mxnet-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Steffen Rochel <steffenroc...@gmail.com>
Subject Re: AWS contributing ONNX-MXNet
Date Mon, 20 Nov 2017 16:37:43 GMT
We modified the blog post and acknowledged Zhi's contributions.
It reads now: "*Special thanks to the dmlc/nnvm community and Zhi Zhang,
whose ONNX code was used as a reference for this implementation."*

Regards,
Steffen

On Fri, Nov 17, 2017 at 10:36 AM Tianqi Chen <tqchen@cs.washington.edu>
wrote:

> I have watched the issue for around two days. Here are my two cents.
>
> First of all, there is no legal constraint to enforce you do anything, but
> as you said(which I fully agree on), we need to assume others have best
> intentions and give goodwill
>
> - It is  great to reuse code, that is what open-source is about
>
> - It is un-arguably true that Zhi created and maintained most of part of
> the original code. While there are minor contributions from other
> contributors. I think Zhi should be personally acknowledged at least(he
> deserve more than that).
>       - As an analogy,  you are not the only one creating the onnx-mxnet
> repo, but never the less you are listed as the author, instead of simply
> saying that comes from AWS
>
> - I would recommend you start with the files of nnvm as your first commit,
> then apply changes to it.
>      - This will take around 5 min or so, copy the file from nnvm, commit,
> override with your new file, commit
>      - It makes it clear what changes are being done
>      - It makes your life easier to adopt new patches when there is a
> bugfix in nnvm or vice versa
>
>
> - Please maintain it, instead of leaving the job to the community. As with
> every great prize comes with great responsibility,  it is great that you
> push out the repo and takes the credit for doing it. The deep learning
> serializable IR land is still unstable and there demand the efforts to put
> in to maintain the code to keep up with the breaking changes and add
> coverage.
>
> Congrats on the release
> Tianqi
>
>
>
> On Thu, Nov 16, 2017 at 2:04 PM, Lupesko, Hagay <lupesko@gmail.com> wrote:
>
> > Hey folks,
> >
> >
> >
> > Today AWS announced contributing ONNX-MXNet, an open source Python
> package
> > that imports ONNX models into MXNet. @roshrini and I (@lupesko) have
> worked
> > on the code, which is now publicly available [1], and published a blog
> post
> > demonstrating usage of the package [2]. Special thanks to dmlc/nnvm team,
> > whose ONNX code was used as a reference for this implementation.
> >
> >
> >
> > What is ONNX?
> >
> > ONNX is an open source format to encode deep learning models. ONNX
> defines
> > a format to store neural network's computational graph, as well as a
> > storage format for operators used within a neural network graph. For more
> > details, check out onnx.ai [3].
> >
> >
> >
> > Why I think ONNX is important for MXNet?
> >
> > ONNX is an emerging standard, that holds a lot of potential for Deep
> > Learning practitioners. With ONNX, people can create and train a network
> > with framework A, and deploy it for inference with framework B. The blog
> > post we published demonstrates using a Super Res model trained with
> > PyTorch, and importing it into MXNet Symbolic API for inference. I
> strongly
> > believe that adopting ONNX early on adds value for deep learning
> > practitioners, and thus supporting it adds value for MXNet as well.
> >
> >
> >
> > As for next steps, I was thinking that porting the functionality and code
> > into MXNet is the logical next step.
> >
> > Would love to get the community's feedback and contributions!
> >
> >
> >
> > [1] https://github.com/onnx/onnx-mxnet
> >
> > [2] https://aws.amazon.com/blogs/ai/announcing-onnx-support-
> > for-apache-mxnet/
> >
> > [3] https://onnx.ai
> >
> >
>

Mime
  • Unnamed multipart/alternative (inline, None, 0 bytes)
View raw message