AdaNet is a lightweight and scalable TensorFlow AutoML framework for training and deploying adaptive neural networks using the AdaNet algorithm [Cortes et al. ICML 2017]. AdaNet combines several learned subnetworks in order to mitigate the complexity inherent in designing effective neural networks.
This is not an official Google product.
To get you started:
Requires Python 2.7, 3.4, 3.5, or 3.6.
adanet
depends on bug fixes and enhancements not present in TensorFlow releases prior to 1.9. You must install or upgrade your TensorFlow package to at least 1.9:
$ pip install "tensorflow>=1.9.0"
You can use the pip package manager to install the official adanet
package from PyPi:
$ pip install adanet
To install from source first you'll need to install bazel
following their installation instructions.
Next clone adanet
and cd
into its root directory:
$ git clone https://github.com/tensorflow/adanet && cd adanet
From the adanet
root directory run the tests:
$ cd adanet
$ bazel test -c opt //...
Once you have verified that everything works well, install adanet
as a pip package .
You are now ready to experiment with adanet
.
import adanet
AdaNet is released under the Apache License 2.0.