TensorFlow 2.0 is not officially released yet, the first official
barrage will be after
TensorFlow 2.0 is released.
Barrage is an opinionated supervised deep learning tool built on top of
TensorFlow 2.x designed to standardize and orchestrate the training and scoring of
complicated models. Barrage is built around a
JSON config and the
TensorFlow 2.x library using the
Official documentation can be found at: https://barrage.readthedocs.io/
- Minimal Code: build well-tested, configurable, and reliable config recipes. Use custom code only when it is absolutely necessary.
- Component Reusability: decompose deep learning dataset processing into fundamental components (e.g. dataset loaders, data transformations, augmentation functions) to maximize reuse between models.
- Process Automation: best practices and artifacting are automatically configured (e.g. saving best checkpoint, creating TensorBoard, etc...) with defaults that can be adjusted in the config.
- Standardize API: takes an opinionated view and selects the production hardened
variant of the many
TensorFlow.KerasAPI choices (e.g. data type choices in model.fit).
- Cross Domain: handles single/multi input/output networks seamlessly across domains (e.g. Computer Vision, Natural Language Processing, Time Series, etc...).
Select Feature Highlights
- Single/multi input/output: flexible across many types of networks.
- Loading: dataset in memory, on disk, in cloud storage, etc ...
- Transforms: fit transforms on a first-pass of the training dataset with the
- pass transform params to network builder (e.g. compute vocabulary size -> embedding layer).
- apply transform at batch time (e.g. mean variance normalization to input).
- undo transform after scoring (e.g. undo mean variance normalization to output).
- Augmentation: chain augmentation functions.
- Sampling: change the number of times a sample is selected in an epoch.
As well as standard
TensorFlow.Keras features such as learning rate scheduling,
sample weights, etc...
# TensorFlow CPU pip install barrage[tensorflow] # TensorFlow GPU pip install barrage[tensorflow-gpu]
git clone https://github.com/briannemsick/barrage cd barrage python setup.py install