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From Leonard Lausen <lau...@apache.org>
Subject RE: [VOTE] Release Apache MXNet (incubating) version 1.7.0.rc0
Date Mon, 13 Jul 2020 20:35:48 GMT
One of the selling points of MXNet is (or used to be) speed and having multiple
releases in series with speed regressions may not be acceptable to users that
adopted MXNet based on the speed advantage. Should we vote on a 1.7 Beta release
and only vote on 1.7 final release once the regressions have been fixed?

On Mon, 2020-07-13 at 19:33 +0000, Patrick Mu wrote:
> It happens only on CPU, and I did more runs and found that the runtime
> fluctuates very badly, but the average regression is ~10%.
> 
> 
> Through the previous benchmarks I also found some worse regression comparing
> 1.6 to 1.5 like inception inference on CPU and those regression was not
> caught.
> 
> My 2-cent is it might not be a blocker for the release, and we can have room
> for improvement for upcoming 2.0 and 1.7.1 if necessary
> 
> Ziyi
> 
> On 2020/07/13 08:40:32, "Chen, Ciyong" <ciyong.chen@intel.com> wrote:
> > Thanks Ziyi,
> > 
> > May I know which platform did you notice the performance regression, CPU or
> > GPU? ~20% regression would be a large gap.
> > 
> > Thanks,
> > -Ciyong
> > 
> > -----Original Message-----
> > From: Patrick Mu <zm2263@columbia.edu>
> > Sent: Monday, July 13, 2020 4:13 PM
> > To: dev@mxnet.apache.org
> > Subject: Re: RE: [VOTE] Release Apache MXNet (incubating) version 1.7.0.rc0
> > 
> > Hi Ciyong,
> > 
> > I have reverted the commit, and I am able to train Yolov3 with no problem.
> > 
> > However I also noticed there is a ~20% regression in 1.7 comparing with 1.6
> > in inference Yolov3 with Module API, so we are going to discuss tomorrow if
> > that would be an issue for 1.7.
> > 
> > Thanks,
> > Ziyi
> > 
> > On 2020/07/13 02:19:28, "Chen, Ciyong" <ciyong.chen@intel.com> wrote:
> > > Hi Ziyi, Xingjian,
> > > 
> > > Thanks for reporting the issues from GluonCV/AutoGluon perspective.
> > > I just did a quick try by reverting the 
> > > https://github.com/apache/incubator-mxnet/pull/18358, then the behavior is
> > > same as 1.6.0 with the cases in the gist (
> > > https://gist.github.com/sxjscience/944066c82e566f1b89b01fa226678890).
> > > 
> > > Considering there's many end-users using Gluon based API/models, and
> > > introducing a new patch to fix this issue could be risky, so I agree that
> > > reverting this PR (#18358) might be the best option for the 1.7.0 release.
> > > But I'm considering is there any other test cases to cover this feature,
> > > which could be helpful to track this kind of code changes in future, or
> > > can you help to verify if this revert do resolve the broken issue at your
> > > side?
> > > 
> > > > Thus, the real issue is: Should we supporting pickling a Gluon Block?
If
> > > > not, should we support combining multiprocessing.pool with the Gluon
> > > > Block?
> > > Seems it's more like a new feature for MXNet Gluon Block, probably we can
> > > make it available in the next patch/minor release?
> > > 
> > > Thanks,
> > > -Ciyong
> > > 
> > > -----Original Message-----
> > > From: Xingjian SHI <xshiab@connect.ust.hk>
> > > Sent: Saturday, July 11, 2020 4:27 AM
> > > To: dev@mxnet.incubator.apache.org; dev@mxnet.apache.org
> > > Subject: Re: [VOTE] Release Apache MXNet (incubating) version 1.7.0.rc0
> > > 
> > > Thanks Ziyi,
> > > 
> > > I've discovered the same issue when I'm trying to use AutoGluon with
> > > 1.7.0rc0 and would like to share my finding:
> > > 
> > > Basically, I don't think Gluon Block is designed to be pickleble. But
> > > pickling do work for some cases in the old version:
> > > 
> > > I've included two cases in the gist (
> > > https://gist.github.com/sxjscience/944066c82e566f1b89b01fa226678890).
> > > 
> > > - Case1: we construct a gluon block, hybridize it and feed one NDArray to
> > > help initialize the block. After that, it will no longer be pickleble.
> > > - Case2: we just construct a gluon block and it will be pickleble in
> > > 1.6.0, but won't be pickleble in 1.7.0.
> > > 
> > > Thus, the real issue is: Should we supporting pickling a Gluon Block? If
> > > not, should we support combining multiprocessing.pool with the Gluon
> > > Block? For reference, PyTorch supports pickling the nn.Module as shown in:
> > > https://gist.github.com/sxjscience/90b812a66d445e759c55eedc3ef93668 and
> > > also in the doc (
> > > https://pytorch.org/tutorials/beginner/saving_loading_models.html).
> > > 
> > > Best,
> > > Xingjian
> > > 
> > > 
> > > ´╗┐On 7/10/20, 11:31 AM, "Patrick Mu" <zm2263@columbia.edu> wrote:
> > > 
> > >     Hi Ciyong,
> > > 
> > >     I just discovered an issue with the 1.7, which causes the Yolo
> > > training with latest Gluon CV Yolo to fail.
> > > 
> > >     The PR that causes the failure is 
> > > https://github.com/apache/incubator-mxnet/pull/18358, which
> > > modifies  basic blocks of Gluon to fix a memory leak issue.
> > > 
> > >     Talked with Leonard, the author of the PR, and he said he found the
> > > root cause, but patching that PR would modifies those Gluon basic blocks
> > > further, which might be risky towards existing models and various customer
> > > models.
> > > 
> > >     So my 2-cents is reverting this PR in 1.7, and try patching the PR in
> > > 1.x and 2.0, meaning that the 1.7 won't have memory usage optimized by
> > > that feature.
> > > 
> > >     I'd like to hear what you think about this issue.
> > > 
> > >     Thanks,
> > >     Ziyi
> > > 
> > > 
> > >     On 2020/07/10 06:18:02, "Chen, Ciyong" <ciyong.chen@intel.com> wrote:
> > >     > Hi Community,
> > >     >
> > >     > I would like to call for action to test/validate/vote for the
> > > release candidate (1.7.0.rc0)
> > >     > As there's not any voting result during the scheduled time window,
I
> > > would like to extend the time windows to July 13, 23:59:59 PST.
> > >     > Please prepare your time and provide feedback if you've tried with
> > > the pre-release code bases, thanks!
> > >     >
> > >     > Best regards,
> > >     > Ciyong
> > >     >
> > >     > -----Original Message-----
> > >     > From: Chen, Ciyong <ciyong.chen@intel.com>
> > >     > Sent: Monday, July 6, 2020 10:48 PM
> > >     > To: dev@mxnet.apache.org
> > >     > Cc: Bob Paulin <bob@apache.org>; Henri Yandell <bayard@apache.org>;
> > > Jason Dai <jasondai@apache.org>; Markus Weimer <weimer@apache.org>;
> > > Michael Wall <mjwall@apache.org>
> > >     > Subject: RE: [VOTE] Release Apache MXNet (incubating) version
> > > 1.7.0.rc0
> > >     >
> > >     > For the language bindings and windows platform, may I have your
> > > support to help verify these features? Thanks!
> > >     >
> > >     > @lanking520 to help verify the Scala/Java @gigasquid to help verify
> > > the Clojure
> > >     > @hetong007 to help verify the R
> > >     > @yajiedesign to help verify the windows platform
> > >     >
> > >     > Best regards,
> > >     > Ciyong Chen
> > >     >
> > >     > -----Original Message-----
> > >     > From: Chen, Ciyong <ciyong.chen@intel.com>
> > >     > Sent: Monday, July 6, 2020 10:39 PM
> > >     > To: dev@mxnet.apache.org
> > >     > Cc: Bob Paulin <bob@apache.org>; Henri Yandell <bayard@apache.org>;
> > > Jason Dai <jasondai@apache.org>; Markus Weimer <weimer@apache.org>;
> > > Michael Wall <mjwall@apache.org>
> > >     > Subject: [VOTE] Release Apache MXNet (incubating) version 1.7.0.rc0
> > >     >
> > >     > Dear MXNet community,
> > >     >
> > >     > This is the vote to release Apache MXNet (incubating) version 1.7.0.
> > > Voting will start July 6, 23:59:59 PST and close on July 9, 23:59:59 PST.
> > >     >
> > >     > Link to release notes:
> > >     > 
> > > https://cwiki.apache.org/confluence/display/MXNET/1.7.0+Release+notes
> > >     >
> > >     > Link to release candidate:
> > >     > https://github.com/apache/incubator-mxnet/releases/tag/1.7.0.rc0
> > >     >
> > >     > Link to source and signatures on apache dist server:
> > >     > 
> > > https://dist.apache.org/repos/dist/dev/incubator/mxnet/1.7.0.rc0<https://dist.apache.org/repos/dist/dev/incubator/mxnet/1.7.0.rc0/
> > > >
> > >     >
> > >     > Please remember to TEST first before voting accordingly:
> > >     > +1 = approve
> > >     > +0 = no opinion
> > >     > -1 = disapprove (provide reason)
> > >     >
> > >     > Additional notes:
> > >     >
> > >     >   *   There was an issue and discussion[1] regarding on a few numpy
> > > operators failed due to numpy 1.19.0 released on Jun 20, 2020, which
> > > exists in all branches (works with numpy <= 1.18.5). As numpy operator is
> > > still an experimental feature in 1.7.0 release and mainly targeting in
> > > MXNet 2.0 release, so I decided to not block the voting and instead let
> > > the Community decide whether this is a blocker for the release.
> > >     >
> > >     > [1] https://github.com/apache/incubator-mxnet/issues/18600
> > >     >
> > >     > Best regards,
> > >     > Ciyong Chen
> > >     >
> > >     >
> > > 
> > > 


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