Awesome
TensorFlow 2.0 Tutorials
Our repo. is the Winner of ⚡#PoweredByTF 2.0 Challenge!.
<p align="center"> <img src="res/tensorflow-2.0.gif" width="250" align="middle"> </p>Timeline:
- Oct. 1, 2019: TensorFlow 2.0 Stable!
- Aug. 24, 2019: TensorFlow 2.0 rc0
- Jun. 8, 2019: TensorFlow 2.0 Beta
- Mar. 7, 2019: Tensorflow 2.0 Alpha
- Jan. 11, 2019: TensorFlow r2.0 preview
- Aug. 14, 2018: TensorFlow 2.0 is coming
Installation
make sure you are using python 3.x.
- CPU install
pip install tensorflow -U
- GPU install
Install CUDA 10.0
(or after) and cudnn
by yourself. and set LD_LIBRARY_PATH
up.
pip install tensorflow-gpu -U
Test installation:
In [2]: import tensorflow as tf
In [3]: tf.__version__
Out[3]: '2.0.0'
In [4]: tf.test.is_gpu_available()
...
totalMemory: 3.95GiB freeMemory: 3.00GiB
...
Out[4]: True
配套TF2视频教程
<p align="center"> <a href="https://study.163.com/course/courseMain.htm?share=2&shareId=480000001847407&courseId=1209092816&_trace_c_p_k2_=dca16f8fd11a4525bac8c89f779b2cfa"> <img src="res/cover.png" width="400"> </a> <a href="https://study.163.com/course/courseMain.htm?share=2&shareId=480000001847407&courseId=1209092816&_trace_c_p_k2_=dca16f8fd11a4525bac8c89f779b2cfa"> <img src="res/TF_QR_163.png"> </a> </p>TensorFlow 2.0的视频教程链接:深度学习与TensorFlow 2实战
Acknowledgement
- 爱可可-爱生活 友情推荐
Includes
- TensorFlow 2.0 Overview
- TensorFlow 2.0 Basic Usage
- Linear Regression
- MNIST, FashionMNIST
- CIFAR10
- Fully Connected Layer
- VGG16
- Inception Network
- ResNet18
- Naive RNN
- LSTM
- ColorBot
- Auto-Encoders
- Variational Auto-Encoders
- DCGAN
- CycleGAN
- WGAN
- Pixel2Pixel
- Faster RCNN
- A2C
- GPT
- BERT
- GCN
Feel free to submit a PR request to make this repo. more complete!
Refered Repos.
Our work is not built from scratch. Great appreciation to these open works!
- https://github.com/madalinabuzau/tensorflow-eager-tutorials
- https://github.com/herbiebradley/CycleGAN-Tensorflow
- https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/eager/python/examples/pix2pix/pix2pix_eager.ipynb
- https://github.com/moono/tf-eager-on-GAN
- https://github.com/Viredery/tf-eager-fasterrcnn
- https://github.com/github/gitignore/blob/master/Python.gitignore