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nvidia dali support #791

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smallzzy opened this issue Feb 5, 2020 · 17 comments · Fixed by #3721
Closed

nvidia dali support #791

smallzzy opened this issue Feb 5, 2020 · 17 comments · Fixed by #3721
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feature Is an improvement or enhancement good first issue Good for newcomers help wanted Open to be worked on won't fix This will not be worked on
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@smallzzy
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smallzzy commented Feb 5, 2020

🚀 Feature

Re-open the case for #513. i.e. Support nvidia dali iterator as a possible data loader.

Pitch

I have submitted a wip pull request to the master. #789
I would like to know if it is ok for the test to be depending on nvidia-dali in addition to apex.

@smallzzy smallzzy added feature Is an improvement or enhancement help wanted Open to be worked on labels Feb 5, 2020
@smallzzy
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smallzzy commented Feb 5, 2020

The dali iterator does not support resetting while epoch is not finished. I suppose I shall provide a warning for that.

@williamFalcon
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@smallzzy this is sick. super excited by this feature

@Borda Borda added this to the 0.6.1 milestone Feb 7, 2020
@Borda Borda modified the milestones: 0.7.0, 0.7.1 Mar 2, 2020
@Borda Borda modified the milestones: 0.7.2, 0.7.3 Mar 26, 2020
@Borda
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Borda commented Mar 26, 2020

@smallzzy we have cleared the API and now it should be stable... Mind resume your addition?

@brunoalano
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Some news about DALI support?

@Borda
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Borda commented Apr 14, 2020

@brunoalano interested in implementing DALI?

@brunoalano
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@Borda Do you have a pipeline what should have be done to support it? But I'm available to do that with a minimal guidance (started using PyTorch Lightning and DALI these days)

@Borda
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Borda commented Apr 14, 2020

we had almost done PR some time ago so I use you can resume from that point... #789

@Borda Borda modified the milestones: 0.7.4, 0.7.5 Apr 24, 2020
@Borda Borda modified the milestones: 0.7.6, 0.8.0, 0.7.7 May 12, 2020
@Borda Borda modified the milestones: 0.7.7, 0.8.0 May 26, 2020
@Borda Borda modified the milestones: 0.8.0, 0.9.0 Jun 9, 2020
@stale
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stale bot commented Aug 8, 2020

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

@stale stale bot added the won't fix This will not be worked on label Aug 8, 2020
@Borda Borda added good first issue Good for newcomers and removed won't fix This will not be worked on labels Aug 9, 2020
@edenlightning edenlightning modified the milestones: 0.9.0, 0.9.x Aug 18, 2020
@edenlightning edenlightning modified the milestones: 0.9.x, 1.1 Sep 22, 2020
@irustandi
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Is anyone working on this currently?

@irustandi
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I tried converting PyTorch Lightning's MNIST example to use DALI, it seems to work out of the box without requiring modification to the PyTorch Lightning's internals. See below.

https://gist.github.com/irustandi/3d180ed3ec9d7ff4e73d3fdbd67df3ca

@Borda
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Borda commented Sep 27, 2020

@irustandi cool, mind add it as example, send a PR?

@irustandi
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@Borda sure, will create the PR.

@irustandi irustandi mentioned this issue Sep 29, 2020
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stale bot commented Oct 28, 2020

This issue has been automatically marked as stale because it hasn't had any recent activity. This issue will be closed in 7 days if no further activity occurs. Thank you for your contributions, Pytorch Lightning Team!

@stale stale bot added the won't fix This will not be worked on label Oct 28, 2020
@stale stale bot closed this as completed Nov 4, 2020
@ImMrMa
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ImMrMa commented Nov 26, 2020

I want to know that if dali with ddp and amp and dali's pipeline in distributed situation can work well? And have a perfect performance?

@Freed-Wu
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Freed-Wu commented Sep 8, 2022

I want to know if pl.seed_everything() is valid for dali's seed?

@Borda
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Borda commented Nov 7, 2022

Good question, I believe so... @awaelchli?

@awaelchli
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Lightning takes care of seeding the PyTorch related, built-in objects. That is, everything in the torch library, numpy, cuda and the dataloader workers. DALI and other libraries have their own logic regarding seeding and the user should consult their documentation regarding usage. pl.seed_everything does not cover these (because it can't).

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9 participants