On 3/1/24 14:54, Neal Gompa wrote:
On Fri, Mar 1, 2024 at 4:52 PM Tim Flink <tfl...@fedoraproject.org> wrote:
On 2/28/24 19:03, Richard Fontana wrote:
On Tue, Feb 27, 2024 at 5:58 PM Tim Flink <tfl...@fedoraproject.org> wrote:
On 2/26/24 19:06, Richard Fontana wrote:
<snip>
4. Is it acceptable to package code which downloads pre-trained weights from a
non-Fedora source upon first use post-installation by a user if that model and
its associated weights are
a. For a specific model?
What do you mean by "upon first use post-installation"? Does that mean
I install the package, and the first time I launch it or whatever, it
automatically downloads some set of pre-trained weights, or is this
something that would be controlled by the user? The example you gave
suggests the latter but I wasn't sure if I was misunderstanding.
Once the package is installed, pre-trained weights would downloaded if and only
if code written to use a specific model with pre-trained weights is run. In the
cases I'm aware of, code that would cause the weights to be downloaded is not
directly part of the packaged libraries and anything that could trigger the
downloading of pre-trained weights would have to be written by a user or
contained in a separate package. If a specific model with pre-trained weights
is not used and not executed by another library/application, the weights will
not be downloaded. With the ViT example, the vitb16 weights would be downloaded
when that code (not included in the package) is run but the vitb32 weights
would not be downloaded unless the example was changed or something else
specified a pre-trained ViT model with the vitb32 weights. Similarly, the
weights for other models (googlenet, as an example) would not be downloaded
unless code that uses that specific model in its pre-trained form is executed
post-installation.
The implementations that I'm familiar with will check for downloaded weights as
the code is initialized. When done in this way, the download is transparent to
the user and unless code using these models/weights is written in such a way
that the user a choice, there is not much a user could do to change the
download URL or prevent the weights from being downloaded. The only ways I can
think of off hand would be to modify the underlying libraries to override the
hard-coded URLs or maybe put identically named files in the cache location but
that would end up being dependant on model implementation. For the specific
libraries I used as examples, I don't know what the local download folder is
off the top of my head, nor do I know if they do any verification of downloads
so putting files into the cached location may not work if they don't match the
intended file contents.
This is just my opinion but I doubt that many people writing code that uses
pre-trained models are going to go out of their way to help users avoid
downloading pre-trained weights. I know that for code that I've written using
pre-trained models, it might be able to execute without the pre-trained weights
but the output would just be noise in that situation. I would have a hard time
justifying the work needed to make those downloads optional since it would make
the code useless for what it was intended to do.
It may also be worth noting that some models with pre-trained weights are
almost useless without those weights. For some (mostly older) models, it's
feasible to train a model from scratch but for many of the recent models, it's
just not feasible. As an example, the weights for Meta's Llama 2 took 3.3
million hours of GPU time to train [1] with a cost into the millions of USD
ignoring what it would take to obtain enough data to train a model that large.
Apologies for my verbosity but I hope that I answered your question and the
extra bits weren't entirely useless.
This sounds like it falls in the same bucket as pip, snapd, gem, and
other similar "package manager" functionality.
Yeah, the capabilities do overlap but in my opinion, the intended uses are
different and that may be worth noting.
pip, as an example is intended to allow users to install python packages
sourced from outside Fedora repos. I don't believe that software which used pip
after installation with no direct user interaction would be allowed in Fedora.
The pre-trained models that I'm familiar with, however, download things
transparently to the user with no warning outside of a log message when the
weights are first downloaded.
As an example, I wrote some code called openqa_classifier [1] to test the
possibility of identifying OpenQA [2] test failures as duplicates of a long
running issue. The code was written only to run an experiment so I wouldn't
package it in its current form but for the sake of argument, let's say that I
packaged it in its current form. Only one of the experiments is relevant here -
the one that looks at whether existing, more sophisticated pre-trained models
can outperform a simple custom model trained from scratch.
If you installed openqa_classifier (pretending that the data was already
available and that I created a sane entry point for the cli) and ran
'openqa_classifier train torch', that command would almost immediately download
pre-trained weights from a URL that's hardcoded in the torchvision module if
those weights didn't already exist locally. The only user-facing indication
that this had happend would be a few lines in the cli output and some new files
on disk.
I'm not arguing against including code which could download pre-trained weights
but I do want to be reasonably sure that I've explained all this correctly.
Tim
[1] https://pagure.io/fedora-qa/openqa_classifier
[2] https://openqa.fedoraproject.org/
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