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Ubuntu Installation TensorFlow

1. Install Pipsudo Install Python-pip Python-dev2. Installing TensorFlow for Python 2.7# Ubuntu/linux --bit, CPU only, Python2.7:$ sudoPipInstall--upgrade https://STORAGE.GOOGLEAPIS.COM/TENSORFLOW/LINUX/CPU/TENSORFLOW-0.8.0-CP27-NONE-LINUX_X86_64.WHL# Ubuntu/linux --bit, GPU enabled, Python2.7. Requires CUDA Toolkit7.5and CuDNN v4.# for other versions, see"Instal

Ubuntu installation Tensorflow-gpu + Keras

variableGedit ~/.BASHRCThen add the path to the Anaconda3 at the end of the fileExport path=/home/your path/anaconda3/bin: $PATHAnd finally make our changes effectiveSOURCE ~/.BASHRCThis way, we enter Python in terminal and the default is open Anaconda3So we can use the Python3 safely.9. Installing Keras and TensorFlowWith the above installation process, the default PIP in our system will be the PIP in Anaconda3, so we only need to use PIP to install Keras and

Easy tutorial for installing TensorFlow under windows with Pycharm

79760616Recently began to learn the relevant knowledge of deep learning, ready to combat, read some about TensorFlow installation blog, around a few bends, so to fill the pit (redundant installed or non-Windows), mainly around the use of pycharm need to tensorflow installation process.Environment: WINDOWS10 Professional Edition. Just want to run a little bit tensorflow

WINDOWS10 Installing the TensorFlow GPU version (PIP3 installation method)

and the version information indicates that the installation was successful.(2), download CUDNNTensorFlow version different, the need for the CUDNN version is not the same, see TensorFlow release notes, such as: tensorflow1.3 Release Notes Configure CUDNN Download to the corresponding version of CUDNN (tensorflow1.3 need cuDNN6, can be downloaded to https://www.zhihu.com/question/37082272), unzip: The extracted bin directory is

Installing TensorFlow (CentOS) under Linux

One, Python installationCentOS comes with python2.7.5, this step can be omitted.Second, Python-pipPip--python index package, lifetimes Linux yum, installs the Management Python software pack.Yum Install Python-pip python-develThird, installation TensorFlowInstalling Linux and python2.7-based TensorFlow 0.9Pip Install https://storage.googleapis.com/tensorflow/linux/cpu/

Learning notes TF049: TensorFlow model storage and loading, queue threads, loading data, custom operations, tf049tensorflow

Learning notes TF049: TensorFlow model storage and loading, queue threads, loading data, custom operations, tf049tensorflow Generate the checkpoint file (chekpoint file). The extension is. ckpt, And the tf. train. Saver object is generated by calling Saver. save. Contains weights and other program-Defined variables, excluding the graph structure. Another program needs to re-create the graphic structure to tell Ten

Installation and use of TensorFlow syntaxnet

Installation of TensorFlow SyntaxnetBefore installing, make sure that Ubuntu, Python, TensorFlow, and some of the appropriate packages are installed successfully.1. Installing Syntaxnet# (1) Pip$ sudo apt-get install python-virtualenv# (2) PIP3$ sudo apt-get install python3-virtualenv2. Create the TensorFlow environment in Virtualenv$ virtualenv--system-sit-packa

Ubuntu 16.04 LTS tensorflow-cpu/cuda9.0 + Cudnn7.0 + tensorflow1.5-gpu_ environment configuration

Before outlining this tutorial for Ubuntu 16.04 Tensorflow-gpu or a CPU version installation, be sure to perform a 1.1.1 operation to verify that your video card is Nividia and supports GPU computing. If you do not support GPU operations, you can only install the TENSORFLOW-CPU version, skipping the 1, 2, 3 headings directly, from 4. Virtualenv + Tensorflow1.5, and choose to install CPU version Note ... Whe

TensorFlow Series-Basic usage

In order to use TensorFlow, we need to understand what TensorFlow is. The following is a description of the 5 characteristics of TensorFlow: Use a graph to indicate that the calculation process uses sessions (sessions) to perform diagrams using tensors to represent data using variables to maintain state using feeds and fetches operations to remove or deposit data

TensorFlow Advanced (iii)---creation and initialization of variables

OP actionweights = tf. Variable (Tf.random_normal ([784, $], stddev=0.35))print(WEIGHTS.OP)MethodAssignAssigns a new value to the variable.x = tf. Variable (5.0,name="x"+ 1.0)EvalIn the session, the value of this variable is computed and returned. This is not a graphical construction method, it does not add operations to graphics. Easy Printing Resultsv = tf. Variable ([1, 2= Tf.global_variables_initializer () with TF. Session () as Sess: sess.run (init) # Specify session print(V.eval

Use TensorFlow to let neural networks create music automatically

A few days ago to see an interesting share, the main idea is how to use TensorFlow teach neural network automatically create music. It sounds so fun, there's wood! As a Coldplay, the first idea was to automatically generate a music like the Coldplay genre, so I started to follow the tutorial on GitHub (project name: Projects Magenta) Step by step, get three days, The final generated music is here (if someone can tell me how to insert music in the blog

Win10 under TensorFlow GPU Edition installation

Get ready:System environment: WINDOWS10 + Anaconda3 + pycharm(1) environment configuration:Open Anaconda Prompt, enter the Tsinghua warehouse image, so the update will be faster:Input:Conda config--add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/--set show_channel_ URLs YesAlso in Anaconda Prompt use Anaconda to create a python3.5 environment, the environment name is TensorFlow, enter the following command:Conda create-n

[Issue record] TensorFlow Test Mnist failed __tensorflow

After the first two TensorFlow test Mnist sample articles uploaded, csdn swallowed my diagram and tested it again when the following problems occurred [test@dl1 mnist]$ python mnist_test_begin.py I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA Library libcublas.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully

How to compile a demo running TensorFlow

1. Install the compilation tool Bazel, you can refer to the official tutorial. https://docs.bazel.build/versions/master/install-ubuntu.html 2. Configure the TensorFlow compilation environment Run the Configure file under the TensorFlow directory and configure it according to your environment. For example, the following: **root@fly-virtual-machine:/home/share/tensorf

Comparison between Caffe, TensorFlow, and MXnet open source libraries

Comparison between Caffe, TensorFlow, and MXnet open source libraries Recently, Google opened up its internal deep learning framework TensorFlow [1] and discussed the three open-source libraries in combination with the open-source MXNet [2] and Caffe [3, among them, only Caffe has carefully read the source code. The other two libraries only read the official documentation and some comments from researchers.

Ubuntu16.04 Install tensorflow+ Install opencv+ install openslide+ install Sogou Input Method

bring up another dialog as shown. Then, cancel only Show current Language (very important, otherwise can not find just installed Sogou Input Method!) Finally, enter Sogou in the input box and click OK. When you're done adding it to the bottom of the list, note that it's the bottom!!! Then the default input method is Sogou input method.Of course, every time I do not click on the only Show current Language, so every time compared to the pain of the sea

"Magenta project" to teach you to create music with TensorFlow neural network

original link: http://www.cnblogs.com/learn-to-rock/p/5677458.htmlaccidentally on the internet to see a I am very interested in the project Magenta, with TensorFlow let neural network automatically create music. The vernacular is: You can use some of the style of music to make models, and then use the training model of the new music processing to create new music. spent a half-time to finally have the results, very happy, but also this half-day experi

Convolutional Networks for Mnist in TensorFlow

It 's written in front . This paper introduces the task of identifying handwritten characters by using convolution neural network based on TensorFlow on Mnist dataset, including: {Two layers of volume base}+{a layer of Relu full link layer}+{the full link layer of Softmax layer}. Because the structure is simple, the code is clear, the whole article to the main code, reading save effort and convenience. 1. Load mnist Data # load Mnist data from tensor

TensorFlow Parallel Computing: multicore (multicore), multithreading (multi-thread), graph segmentation (graph Partition) _tensorflow

GitHub Download Complete code Https://github.com/rockingdingo/tensorflow-tutorial/tree/master/mnist Brief introduction It takes a long time to use the TensorFlow training depth neural network model, because the parallel computing provides an important way to improve the running speed. TensorFlow provides a variety of ways to run the program in parallel, and the

tensorflow-related APIs

tensorflow-Correlation Apitensorflow Correlation function understanding Task Time: Unknown time Tf.truncated_normaltruncated_normal( shape, mean=0.0, stddev=1.0, dtype=tf.float32, seed=None, name=None)Function Description:Produces a truncated normal distribution random number, the value range is [mean - 2 * stddev, mean + 2 * stddev] .Parameter list: Name of parameter must-Choose type Descr

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