Catalyst – Accelerated DL & RL
tl;dr
– collect all the technical, dev-heavy, Deep Learning stuff in a framework
– make it easy to re-use boring day-to-day components
– focus on research and hypothesis testing in our projects
Most of the time in Deep Learning all you need to do is to specify the model dataflow, or how batches of data should be fed to the model. Why then, so much of our time is spent implementing those pipelines and debugging training loops rather than developing something new?
They think that it is possible to separate the engineering from the research so that we can invest our time once in the high-quality, reusable engineering backbone and use it across all the projects.
That is how Catalyst was born – an Open Source PyTorch framework, that allows you to write compact but full-features pipelines and let you focus on the core part of your project.
Link: https://github.com/catalyst-team/catalyst
Official TG channel: https://t.me/catalyst_team
tl;dr
– collect all the technical, dev-heavy, Deep Learning stuff in a framework
– make it easy to re-use boring day-to-day components
– focus on research and hypothesis testing in our projects
Most of the time in Deep Learning all you need to do is to specify the model dataflow, or how batches of data should be fed to the model. Why then, so much of our time is spent implementing those pipelines and debugging training loops rather than developing something new?
They think that it is possible to separate the engineering from the research so that we can invest our time once in the high-quality, reusable engineering backbone and use it across all the projects.
That is how Catalyst was born – an Open Source PyTorch framework, that allows you to write compact but full-features pipelines and let you focus on the core part of your project.
Link: https://github.com/catalyst-team/catalyst
Official TG channel: https://t.me/catalyst_team