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Posted to dev@mxnet.apache.org by "Lupesko, Hagay" <lu...@gmail.com> on 2017/11/16 22:04:05 UTC
AWS contributing ONNX-MXNet
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
Re: AWS contributing ONNX-MXNet
Posted by Mu Li <mu...@gmail.com>.
Thanks for letting the mxnet community know it. Given this new converter is
derived from the nnvm-onnx converted developed by Zhi and Tianqi, see this
link
<https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/common.py#L12>
and that link
<https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/import_helper.py#L12>.
Also the nnvm-onnx converter has been annouced on tvmlang.org
<http://tvmlang.org/2017/10/06/nnvm-compiler-announcement.html> , also with
this tutorial
<http://nnvm.tvmlang.org/tutorials/from_onnx.html#sphx-glr-tutorials-from-onnx-py>.
I
think it is worth to *acknowledge* the contributions from our community
members in the announcement to maintain a healthy connection.
On Thu, Nov 16, 2017 at 2:04 PM, Lupesko, Hagay <lu...@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
>
>
Re: AWS contributing ONNX-MXNet
Posted by Steffen Rochel <st...@gmail.com>.
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 <tq...@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 <lu...@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
> >
> >
>
Re: AWS contributing ONNX-MXNet
Posted by Tianqi Chen <tq...@cs.washington.edu>.
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 <lu...@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
>
>
Re: AWS contributing ONNX-MXNet
Posted by Hen <ba...@apache.org>.
It was contributed to 'ONNX'. Which is a joint Facebook/Microsoft project
of some kind ( http://onnx.ai/ ).
Hen
On Fri, Nov 17, 2017 at 12:35 AM, Isabel Drost-Fromm <is...@apache.org>
wrote:
>
>
> Am 16. November 2017 23:04:05 MEZ schrieb "Lupesko, Hagay" <
> lupesko@gmail.com>:
> >Today AWS announced contributing ONNX-MXNet,
>
>
> Just for clarification: this package is going to be/ intended to be
> contributed where to? Or do you mean "published under a free and open
> source license"?
>
> Isabel
>
> --
> Diese Nachricht wurde von meinem Android-Gerät mit K-9 Mail gesendet.
>
Re: AWS contributing ONNX-MXNet
Posted by Isabel Drost-Fromm <is...@apache.org>.
Am 16. November 2017 23:04:05 MEZ schrieb "Lupesko, Hagay" <lu...@gmail.com>:
>Today AWS announced contributing ONNX-MXNet,
Just for clarification: this package is going to be/ intended to be contributed where to? Or do you mean "published under a free and open source license"?
Isabel
--
Diese Nachricht wurde von meinem Android-Gerät mit K-9 Mail gesendet.
Re: AWS contributing ONNX-MXNet
Posted by "Zha, Sheng" <zh...@amazon.com>.
Hi Hagay,
> But why assume this was done on intention?
Given that you mentioned that you talked to Mu on this, would it be right to assume that you have paid sufficient attention and have been extra careful on acknowledgements already?
> import_onnx.py [1] is the only one that seem to have been missed… Monday to discuss in details.
Sure, happy to talk to you then. I’d like to see the reasons why the other three files I listed don’t deserve acknowledgement.
Given the similarity in the code, I can’t help but conclude that code in one is copied from another source, and in order to do that you must already be aware of the origin of the code. So, how can files can be missed unintentionally? Otherwise, I’ll do my best in assuming the best intention in your actions. Thanks.
Best regards,
-sz
On 11/16/17, 7:04 PM, "Lupesko, Hagay" <lu...@gmail.com> wrote:
Chiming in as well.
First and foremost, I agree wholeheartedly that acknowledgments are due when deserved. In fact, we took care to add acknowledgments in the code, and in the blog post for that precise reason!
I also personally talked with Mu, to make sure these are in order and appropriate, and he had no comments.
Have we missed acknowledgments? Maybe (more on that below). But why assume this was done on intention?
Addressing specific points (I won’t repeat Henri’s points):
- I’m happy to take another look and see whether more files need to have the “ack” statement. But looking into it again, import_onnx.py [1] is the only one that seem to have been missed, and ack was already added. Sheng – I’ll grab some time with you Monday to discuss in details.
- The tutorial itself was actually referenced from PyTorch, not nnvm. This is acknowledged by onnx-mxnet code, as well as the nnvm code.
- We intentionally ack-ed an open source community (dmlc/nnvm) and not individuals. There’s more than Tianqi and Zhi that worked on nnvm and onnx, it is a whole community that we thank to.
- “I was wondering why your below email didn't include such acknowledgement?” – as noted by Hen, the email did include the ack.
One last thing, quoting Sheng: “In general, to have a healthy community, I believe the right things to do would be…”
I would stress out that in order to have a healthy community, we should always assume others have best intentions – this will make us a stronger community, one that works together, and one that if fun to be part of.
Hagay
[1] https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/import_onnx.py
On 11/16/17, 18:06, "Hen" <ba...@apache.org> wrote:
On Thu, Nov 16, 2017 at 4:32 PM, Sheng Zha <sz...@gmail.com> wrote:
> Hi Hagay,
>
> (cc'd Zhi, Tianqi to make sure real authors are aware)
>
>
>
> At first glance the code in the repo you shared (i.e.
> https://github.com/onnx/onnx-mxnet) looks very
>
> familiar, so I did some searching. It looks like *almost all* the code
> are adopted from the *nnvm onnx*
>
> frontend, but the main contributor (*Zhi Zhang*, committer of mxnet, and
> intern at AWS) from this same
>
> community was not given his due credit in your email. To elaborate on why
> I think almost all the
>
> onnx-mxnet code is from nnvm onnx frontend:
>
>
>
> The following is the content of this repo:
>
> ├── LICENSE.txt
>
> ├── README.md
>
> ├── onnx_mxnet
>
> │ ├── __init__.py
>
> │ ├── common.py
>
> │ ├── import_helper.py
>
> │ ├── import_onnx.py
>
> │ └── tests
>
> │ ├── test_models.py
>
> │ └── test_super_resolution.py
>
> ├── setup.py
>
> ├── super_res_input.jpg
>
> └── super_res_output.jpg
>
> (Also attached a screenshot of the commit history of onnx_mxnet at the
> moment, as well as a copy of the git package, in case commit hash mismatch
> happens)
>
>
>
> - Out of the 6 files under onnx_mxnet package
> - the following two files are marked as being derived from nnvm:
> - common.py
> <https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/common.py#L12>
> - import_helper.py
> <https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/import_helper.py#L12>
> - the rest four files that are not marked as being derived from
> nnvm:
> - __init__.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/__init__.py#L15>:
> looks like a copy from nnvm/frontend/onnx.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L392>
> - import_onnx.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/import_onnx.py#L18> looks
> like a copy from nnvm/frontend/onnx.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L345>
> - tests/test_models.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py>
> - this part
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py#L35> looks
> like a copy from nnvm frontend/onnx/model_zoo/__init__.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/frontend/onnx/model_zoo/__init__.py#L7>
> - this part
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py#L63> looks
> like a copy from nnvm frontend/onnx/test_forward.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/frontend/onnx/test_forward.py#L9>
> - tests/test_super_resolution.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_super_resolution.py#L24> looks
> like a copy from nnvm tutorials/from_onnx.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tutorials/from_onnx.py#L22>
>
>
>
>
>
> Looks like in the blog post here
> <https://aws.amazon.com/blogs/ai/announcing-onnx-support-for-apache-mxnet/>,
> there is one line giving credit to nnvm authors:
>
> *"Special thanks to the dmlc/nnvm community, whose ONNX code was used as a
> reference for this implementation."*
>
>
>
> I was wondering why your below email didn't include such acknowledgement?
> In general, to have a healthy community, I believe the right things to do
> would be:
>
> 1. Give the due credit to the original authors in communications.
>
> 2. Keep original authors' names in the file licenses, which is a required
> for apache 2.0 license <http://www.apache.org/licenses/LICENSE-2.0> that
> is used in both packages.
>
> 3. For code that you reorganized, keep a reference of the source from
> which it’s adopted, which is good practice when contributing open-source.
>
On #2 - the Apache license does not require that author's names be kept in
files (I presume you're referring to the Author comment in the tutorial
file as I didn't see any others).
The Apache license requires that (section 4):
- You must give any other recipients of the Work or Derivative Works a copy
of this License; and
- You must cause any modified files to carry prominent notices stating that
You changed the files; and
- You must retain, in the Source form of any Derivative Works that You
distribute, all copyright, patent, trademark, and attribution notices from
the Source form of the Work, excluding those notices that do not pertain to
any part of the Derivative Works; and
- If the Work includes a "NOTICE" text file as part of its distribution,
then any Derivative Works that You distribute must include a readable copy
of the attribution notices contained within such NOTICE file,
Going through each in turn:
1) The repo contains a copy of the Apache 2.0 license,
2) 2 of the 6 files contain prominent notices; I agree that the other 4
should contain a prominent notice if they're derived (I haven't compared
the files, but I don't doubt your research),
3) There are no additional copyright, patent, trademark or attribution
notices in the files copied (this is why Apache requires a source header
for its projects; DMLC does not appear to have source headers on their
files, its equivalent of Apache's legal committee should strongly think
about that standardizing on that for all its projects imo);
4) There is no NOTICE file (again, imo the DMLC legal thinkers should
strongly think about having NOTICE files imo).
So agreed that there's a change to make, but there's no requirement to keep
author's names in files. Note that there is a practice (and it's a
recommended or even mandatory legal practice, I'm not sure which) to keep a
Copyright Owner's name in a file, but author and copyright owner are
different concepts.
Hen
Re: AWS contributing ONNX-MXNet
Posted by "Lupesko, Hagay" <lu...@gmail.com>.
Thanks for your notes Mu.
The tutorial on both nnvm and onnx-mxnet is referenced from ONNX PyTorch tutorial. And both code repos ack that, as appropriate, and without including any specific names.
When I looked at the nnvm onnx code, the commit history shows more than just Tianqi and Zhi, which made it seem more appropriate to refer to the entire dmlc/nnvm community.
Hagay
On 11/16/17, 19:49, "Mu Li" <limu.cn@gmail.com on behalf of muli.cmu@gmail.com> wrote:
Thanks for pointing it out, Hagay. I actually missed the "Special thanks to
dmlc/nnvm team" sentence. I was looking for Zhi and Tianqi's names, because
the onnx converter was mainly done by both of them. However I do not
entirely agree that I "had no comments". I actually pointed out the initial
draft is similar to the nnvm tutorial two days ago. Hagay made a few
updates, but unfortunately, I didn't have a chance to have a look at the
updated version before the announcement. Otherwise, I should leave a
comment to put individual contributors names on it.
On Thu, Nov 16, 2017 at 7:03 PM, Lupesko, Hagay <lu...@gmail.com> wrote:
> Chiming in as well.
>
> First and foremost, I agree wholeheartedly that acknowledgments are due
> when deserved. In fact, we took care to add acknowledgments in the code,
> and in the blog post for that precise reason!
> I also personally talked with Mu, to make sure these are in order and
> appropriate, and he had no comments.
> Have we missed acknowledgments? Maybe (more on that below). But why assume
> this was done on intention?
>
> Addressing specific points (I won’t repeat Henri’s points):
> - I’m happy to take another look and see whether more files need to have
> the “ack” statement. But looking into it again, import_onnx.py [1] is the
> only one that seem to have been missed, and ack was already added. Sheng –
> I’ll grab some time with you Monday to discuss in details.
> - The tutorial itself was actually referenced from PyTorch, not nnvm. This
> is acknowledged by onnx-mxnet code, as well as the nnvm code.
> - We intentionally ack-ed an open source community (dmlc/nnvm) and not
> individuals. There’s more than Tianqi and Zhi that worked on nnvm and onnx,
> it is a whole community that we thank to.
> - “I was wondering why your below email didn't include such
> acknowledgement?” – as noted by Hen, the email did include the ack.
>
> One last thing, quoting Sheng: “In general, to have a healthy community, I
> believe the right things to do would be…”
> I would stress out that in order to have a healthy community, we should
> always assume others have best intentions – this will make us a stronger
> community, one that works together, and one that if fun to be part of.
>
> Hagay
>
> [1] https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/
> import_onnx.py
>
> On 11/16/17, 18:06, "Hen" <ba...@apache.org> wrote:
>
> On Thu, Nov 16, 2017 at 4:32 PM, Sheng Zha <sz...@gmail.com> wrote:
>
> > Hi Hagay,
> >
> > (cc'd Zhi, Tianqi to make sure real authors are aware)
> >
> >
> >
> > At first glance the code in the repo you shared (i.e.
> > https://github.com/onnx/onnx-mxnet) looks very
> >
> > familiar, so I did some searching. It looks like *almost all* the
> code
> > are adopted from the *nnvm onnx*
> >
> > frontend, but the main contributor (*Zhi Zhang*, committer of mxnet,
> and
> > intern at AWS) from this same
> >
> > community was not given his due credit in your email. To elaborate
> on why
> > I think almost all the
> >
> > onnx-mxnet code is from nnvm onnx frontend:
> >
> >
> >
> > The following is the content of this repo:
> >
> > ├── LICENSE.txt
> >
> > ├── README.md
> >
> > ├── onnx_mxnet
> >
> > │ ├── __init__.py
> >
> > │ ├── common.py
> >
> > │ ├── import_helper.py
> >
> > │ ├── import_onnx.py
> >
> > │ └── tests
> >
> > │ ├── test_models.py
> >
> > │ └── test_super_resolution.py
> >
> > ├── setup.py
> >
> > ├── super_res_input.jpg
> >
> > └── super_res_output.jpg
> >
> > (Also attached a screenshot of the commit history of onnx_mxnet at
> the
> > moment, as well as a copy of the git package, in case commit hash
> mismatch
> > happens)
> >
> >
> >
> > - Out of the 6 files under onnx_mxnet package
> > - the following two files are marked as being derived from
> nnvm:
> > - common.py
> > <https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/
> common.py#L12>
> > - import_helper.py
> > <https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/
> import_helper.py#L12>
> > - the rest four files that are not marked as being derived from
> > nnvm:
> > - __init__.py
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/__init__.py#L15>:
> > looks like a copy from nnvm/frontend/onnx.py
> > <https://github.com/dmlc/nnvm/blob/
> 3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L392
> >
> > - import_onnx.py
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/import_onnx.py#L18>
> looks
> > like a copy from nnvm/frontend/onnx.py
> > <https://github.com/dmlc/nnvm/blob/
> 3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L345
> >
> > - tests/test_models.py
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py>
> > - this part
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/
> test_models.py#L35> looks
> > like a copy from nnvm frontend/onnx/model_zoo/__
> init__.py
> > <https://github.com/dmlc/nnvm/blob/
> 3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/
> frontend/onnx/model_zoo/__init__.py#L7>
> > - this part
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/
> test_models.py#L63> looks
> > like a copy from nnvm frontend/onnx/test_forward.py
> > <https://github.com/dmlc/nnvm/blob/
> 3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/
> frontend/onnx/test_forward.py#L9>
> > - tests/test_super_resolution.py
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/
> test_super_resolution.py#L24> looks
> > like a copy from nnvm tutorials/from_onnx.py
> > <https://github.com/dmlc/nnvm/blob/
> 3da53e46db57c438b05fbebe8aa332ee8c5994d1/tutorials/from_onnx.py#L22>
> >
> >
> >
> >
> >
> > Looks like in the blog post here
> > <https://aws.amazon.com/blogs/ai/announcing-onnx-support-
> for-apache-mxnet/>,
> > there is one line giving credit to nnvm authors:
> >
> > *"Special thanks to the dmlc/nnvm community, whose ONNX code was
> used as a
> > reference for this implementation."*
> >
> >
> >
> > I was wondering why your below email didn't include such
> acknowledgement?
> > In general, to have a healthy community, I believe the right things
> to do
> > would be:
> >
> > 1. Give the due credit to the original authors in communications.
> >
> > 2. Keep original authors' names in the file licenses, which is a
> required
> > for apache 2.0 license <http://www.apache.org/licenses/LICENSE-2.0>
> that
> > is used in both packages.
> >
> > 3. For code that you reorganized, keep a reference of the source from
> > which it’s adopted, which is good practice when contributing
> open-source.
> >
>
> On #2 - the Apache license does not require that author's names be
> kept in
> files (I presume you're referring to the Author comment in the tutorial
> file as I didn't see any others).
>
> The Apache license requires that (section 4):
>
> - You must give any other recipients of the Work or Derivative Works a
> copy
> of this License; and
> - You must cause any modified files to carry prominent notices stating
> that
> You changed the files; and
> - You must retain, in the Source form of any Derivative Works that You
> distribute, all copyright, patent, trademark, and attribution notices
> from
> the Source form of the Work, excluding those notices that do not
> pertain to
> any part of the Derivative Works; and
> - If the Work includes a "NOTICE" text file as part of its
> distribution,
> then any Derivative Works that You distribute must include a readable
> copy
> of the attribution notices contained within such NOTICE file,
>
> Going through each in turn:
>
> 1) The repo contains a copy of the Apache 2.0 license,
> 2) 2 of the 6 files contain prominent notices; I agree that the other 4
> should contain a prominent notice if they're derived (I haven't
> compared
> the files, but I don't doubt your research),
> 3) There are no additional copyright, patent, trademark or attribution
> notices in the files copied (this is why Apache requires a source
> header
> for its projects; DMLC does not appear to have source headers on their
> files, its equivalent of Apache's legal committee should strongly think
> about that standardizing on that for all its projects imo);
> 4) There is no NOTICE file (again, imo the DMLC legal thinkers should
> strongly think about having NOTICE files imo).
>
> So agreed that there's a change to make, but there's no requirement to
> keep
> author's names in files. Note that there is a practice (and it's a
> recommended or even mandatory legal practice, I'm not sure which) to
> keep a
> Copyright Owner's name in a file, but author and copyright owner are
> different concepts.
>
> Hen
>
>
>
>
Re: AWS contributing ONNX-MXNet
Posted by Mu Li <mu...@gmail.com>.
Thanks for pointing it out, Hagay. I actually missed the "Special thanks to
dmlc/nnvm team" sentence. I was looking for Zhi and Tianqi's names, because
the onnx converter was mainly done by both of them. However I do not
entirely agree that I "had no comments". I actually pointed out the initial
draft is similar to the nnvm tutorial two days ago. Hagay made a few
updates, but unfortunately, I didn't have a chance to have a look at the
updated version before the announcement. Otherwise, I should leave a
comment to put individual contributors names on it.
On Thu, Nov 16, 2017 at 7:03 PM, Lupesko, Hagay <lu...@gmail.com> wrote:
> Chiming in as well.
>
> First and foremost, I agree wholeheartedly that acknowledgments are due
> when deserved. In fact, we took care to add acknowledgments in the code,
> and in the blog post for that precise reason!
> I also personally talked with Mu, to make sure these are in order and
> appropriate, and he had no comments.
> Have we missed acknowledgments? Maybe (more on that below). But why assume
> this was done on intention?
>
> Addressing specific points (I won’t repeat Henri’s points):
> - I’m happy to take another look and see whether more files need to have
> the “ack” statement. But looking into it again, import_onnx.py [1] is the
> only one that seem to have been missed, and ack was already added. Sheng –
> I’ll grab some time with you Monday to discuss in details.
> - The tutorial itself was actually referenced from PyTorch, not nnvm. This
> is acknowledged by onnx-mxnet code, as well as the nnvm code.
> - We intentionally ack-ed an open source community (dmlc/nnvm) and not
> individuals. There’s more than Tianqi and Zhi that worked on nnvm and onnx,
> it is a whole community that we thank to.
> - “I was wondering why your below email didn't include such
> acknowledgement?” – as noted by Hen, the email did include the ack.
>
> One last thing, quoting Sheng: “In general, to have a healthy community, I
> believe the right things to do would be…”
> I would stress out that in order to have a healthy community, we should
> always assume others have best intentions – this will make us a stronger
> community, one that works together, and one that if fun to be part of.
>
> Hagay
>
> [1] https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/
> import_onnx.py
>
> On 11/16/17, 18:06, "Hen" <ba...@apache.org> wrote:
>
> On Thu, Nov 16, 2017 at 4:32 PM, Sheng Zha <sz...@gmail.com> wrote:
>
> > Hi Hagay,
> >
> > (cc'd Zhi, Tianqi to make sure real authors are aware)
> >
> >
> >
> > At first glance the code in the repo you shared (i.e.
> > https://github.com/onnx/onnx-mxnet) looks very
> >
> > familiar, so I did some searching. It looks like *almost all* the
> code
> > are adopted from the *nnvm onnx*
> >
> > frontend, but the main contributor (*Zhi Zhang*, committer of mxnet,
> and
> > intern at AWS) from this same
> >
> > community was not given his due credit in your email. To elaborate
> on why
> > I think almost all the
> >
> > onnx-mxnet code is from nnvm onnx frontend:
> >
> >
> >
> > The following is the content of this repo:
> >
> > ├── LICENSE.txt
> >
> > ├── README.md
> >
> > ├── onnx_mxnet
> >
> > │ ├── __init__.py
> >
> > │ ├── common.py
> >
> > │ ├── import_helper.py
> >
> > │ ├── import_onnx.py
> >
> > │ └── tests
> >
> > │ ├── test_models.py
> >
> > │ └── test_super_resolution.py
> >
> > ├── setup.py
> >
> > ├── super_res_input.jpg
> >
> > └── super_res_output.jpg
> >
> > (Also attached a screenshot of the commit history of onnx_mxnet at
> the
> > moment, as well as a copy of the git package, in case commit hash
> mismatch
> > happens)
> >
> >
> >
> > - Out of the 6 files under onnx_mxnet package
> > - the following two files are marked as being derived from
> nnvm:
> > - common.py
> > <https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/
> common.py#L12>
> > - import_helper.py
> > <https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/
> import_helper.py#L12>
> > - the rest four files that are not marked as being derived from
> > nnvm:
> > - __init__.py
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/__init__.py#L15>:
> > looks like a copy from nnvm/frontend/onnx.py
> > <https://github.com/dmlc/nnvm/blob/
> 3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L392
> >
> > - import_onnx.py
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/import_onnx.py#L18>
> looks
> > like a copy from nnvm/frontend/onnx.py
> > <https://github.com/dmlc/nnvm/blob/
> 3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L345
> >
> > - tests/test_models.py
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py>
> > - this part
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/
> test_models.py#L35> looks
> > like a copy from nnvm frontend/onnx/model_zoo/__
> init__.py
> > <https://github.com/dmlc/nnvm/blob/
> 3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/
> frontend/onnx/model_zoo/__init__.py#L7>
> > - this part
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/
> test_models.py#L63> looks
> > like a copy from nnvm frontend/onnx/test_forward.py
> > <https://github.com/dmlc/nnvm/blob/
> 3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/
> frontend/onnx/test_forward.py#L9>
> > - tests/test_super_resolution.py
> > <https://github.com/onnx/onnx-mxnet/blob/
> 4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/
> test_super_resolution.py#L24> looks
> > like a copy from nnvm tutorials/from_onnx.py
> > <https://github.com/dmlc/nnvm/blob/
> 3da53e46db57c438b05fbebe8aa332ee8c5994d1/tutorials/from_onnx.py#L22>
> >
> >
> >
> >
> >
> > Looks like in the blog post here
> > <https://aws.amazon.com/blogs/ai/announcing-onnx-support-
> for-apache-mxnet/>,
> > there is one line giving credit to nnvm authors:
> >
> > *"Special thanks to the dmlc/nnvm community, whose ONNX code was
> used as a
> > reference for this implementation."*
> >
> >
> >
> > I was wondering why your below email didn't include such
> acknowledgement?
> > In general, to have a healthy community, I believe the right things
> to do
> > would be:
> >
> > 1. Give the due credit to the original authors in communications.
> >
> > 2. Keep original authors' names in the file licenses, which is a
> required
> > for apache 2.0 license <http://www.apache.org/licenses/LICENSE-2.0>
> that
> > is used in both packages.
> >
> > 3. For code that you reorganized, keep a reference of the source from
> > which it’s adopted, which is good practice when contributing
> open-source.
> >
>
> On #2 - the Apache license does not require that author's names be
> kept in
> files (I presume you're referring to the Author comment in the tutorial
> file as I didn't see any others).
>
> The Apache license requires that (section 4):
>
> - You must give any other recipients of the Work or Derivative Works a
> copy
> of this License; and
> - You must cause any modified files to carry prominent notices stating
> that
> You changed the files; and
> - You must retain, in the Source form of any Derivative Works that You
> distribute, all copyright, patent, trademark, and attribution notices
> from
> the Source form of the Work, excluding those notices that do not
> pertain to
> any part of the Derivative Works; and
> - If the Work includes a "NOTICE" text file as part of its
> distribution,
> then any Derivative Works that You distribute must include a readable
> copy
> of the attribution notices contained within such NOTICE file,
>
> Going through each in turn:
>
> 1) The repo contains a copy of the Apache 2.0 license,
> 2) 2 of the 6 files contain prominent notices; I agree that the other 4
> should contain a prominent notice if they're derived (I haven't
> compared
> the files, but I don't doubt your research),
> 3) There are no additional copyright, patent, trademark or attribution
> notices in the files copied (this is why Apache requires a source
> header
> for its projects; DMLC does not appear to have source headers on their
> files, its equivalent of Apache's legal committee should strongly think
> about that standardizing on that for all its projects imo);
> 4) There is no NOTICE file (again, imo the DMLC legal thinkers should
> strongly think about having NOTICE files imo).
>
> So agreed that there's a change to make, but there's no requirement to
> keep
> author's names in files. Note that there is a practice (and it's a
> recommended or even mandatory legal practice, I'm not sure which) to
> keep a
> Copyright Owner's name in a file, but author and copyright owner are
> different concepts.
>
> Hen
>
>
>
>
Re: AWS contributing ONNX-MXNet
Posted by "Lupesko, Hagay" <lu...@gmail.com>.
Chiming in as well.
First and foremost, I agree wholeheartedly that acknowledgments are due when deserved. In fact, we took care to add acknowledgments in the code, and in the blog post for that precise reason!
I also personally talked with Mu, to make sure these are in order and appropriate, and he had no comments.
Have we missed acknowledgments? Maybe (more on that below). But why assume this was done on intention?
Addressing specific points (I won’t repeat Henri’s points):
- I’m happy to take another look and see whether more files need to have the “ack” statement. But looking into it again, import_onnx.py [1] is the only one that seem to have been missed, and ack was already added. Sheng – I’ll grab some time with you Monday to discuss in details.
- The tutorial itself was actually referenced from PyTorch, not nnvm. This is acknowledged by onnx-mxnet code, as well as the nnvm code.
- We intentionally ack-ed an open source community (dmlc/nnvm) and not individuals. There’s more than Tianqi and Zhi that worked on nnvm and onnx, it is a whole community that we thank to.
- “I was wondering why your below email didn't include such acknowledgement?” – as noted by Hen, the email did include the ack.
One last thing, quoting Sheng: “In general, to have a healthy community, I believe the right things to do would be…”
I would stress out that in order to have a healthy community, we should always assume others have best intentions – this will make us a stronger community, one that works together, and one that if fun to be part of.
Hagay
[1] https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/import_onnx.py
On 11/16/17, 18:06, "Hen" <ba...@apache.org> wrote:
On Thu, Nov 16, 2017 at 4:32 PM, Sheng Zha <sz...@gmail.com> wrote:
> Hi Hagay,
>
> (cc'd Zhi, Tianqi to make sure real authors are aware)
>
>
>
> At first glance the code in the repo you shared (i.e.
> https://github.com/onnx/onnx-mxnet) looks very
>
> familiar, so I did some searching. It looks like *almost all* the code
> are adopted from the *nnvm onnx*
>
> frontend, but the main contributor (*Zhi Zhang*, committer of mxnet, and
> intern at AWS) from this same
>
> community was not given his due credit in your email. To elaborate on why
> I think almost all the
>
> onnx-mxnet code is from nnvm onnx frontend:
>
>
>
> The following is the content of this repo:
>
> ├── LICENSE.txt
>
> ├── README.md
>
> ├── onnx_mxnet
>
> │ ├── __init__.py
>
> │ ├── common.py
>
> │ ├── import_helper.py
>
> │ ├── import_onnx.py
>
> │ └── tests
>
> │ ├── test_models.py
>
> │ └── test_super_resolution.py
>
> ├── setup.py
>
> ├── super_res_input.jpg
>
> └── super_res_output.jpg
>
> (Also attached a screenshot of the commit history of onnx_mxnet at the
> moment, as well as a copy of the git package, in case commit hash mismatch
> happens)
>
>
>
> - Out of the 6 files under onnx_mxnet package
> - the following two files are marked as being derived from nnvm:
> - common.py
> <https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/common.py#L12>
> - import_helper.py
> <https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/import_helper.py#L12>
> - the rest four files that are not marked as being derived from
> nnvm:
> - __init__.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/__init__.py#L15>:
> looks like a copy from nnvm/frontend/onnx.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L392>
> - import_onnx.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/import_onnx.py#L18> looks
> like a copy from nnvm/frontend/onnx.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L345>
> - tests/test_models.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py>
> - this part
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py#L35> looks
> like a copy from nnvm frontend/onnx/model_zoo/__init__.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/frontend/onnx/model_zoo/__init__.py#L7>
> - this part
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py#L63> looks
> like a copy from nnvm frontend/onnx/test_forward.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/frontend/onnx/test_forward.py#L9>
> - tests/test_super_resolution.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_super_resolution.py#L24> looks
> like a copy from nnvm tutorials/from_onnx.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tutorials/from_onnx.py#L22>
>
>
>
>
>
> Looks like in the blog post here
> <https://aws.amazon.com/blogs/ai/announcing-onnx-support-for-apache-mxnet/>,
> there is one line giving credit to nnvm authors:
>
> *"Special thanks to the dmlc/nnvm community, whose ONNX code was used as a
> reference for this implementation."*
>
>
>
> I was wondering why your below email didn't include such acknowledgement?
> In general, to have a healthy community, I believe the right things to do
> would be:
>
> 1. Give the due credit to the original authors in communications.
>
> 2. Keep original authors' names in the file licenses, which is a required
> for apache 2.0 license <http://www.apache.org/licenses/LICENSE-2.0> that
> is used in both packages.
>
> 3. For code that you reorganized, keep a reference of the source from
> which it’s adopted, which is good practice when contributing open-source.
>
On #2 - the Apache license does not require that author's names be kept in
files (I presume you're referring to the Author comment in the tutorial
file as I didn't see any others).
The Apache license requires that (section 4):
- You must give any other recipients of the Work or Derivative Works a copy
of this License; and
- You must cause any modified files to carry prominent notices stating that
You changed the files; and
- You must retain, in the Source form of any Derivative Works that You
distribute, all copyright, patent, trademark, and attribution notices from
the Source form of the Work, excluding those notices that do not pertain to
any part of the Derivative Works; and
- If the Work includes a "NOTICE" text file as part of its distribution,
then any Derivative Works that You distribute must include a readable copy
of the attribution notices contained within such NOTICE file,
Going through each in turn:
1) The repo contains a copy of the Apache 2.0 license,
2) 2 of the 6 files contain prominent notices; I agree that the other 4
should contain a prominent notice if they're derived (I haven't compared
the files, but I don't doubt your research),
3) There are no additional copyright, patent, trademark or attribution
notices in the files copied (this is why Apache requires a source header
for its projects; DMLC does not appear to have source headers on their
files, its equivalent of Apache's legal committee should strongly think
about that standardizing on that for all its projects imo);
4) There is no NOTICE file (again, imo the DMLC legal thinkers should
strongly think about having NOTICE files imo).
So agreed that there's a change to make, but there's no requirement to keep
author's names in files. Note that there is a practice (and it's a
recommended or even mandatory legal practice, I'm not sure which) to keep a
Copyright Owner's name in a file, but author and copyright owner are
different concepts.
Hen
Re: FW: AWS contributing ONNX-MXNet
Posted by Hen <ba...@apache.org>.
On Thu, Nov 16, 2017 at 4:32 PM, Sheng Zha <sz...@gmail.com> wrote:
> Hi Hagay,
>
> (cc'd Zhi, Tianqi to make sure real authors are aware)
>
>
>
> At first glance the code in the repo you shared (i.e.
> https://github.com/onnx/onnx-mxnet) looks very
>
> familiar, so I did some searching. It looks like *almost all* the code
> are adopted from the *nnvm onnx*
>
> frontend, but the main contributor (*Zhi Zhang*, committer of mxnet, and
> intern at AWS) from this same
>
> community was not given his due credit in your email. To elaborate on why
> I think almost all the
>
> onnx-mxnet code is from nnvm onnx frontend:
>
>
>
> The following is the content of this repo:
>
> ├── LICENSE.txt
>
> ├── README.md
>
> ├── onnx_mxnet
>
> │ ├── __init__.py
>
> │ ├── common.py
>
> │ ├── import_helper.py
>
> │ ├── import_onnx.py
>
> │ └── tests
>
> │ ├── test_models.py
>
> │ └── test_super_resolution.py
>
> ├── setup.py
>
> ├── super_res_input.jpg
>
> └── super_res_output.jpg
>
> (Also attached a screenshot of the commit history of onnx_mxnet at the
> moment, as well as a copy of the git package, in case commit hash mismatch
> happens)
>
>
>
> - Out of the 6 files under onnx_mxnet package
> - the following two files are marked as being derived from nnvm:
> - common.py
> <https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/common.py#L12>
> - import_helper.py
> <https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/import_helper.py#L12>
> - the rest four files that are not marked as being derived from
> nnvm:
> - __init__.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/__init__.py#L15>:
> looks like a copy from nnvm/frontend/onnx.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L392>
> - import_onnx.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/import_onnx.py#L18> looks
> like a copy from nnvm/frontend/onnx.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L345>
> - tests/test_models.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py>
> - this part
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py#L35> looks
> like a copy from nnvm frontend/onnx/model_zoo/__init__.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/frontend/onnx/model_zoo/__init__.py#L7>
> - this part
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py#L63> looks
> like a copy from nnvm frontend/onnx/test_forward.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/frontend/onnx/test_forward.py#L9>
> - tests/test_super_resolution.py
> <https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_super_resolution.py#L24> looks
> like a copy from nnvm tutorials/from_onnx.py
> <https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tutorials/from_onnx.py#L22>
>
>
>
>
>
> Looks like in the blog post here
> <https://aws.amazon.com/blogs/ai/announcing-onnx-support-for-apache-mxnet/>,
> there is one line giving credit to nnvm authors:
>
> *"Special thanks to the dmlc/nnvm community, whose ONNX code was used as a
> reference for this implementation."*
>
>
>
> I was wondering why your below email didn't include such acknowledgement?
> In general, to have a healthy community, I believe the right things to do
> would be:
>
> 1. Give the due credit to the original authors in communications.
>
> 2. Keep original authors' names in the file licenses, which is a required
> for apache 2.0 license <http://www.apache.org/licenses/LICENSE-2.0> that
> is used in both packages.
>
> 3. For code that you reorganized, keep a reference of the source from
> which it’s adopted, which is good practice when contributing open-source.
>
On #2 - the Apache license does not require that author's names be kept in
files (I presume you're referring to the Author comment in the tutorial
file as I didn't see any others).
The Apache license requires that (section 4):
- You must give any other recipients of the Work or Derivative Works a copy
of this License; and
- You must cause any modified files to carry prominent notices stating that
You changed the files; and
- You must retain, in the Source form of any Derivative Works that You
distribute, all copyright, patent, trademark, and attribution notices from
the Source form of the Work, excluding those notices that do not pertain to
any part of the Derivative Works; and
- If the Work includes a "NOTICE" text file as part of its distribution,
then any Derivative Works that You distribute must include a readable copy
of the attribution notices contained within such NOTICE file,
Going through each in turn:
1) The repo contains a copy of the Apache 2.0 license,
2) 2 of the 6 files contain prominent notices; I agree that the other 4
should contain a prominent notice if they're derived (I haven't compared
the files, but I don't doubt your research),
3) There are no additional copyright, patent, trademark or attribution
notices in the files copied (this is why Apache requires a source header
for its projects; DMLC does not appear to have source headers on their
files, its equivalent of Apache's legal committee should strongly think
about that standardizing on that for all its projects imo);
4) There is no NOTICE file (again, imo the DMLC legal thinkers should
strongly think about having NOTICE files imo).
So agreed that there's a change to make, but there's no requirement to keep
author's names in files. Note that there is a practice (and it's a
recommended or even mandatory legal practice, I'm not sure which) to keep a
Copyright Owner's name in a file, but author and copyright owner are
different concepts.
Hen
Re: FW: AWS contributing ONNX-MXNet
Posted by Sheng Zha <sz...@gmail.com>.
Hi Hagay,
(cc'd Zhi, Tianqi to make sure real authors are aware)
At first glance the code in the repo you shared (i.e.
https://github.com/onnx/onnx-mxnet) looks very
familiar, so I did some searching. It looks like *almost all* the code are
adopted from the *nnvm onnx*
frontend, but the main contributor (*Zhi Zhang*, committer of mxnet, and
intern at AWS) from this same
community was not given his due credit in your email. To elaborate on why I
think almost all the
onnx-mxnet code is from nnvm onnx frontend:
The following is the content of this repo:
├── LICENSE.txt
├── README.md
├── onnx_mxnet
│ ├── __init__.py
│ ├── common.py
│ ├── import_helper.py
│ ├── import_onnx.py
│ └── tests
│ ├── test_models.py
│ └── test_super_resolution.py
├── setup.py
├── super_res_input.jpg
└── super_res_output.jpg
(Also attached a screenshot of the commit history of onnx_mxnet at the
moment, as well as a copy of the git package, in case commit hash mismatch
happens)
- Out of the 6 files under onnx_mxnet package
- the following two files are marked as being derived from nnvm:
- common.py
<https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/common.py#L12>
- import_helper.py
<https://github.com/onnx/onnx-mxnet/blob/master/onnx_mxnet/import_helper.py#L12>
- the rest four files that are not marked as being derived from nnvm:
- __init__.py
<https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/__init__.py#L15>:
looks like a copy from nnvm/frontend/onnx.py
<https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L392>
- import_onnx.py
<https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/import_onnx.py#L18>
looks
like a copy from nnvm/frontend/onnx.py
<https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/python/nnvm/frontend/onnx.py#L345>
- tests/test_models.py
<https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py>
- this part
<https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py#L35>
looks
like a copy from nnvm frontend/onnx/model_zoo/__init__.py
<https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/frontend/onnx/model_zoo/__init__.py#L7>
- this part
<https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_models.py#L63>
looks
like a copy from nnvm frontend/onnx/test_forward.py
<https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tests/python/frontend/onnx/test_forward.py#L9>
- tests/test_super_resolution.py
<https://github.com/onnx/onnx-mxnet/blob/4ebc02e8f1cc523049f0928b6dbc566a93dd2f47/onnx_mxnet/tests/test_super_resolution.py#L24>
looks
like a copy from nnvm tutorials/from_onnx.py
<https://github.com/dmlc/nnvm/blob/3da53e46db57c438b05fbebe8aa332ee8c5994d1/tutorials/from_onnx.py#L22>
Looks like in the blog post here
<https://aws.amazon.com/blogs/ai/announcing-onnx-support-for-apache-mxnet/>,
there is one line giving credit to nnvm authors:
*"Special thanks to the dmlc/nnvm community, whose ONNX code was used as a
reference for this implementation."*
I was wondering why your below email didn't include such acknowledgement?
In general, to have a healthy community, I believe the right things to do
would be:
1. Give the due credit to the original authors in communications.
2. Keep original authors' names in the file licenses, which is a required
for apache 2.0 license <http://www.apache.org/licenses/LICENSE-2.0> that is
used in both packages.
3. For code that you reorganized, keep a reference of the source from which
it’s adopted, which is good practice when contributing open-source.
Best regards,
-sz
On 11/16/17, 2:04 PM, "Lupesko, Hagay" <lu...@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