Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2020-07-22 Thread Sheng Zha
@fhieber we are planning to release the first public beta on this somewhere in 
August. At the moment we are finalizing some API changes and also validating 
them in GluonNLP. We will publish a transition doc as part of the public beta.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2020-07-22 Thread Felix Hieber
@szha is there a recent estimate on the timeline for MXNet 2.0? Would you 
recommend to develop downstream toolkits (e.g. Sockeye) against the master 
branch now or rather wait a little bit longer?
Is there already documentation on how to transition MXNet 1.x projects to 2.x?

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2020-04-13 Thread Da Zheng
A quick comment: DGL contains all sampling implementation and no longer relies 
on the implementation in MXNet. I think we should deprecate the graph sampling 
implementation in MXNet.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2020-03-29 Thread lilongyue
> @lilongyue the integration of bytePS to mxnet is in this PR #17555
that's great !



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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2020-03-28 Thread Haibin Lin
@lilongyue the integration of bytePS to mxnet is in this PR 
https://github.com/apache/incubator-mxnet/pull/17555

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2020-03-27 Thread lilongyue
@szha 
i checked some docs and projects about distributed training ,
'Horovod' is project from uber team , 'Gloo' is project from facebook team.
The basic idea is to use trick from HPC computing field which is more efficient 
then traditional param-server:
http://andrew.gibiansky.com/blog/machine-learning/baidu-allreduce/?from=timeline
There is a tool called openmpi on which the 'Horvod' project is based ,but i 
found openmpi is too difficult to configure and use .
I also check the 'Gloo' which seems to use 'redis' to replace 'openmpi' .
I strongly suggest not to use Horovod directly which is based on openmpi that 
is too complex and old.

maybe we could figure some way to directly do distributed training over redis ?

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2020-03-03 Thread Bumblebee269
We use the c++ interface for inference on a sorting machine. But also we would 
like to provide the users of our machines an easy and integrated user interface 
for training new sorting recipes. Now we use python or Mathematica scripts 
which is far of user friendly for non-programmers. So we want to use the c++ 
(shielded with a C# wrapper) to provide a custom training environment for 
non-programmers.

Unfortunately, building the mxnet library with c++ support on Windows machine 
with MKL / CUDA is an ongoing nightmare. But we really like MxNet

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2020-02-25 Thread kalcohol
> @kalcohol please create a new issue about "static linking lib is (very) far 
> away from easy to use", describing your setup in more detail and potentially 
> suggestions how to improve the user experience.

#17692 add this tiny requist.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2020-02-25 Thread Leonard Lausen
@kalcohol please create a new issue about "static linking lib is (very) far 
away from easy to use", describing your setup in more detail and potentially 
suggestions how to improve the user experience.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2020-02-25 Thread kalcohol
Thanks for this awesome work, it has benefited me a great deal.

Here are some disadvantages(may be) listed blow:
1. it seems that c and c++ interface both could work, but can not finish single 
task only by one;
2. low bit training or inference is not available via c/c++(ver. 1.6.0 fix fp16 
training);
3. static linking lib is (very) far away from easy to use, cmake configure 
file(like MxNetConfig.cmake, etc.) will enough for end users to integrate 
libmxnet.a and other large bunch of static third party libs(it's not easy to 
maintain gentlemanly demeanor all a day when manually linking these day by 
day). people could easy to hack loading interface of dynamic library.
4. smaller size of lib will more friendly to edge device.
5. more c++ training demo, including how to use kvstore(multiple cards and 
multiple servers), it's really not easy to understand.

Good day everyone.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2020-02-19 Thread Lin Yuan
Is there a plan to remove the cudnn_off argument from the neural network 
operators such as Dropout, Convolution, Pool etc. It creates a few usability 
issues:
(1) Once a model is exported. It requires users to change this flag in all the 
layers manually if they want to enable/disable cuDNN. When the cudnn_off is set 
to true in some layers, the global env variable `MXNET_CUDNN_AUTOTUNE_DEFAULT` 
becomes don't care. It's very confusing to users to see an error message like 
"Please turn off MXNET_CUDNN_AUTOTUNE_DEFAULT" by indeed it does not do 
anything.
(2) Why did we expose such implementation detail to users at the first place? 
In the worst case, we should just provide a global variable to turn on/off 
cuDNN in all layers instead of at operator level.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-12-30 Thread Sheng Zha
@TaoLv one promising direction that the community is converging to is the 
interface based on packed function (motivation as described by @tqchen in 
https://github.com/apache/incubator-mxnet/issues/17097#issuecomment-56760). 
What this means to the project is that the existing c API will be updated to 
follow the packed function interface.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-12-30 Thread Tao Lv
> 3.1. C-API Clean-up
C-API is the foundational API in MXNet that all language bindings depend on.

@szha I'm looking at the item 3.1.2. Could you please explain the scope of 
C-API? Do you mean those APIs sit in the src/c_api/ folder?


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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-12-27 Thread Tao Lv
+1 for using master branch for 2.0 development. I think we need 3 branches at 
least:
1. master branch: for 2.0 development
2. v1.x:  for 1.x development and maintenance
3. v1.7.x: for 1.7.x release

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-12-27 Thread Leonard Lausen
In the past we always kept development on the master branch, thus how about 
branching out 1.7.0 release branch and keeping development on master?

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-12-26 Thread Xingjian Shi
Should we create a new branch for 2.0? I think we are also planing for 1.7.0 
https://github.com/apache/incubator-mxnet/issues/16864

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-12-15 Thread Sheng Zha
Once 1.6 release is complete, we will create a branch for MXNet 1.x for future 
releases and start using master branch for 2.0 development.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-12-15 Thread Sheng Zha
The status of MXNet 2.0 project is tracked at: 
https://github.com/apache/incubator-mxnet/projects/18. The status for each 
project will be updated by the contributor who's driving it. If you have more 
projects that you intend to drive please first discuss here.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-12-11 Thread Erwan BERNARD
That's a bit what amalgamation part was for ? a simplified inference interface. 
The last time I use amalgamation (some years ago) it was often break by update 
and not really maintain.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-12-09 Thread Tham
> 
> 
> @stereomatchingkiss good point. What are you using c/c++ api for?

1. Develop stand alone app on desktop and mobile
2. Wrapper of another language(ex : php)
3. Run the inference task on aws lambda, we do not want to prune the libs of 
python manually if we could build a slim library of mxnet/tensorflow/pytorch. 

Maybe you could open a post to ask the users what are they expect for c or c++ 
api, I guess most of them only need to use the api to perform inference task 
but not training(python do a great job about this), this should help you shrink 
the size of the libs and made the codes less complicated. 

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-12-09 Thread Sheng Zha
@stereomatchingkiss good point. What are you using c/c++ api for?

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-12-09 Thread Tham
Any plan to simplify the build of c and c++ api for mxnet2.0?It is hard(or very 
hard) to build a working version of mxnet with cpp api on different 
platforms(windows, linux, mac), every new release of the mxnet may or may not 
break somethings and we need to spend many hours to figure out how to make it 
work.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-09-25 Thread Rishik Mourya
Just a quick cheer up for a new website of MXNet... its way more awesome and 
beautiful than I expected.
Though minor bugs are still there, for ex- most of the link in the tutorials 
are broken and not working.
Anyways great work so far.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-09-16 Thread Sheng Zha
@pengzhao-intel a tentative target date is by end of Q1 2020.

@zachgk we will create a branch for 2.0. Initially we will keep master to be 
1.x and have 2.0 in a new branch. After 1.6 release we will revisit how to make 
the 2.0 branch the master.

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-09-16 Thread Zach Kimberg
Is there a plan to create a branch either for the 1.x version and have master 
reflect 2.0 or to create a branch for the 2.0 version and keep master on 1.x 
for now?

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Re: [apache/incubator-mxnet] [RFC] Apache MXNet 2.0 Roadmap (#16167)

2019-09-15 Thread PatricZhao
@szha Really great proposal and we may want to add some items in 2.0 too.
Is there a timeline of 2.0?


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