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Developing a complex depth learning model using Keras + TensorFlow
This post was last edited by Oner at 2017-5-25 19:37Question guide: 1. Why Choose Keras. 2. How to install Keras and TensorFlow as the back end. 3. What is the Keras
a alternative to that command, and found this, which worked!!Conda install-c Conda-forge TensorFlowStep 4: From inside the Anaconda prompt, I opened python by typing "python". Next, I did this, line by line:Import TensorFlow as tf hello = tf.constant (' Hello, tensorflow! ') Sess = tf. Session () print (Sess.run (hello))It said "B ' Hello, tensorflow! '" which I
was successful.Second, installation TensorFlowOpen Anaconda Prompt1. Upgrade Pip to the latest version:2. Create an environment named TensorFlow and install the Python3.5.2Conda Create--name TensorFlow python=3.5.2Enter Y, enter. After the installation is complete:3. Activate this environment: Activate TensorFlow4. Installing TensorFlowPip Install TensorFlowNote: To install
Win10 + python3.6 + VSCode + tensorflow-gpu + keras + cuda8 + cuDN6N environment configuration, win10cudn6n
Preface:
Before getting started, I knew almost nothing about python or tensorflow, so I took a lot of detours When configuring this environment, it took a whole week to complete the environment... However, the most annoying thing is that it is difficult to
integrated Numpy, making it one of the most commonly used libraries in the General deep learning field from the very beginning. Today, Theano still works well, but because it does not support multi-GPU and horizontal scaling, in the TensorFlow craze (they target the same field), Theano is already forgotten.
Learning Materials Link: http://outlace.com/Beginner-Tutorial-Theano/
about
http://blog.csdn.net/jerr__y/article/details/53695567 Introduction: This article mainly describes how to configure the GPU version of the TensorFlow environment in Ubuntu system. Mainly include:-Cuda Installation-CUDNN Installation-TensorFlow Installation-Keras InstallationAmong them, Cuda installs this part is the most important, Cuda installs after, whether is
In the previous TensorFlow Exercise 1 I mentioned a high-level library using TensorFlow as the backend, called Keras, which is a high-level neural network Python library. In TensorFlow Exercise 1, I was manually defining a neural network, with a few lines of code to take care of it.
The first
. Then this version should be a driver that matches CUDA8 with each other. )
Install cudnn5.1 (HTTPS://DEVELOPER.NVIDIA.COM/CUDNN) unzip the installation package just down, copy the files under these three folders to the Cuda folder below.
After the Anaconda installation is complete, you should be able to see whether the version is 3.5 by tapping Python directly in the Windows Command window.
Create a TensorFlow virtual environment c:> Conda cre
Reprint Please specify:Look at Daniel's small freshness : http://www.cnblogs.com/luruiyuan/This article original website : http://www.cnblogs.com/luruiyuan/p/6660142.htmlThe Ubuntu version I used was 16.04, and using Gnome as the desktop (which doesn't matter) has gone through a lot of twists and turns and finally completed the installation of Keras with TensorFlow as the back end.Installation of the
TensorFlow and Theano and Keras are deep learning frameworks, TensorFlow and Theano are more flexible and difficult to learn, they are actually a differentiator.
Keras is actually TensorFlow and Keras interface (
Keras mixed with TensorFlow Keras and TensorFlow using tensorfow Fly Keras
Recently, TensorFlow has updated its new version to 1.4. Many updates have been made, and it is of course important to add Tf.keras. After all,
This article is void
My next installment is the TensorFlow and Keras truth.
Environment:
Anaconda4.2;python3.5;windows10,64,cuda
Previous hard cuda9.1 useless, we want to use the GPU must choose cuda8.0, I thought the official will be corresponding update, naive. First TensorFlow don't recognize, moreover cudnn own all do not recognize, only 8.0.
The laboratory installed new Keras, found Keras default back end is TensorFlow, want to change back to Theano, see the official document also didn't understand, finally buttoned up, very simple.Description of Chinese document: Keras Chinese document, switch back end
In fact, in C:\Users\75538 (75538 is my windos user
Install keras (tensorflow is the background) and kerastensorflow in Ubuntu
0 System Version Ubuntu16.04
1. system update (the speed is very slow. You can skip this step to see if it will affect subsequent installation)
sudo apt updatesudo apt upgrade
2. Install python Basic Development Kit
sudo apt install -y python-dev python-pip python-nose gcc g++ git gfortran vim
3. Download Anaconda and install it on
the profile file ( Note: If you are not using version 8.0, you need to modify the version number ):→~ Export cuda_home=/usr/local/cuda-8.0→~ Export Path=/usr/local/cuda-8.0/bin${path:+:${path}}→~ Export Ld_library_path=/usr/local/cuda-8.0/lib64${ld_library_path:+:${ld_library_path}}After modification:→~ Source/etc/profileVerify that the configuration is successful:→~ nvcc-vThe following message appears to be successful: 4. Installing the CUDNN Acceleration LibraryThis article uses the CUDA8.0,
Keras Installation:It is best to build in the Anaconda virtual environment:Conda create-n Environment Name python=3.6Enter the environment:Source Activate Environment nameInstall Keras:Pip Install KerasPip Install TheanoPip Install tensorflow-gpu==1.2.0If you use Theano as backend, you need to Conda install PYGPU to support parallel and gou operations.
If Modulenotfounderror:no module named ' Mkl ' appear
Tags: caff href tps medium mode line DAO use UDAToday use Anaconda3 to install TensorFlow and Caffe, the main reference blogNow the computer environment:ubuntu16.04cuda8.0cudnn6.0Anaconda31. From Scipy.misc import imread,imresize errorHint error importerror:cannot import name ImreadBut import scipy is displayed correctly.Solution: Pip install Pillow. 2. Libcublas.so.9.0:cannot open Shared object file:no such file or directoryCause: The new version of
Recently tried to learn tensorflow, but because the problem of learning resources leads to a series of problems, in simple terms, to learn tensorflow, to directly view the guidance of the GitHub, rather than according to the blog, Baidu on the guidance, because the version of the change too fast, similar to the College of Geeks, Blog guidance and code has not run, according to the error step-by-step process
Installing Anaconda3
A key step:conda install pip
The following to install a variety of packages you need, generally no more error.pip install tensorflow-gpu ==1.5.0rc1pip install -U keras
If you need to install Theano, you need to install its dependency package, which isconda install mingw libpythonpip install -U theano
Install OpenCV3 (Windows environment):pip install -U opencv-contrib-pyt
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