# FastEstimator
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FastEstimator is a high-level deep learning library built on TensorFlow2 and PyTorch. With the help of FastEstimator, you can easily build a high-performance deep learning model and run it anywhere. :wink:
## Prerequisites:
* Python >= 3.6
* TensorFlow >= 2.3.0
* PyTorch >= 1.6.0
## Installation:
### 1. Install Dependencies:
* Install TensorFlow [here](https://www.tensorflow.org/install)
* Install PyTorch [here](https://pytorch.org/get-started/locally/) (for GPU users, **choose CUDA 10.1**)
* Extra Dependencies:
* Windows:
* Install Visual C++ 2015 build tools [here](https://go.microsoft.com/fwlink/?LinkId=691126) and install default option.
* Install latest Visual C++ redistributable [here](https://support.microsoft.com/en-us/help/2977003/the-latest-supported-visual-c-downloads) and choose x86 for 32 bit OS, x64 for 64 bit OS.
* Linux:
``` bash
$ apt-get install libglib2.0-0 libsm6 libxrender1 libxext6
```
* Mac:
``` bash
$ echo No extra dependency needed ":)"
```
### 2. Install FastEstimator:
* Stable (Linux/Mac):
``` bash
$ pip install fastestimator
```
* Stable (Windows):
First download zip file from [available releases](https://github.com/fastestimator/fastestimator/releases)
``` bash
$ pip install fastestimator-x.x.x.zip
```
* Most Recent (Linux/Mac):
``` bash
$ pip install fastestimator-nightly
```
* Most Recent (Windows):
First download zip file [here](https://github.com/fastestimator/fastestimator/archive/master.zip)
``` bash
$ pip install fastestimator-master.zip
```
## Docker Hub
Docker containers create isolated virtual environments that share resources with a host machine. Docker provides an easy way to set up a FastEstimator environment. You can simply pull our image from [Docker Hub](https://hub.docker.com/r/fastestimator/fastestimator/tags) and get started:
* GPU:
``` bash
docker pull fastestimator/fastestimator:latest-gpu
```
* CPU:
``` bash
docker pull fastestimator/fastestimator:latest-cpu
```
## Useful Links:
* [Website](https://www.fastestimator.org): More info about FastEstimator API and news.
* [Tutorial Series](https://github.com/fastestimator/fastestimator/tree/master/tutorial): Everything you need to know about FastEstimator.
* [Application Hub](https://github.com/fastestimator/fastestimator/tree/master/apphub): End-to-end deep learning examples in FastEstimator.
## Citation
Please cite FastEstimator in your publications if it helps your research:
```
@misc{fastestimator,
title = {FastEstimator: A Deep Learning Library for Fast Prototyping and Productization},
author = {Xiaomeng Dong and Junpyo Hong and Hsi-Ming Chang and Michael Potter and Aritra Chowdhury and
Purujit Bahl and Vivek Soni and Yun-Chan Tsai and Rajesh Tamada and Gaurav Kumar and Caroline Favart and
V. Ratna Saripalli and Gopal Avinash},
note = {NeurIPS Systems for ML Workshop},
year = {2019},
url = {http://learningsys.org/neurips19/assets/papers/10_CameraReadySubmission_FastEstimator_final_camera.pdf}
}
```
## License
[Apache License 2.0](https://github.com/fastestimator/fastestimator/blob/master/LICENSE)
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