How can I get to Haidian social security center
Publish: 2021-05-09 07:58:47
1. 1. Download
1.1 system image
because I tried Ubuntu 14.04, after installing NVIDIA driver, there will be a problem of circular login, and I can't find an effective solution, so I can only choose Ubuntu 16.04
1.2 CUDA 8.0
note:
(1) under the CUDA download page of NVIDIA, select the CUDA version you want to use to download
(2) we use cuda8.0 here (there is a prompt on the page that gtx1070 and gtx1080 support version 8.0). If students do not use the above two versions of GPU, they can download cuda7.5. Download
(3) registration is required for downloading
(4) graphic selection
1.3 cudnn V5
Description:
(1) to download, you need to fill in a questionnaire. For three options, it is recommended to fill in carefully. After all, they give us free use
(2) after filling in, click the small box in front of I agree to, and the following will appear:
1.4 tensorflow 0.11
tensorflow GitHub, This tutorial uses the fourth source code to install
virtualenv installation
Anaconda installation
docker installation
installing from sources
note:
(1) open the download page and scroll down to the following figure:
(2) Click Python 2 to start the download
finally, save all the files downloaded from 1.2-1.4 to your mobile hard disk / U disk, and wait for them to be used ring installation
2. Install Ubuntu 16.04 lts system
install Ubuntu 16.04:
note:
(1) the original English system we install directly is also in English
(2) in the third step of the above link, the installation type is custom. Our choice is to clear the entire disk and install it. If you have a Windows system, you will also be prompted to install the coexisting mode of Ubuntu 16.04 and windows. This is your choice, remember! This place is carefully chosen
(3) thank you for your online experience
3. Install NVIDIA driver
open terminal and input the following command:
sudo apt get Update1
then set - & gt; Software update - & gt; Additional drive - & gt; Select NVIDIA's latest driver (361) - & gt; Application change
3. CUDA 8.0
3.1 install CUDA
open terminal in CUDA's directory and enter the following commands in turn:
CD / home / * * (own user name) / desktop / \\\\\\_ 8.0.27-1_ AMD64. DEB
sudo apt get update
sudo apt get install cuda1234
3.2 GCC downgrading
Ubuntu's gcc compiler is 5.4.0, but cuda8.0 does not support compilers above 5.0, so it needs to be downgrading, Rece compiler version to 4.9:
execute in terminal:
sudo apt get install G + + - 4.9
sudo update alternates -- install / usr / bin / GCC GCC / usr / bin / gcc-4.9 20
sudo update alternates -- install / usr / bin / GCC / usr / bin / gcc-5 10
sudo update alternates -- install / usr / bin / G + + G + + / usr / bin / G + + - 4.9 20
sudo update alternates Ves -- install / usr / bin / G + + G + + / usr / bin / G + + - 5 10
sudo update alternates -- install / usr / bin / cc CC / usr / bin / GCC 30
sudo update alternates -- set CC / usr / bin / GCC
sudo update alternates -- install / usr / bin / C + + C + + / usr / bin / G + + 30
sudo update alternates -- set C + + / usr / bin / G + + 123456789
3. Install cudnn
open term In this paper, the following commands are input in order: < br / < br / < br / < br / < CD / home / [(your user name) / desktop / \\\\\\\\\\\\it's not easy 4 # ()
sudo Chmod a + R / usr / local / CUDA / include / cudnn. H / usr / local / CUDA / lib64 / libcudnn * 12345
4. Install other dependencies
4.1 to configure environment variables
according to the above tutorial, enter the following command in terminal:
sudo GEDIT ~ /. Bash_ Profile # open.bash_ Profile1
and then add:
export LD at the end of the open text_ LIBRARY_ PATH="$ LD_ LIBRARY_ PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"< br />export CUDA_ Home = / usr / local / cuda12
continue to enter in terminal:
source ~ /. Bash_ Profile # makes the changed environment variables take effect 1
of course, there are other tutorials written in the file ~ /. Bashrc, and the method is similar to the above. This method can be implemented if there is a problem with the. / config file later
4.2 install other libraries
/ tensorflow / tensorflow / blob / Master / tensorflow / g3doc / get_ started/os_ Setup. MD
we installed it on the tensorflow official website of GitHub according to the prompts, with the address above
step by step screenshot is as follows
enter the following command in terminal:
sudo apt get install Python PIP Python dev 1
4. Install bazel
4.1 install bazel dependency
because this tutorial uses tensorflow source code to compile / install, you need to use bazel build
in terminal, enter the following commands 1-7 in turn
4.2 to install bazel
and then return to the previous tensorflow installation tutorial page: tensorflow / tensorflow / blob / Master / tensorflow / g3doc / get_ started/os_ Setup. MD
click the link: install for your system, jump to bazel's download page:
Download bazel-0.3.2-install-linux-x86_ 64.sh to the desktop, and then enter the following command in terminal
CD / home / * * (your user name) / desktop / ################################_ TO_ Install. Sh # authorize. Sh files
. / path_ TO_ Install.sh -- user # run. Sh file 123
4.3 install the third-party library
enter the following command in terminal
sudo apt get install Python numpy swing Python dev Python wheel # install the third-party library
sudo apt get install git
git clone git://github.com/numpy/numpy.git Numpy 123
5. Install tensorflow
5.1 download tensorflow
5 Enter the following command in terminal
git clone / tensorflow / tensorflow1
in particular, I use tensorflow version 0.11, which requires CUDA 7.5 or above and cudnn V5
is the default download directory in / home
5.2 to configure tensorflow
or just the website
/ tensorflow / tensorflow / blob / Master / tensorflow / g3doc / get_ started/os_ Setup. MD
enter the following command in terminal:
Cd ~ / tensorflow # switch to tensorflow folder
. / configure # execute configure file 12
and then operate according to the following options:
5.3 create PIP
enter the following command in terminal:
bazel build - C opt / / tensorflow / tools / pip_ package:build_ pip_ package
bazel build -c opt --config=cuda //tensorflow/tools/pip_ package:build_ pip_ package
bazel-bin/tensorflow/tools/pip_ package/build_ pip_ package /tmp/tensorflow_ PKG
sudo PIP install / home / * * (your own user name) / desktop / tensorflow-0.10.0-cp2-none-any.whl1234
5.4 set tensorflow environment
bazel build - C opt / / tensorflow / tools / pip_ package:build_ pip_ package
# To build with GPU support:
bazel build -c opt --config=cuda //tensorflow/tools/pip_ package:build_ pip_ package
mkdir _ python_ build
cd _ python_ build
ln -s ../bazel-bin/tensorflow/tools/pip_ package/build_ pip_ package.runfiles/org_ tensorflow/* .
ln -s ../tensorflow/tools/pip_ Package / *.
Python setup. Py develop12345678
this is a great success ~
6. Test tensorflow
test here. If you can see the same picture as me, congratulations on your successful configuration of tensorflow for GPU!
1.1 system image
because I tried Ubuntu 14.04, after installing NVIDIA driver, there will be a problem of circular login, and I can't find an effective solution, so I can only choose Ubuntu 16.04
1.2 CUDA 8.0
note:
(1) under the CUDA download page of NVIDIA, select the CUDA version you want to use to download
(2) we use cuda8.0 here (there is a prompt on the page that gtx1070 and gtx1080 support version 8.0). If students do not use the above two versions of GPU, they can download cuda7.5. Download
(3) registration is required for downloading
(4) graphic selection
1.3 cudnn V5
Description:
(1) to download, you need to fill in a questionnaire. For three options, it is recommended to fill in carefully. After all, they give us free use
(2) after filling in, click the small box in front of I agree to, and the following will appear:
1.4 tensorflow 0.11
tensorflow GitHub, This tutorial uses the fourth source code to install
virtualenv installation
Anaconda installation
docker installation
installing from sources
note:
(1) open the download page and scroll down to the following figure:
(2) Click Python 2 to start the download
finally, save all the files downloaded from 1.2-1.4 to your mobile hard disk / U disk, and wait for them to be used ring installation
2. Install Ubuntu 16.04 lts system
install Ubuntu 16.04:
note:
(1) the original English system we install directly is also in English
(2) in the third step of the above link, the installation type is custom. Our choice is to clear the entire disk and install it. If you have a Windows system, you will also be prompted to install the coexisting mode of Ubuntu 16.04 and windows. This is your choice, remember! This place is carefully chosen
(3) thank you for your online experience
3. Install NVIDIA driver
open terminal and input the following command:
sudo apt get Update1
then set - & gt; Software update - & gt; Additional drive - & gt; Select NVIDIA's latest driver (361) - & gt; Application change
3. CUDA 8.0
3.1 install CUDA
open terminal in CUDA's directory and enter the following commands in turn:
CD / home / * * (own user name) / desktop / \\\\\\_ 8.0.27-1_ AMD64. DEB
sudo apt get update
sudo apt get install cuda1234
3.2 GCC downgrading
Ubuntu's gcc compiler is 5.4.0, but cuda8.0 does not support compilers above 5.0, so it needs to be downgrading, Rece compiler version to 4.9:
execute in terminal:
sudo apt get install G + + - 4.9
sudo update alternates -- install / usr / bin / GCC GCC / usr / bin / gcc-4.9 20
sudo update alternates -- install / usr / bin / GCC / usr / bin / gcc-5 10
sudo update alternates -- install / usr / bin / G + + G + + / usr / bin / G + + - 4.9 20
sudo update alternates Ves -- install / usr / bin / G + + G + + / usr / bin / G + + - 5 10
sudo update alternates -- install / usr / bin / cc CC / usr / bin / GCC 30
sudo update alternates -- set CC / usr / bin / GCC
sudo update alternates -- install / usr / bin / C + + C + + / usr / bin / G + + 30
sudo update alternates -- set C + + / usr / bin / G + + 123456789
3. Install cudnn
open term In this paper, the following commands are input in order: < br / < br / < br / < br / < CD / home / [(your user name) / desktop / \\\\\\\\\\\\it's not easy 4 # ()
sudo Chmod a + R / usr / local / CUDA / include / cudnn. H / usr / local / CUDA / lib64 / libcudnn * 12345
4. Install other dependencies
4.1 to configure environment variables
according to the above tutorial, enter the following command in terminal:
sudo GEDIT ~ /. Bash_ Profile # open.bash_ Profile1
and then add:
export LD at the end of the open text_ LIBRARY_ PATH="$ LD_ LIBRARY_ PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"< br />export CUDA_ Home = / usr / local / cuda12
continue to enter in terminal:
source ~ /. Bash_ Profile # makes the changed environment variables take effect 1
of course, there are other tutorials written in the file ~ /. Bashrc, and the method is similar to the above. This method can be implemented if there is a problem with the. / config file later
4.2 install other libraries
/ tensorflow / tensorflow / blob / Master / tensorflow / g3doc / get_ started/os_ Setup. MD
we installed it on the tensorflow official website of GitHub according to the prompts, with the address above
step by step screenshot is as follows
enter the following command in terminal:
sudo apt get install Python PIP Python dev 1
4. Install bazel
4.1 install bazel dependency
because this tutorial uses tensorflow source code to compile / install, you need to use bazel build
in terminal, enter the following commands 1-7 in turn
4.2 to install bazel
and then return to the previous tensorflow installation tutorial page: tensorflow / tensorflow / blob / Master / tensorflow / g3doc / get_ started/os_ Setup. MD
click the link: install for your system, jump to bazel's download page:
Download bazel-0.3.2-install-linux-x86_ 64.sh to the desktop, and then enter the following command in terminal
CD / home / * * (your user name) / desktop / ################################_ TO_ Install. Sh # authorize. Sh files
. / path_ TO_ Install.sh -- user # run. Sh file 123
4.3 install the third-party library
enter the following command in terminal
sudo apt get install Python numpy swing Python dev Python wheel # install the third-party library
sudo apt get install git
git clone git://github.com/numpy/numpy.git Numpy 123
5. Install tensorflow
5.1 download tensorflow
5 Enter the following command in terminal
git clone / tensorflow / tensorflow1
in particular, I use tensorflow version 0.11, which requires CUDA 7.5 or above and cudnn V5
is the default download directory in / home
5.2 to configure tensorflow
or just the website
/ tensorflow / tensorflow / blob / Master / tensorflow / g3doc / get_ started/os_ Setup. MD
enter the following command in terminal:
Cd ~ / tensorflow # switch to tensorflow folder
. / configure # execute configure file 12
and then operate according to the following options:
5.3 create PIP
enter the following command in terminal:
bazel build - C opt / / tensorflow / tools / pip_ package:build_ pip_ package
bazel build -c opt --config=cuda //tensorflow/tools/pip_ package:build_ pip_ package
bazel-bin/tensorflow/tools/pip_ package/build_ pip_ package /tmp/tensorflow_ PKG
sudo PIP install / home / * * (your own user name) / desktop / tensorflow-0.10.0-cp2-none-any.whl1234
5.4 set tensorflow environment
bazel build - C opt / / tensorflow / tools / pip_ package:build_ pip_ package
# To build with GPU support:
bazel build -c opt --config=cuda //tensorflow/tools/pip_ package:build_ pip_ package
mkdir _ python_ build
cd _ python_ build
ln -s ../bazel-bin/tensorflow/tools/pip_ package/build_ pip_ package.runfiles/org_ tensorflow/* .
ln -s ../tensorflow/tools/pip_ Package / *.
Python setup. Py develop12345678
this is a great success ~
6. Test tensorflow
test here. If you can see the same picture as me, congratulations on your successful configuration of tensorflow for GPU!
2. How can we not go to this floating board? Is it the card owner? Can the characters move? When the guard board comes, you can go there. If there's something strange on the opposite side, it's OK. Otherwise, you can try to reopen the game
3. Break the army to attract the monster away, and then the mage will fight wildly, ring star, assist, attack and blood
4.
bus line: Metro Line 3, the whole journey is about 12.2km
1. Take Metro Line 3 from Dashi, pass 6 stops, reach Zhujiang New Town Station
2. Walk about 780m to Yajule center
5. Guangzhou Yajule garden
No.398, Xingnan Avenue, Nancun Town, Panyu District, Guangzhou City, Guangdong Province
walk to Yuangang
about 16 minutes (1.3 km)
Yuangang
bus and subway feeder line 8 air conditioned bus to: Dashi station of subway
(11 minutes, 6 stops)
tangbu West
walk to NANDA intersection
about 6 minutes
NANDA intersection
air conditioned bus No. 310 goes to Guanggong general station of University City
(1 hour, 0 minutes, 11 stops)
Guangda apartment
walk to Waihuan West Road of University City of Panyu District, Guangzhou City, Guangdong Province
about 24 minutes (2.0 km)
<
Guangdong science and technology center
Panyu District, Guangzhou City, Guangdong Province
University City Outer Ring West Road
journey time: about 2 hours and 1 minute
No.398, Xingnan Avenue, Nancun Town, Panyu District, Guangzhou City, Guangdong Province
walk to Yuangang
about 16 minutes (1.3 km)
Yuangang
bus and subway feeder line 8 air conditioned bus to: Dashi station of subway
(11 minutes, 6 stops)
tangbu West
walk to NANDA intersection
about 6 minutes
NANDA intersection
air conditioned bus No. 310 goes to Guanggong general station of University City
(1 hour, 0 minutes, 11 stops)
Guangda apartment
walk to Waihuan West Road of University City of Panyu District, Guangzhou City, Guangdong Province
about 24 minutes (2.0 km)
<
Guangdong science and technology center
Panyu District, Guangzhou City, Guangdong Province
University City Outer Ring West Road
journey time: about 2 hours and 1 minute
6. Hello Walk about 60 meters from Guangzhou Baiyun International Airport (New Airport) to the entrance and exit of the South Station of the subway airport, take Metro Line 3 (Airport South - TIYU West) (take 12 stops) to TIYU West Road station, then transfer to Metro Line 3 (Tianhe passenger station - Panyu Square) (take 7 stops) to the entrance and exit a of Dashi station, Go ahead to Dashi metro station (Panyu) and take bus line 8 (take 14) to likoufu station (Panyu). Walk about 250 meters to Guangzhou Yajule Garden (southeast gate)
. Walk about 60 meters from Guangzhou Baiyun International Airport (New Airport) to the entrance and exit of Metro South Station, take Metro Line 3 (Airport South - TIYU West) (take station 12) to Metro TIYU West Road station, then transfer to Metro Line 3 (Tianhe passenger station - Panyu Square) (take station 7) to Dashi station entrance and exit a, Go ahead to Dashi metro station (Panyu), transfer to bus and Metro feeder line 8 (take 10 stops) and get off at Guangzhou Yajule Garden Station (Panyu). Walk about 110 meters to Guangzhou Yajule Garden (Northwest Gate)
. Walk about 60 meters from Guangzhou Baiyun International Airport (New Airport) to the entrance and exit of Metro South Station, take Metro Line 3 (Airport South - TIYU West) (take station 12) to Metro TIYU West Road station, then transfer to Metro Line 3 (Tianhe passenger station - Panyu Square) (take station 7) to Dashi station entrance and exit a, Go ahead to Dashi metro station (Panyu), transfer to bus and Metro feeder line 8 (take 10 stops) and get off at Guangzhou Yajule Garden Station (Panyu). Walk about 110 meters to Guangzhou Yajule Garden (Northwest Gate)
7.
Real estate name: Guangzhou Yajule Huangpu Innovation Center
City: Guangzhou
alias: Yajule Huangpu Innovation Center
real estate location: intersection of fengle North Road and bishancun Road, Huangpu District, Guangzhou City, Guangdong Province (opposite to GAC Honda or navigation Yajule Huangpu Innovation Center)
property right period: 70 years
building type: Tower, small high-rise, super high-rise, High rise,
bus line: there is a bus stop in Bishan village at the entrance of the project; Bus routes: B24, 326, 943, 320, 355, 324, 338, 339, 344, 366, 438, 459 and 944
other modes of transportation: 800 meters to the intersection station of Metro Line 7 phase II (under construction), Metro Line 19 (under planning), Metro Line 23 (under planning), and dashadong station of Metro Line 5
Planning Information: it covers an area of 110296 square meters, the plot ratio has no data, the greening rate is 30%, a total of 15 buildings, parking spaces -
surrounding facilities: [Hospital] the First Affiliated Hospital of Sun Yat sen University (Huangpu Park) (Grade 3A hospital), the Fifth Affiliated Hospital of Guangzhou Medical University (grade III General Hospital)< In addition, there are Yuzhu kindergarten, Bishan kindergarten, Huangpu Hengsha kindergarten, Lotte Chinese and English kindergarten, etc.
Jitang Park, Huangpu children's Park and Huangpu sports development center
internal support: experiential pedestrian street
(the information contained is for reference only, and the final information is subject to the information of the sales office.)
Click to view more comprehensive, timely and accurate new house information
8. [Shuangliu International Airport (T2 terminal)] get on the airport special line 4 and get off at [Huayang passenger station]
[Huayang passenger station] get on the road T36 and get off at [Lu Shan Avenue Han Po Ling Station]
[Lu Shan Avenue Han Po Ling Station]
[Lu Shan Avenue Han Po Ling Station]
get on the road t33 (or T208) and get off at [normal university No.1 middle station]
walk 230 meters to Cheng Yaju Le Hao Sheng Hotel
it is recommended to download one Navigation app to see the route more clearly, hope to adopt
[Huayang passenger station] get on the road T36 and get off at [Lu Shan Avenue Han Po Ling Station]
[Lu Shan Avenue Han Po Ling Station]
[Lu Shan Avenue Han Po Ling Station]
get on the road t33 (or T208) and get off at [normal university No.1 middle station]
walk 230 meters to Cheng Yaju Le Hao Sheng Hotel
it is recommended to download one Navigation app to see the route more clearly, hope to adopt
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