Hi Paul and Emilio (again),
> -Original Message-
> From: Shengqi Chen
> Sent: Thursday, February 20, 2025 10:23 PM
>
> > (Emilio)
> > Britney schedules the pytorch tests against rdeps in testing, to ensure they
> > don't break, as pytorch could migrate before and independently of its rde
Hi Paul and Emilio,
> -Original Message-
> From: Paul Gevers
>
> (Paul)
> Will you think about fixing this (eventually)? Having libraries
> co-installable is a common theme, particularly during transitions and
> during upgrades.
I would like to, but I have little idea how to handle it no
Hi,
On 20-02-2025 08:23, Chen Shengqi wrote:
So this is causing both libraries to be dlopen-ed when pytorch-foo
tries to import torch in Python, and this is obviously broken.
Will you think about fixing this (eventually)? Having libraries
co-installable is a common theme, particularly during
On 20/02/2025 06:30, Shengqi Chen wrote:
Hi Emilio,
2025年2月19日 15:40，Emilio Pozuelo Monfort 写道：
Scheduled now.
They are all good now. Thanks!
I still have some questions, since this is my first time to do a
transition independently:
For onednn and xnnpack, the newly built packages are sho
Hi,
> -Original Message-
> From: Paul Gevers
> Sent: Thursday, February 20, 2025 3:10 PM>
>
> Yes, but what depends on how bad those failures are for real users that
> would do a partial upgrade. As the test times out without any useful
> output, I can't see what's going on except that
Hi,
On 20-02-2025 06:30, Shengqi Chen wrote:
And for pytorch, its migration depends on the autopkgtest of
pytorch-{scatter,sparse}. But seems britney does not run tests for
binNMU versions (#944458), so the results on the tracker page are
all failure. Do we need any human intervention on this?
Hi Emilio,
> 2025年2月19日 15:40，Emilio Pozuelo Monfort 写道：
>
> Scheduled now.
They are all good now. Thanks!
I still have some questions, since this is my first time to do a
transition independently:
For onednn and xnnpack, the newly built packages are shown as
“unknown” state in the tracker. I
On 19/02/2025 07:16, Chen Shengqi wrote:
Hi,
-Original Message-
From: Emilio Pozuelo Monfort
Sent: Monday, February 17, 2025 10:22 PM
For pytorch{,-cuda}:
* pytorch-{cluster,scatter,vision,ignite}, baler: builds without issue
* pytorch-sparse: failed, in testing, @lumin is looking i
Hi,
> -Original Message-
> From: Emilio Pozuelo Monfort
> Sent: Monday, February 17, 2025 10:22 PM
> >
> > For pytorch{,-cuda}:
> >
> > * pytorch-{cluster,scatter,vision,ignite}, baler: builds without issue
> > * pytorch-sparse: failed, in testing, @lumin is looking into it
> > * skorch,
Control: tags -1 confirmed
On 07/02/2025 11:11, Shengqi Chen wrote:
Hi,
2025年2月2日 11:00，Emilio Pozuelo Monfort 写道：
Yes, I noticed that xnnpack in experimental depends on pytorch/experimental.
I think this should be the reversed way (pytorch depends on xnnpack)?
But pytorch is causing aut
Hi,
> 2025年2月2日 11:00，Emilio Pozuelo Monfort 写道：
>
> Yes, I noticed that xnnpack in experimental depends on pytorch/experimental.
I think this should be the reversed way (pytorch depends on xnnpack)?
> But pytorch is causing autopkgtest regressions on a couple of rdeps:
Thanks & noticed.
* p
On 02/02/2025 00:01, Shengqi Chen wrote:
Control: retitle -1 transition: xnnpack, onednn, pytorch{,-cuda}
Hi,
2025年1月28日 08:33，Shengqi Chen 写道：
They have exact same reverse dependencies (pytorch and onnxruntime)
that are also maintained by the deep learning team:
* pytorch needs a new upstr
Control: retitle -1 transition: xnnpack, onednn, pytorch{,-cuda}
Hi,
> 2025年1月28日 08:33，Shengqi Chen 写道：
>
> They have exact same reverse dependencies (pytorch and onnxruntime)
> that are also maintained by the deep learning team:
>
> * pytorch needs a new upstream version (2.6+) that we are p
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