1 is available.
You should consider upgrading via the 'C:\Users\dev\AppData\Local\Microsoft\WindowsApps\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\python.exe -m pip install --upgrade pip' command.
pip3 install six numpy wheel
pip3 install keras_applications==1.0.6 --no-deps
pip3 install keras_preprocessing==1.0.5 --no-deps
看 提示,貌似只可以安装到python3.8上面,python3.9 不支持哦。还是有警告
Downloading numpy-1.20.1-cp38-cp38-win_amd64.whl (13.7 MB)
WARNING: The script wheel.exe is installed in 'C:\Users\dev\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The script f2py.exe is installed in 'C:\Users\dev\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
Successfully installed numpy-1.20.1 six-1.15.0 wheel-0.36.2
Collecting keras_applications==1.0.6
Downloading Keras_Applications-1.0.6-py2.py3-none-any.whl (44 kB)
|████████████████████████████████| 44 kB 411 kB/s
Installing collected packages: keras-applications
Successfully installed keras-applications-1.0.6
C:\Users\dev>pip3 install keras_preprocessing==1.0.5 --no-deps
Collecting keras_preprocessing==1.0.5
Downloading Keras_Preprocessing-1.0.5-py2.py3-none-any.whl (30 kB)
Installing collected packages: keras-preprocessing
Successfully installed keras-preprocessing-1.0.5
第一步:安装MSYS2 shell,下载后,直接双击,点击安装,可自定义安装路径。
第二步:配置环境变量,在电脑-高级-环境变量中的path中添加“你的根目录\msys64\usr\bin”和“你的根目录\msys64\usr\bin\bash.exe”
第三步:打开cmd,输入pacman -Syu,回车会出现下图,然后输入y 安装失败
mingw32 891.1 KiB 14.4 KiB/s 01:02 [#####################] 100%
mingw32.sig 438.0 B 0.00 B/s 00:00 [#####################] 100%
error: mingw32: signature from "David Macek <[email protected]>" is unknown trust
error: failed to update mingw32 (invalid or corrupted database (PGP signature))
mingw64 894.5 KiB 23.2 KiB/s 00:39 [#####################] 100%
mingw64.sig 438.0 B 0.00 B/s 00:00 [#####################] 100%
error: mingw64: signature from "David Macek <[email protected]>" is unknown trust
error: failed to update mingw64 (invalid or corrupted database (PGP signature))
msys 300.4 KiB 33.2 KiB/s 00:09 [#####################] 100%
msys.sig 438.0 B 0.00 B/s 00:00 [#####################] 100%
error: msys: signature from "David Macek <[email protected]>" is unknown trust
bazel
Extracting Bazel installation...
Starting local Bazel server and connecting to it...
[bazel release 4.0.0]
Usage: bazel <command> <options> ...
Available commands:
analyze-profile Analyzes build profile data.
aquery Analyzes the given targets and queries the action graph.
build Builds the specified targets.
canonicalize-flags Canonicalizes a list of bazel options.
clean Removes output files and optionally stops the server.
coverage Generates code coverage report for specified test targets.
cquery Loads, analyzes, and queries the specified targets w/ configurations.
dump Dumps the internal state of the bazel server process.
fetch Fetches external repositories that are prerequisites to the targets.
help Prints help for commands, or the index.
info Displays runtime info about the bazel server.
license Prints the license of this software.
mobile-install Installs targets to mobile devices.
print_action Prints the command line args for compiling a file.
query Executes a dependency graph query.
run Runs the specified target.
shutdown Stops the bazel server.
sync Syncs all repositories specified in the workspace file
test Builds and runs the specified test targets.
version Prints version information for bazel.
Getting more help:
bazel help <command>
Prints help and options for <command>.
bazel help startup_options
Options for the JVM hosting bazel.
bazel help target-syntax
Explains the syntax for specifying targets.
bazel help info-keys
Displays a list of keys used by the info command.
https://github.com/bazelbuild/bazel/releases/tag/3.7.2
You have bazel 4.0.0 installed.
Please downgrade your bazel installation to version 3.99.0 or lower to build TensorFlow! To downgrade: download the installer for the old version (from https://github.com/bazelbuild/bazel/releases) then run the installer.
Traceback (most recent call last):
File "D:\tools\tensorflow\tensorflow-master\configure.py", line 1482, in <module>
main()
File "D:\tools\tensorflow\tensorflow-master\configure.py", line 1401, in main
raise UserInputError(
__main__.UserInputError: Invalid CUDA setting were provided 10 times in a row. Assuming to be a scripting mistake.
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文章浏览阅读2.4k次,点赞8次,收藏19次。hashmap_hashmap
文章浏览阅读7.3k次,点赞10次,收藏31次。数据密集型应用系统设计_ddia
文章浏览阅读2.2k次。LuaSocket 是 Lua 的网络模块库,它可以很方便地提供TCP、UDP、DNS、FTP、HTTP、SMTP、MIME 等多种网络协议的访问操作。它由两部分组成:一部分是用 C 写的核心,提供对 TCP 和 UDP 传输层的访问支持。另外一部分是用 Lua 写的,负责应用功能的网络接口处理。安装 LuaSocket如果你安装有 Lua 模块的安装和部署工具 -- Lu_luasocket-2.0.2
文章浏览阅读1.1k次。用 input type=file 来上传文件需要借住 javascript 来完成,客户端的执行过程大概是这样:用户单击“浏览”选择待上传的文件后触发 input 的onchange事件,在onchange事件中调用一个方法,该方法负责把文件提交到服务器,由服务器来完成文件的上传。这种方法上传文件每上传一次后需要重写 input type=file,这就涉及到把 input type=file ..._input type file onchange
文章浏览阅读3.5k次。Python在windows系统运行时,提示ModuleNotFoundError: No module named ‘win32con’。但是去很多地方都找不到这个包解决方案是:conda install scripyscipy 包中包含了win32con这个包,nice._modulenotfounderror: no module named 'win32com
文章浏览阅读349次。#resultt_class.type= <class 'torch.Tensor'>t_class= tensor([[ 3], [ 6], [ 9], [ 5], [ 5], [ 1], [ 2], [ 2], [ 0], [ 7], [ 1], [ 3], [ 3], [ .._for ~ else语句的执行过程
文章浏览阅读1.1w次,点赞4次,收藏15次。文章目录概述概述#kafkaspring.kafka.bootstrap-servers=10.11.114.247:9092spring.kafka.producer.acks=1spring.kafka.producer.retries=3spring.kafka.producer.batch-size=16384spring.kafka.producer.buffer-memory=33554432spring.kafka.producer.key-serializer=org.a_spring kafka生产者源码
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