Hi Sam,
On 2019-05-23 15:33, Sam Hartman wrote:
> I don't think that's entirely true.
Yes, that's a bit cruel to upstream.
> Reproducibility is still an issue, but is no more or less an issue than
> with any other software.
Bit-by-bit reproducibility is not quite practical for now. The
refined
Hi Andy,
Thanks for you comments.
On 2019-05-23 09:28, Andy Simpkins wrote:
> Your wording "The model /should/be reproducible with a fixed random seed."
> feels
> correct but wonder if guidance notes along the following lines should be
> added?
>
> *unless* we can reproduce the same result
Hi,
On 2019-05-22 12:43, Sam Hartman wrote:
> So, I think it's problematic to apply old assumptions to new areas. The
> reproducible builds world has gotten a lot further with bit-for-bit
> identical builds than I ever imagined they would.
I overhauled the reproducibility section. And lowered th
The following is a listing of packages for which help has been requested
through the WNPP (Work-Needing and Prospective Packages) system in the
last week.
Total number of orphaned packages: 1409 (new: 0)
Total number of packages offered up for adoption: 158 (new: 0)
Total number of packages reques
Package: wnpp
Severity: wishlist
Owner: Nobuhiro Iwamatsu
* Package name: trivy
Version : 0.1.1
Upstream Author : Teppei Fukuda
* URL : https://github.com/knqyf263/trivy/
* License : AGPL-3
Programming Lang: Go
Description : A Simple and Comprehensive
Sam.
Whilst i agree that "assets" in some packages may not have sources with them
and the application may still be in main if it pulls in those assets from
contrib or non free.
I am trying to suggest the same thing here. If the data set is unknown this is
the *same* as a dependancy on a rando
> "Andy" == Andy Simpkins writes:
Andy> wouldn't put that in main. It is my belief that we consider
Andy> training data sets as 'source' in much the same way /Andy
I agree that we consider training data sets as source.
We require the binaries we ship to be buildable from sourc
Package: wnpp
Severity: wishlist
Owner: G Vaishno Chaitanya
* Package name: autoload
Version : 1.2
Upstream Author : G Vaishno Chaitanya
* URL : https://autoload.dev
* License : GPL3
Programming Lang: BASH, Py
Description: Package Deployment Automation and Orc
> "Andy" == Andy Simpkins writes:
Andy> *unless* we can reproduce the same results, from the same
Andy> training data, you cannot classify as group 1, "Free
Andy> Model", because verification that training has been
Andy> carried out on the dataset explicitly licens
Sean Whitton writes ("Re: dgit FAQ"):
> On Wed 22 May 2019 at 04:57PM +02, Marc Haber wrote:
> > It's missing a Q1: What is dgit, why should I use it and how do I do
> > that, and a Q2: How would I check out dgit without my mistakes being
> > visible.
>
> Added. Thanks.
I expanded a bit on the "
Package: wnpp
Severity: wishlist
Owner: Ole Streicher
X-Debbugs-Cc: debian-as...@lists.debian.org, debian-devel@lists.debian.org,
debian-pyt...@lists.debian.org
* Package name : parfive
Version : 1.0.0
Upstream Author : Stuart Mumford
* URL : https://github.com/Cad
On 22/05/2019 03:53, Mo Zhou wrote:
Hi Tzafrir,
On 2019-05-21 19:58, Tzafrir Cohen wrote:
Is there a way to prove in some way (reproducible build or something
similar) that the results were obtained from that set using the specific
algorithm?
I wrote a dedicated section about reproducibility
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