RE: mxnet slack channel requesat
Please add slack, thanks -Original Message- From: Naveen Swamy [mailto:mnnav...@gmail.com] Sent: Friday, May 25, 2018 9:04 AM To: dev@mxnet.incubator.apache.org Cc: d...@mxnet.apache.org Subject: Re: mxnet slack channel requesat done On Wed, May 23, 2018 at 6:26 PM, ZhangQingsheng < qingshe...@yahoo.com.invalid> wrote: > I would like to join the mxnet slack channel. My email address is > qingshe...@yahoo.com. > > > 发送自 Windows 10 版邮件应用 > >
Re: backward compatibility of models saved with 1.2.0
Hi Mario, I can't give you much details. But it looks there is a bug exporting the parameters' names to a JSON models. I wonder if anybody else in the community has faced this bug. Cheers, On Mon, May 28, 2018 at 5:42 PM, Marco de Abreu < marco.g.ab...@googlemail.com> wrote: > Hello Sergio, > > you are right. We are following semantic versioning and thus, every model > produced within the same major version (e.g.1.x) has to be backwards > compatible. > > Could you please provide a small example so we can reproduce this? We > definitely do not want our users to retrain their model if they update > MXNet. That's a serious issue and we'd love to follow up. > > Best regards, > Marco > > Sergio Fernández schrieb am Di., 29. Mai 2018, 02:35: > > > Hi, > > > > I can't find anything related on that in the 1.2.-0-incubating changelog, > > so I assume models produced by the latest version would be backward > > compatible with old versions, such as 1.1.0. But we've found that the > > parameter model produced is very different and doesn't load. > > > > Can you point me to any documentation that could help us to load the > model > > in 1.1.0 without re-training? > > > > Thanks. > > >
Re: backward compatibility of models saved with 1.2.0
Created a github issue detailing the problem with a reproducible example: https://github.com/apache/incubator-mxnet/issues/11091 Thanks, Thomas 2018-05-29 11:50 GMT-07:00 Sergio Fernández : > Hi Mario, > > I can't give you much details. But it looks there is a bug exporting the > parameters' names to a JSON models. > > I wonder if anybody else in the community has faced this bug. > > Cheers, > > > On Mon, May 28, 2018 at 5:42 PM, Marco de Abreu < > marco.g.ab...@googlemail.com> wrote: > > > Hello Sergio, > > > > you are right. We are following semantic versioning and thus, every model > > produced within the same major version (e.g.1.x) has to be backwards > > compatible. > > > > Could you please provide a small example so we can reproduce this? We > > definitely do not want our users to retrain their model if they update > > MXNet. That's a serious issue and we'd love to follow up. > > > > Best regards, > > Marco > > > > Sergio Fernández schrieb am Di., 29. Mai 2018, > 02:35: > > > > > Hi, > > > > > > I can't find anything related on that in the 1.2.-0-incubating > changelog, > > > so I assume models produced by the latest version would be backward > > > compatible with old versions, such as 1.1.0. But we've found that the > > > parameter model produced is very different and doesn't load. > > > > > > Can you point me to any documentation that could help us to load the > > model > > > in 1.1.0 without re-training? > > > > > > Thanks. > > > > > >
Re: backward compatibility of models saved with 1.2.0
Thanks Thomas for producing a minimal example to reproduce the issue. On Tue, May 29, 2018 at 3:49 PM Thomas DELTEIL wrote: > Created a github issue detailing the problem with a reproducible example: > https://github.com/apache/incubator-mxnet/issues/11091 > > Thanks, > > Thomas > > 2018-05-29 11:50 GMT-07:00 Sergio Fernández : > > > Hi Mario, > > > > I can't give you much details. But it looks there is a bug exporting the > > parameters' names to a JSON models. > > > > I wonder if anybody else in the community has faced this bug. > > > > Cheers, > > > > > > On Mon, May 28, 2018 at 5:42 PM, Marco de Abreu < > > marco.g.ab...@googlemail.com> wrote: > > > > > Hello Sergio, > > > > > > you are right. We are following semantic versioning and thus, every > model > > > produced within the same major version (e.g.1.x) has to be backwards > > > compatible. > > > > > > Could you please provide a small example so we can reproduce this? We > > > definitely do not want our users to retrain their model if they update > > > MXNet. That's a serious issue and we'd love to follow up. > > > > > > Best regards, > > > Marco > > > > > > Sergio Fernández schrieb am Di., 29. Mai 2018, > > 02:35: > > > > > > > Hi, > > > > > > > > I can't find anything related on that in the 1.2.-0-incubating > > changelog, > > > > so I assume models produced by the latest version would be backward > > > > compatible with old versions, such as 1.1.0. But we've found that the > > > > parameter model produced is very different and doesn't load. > > > > > > > > Can you point me to any documentation that could help us to load the > > > model > > > > in 1.1.0 without re-training? > > > > > > > > Thanks. > > > > > > > > > >
Good First Issue label
Just wanted to bring everyone's attention to the label: Good First Issue. When you're going through new issues and labelling, keep this one in mind, so there are opportunities for new members to the project. I think a lot of people would like to contribute, but often the issues are so complex they don't know where or how to start. If you see a pattern in issues or a task that can be broken up into manageable bits, create a Good First Issue - something that is clear and attainable. I think the other similar label, Call for Contribution, encompasses larger feature sets, rather than introductory kinds of contributions. Cheers, Aaron
Re: Good First Issue label
Awesome! On Tue, May 29, 2018, 6:03 PM Aaron Markham wrote: > Just wanted to bring everyone's attention to the label: Good First Issue. > > When you're going through new issues and labelling, keep this one in mind, > so there are opportunities for new members to the project. I think a lot of > people would like to contribute, but often the issues are so complex they > don't know where or how to start. > > If you see a pattern in issues or a task that can be broken up into > manageable bits, create a Good First Issue - something that is clear and > attainable. I think the other similar label, Call for Contribution, > encompasses larger feature sets, rather than introductory kinds of > contributions. > > Cheers, > Aaron >
