pyblaze 1.1.6

Large-Scale Machine and Deep Learning in PyTorch.

PyBlaze

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

Features

Generally, PyBlaze provides an object-oriented approach to extend PyTorch's API. The core design objective is to provide an API both as simple and as extensible as possible. PyBlaze's features include the following:

• Training and prediction loops with minimal code required and callback support.
• Out-of-the-box multi-GPU support where not a single additional line of code is required.
• Intuitive multiprocessing by providing easy for-loop vectorization.
• Modules and functions missing in PyTorch.

Currently, PyBlaze 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 PyBlaze is not meant to be a wrapper for PyTorch as Keras is for TensorFlow - it only provides extensions.

Installation

PyBlaze is available on PyPi and can simply be installed as follows:

pip install pyblaze

Quickstart

An introduction to PyBlaze is given as a tutorial training an image classifier. It can be found in the documentation's guide section.

License

PyBlaze is licensed under the MIT License.