Tensorflow2.0 learning (a)

Master information platform : the basis of today learn about Tensorflow2.0

Core library, @ tf.function, can easily be dynamic graphic language, become a static map, calculated in a way to accelerate

TensorFlow Lite

TensorFlow.JS

TensorFlow Extended 

Constitute TensorFlow ecosystem

Advantage:

1, GPU acceleration

When large amounts of data reflected in the calculation, the computation time. If the CPU operation, the calculations are completed by serial mode

GPU will speed operation, parallel operation, fast run.

2, automatic derivative

It comes with automatic derivation tool to facilitate rapid derivation.

3, neural network

Direct call interface TensorFlow provided, we do not need to own to achieve.

tf.matmul                     layers.Demse

tf.nn.conv2d                layers.Conv2D

tf.nn.relu                      layers.SimpleRNN

tf.nn.max_pool2d        layers.LSTM

tf.nn.sigmoid               layers.RelU

tf.nn.softmax              layers.MaxPool2D

First, the installation environment

Win10 

Anaconda 、Python3.7

CUDA 10.0 cuDNN

TensorFlow 2.0

PyCharm

1, Anaconda installation, not repeat them here, not the friends themselves Baidu

Tests are not installed Anaconda, directly open the command line, type: conda list

Contents shown below will appear, i.e. installation

 

2, CUDA installation

Before installation, assuming your PC is Nvidia graphics card, the graphics cards GTX 1060 6g

CUDA is mounted has the following steps

(1) CUDA drive itself is mounted

(2) CUDA is mounted cuDNN

(3) configuration settings

Download CUDA

https://developer.nvidia.com/cuda-10.0-download-archive?target_os=Windows&target_arch=x86_64&target_version=10&target_type=exelocal

 

 

After the download is complete, double-click operation

 

 

 

 

 

GeForce removed

Launched CUDA, if the VS installation, can be installed, if not installed, removed, or easy error

 

Wait for the installation to complete

 

After installation, the default path, to see if the installation was successful

 

 

If they are present, and the installation is not being given, so that the installation was successful

Here we are then install cuDNN, Download:

https://developer.nvidia.com/rdp/cudnn-download

 


Once downloaded, unpacked we'll get a folder cuda asking about the price, we will cuda folder renamed, cudnn

 

Then copy cudnn installation path to go below cuda

 

Environment variable configuration, this computer, right property,

 

 

 

After installing cuda, will automatically help us to add two environment variables which

 

We also need to add the path cudnn, and the CUPTI

 

These few lines specified, must have a 4 lines. Or will be error

We next tested to see if the installation is complete, cmd, enter nvcc -V, the following appears, then the installation is complete, the version number

 

Today introduced here, next time we continue to learn.
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Origin www.cnblogs.com/1994jinnan/p/11955122.html