tensorflow repository

Recently reinstalled the system, installed the TensorFlow configuration environmentSum up.Resourceshttp://blog.csdn.net/ZWX2445205419/article/details/69429518http://blog.csdn.net/u013294888/article/details/56666023Http://www.2cto.com/kf/201612/578337.htmlhttp://blog.csdn.net/10km/article/details/61915535Nvidia driver installation MethodHttps://wiki.ubuntu.com.cn/NVIDIAQuery the NVIDIA Driver modelHttp://www.nvidia.com/Download/index.aspx?lang=en-usQue

Create your own code repository !, Own code repository Here, we will first create a storage warehouse with the @ property attribute, which is similar to many block warehouses of apple, and so on. How can we create it: Apple helped us do a good job. You just need to drag the project to complete the work. So how can we create something like this?For example, when we declare an attribute: @ Property (nonat

Configure the yum repository and rpm package, and the yum repository rpm Job 1: 1) Add a 15 gb scsi hard disk before enabling Linux. 2) enable the system, right-click the desktop, and open the terminal. 3) It is a newly added hard disk partition. The size of a primary partition is 5 GB, and the remaining space is extended. One logical partition is divided on the extended partition, And the size is 5 GB.

Label:Warning:permanently added the RSA host key for IP address ' 192.30.252.131 ' to the list of known hosts. Permission denied (PublicKey).Fatal:could not read from remote repository.Sure you have the correct access rightsand the repository exists. This problem occurs because no SSH key is added to the GitHub account Here's how to fix it in terminal input. Ssh-keygen-t rsa-c "forwhat.cn"//note. forwhat.cn for User name If the execution succeeds. Re

The TensorFlow and the black Tech. Google hosted the first TensorFlow developer summit in Mountain View, California, February 16, 2017 (Beijing time) 2 o'clock in the morning. Google site announced the world's leading deep learning open source Framework TensorFlow officially released the V1.0 version, and to ensure that Google's current release API interface to m

namespace data. test { // Data Universal operation implementation /// /// public class repository : testrepositorybase, irepository where tentity: Class, ientity { member Public void Update (tentity entity) { emitmapper. objectmappermanager. defaultinstance. getmapper (). map (entity, originalentity); base. submitchanges (); } Public void Update (ilist List) { list. toli

First, the premiseInstall Git:yum installed git on the virtual machine, no virtual machine can see Windows install Linux virtual machine (CENTOS7) virtual machine address: 192.168.240.139 Create a git directory under the native D drive. and new Git1 and git2 two directories git1 and Git2 are used to clone the remote warehouse, and then the simulation team two people collaborate, one party submits the file, the other party updates the file second, remote initialization of the warehouse Initial

Install TensorFlow in Python2.7 in Ubuntu 16.04 My system environment: Ubuntu 16.04 LTS Python 1, 2.7 Python 1, 3.5 Two TensorFlow versions: TensorFlow is installed in the following ways: Virtualenv Pip Docker Anaconda Source code compilation Pip is the Python software package management system: Pip Install Packages recursive abbreviation The Command

/centos/6/extras/x86_64/#mirrorlist =http://mirrorlist.centos.org/?release=6arch= $basearch repo=extrasGpgcheck=1Gpgkey=http://mirror.centos.org/centos/rpm-gpg-key-centos-6#additional packages that extend functionality of existing packages[Centosplus]Name=centos-6-plus-163.combaseurl=http://mirrors.163.com/centos/6/centosplus/x86_64/#mirrorlist =http://mirrorlist.centos.org/?release=6arch= $basearch repo=centosplusGpgcheck=1Enabled=0Gpgkey=http://mirror.centos.org/centos/rpm-gpg-key-centos-6#con

.trcActive Problem Count 3Active Incident Count 8As you can see, the view V$diag_info includes the number of issues and events. For example, use the following command to view all ora-errors:Adrci> Set HomePath Diag/rdbms/rac/racAdrci> Set Editor VIAdrci> show alert-p "Message_text like '%ora-% '"ADR Home =/home/oracle/diag/rdbms/rac/rac:*************************************************************************Output the results to file:/tmp/alert_10191_1638_rac_1.ado2012-03-29 20:56:12.266000 +08

Install TensorFlow in virtualenv mode on Ubuntu This article describes how to install tensorflow in virtualenv mode on Ubuntu. Install pip and virtualenv: # Ubuntu/Linux 64-bit Sudo apt-get install python-pip python-dev python-virtualenv # Mac OS X Sudo easy_install pip Sudo pip install -- upgrade virtualenv Create a Virtualenv virtual environment: Go to the parent directory where you want to install

Brief Introduction Tensorflow-bitcoin-robot: A Bitcoin price prediction robot based on the TensorFlow lstm model. The article includes a few parts:1. Why try to do this project.2. Why did you choose this model?3. Where does the data from the model come from.4. The optimization process of the model.5. The direction in which the project can be further improved. The recent performance of the digital currency,

This problem occurs at the time of the update Error:cannot Retrieve repository metadata (Repomd.xml) for Repository:epel. Please verify its path and try againThe question is very simple. And it's very obvious.Solution Execute the cleanup command, Yum Clean metadataYum Clean All We'd better rebuild it after we finish the execution. RPM--REBUILDDB The update command can be executed again Yum Update

The error code is as follows when you use Yum install again after installing Gitlab: Error: Cannot retrieve repository metadata (Repomd.xml) for Repository:gitlab_gitlab-ce. Please verify its path and try again The solution is as follows: A. Open/etc/yum.repos.d/xxxxx.repo, for this example is/etc/yum.repost.d/xxx.repoB. Change the enabled=1 in item [XXX] to Enabled=0 According to the above code prompts, my is gitlab_gitlab-ce the error, so wi

TensorFlow is an open source software library that uses data flow diagrams for numerical calculations. In other words, that's the best way to build a deep learning model. This article collates some excellent tutorials and a list of projects on TensorFlow. First, the tutorial TensorFlow Tutorial 1-from basics to more interesting

It was an incredibly simple thing to install TensorFlow, but it was on my computer for one weeks. During the encounter all kinds of trouble, all kinds of pits, in this record, convenient for everyone. Errors include: Undefined symbol:zgelsd_ Importerror:cannot import name ' MultiArray ' WHL is not a supported wheel 1, install Anaconda: https://www.continuum.io/downloads/(i installed linux-64-python3.6)I started off directly in Py

In a previous tutorial series I went over some of the theory behind recurrent neural (Networks) and the Rnns N of a simple RNN from scratch. That's a useful exercise, but in practice we do libraries like tensorflow with high-level primitives for dealing S. With this using an RNN should is as easy as calling a function, right? Unfortunately that ' s not quite the case. In this post I want the some of the best practices for working with Rnns in

Document Source reprint: http://blog.csdn.net/u010099080/article/details/53418159Http://blog.nitishmutha.com/tensorflow/2017/01/22/TensorFlow-with-gpu-for-windows.htmlPre-Installation PreparationThere are two versions of TensorFlow: CPU version and GPU version. The GPU version requires CUDA and CuDNN support, and the CPU version is not required. If you want to in

This shows the process of compiling the TensorFlow from the source code.The original tutorial https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/get_started/os_setup.md# on GitHub Installing-from-sourcesFirst, install the Build tool Bazel (Http://www.bazel.io/docs/install.html#install-on-ubuntu)Insta

"Google" + "deep learning", two tags let the December 2015 Google open-source deep learning tool TensorFlow after its release quickly became the world's hottest open source project, April 2016, open source TensorFlow support distributed features, The application to the production environment is further.The TensorFlow API supports Python 2.7 and Python 3.3+, with