FastEstimator

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. 😉

Prerequisites:

• Python >= 3.6
• TensorFlow == 2.4.1
• PyTorch >= 1.7.1

Installation:

1. Install Dependencies:

• Install TensorFlow here

• Install PyTorch here (for GPU users, choose CUDA 11.0)

• Extra Dependencies:

  • Windows:

    • Install Visual C++ 2015 build tools here and install default option.

    • Install latest Visual C++ redistributable here and choose x86 for 32 bit OS, x64 for 64 bit OS.

  • Linux:

    $ apt-get install libglib2.0-0 libsm6 libxrender1 libxext6

  • Mac:

    $ echo No extra dependency needed ":)"

2. Install FastEstimator:

• Stable (Linux/Mac):

  $ pip install fastestimator

• Stable (Windows):

  First download zip file from available releases

  $ pip install fastestimator-x.x.x.zip

• Most Recent (Linux/Mac):

  $ pip install fastestimator-nightly

• Most Recent (Windows):

  First download zip file here

  $ 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 and get started:

• GPU:

  docker pull fastestimator/fastestimator:latest-gpu

• CPU:

  docker pull fastestimator/fastestimator:latest-cpu

Useful Links:

• Website: More info about FastEstimator API and news.
• Tutorial Series: Everything you need to know about FastEstimator.
• Application Hub: 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