BxTorch 0.7.3

Large-Scale Machine and Deep Learning in PyTorch.

BxTorch

BxTorch is a high-level library for large-scale machine learning in PyTorch. It is engineered both to cut obsolete boilerplate code while preserving the flexibility of PyTorch to create just about any deep learning model.

Installation

BxTorch is available on PyPi, so simply run the following command:

pip install bxtorch

Features

Generally, BxTorch provides an object-oriented approach to abstracting PyTorch's API. The core design objective is to provide an API both as simple and as extensible as possible. The goal of this library is to be able to iterate between different models easily instead of squeezing out milliseconds where it is not required.

Still, being focused on large-scale machine learning, BxTorch aims to make it as easy as possible working with large datasets. This includes out-of-the-box multi-GPU support where the user does not need to write a single line of code. Currently, BxTorch only provides means for running training/inference on a single machine. In case this is insufficient, you might be better off using PyTorch's distributed package directly.

It must be emphasized that BxTorch is not meant to be a wrapper for PyTorch as Keras is for TensorFlow - it only provides extensions.

Documentation

Examples of the usage of BxTorch can be found in the docs folder. Method documentation is currently only available as docstrings.

License

BxTorch is licensed under the MIT License.