Hi Stephan,
You are correct that MyGrad takes an object-oriented design, rather than a
functional one. This enables a more imperative style of workflow [1], which
is how many people approach doing data science in notebooks and REPLs.
MyGrad feels similar to NumPy and PyTorch in this way.
Ultimate
On Sun, Apr 18, 2021 at 9:11 AM Ryan Soklaski wrote:
> MyGrad is not meant to "compete" with the likes of PyTorch and JAX, which
> are fantastically-fast and powerful autodiff libraries. Rather, its
> emphasis is on being lightweight and seamless to use in NumPy-centric
> workflows.
>
Thanks for
All,
I am excited to announce the release of MyGrad 2.0.
MyGrad's primary goal is to make automatic differentiation accessible and
easy to use across the NumPy ecosystem (see [1] for more detailed comments).
Source: https://github.com/rsokl/MyGrad
Docs: https://mygrad.readthedocs.io/en/latest/
