Magnification of extracted tiles

It is unclear if the MPP of the extracted should be 0.5, similar to the way the models were trained.
It is reasonable that if the model was trained on MPP=0.5, it should be applied on the same magnification. However, there were no details on this matter in the code description.

Good suggestion! We will add more instructions next.

Dear Hanwen,
I am heading a digital pathology team and we are about to finalize our last
experiments to be submitted to Nature Medicine.
We would like to try to finetune your gigapath model's weights using our
data as part of the experiments. i.e. - continue training the SSL model
using our data in a supervised manner.
Is there a way to do that using your code?
I posted this issue on Github as well:
"I am working with a dataset comprising 10,000 patients, each with an
associated target. I am interested in fine-tuning the SSL feature extractor
in a supervised manner to extract tile-level features that are more
specific to my task.
Could you kindly provide guidance on how to implement this using your code?
If this functionality is not currently supported, would it be possible for
you to make it available?
Thank you for your time and assistance."
Thanks a lot.
Best,
Gil
On Tue, Jun 11, 2024 at 4:45 AM Hanwen Xu @.***> wrote:

Good suggestion! We will add more instructions next.
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Hi Dr.Gil, yes I feel excited that you're interested in fine-tuning our model. Can I get more background of this task? Is it a slide-level prediction task or tile-level? Our current pipeline is (1) extract the features with a frozen tile-encoder (2) fine-tune the slide encoder to adapt to specific tasks. If our task here could accept this pipeline, then the answer is yes and I'm happy to help set up your experiments. Also, feel free to directly email me at<EMAIL_ADDRESS>I'm looking forward to your work!

Dear Hanwen,
I hope this message finds you well. I just wanted to follow up with you on
my previous email about the tile encoder.
 Thus, I just wanted to clarify and suggest two
things that either of them would help us:

Could you share the code for training the tile encoder?
Or, if an existing framework was used, could you clarify how it was
implemented?
This would be very helpful for our current study and may significantly
accelerate our submission to Nature Medicine.

Thank you for your time,
Best,
Gil
On Mon, Oct 14, 2024 at 4:08 PM Gil Shamai @.***> wrote:

Dear Hanwen,
Thank you for your email.
Sure, in this task, we would like to perform a slide-level task to predict
a molecular marker from H&E images. We fine-tuned your slide encoder for
this task. However, our cohort is large (10K patients), and thus we believe
that the training can be improved by finetuning not only the slide encoder
but also your frozen tile encoder.
This potential improvement may be critical for proving a new hypothesis we
are studying.
Does this make any sense?
Best,
Gil
On Mon, Oct 14, 2024 at 10:42 AM Hanwen Xu @.***>
wrote:

Hi Dr.Gil, yes I feel excited that you're interested in fine-tuning our
model. Can I get more background of this task? Is it a slide-level
prediction task or tile-level? Our current pipeline is (1) extract the
features with a frozen tile-encoder (2) fine-tune the slide encoder to
adapt to specific tasks. If our task here could accept this pipeline, then
the answer is yes and I'm happy to help set up your experiments. Also, feel
free to directly email me at @.***, I'm looking forward
to your work!
—
Reply to this email directly, view it on GitHub
https://github.com/prov-gigapath/prov-gigapath/issues/31#issuecomment-2410304763,
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.
You are receiving this because you authored the thread.Message ID:
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Ah I see. Unfortunately I didn't have existing codes for end-to-end
finetuning because end-to-end finetuning will be computationally intensive.
But I do have the code for DINOv2 finetuning and that's only for tile-level
tasks. Does the following work: (1) Finetune tile encoder on your large
cohort by distributing the slide-level labels to tile level. (2) Freeze the
tile encoder from stage 1, and then finetune the slide encoder. If this
works, I can set up this pipeline for you. I'm a bit busy these days so
sorry for the late response. If this works, I will set it up for you before
Friday.
On Mon, Oct 28, 2024 at 6:25 AM Dr. Gil Shamai @.***>
wrote:

Dear Hanwen,
I hope this message finds you well. I just wanted to follow up with you on
my previous email about the tile encoder.
 Thus, I just wanted to clarify and suggest
two
things that either of them would help us:

Could you share the code for training the tile encoder?
Or, if an existing framework was used, could you clarify how it was
implemented?
This would be very helpful for our current study and may significantly
accelerate our submission to Nature Medicine.

Thank you for your time,
Best,
Gil
On Mon, Oct 14, 2024 at 4:08 PM Gil Shamai @.***> wrote:

Dear Hanwen,
Thank you for your email.
Sure, in this task, we would like to perform a slide-level task to
predict
a molecular marker from H&E images. We fine-tuned your slide encoder for
this task. However, our cohort is large (10K patients), and thus we
believe
that the training can be improved by finetuning not only the slide
encoder
but also your frozen tile encoder.
This potential improvement may be critical for proving a new hypothesis
we
are studying.
Does this make any sense?
Best,
Gil
On Mon, Oct 14, 2024 at 10:42 AM Hanwen Xu @.***>
wrote:

Hi Dr.Gil, yes I feel excited that you're interested in fine-tuning our
model. Can I get more background of this task? Is it a slide-level
prediction task or tile-level? Our current pipeline is (1) extract the
features with a frozen tile-encoder (2) fine-tune the slide encoder to
adapt to specific tasks. If our task here could accept this pipeline,
then
the answer is yes and I'm happy to help set up your experiments. Also,
feel
free to directly email me at @.***, I'm looking forward
to your work!
—
Reply to this email directly, view it on GitHub
<
https://github.com/prov-gigapath/prov-gigapath/issues/31#issuecomment-2410304763>,

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<
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Dear Hanwen,
Thank you for the detailed response.
I am CC-ing Hen Davidov who is our deep learning expert and would be able
to follow up with more details on what we need.
Option (1) sounds like an appropriate solution for our problem. We weren't
aware that the DINOv2 finetuning code was still compatible with your tile
encoder. We'd very much appreciate help with setting that up, especially if
some modifications to the relevant open source code are necessary. Is that
the case?
Best,
Gil
On Mon, Oct 28, 2024, 19:21 Hanwen Xu @.***> wrote:

Ah I see. Unfortunately I didn't have existing codes for end-to-end
finetuning because end-to-end finetuning will be computationally
intensive.
But I do have the code for DINOv2 finetuning and that's only for
tile-level
tasks. Does the following work: (1) Finetune tile encoder on your large
cohort by distributing the slide-level labels to tile level. (2) Freeze
the
tile encoder from stage 1, and then finetune the slide encoder. If this
works, I can set up this pipeline for you. I'm a bit busy these days so
sorry for the late response. If this works, I will set it up for you
before
Friday.
On Mon, Oct 28, 2024 at 6:25 AM Dr. Gil Shamai @.***>
wrote:

Dear Hanwen,
I hope this message finds you well. I just wanted to follow up with you
on
my previous email about the tile encoder.
 Thus, I just wanted to clarify and suggest
two
things that either of them would help us:

Could you share the code for training the tile encoder?
Or, if an existing framework was used, could you clarify how it was
implemented?
This would be very helpful for our current study and may significantly
accelerate our submission to Nature Medicine.

Thank you for your time,
Best,
Gil
On Mon, Oct 14, 2024 at 4:08 PM Gil Shamai @.***> wrote:

Dear Hanwen,
Thank you for your email.
Sure, in this task, we would like to perform a slide-level task to
predict
a molecular marker from H&E images. We fine-tuned your slide encoder
for
this task. However, our cohort is large (10K patients), and thus we
believe
that the training can be improved by finetuning not only the slide
encoder
but also your frozen tile encoder.
This potential improvement may be critical for proving a new
hypothesis
we
are studying.
Does this make any sense?
Best,
Gil
On Mon, Oct 14, 2024 at 10:42 AM Hanwen Xu @.***>
wrote:

Hi Dr.Gil, yes I feel excited that you're interested in fine-tuning
our
model. Can I get more background of this task? Is it a slide-level
prediction task or tile-level? Our current pipeline is (1) extract
the
features with a frozen tile-encoder (2) fine-tune the slide encoder
to
adapt to specific tasks. If our task here could accept this pipeline,
then
the answer is yes and I'm happy to help set up your experiments.
Also,
feel
free to directly email me at @.***, I'm looking forward
to your work!
—
Reply to this email directly, view it on GitHub
<

https://github.com/prov-gigapath/prov-gigapath/issues/31#issuecomment-2410304763>,

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<

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.
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You are receiving this because you authored the thread.Message ID:
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Yes, I'm happy to help with setting up the option (1). Is your task the
classification task? If so, I can provide the finetuning script taking the
train.csv and test.csv as input. Each csv has the "image_path" and "labels"
as columns. You can then finetune by directly replacing the csv with your
customized csv files.
Best,
Hanwen
On Mon, Oct 28, 2024 at 3:37 PM Dr. Gil Shamai @.***>
wrote:

Dear Hanwen,
Thank you for the detailed response.
I am CC-ing Hen Davidov who is our deep learning expert and would be able
to follow up with more details on what we need.
Option (1) sounds like an appropriate solution for our problem. We weren't
aware that the DINOv2 finetuning code was still compatible with your tile
encoder. We'd very much appreciate help with setting that up, especially
if
some modifications to the relevant open source code are necessary. Is that
the case?
Best,
Gil
On Mon, Oct 28, 2024, 19:21 Hanwen Xu @.***> wrote:

Ah I see. Unfortunately I didn't have existing codes for end-to-end
finetuning because end-to-end finetuning will be computationally
intensive.
But I do have the code for DINOv2 finetuning and that's only for
tile-level
tasks. Does the following work: (1) Finetune tile encoder on your large
cohort by distributing the slide-level labels to tile level. (2) Freeze
the
tile encoder from stage 1, and then finetune the slide encoder. If this
works, I can set up this pipeline for you. I'm a bit busy these days so
sorry for the late response. If this works, I will set it up for you
before
Friday.
On Mon, Oct 28, 2024 at 6:25 AM Dr. Gil Shamai @.***>
wrote:

Dear Hanwen,
I hope this message finds you well. I just wanted to follow up with
you
on
my previous email about the tile encoder.
 Thus, I just wanted to clarify and
suggest
two
things that either of them would help us:

Could you share the code for training the tile encoder?
Or, if an existing framework was used, could you clarify how it was
implemented?
This would be very helpful for our current study and may significantly
accelerate our submission to Nature Medicine.

Thank you for your time,
Best,
Gil
On Mon, Oct 14, 2024 at 4:08 PM Gil Shamai @.***> wrote:

Dear Hanwen,
Thank you for your email.
Sure, in this task, we would like to perform a slide-level task to
predict
a molecular marker from H&E images. We fine-tuned your slide encoder
for
this task. However, our cohort is large (10K patients), and thus we
believe
that the training can be improved by finetuning not only the slide
encoder
but also your frozen tile encoder.
This potential improvement may be critical for proving a new
hypothesis
we
are studying.
Does this make any sense?
Best,
Gil
On Mon, Oct 14, 2024 at 10:42 AM Hanwen Xu @.***>
wrote:

Hi Dr.Gil, yes I feel excited that you're interested in fine-tuning
our
model. Can I get more background of this task? Is it a slide-level
prediction task or tile-level? Our current pipeline is (1) extract
the
features with a frozen tile-encoder (2) fine-tune the slide encoder
to
adapt to specific tasks. If our task here could accept this
pipeline,
then
the answer is yes and I'm happy to help set up your experiments.
Also,
feel
free to directly email me at @.***, I'm looking forward
to your work!
—
Reply to this email directly, view it on GitHub
<

https://github.com/prov-gigapath/prov-gigapath/issues/31#issuecomment-2410304763>,

or unsubscribe
<

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Dear Hanwen,
Thank you, that sounds exactly like what we need! We appreciate the help.
What kind of slide formats does your code accept?
CC-ing Hen again so you can communicate directly.
Best,
Gil
On Tue, Oct 29, 2024 at 12:48 AM Hanwen Xu @.***> wrote:

Yes, I'm happy to help with setting up the option (1). Is your task the
classification task? If so, I can provide the finetuning script taking the
train.csv and test.csv as input. Each csv has the "image_path" and
"labels"
as columns. You can then finetune by directly replacing the csv with your
customized csv files.
Best,
Hanwen
On Mon, Oct 28, 2024 at 3:37 PM Dr. Gil Shamai @.***>
wrote:

Dear Hanwen,
Thank you for the detailed response.
I am CC-ing Hen Davidov who is our deep learning expert and would be
able
to follow up with more details on what we need.
Option (1) sounds like an appropriate solution for our problem. We
weren't
aware that the DINOv2 finetuning code was still compatible with your
tile
encoder. We'd very much appreciate help with setting that up, especially
if
some modifications to the relevant open source code are necessary. Is
that
the case?
Best,
Gil
On Mon, Oct 28, 2024, 19:21 Hanwen Xu @.***> wrote:

Ah I see. Unfortunately I didn't have existing codes for end-to-end
finetuning because end-to-end finetuning will be computationally
intensive.
But I do have the code for DINOv2 finetuning and that's only for
tile-level
tasks. Does the following work: (1) Finetune tile encoder on your
large
cohort by distributing the slide-level labels to tile level. (2)
Freeze
the
tile encoder from stage 1, and then finetune the slide encoder. If
this
works, I can set up this pipeline for you. I'm a bit busy these days
so
sorry for the late response. If this works, I will set it up for you
before
Friday.
On Mon, Oct 28, 2024 at 6:25 AM Dr. Gil Shamai @.***>
wrote:

Dear Hanwen,
I hope this message finds you well. I just wanted to follow up with
you
on
my previous email about the tile encoder.
 Thus, I just wanted to clarify and
suggest
two
things that either of them would help us:

Could you share the code for training the tile encoder?
Or, if an existing framework was used, could you clarify how it
was
implemented?
This would be very helpful for our current study and may
significantly
accelerate our submission to Nature Medicine.

Thank you for your time,
Best,
Gil
On Mon, Oct 14, 2024 at 4:08 PM Gil Shamai @.***> wrote:

Dear Hanwen,
Thank you for your email.
Sure, in this task, we would like to perform a slide-level task to
predict
a molecular marker from H&E images. We fine-tuned your slide
encoder
for
this task. However, our cohort is large (10K patients), and thus
we
believe
that the training can be improved by finetuning not only the slide
encoder
but also your frozen tile encoder.
This potential improvement may be critical for proving a new
hypothesis
we
are studying.
Does this make any sense?
Best,
Gil
On Mon, Oct 14, 2024 at 10:42 AM Hanwen Xu @.***>
wrote:

Hi Dr.Gil, yes I feel excited that you're interested in
fine-tuning
our
model. Can I get more background of this task? Is it a
slide-level
prediction task or tile-level? Our current pipeline is (1)
extract
the
features with a frozen tile-encoder (2) fine-tune the slide
encoder
to
adapt to specific tasks. If our task here could accept this
pipeline,
then
the answer is yes and I'm happy to help set up your experiments.
Also,
feel
free to directly email me at @.***, I'm looking forward
to your work!
—
Reply to this email directly, view it on GitHub
<

https://github.com/prov-gigapath/prov-gigapath/issues/31#issuecomment-2410304763>,

or unsubscribe
<

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Dear Hanwen,
I wanted to follow up on my previous email in case it may have been missed.
Your assistance would be invaluable in helping us expedite our study, and I
would greatly appreciate any guidance or support you can provide.
Thank you very much for your time and consideration.
Best,
Gil
On Tue, Oct 29, 2024 at 11:03 AM Gil Shamai @.***> wrote:

Dear Hanwen,
Thank you, that sounds exactly like what we need! We appreciate the help.
What kind of slide formats does your code accept?
CC-ing Hen again so you can communicate directly.
Best,
Gil
On Tue, Oct 29, 2024 at 12:48 AM Hanwen Xu @.***>
wrote:

Yes, I'm happy to help with setting up the option (1). Is your task the
classification task? If so, I can provide the finetuning script taking
the
train.csv and test.csv as input. Each csv has the "image_path" and
"labels"
as columns. You can then finetune by directly replacing the csv with your
customized csv files.
Best,
Hanwen
On Mon, Oct 28, 2024 at 3:37 PM Dr. Gil Shamai @.***>
wrote:

Dear Hanwen,
Thank you for the detailed response.
I am CC-ing Hen Davidov who is our deep learning expert and would be
able
to follow up with more details on what we need.
Option (1) sounds like an appropriate solution for our problem. We
weren't
aware that the DINOv2 finetuning code was still compatible with your
tile
encoder. We'd very much appreciate help with setting that up,
especially
if
some modifications to the relevant open source code are necessary. Is
that
the case?
Best,
Gil
On Mon, Oct 28, 2024, 19:21 Hanwen Xu @.***> wrote:

Ah I see. Unfortunately I didn't have existing codes for end-to-end
finetuning because end-to-end finetuning will be computationally
intensive.
But I do have the code for DINOv2 finetuning and that's only for
tile-level
tasks. Does the following work: (1) Finetune tile encoder on your
large
cohort by distributing the slide-level labels to tile level. (2)
Freeze
the
tile encoder from stage 1, and then finetune the slide encoder. If
this
works, I can set up this pipeline for you. I'm a bit busy these days
so
sorry for the late response. If this works, I will set it up for you
before
Friday.
On Mon, Oct 28, 2024 at 6:25 AM Dr. Gil Shamai @.***>
wrote:

Dear Hanwen,
I hope this message finds you well. I just wanted to follow up with
you
on
my previous email about the tile encoder.
 Thus, I just wanted to clarify and
suggest
two
things that either of them would help us:

Could you share the code for training the tile encoder?
Or, if an existing framework was used, could you clarify how it
was
implemented?
This would be very helpful for our current study and may
significantly
accelerate our submission to Nature Medicine.

Thank you for your time,
Best,
Gil
On Mon, Oct 14, 2024 at 4:08 PM Gil Shamai @.***> wrote:

Dear Hanwen,
Thank you for your email.
Sure, in this task, we would like to perform a slide-level task
to
predict
a molecular marker from H&E images. We fine-tuned your slide
encoder
for
this task. However, our cohort is large (10K patients), and thus
we
believe
that the training can be improved by finetuning not only the
slide
encoder
but also your frozen tile encoder.
This potential improvement may be critical for proving a new
hypothesis
we
are studying.
Does this make any sense?
Best,
Gil
On Mon, Oct 14, 2024 at 10:42 AM Hanwen Xu @.***>
wrote:

Hi Dr.Gil, yes I feel excited that you're interested in
fine-tuning
our
model. Can I get more background of this task? Is it a
slide-level
prediction task or tile-level? Our current pipeline is (1)
extract
the
features with a frozen tile-encoder (2) fine-tune the slide
encoder
to
adapt to specific tasks. If our task here could accept this
pipeline,
then
the answer is yes and I'm happy to help set up your experiments.
Also,
feel
free to directly email me at @.***, I'm looking forward
to your work!
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Yes it's ready. Can you provide me with your email address? Then I will
share it with you.
Regards,
Hanwen
On Sun, Nov 3, 2024 at 4:23 AM Dr. Gil Shamai @.***>
wrote:

Dear Hanwen,   I wanted to follow up on my previous email in case
it may have been missed.  Your assistance would be invaluable in
helping us expedite our study, and I  would greatly appreciate any
guidance or support you can provide.   Thank you very much for your
time and consideration.   Best,  Gil    On Tue, Oct
29, 2024 at 11:03 AM Gil Shamai @.> wrote:   > Dear
Hanwen,  > Thank you, that sounds exactly like what we need! We
appreciate the help.  > What kind of slide formats does your code
accept?  > CC-ing Hen again so you can communicate directly.
> Best,  > Gil  >  > On Tue, Oct 29, 2024 at
12:48 AM Hanwen Xu @.>  > wrote:  >  >>
Yes, I'm happy to help with setting up the option (1). Is your task the
 >> classification task? If so, I can provide the finetuning
script taking  >> the  >> train.csv and test.csv as
input. Each csv has the "image_path" and  >>
"labels"  >> as columns. You can then finetune by
directly replacing the csv with your  >> customized csv files.
 >>  >> Best,  >>  >> Hanwen
>>  >> On Mon, Oct 28, 2024 at 3:37 PM Dr. Gil Shamai
@.>  >> wrote:  >>  >> > Dear
Hanwen,  >> > Thank you for the detailed response.
>> > I am CC-ing Hen Davidov who is our deep learning expert and
would be  >> able  >> > to follow up with more
details on what we need.  >> >  >> > Option (1)
sounds like an appropriate solution for our problem. We  >>
weren't  >> > aware that the DINOv2 finetuning code was
still compatible with your  >> tile  >> > encoder.
We'd very much appreciate help with setting that up,  >>
especially  >> > if  >> > some modifications to
the relevant open source code are necessary. Is  >> that
>> > the case?  >> > Best,  >> > Gil
 >> >  >> > On Mon, Oct 28, 2024, 19:21 Hanwen Xu
@.> wrote:  >> >  >> > > Ah I see.
Unfortunately I didn't have existing codes for end-to-end  >>
> > finetuning because end-to-end finetuning will be computationally
 >> > > intensive.  >> > > But I do have
the code for DINOv2 finetuning and that's only for  >> >
> tile-level  >> > > tasks. Does the following work: (1)
Finetune tile encoder on your  >> large  >> > >
cohort by distributing the slide-level labels to tile level. (2)
>> Freeze  >> > > the  >> > > tile
encoder from stage 1, and then finetune the slide encoder. If  >>
this  >> > > works, I can set up this pipeline for you.
I'm a bit busy these days  >> so  >> > >
sorry for the late response. If this works, I will set it up for you
>> > > before  >> > > Friday.  >>
> >  >> > > On Mon, Oct 28, 2024 at 6:25 AM Dr. Gil
Shamai @.>  >> > > wrote:  >> >
>  >> > > > Dear Hanwen,  >> > > >
I hope this message finds you well. I just wanted to follow up with
>> > you  >> > > on  >> > > >
my previous email about the tile encoder.  >> > > >
Given our large cohort size and its distinctive features, we'd like
 >> to  >> > > > finetune the tile extractor.
Thus, I just wanted to clarify and  >> > suggest  >>
> > > two  >> > > > things that either of them
would help us:  >> > > > 1) Could you share the code for
training the tile encoder?  >> > > > 2) Or, if an
existing framework was used, could you clarify how it  >> was
 >> > > > implemented?  >> > > > This
would be very helpful for our current study and may  >>
significantly  >> > > > accelerate our submission to
Nature Medicine.  >> > > >  >> > > >
Thank you for your time,  >> > > > Best,  >>
> > > Gil  >> > > >  >> > >
> On Mon, Oct 14, 2024 at 4:08 PM Gil Shamai @.> wrote:
>> > > >  >> > > > > Dear Hanwen,
>> > > > > Thank you for your email.  >> >
> > > Sure, in this task, we would like to perform a slide-level
task  >> to  >> > > > predict  >>
> > > > a molecular marker from H&E images. We fine-tuned
your slide  >> encoder  >> > > for  >>
> > > > this task. However, our cohort is large (10K patients),
and thus  >> we  >> > > > believe
>> > > > > that the training can be improved by
finetuning not only the  >> slide  >> > > >
encoder  >> > > > > but also your frozen tile
encoder.  >> > > > > This potential improvement may
be critical for proving a new  >> > > hypothesis
>> > > > we  >> > > > > are studying.
 >> > > > > Does this make any sense?  >>
> > > > Best,  >> > > > > Gil
>> > > > >  >> > > > >
>> > > > >  >> > > > > On Mon, Oct
14, 2024 at 10:42 AM Hanwen Xu @.>  >> > > >
> wrote:  >> > > > >  >> > > >
>> Hi Dr.Gil, yes I feel excited that you're interested in
>> fine-tuning  >> > > our  >> > >
> >> model. Can I get more background of this task? Is it a
>> slide-level  >> > > > >> prediction task
or tile-level? Our current pipeline is (1)  >> extract
>> > > the  >> > > > >> features with
a frozen tile-encoder (2) fine-tune the slide  >> encoder
>> > > to  >> > > > >> adapt to
specific tasks. If our task here could accept this  >> >
pipeline,  >> > > > then  >> > > >
>> the answer is yes and I'm happy to help set up your
experiments.  >> > > Also,  >> > > >
feel  >> > > > >> free to directly email me at
@., I'm looking forward  >> > > > >>
to your work!  >> > > > >>  >> > >
> >> —  >> > > > >> Reply to this email
directly, view it on GitHub  >> > > > >> <
>> > > >  >> > >  >> >
>>
https://github.com/prov-gigapath/prov-gigapath/issues/31#issuecomment-2410304763>,
 >>  >> >  >> > >  >> >
> >  >> > > > >> or unsubscribe
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sure,
@.***
OR
@.***
On Tue, Nov 5, 2024 at 5:43 PM Hanwen Xu @.***> wrote:

Yes it's ready. Can you provide me with your email address? Then I
will  share it with you.   Regards,   Hanwen
On Sun, Nov 3, 2024 at 4:23 AM Dr. Gil Shamai @.>  wrote:
  > Dear Hanwen, <br> <br> I wanted to follow up on
my previous email in case  > it may have been missed. <br>
Your assistance would be invaluable in  > helping us expedite our
study, and I <br> would greatly appreciate any  > guidance or
support you can provide. <br> <br> Thank you very much for your
 > time and consideration. <br> <br> Best, <br>
Gil <br> <br> <br> On Tue, Oct  > 29, 2024 at
11:03 AM Gil Shamai @.> wrote: <br> <br>
> Dear  > Hanwen, <br> > Thank you, that sounds
exactly like what we need! We  > appreciate the help. <br>
> What kind of slide formats does your code  > accept?
<br> > CC-ing Hen again so you can communicate directly.
<br>  > > Best, <br> > Gil <br>
> <br> > On Tue, Oct 29, 2024 at  > 12:48 AM
Hanwen Xu @.> <br> > wrote: <br>
> <br> >>  > Yes, I'm happy to
help with setting up the option (1). Is your task the  > <br>
>> classification task? If so, I can provide the finetuning
 > script taking <br> >> the <br>
>> train.csv and test.csv as  > input. Each csv has
the "image_path" and <br> >>
> "labels" <br> >> as columns. You
can then finetune by  > directly replacing the csv with your
<br> >> customized csv files.  > <br>
>> <br> >> Best, <br>
>> <br> >> Hanwen <br>  >
>> <br> >> On Mon, Oct 28, 2024 at
3:37 PM Dr. Gil Shamai  > @.> <br>
>> wrote: <br> >> <br>
>> > Dear  > Hanwen, <br>
>> > Thank you for the detailed response. <br>
 > >> > I am CC-ing Hen Davidov who is our deep
learning expert and  > would be <br> >> able
<br> >> > to follow up with more  >
details on what we need. <br> >> > <br>
>> > Option (1)  > sounds like an appropriate
solution for our problem. We <br> >>  >
weren't <br> >> > aware that the DINOv2
finetuning code was  > still compatible with your <br>
>> tile <br> >> > encoder.
> We'd very much appreciate help with setting that up,
<br> >>  > especially <br>
>> > if <br> >> > some
modifications to  > the relevant open source code are necessary. Is
<br> >> that <br>  > >>
> the case? <br> >> > Best, <br>
>> > Gil  > <br> >>
> <br> >> > On Mon, Oct 28, 2024, 19:21
Hanwen Xu  > @.> wrote: <br> >>
> <br> >> > > Ah I see.  >
Unfortunately I didn't have existing codes for end-to-end
<br> >>  > > > finetuning because
end-to-end finetuning will be computationally  > <br>
>> > > intensive. <br> >>
> > But I do have  > the code for DINOv2 finetuning
and that's only for <br> >> >  >
> tile-level <br> >> > > tasks.
Does the following work: (1)  > Finetune tile encoder on your
<br> >> large <br> >> >
>  > cohort by distributing the slide-level labels to tile
level. (2) <br>  > >> Freeze <br>
>> > > the <br> >> >
> tile  > encoder from stage 1, and then finetune the slide
encoder. If <br> >>  > this <br>
>> > > works, I can set up this pipeline for
you.  > I'm a bit busy these days <br>
>> so <br> >> > >  >
sorry for the late response. If this works, I will set it up for you
<br>  > >> > > before <br>
>> > > Friday. <br> >>
> > > <br> >> > > On
Mon, Oct 28, 2024 at 6:25 AM Dr. Gil  > Shamai @.>
<br> >> > > wrote: <br>
>> >  > > <br> >>
> > > Dear Hanwen, <br> >>
> > >  > I hope this message finds you well. I
just wanted to follow up with <br>  > >>
> you <br> >> > > on <br>
>> > > >  > my previous email
about the tile encoder. <br> >> > >
>  > Given our large cohort size and its distinctive
features, we'd like  > <br> >> to
<br> >> > > > finetune the tile
extractor.  > Thus, I just wanted to clarify and <br>
>> > suggest <br> >>  >
> > > two <br> >> >
> > things that either of them  > would help us:
<br> >> > > > 1) Could you share
the code for  > training the tile encoder? <br>
>> > > > 2) Or, if an  > existing
framework was used, could you clarify how it <br> >>
was  > <br> >> > > >
implemented? <br> >> > > > This
 > would be very helpful for our current study and may <br>
>>  > significantly <br> >>
> > > accelerate our submission to  > Nature
Medicine. <br> >> > > > <br>
>> > > >  > Thank you for your
time, <br> >> > > > Best,
<br> >>  > > > > Gil
<br> >> > > > <br>
>> > >  > > On Mon, Oct 14, 2024
at 4:08 PM Gil Shamai @.> wrote: <br>  >
>> > > > <br> >>
> > > > Dear Hanwen, <br>  >
>> > > > > Thank you for your
email. <br> >> >  > > >
> Sure, in this task, we would like to perform a slide-level
> task <br> >> to <br> >>
> > > predict <br> >>  >
> > > > a molecular marker from H&E
images. We fine-tuned  > your slide <br> >>
encoder <br> >> > > for <br>
>>  > > > > > this task.
However, our cohort is large (10K patients),  > and thus <br>
>> we <br> >> > > >
believe <br>  > >> > > >
> that the training can be improved by  > finetuning not only
the <br> >> slide <br> >> >
> >  > encoder <br> >> >
> > > but also your frozen tile  > encoder.
<br> >> > > > > This
potential improvement may  > be critical for proving a new
<br> >> > > hypothesis <br>
> >> > > > we <br>
>> > > > > are studying.
> <br> >> > > > > Does
this make any sense? <br> >>  > >
> > > Best, <br> >> >
> > > Gil <br>  > >>
> > > > <br> >> >
> > > <br>  > >> >
> > > <br> >> > >
> > On Mon, Oct  > 14, 2024 at 10:42 AM Hanwen Xu
@.> <br> >> > > >
 > > wrote: <br> >> > >
> > <br> >> > > >
 > >> Hi Dr.Gil, yes I feel excited that
you're interested in <br>  > >>
fine-tuning <br> >> > > our <br>
>> > >  > > >>
model. Can I get more background of this task? Is it a <br>  >
>> slide-level <br> >> > >
> >> prediction task  > or tile-level? Our
current pipeline is (1) <br> >> extract <br>
> >> > > the <br> >>
> > > >> features with  > a
frozen tile-encoder (2) fine-tune the slide <br> >>
encoder <br>  > >> > > to
<br> >> > > > >>
adapt to  > specific tasks. If our task here could accept this
<br> >> >  > pipeline, <br>
>> > > > then <br>
>> > > >  > >> the
answer is yes and I'm happy to help set up your  >
experiments. <br> >> > > Also, <br>
>> > > >  > feel <br>
>> > > > >> free to
directly email me at  > @., I'm looking forward
<br> >> > > > >>
 > to your work! <br> >> > >
> >> <br> >> > >
 > > >> — <br> >> >
> > >> Reply to this email  > directly,
view it on GitHub <br> >> > > >
>> < <br>  > >> >
> > <br> >> > > <br>
>> > <br>  > >>  >
https://github.com/prov-gigapath/prov-gigapath/issues/31#issuecomment-2410304763&gt;,
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Dear Hanwen,
I haven't received an email from you yet.
Please let me know if you sent an email so that I can see it did not go to
the spam folder.
Best,
Gil
On Tue, Nov 5, 2024 at 5:56 PM Gil Shamai @.***> wrote:

sure,
@.***
OR
@.***
On Tue, Nov 5, 2024 at 5:43 PM Hanwen Xu @.***> wrote:

Yes it's ready. Can you provide me with your email address? Then I
will  share it with you.   Regards,   Hanwen
On Sun, Nov 3, 2024 at 4:23 AM Dr. Gil Shamai @.>  wrote:
  > Dear Hanwen, <br> <br> I wanted to follow up on
my previous email in case  > it may have been missed. <br>
Your assistance would be invaluable in  > helping us expedite our
study, and I <br> would greatly appreciate any  > guidance or
support you can provide. <br> <br> Thank you very much for your
 > time and consideration. <br> <br> Best, <br>
Gil <br> <br> <br> On Tue, Oct  > 29, 2024 at
11:03 AM Gil Shamai @.> wrote: <br> <br>
> Dear  > Hanwen, <br> > Thank you, that sounds
exactly like what we need! We  > appreciate the help. <br>
> What kind of slide formats does your code  > accept?
<br> > CC-ing Hen again so you can communicate directly.
<br>  > > Best, <br> > Gil <br>
> <br> > On Tue, Oct 29, 2024 at  > 12:48 AM
Hanwen Xu @.> <br> > wrote: <br>
> <br> >>  > Yes, I'm happy to
help with setting up the option (1). Is your task the  > <br>
>> classification task? If so, I can provide the finetuning
 > script taking <br> >> the <br>
>> train.csv and test.csv as  > input. Each csv has
the "image_path" and <br> >>
> "labels" <br> >> as columns. You
can then finetune by  > directly replacing the csv with your
<br> >> customized csv files.  > <br>
>> <br> >> Best, <br>
>> <br> >> Hanwen <br>  >
>> <br> >> On Mon, Oct 28, 2024 at
3:37 PM Dr. Gil Shamai  > @.> <br>
>> wrote: <br> >> <br>
>> > Dear  > Hanwen, <br>
>> > Thank you for the detailed response. <br>
 > >> > I am CC-ing Hen Davidov who is our deep
learning expert and  > would be <br> >> able
<br> >> > to follow up with more  >
details on what we need. <br> >> > <br>
>> > Option (1)  > sounds like an appropriate
solution for our problem. We <br> >>  >
weren't <br> >> > aware that the DINOv2
finetuning code was  > still compatible with your <br>
>> tile <br> >> > encoder.
> We'd very much appreciate help with setting that up,
<br> >>  > especially <br>
>> > if <br> >> > some
modifications to  > the relevant open source code are necessary. Is
<br> >> that <br>  > >>
> the case? <br> >> > Best, <br>
>> > Gil  > <br> >>
> <br> >> > On Mon, Oct 28, 2024, 19:21
Hanwen Xu  > @.> wrote: <br> >>
> <br> >> > > Ah I see.  >
Unfortunately I didn't have existing codes for end-to-end
<br> >>  > > > finetuning because
end-to-end finetuning will be computationally  > <br>
>> > > intensive. <br> >>
> > But I do have  > the code for DINOv2 finetuning
and that's only for <br> >> >  >
> tile-level <br> >> > > tasks.
Does the following work: (1)  > Finetune tile encoder on your
<br> >> large <br> >> >
>  > cohort by distributing the slide-level labels to tile
level. (2) <br>  > >> Freeze <br>
>> > > the <br> >> >
> tile  > encoder from stage 1, and then finetune the slide
encoder. If <br> >>  > this <br>
>> > > works, I can set up this pipeline for
you.  > I'm a bit busy these days <br>
>> so <br> >> > >  >
sorry for the late response. If this works, I will set it up for you
<br>  > >> > > before <br>
>> > > Friday. <br> >>
> > > <br> >> > > On
Mon, Oct 28, 2024 at 6:25 AM Dr. Gil  > Shamai @.>
<br> >> > > wrote: <br>
>> >  > > <br> >>
> > > Dear Hanwen, <br> >>
> > >  > I hope this message finds you well. I
just wanted to follow up with <br>  > >>
> you <br> >> > > on <br>
>> > > >  > my previous email
about the tile encoder. <br> >> > >
>  > Given our large cohort size and its distinctive
features, we'd like  > <br> >> to
<br> >> > > > finetune the tile
extractor.  > Thus, I just wanted to clarify and <br>
>> > suggest <br> >>  >
> > > two <br> >> >
> > things that either of them  > would help us:
<br> >> > > > 1) Could you share
the code for  > training the tile encoder? <br>
>> > > > 2) Or, if an  > existing
framework was used, could you clarify how it <br> >>
was  > <br> >> > > >
implemented? <br> >> > > > This
 > would be very helpful for our current study and may <br>
>>  > significantly <br> >>
> > > accelerate our submission to  > Nature
Medicine. <br> >> > > > <br>
>> > > >  > Thank you for your
time, <br> >> > > > Best,
<br> >>  > > > > Gil
<br> >> > > > <br>
>> > >  > > On Mon, Oct 14, 2024
at 4:08 PM Gil Shamai @.> wrote: <br>  >
>> > > > <br> >>
> > > > Dear Hanwen, <br>  >
>> > > > > Thank you for your
email. <br> >> >  > > >
> Sure, in this task, we would like to perform a slide-level
> task <br> >> to <br> >>
> > > predict <br> >>  >
> > > > a molecular marker from H&E
images. We fine-tuned  > your slide <br> >>
encoder <br> >> > > for <br>
>>  > > > > > this task.
However, our cohort is large (10K patients),  > and thus <br>
>> we <br> >> > > >
believe <br>  > >> > > >
> that the training can be improved by  > finetuning not only
the <br> >> slide <br> >> >
> >  > encoder <br> >> >
> > > but also your frozen tile  > encoder.
<br> >> > > > > This
potential improvement may  > be critical for proving a new
<br> >> > > hypothesis <br>
> >> > > > we <br>
>> > > > > are studying.
> <br> >> > > > > Does
this make any sense? <br> >>  > >
> > > Best, <br> >> >
> > > Gil <br>  > >>
> > > > <br> >> >
> > > <br>  > >> >
> > > <br> >> > >
> > On Mon, Oct  > 14, 2024 at 10:42 AM Hanwen Xu
@.> <br> >> > > >
 > > wrote: <br> >> > >
> > <br> >> > > >
 > >> Hi Dr.Gil, yes I feel excited that
you're interested in <br>  > >>
fine-tuning <br> >> > > our <br>
>> > >  > > >>
model. Can I get more background of this task? Is it a <br>  >
>> slide-level <br> >> > >
> >> prediction task  > or tile-level? Our
current pipeline is (1) <br> >> extract <br>
> >> > > the <br> >>
> > > >> features with  > a
frozen tile-encoder (2) fine-tune the slide <br> >>
encoder <br>  > >> > > to
<br> >> > > > >>
adapt to  > specific tasks. If our task here could accept this
<br> >> >  > pipeline, <br>
>> > > > then <br>
>> > > >  > >> the
answer is yes and I'm happy to help set up your  >
experiments. <br> >> > > Also, <br>
>> > > >  > feel <br>
>> > > > >> free to
directly email me at  > @., I'm looking forward
<br> >> > > > >>
 > to your work! <br> >> > >
> >> <br> >> > >
 > > >> — <br> >> >
> > >> Reply to this email  > directly,
view it on GitHub <br> >> > > >
>> < <br>  > >> >
> > <br> >> > > <br>
>> > <br>  > >>  >
https://github.com/prov-gigapath/prov-gigapath/issues/31#issuecomment-2410304763&gt;,
 > <br> >> <br> >> >
<br> >> > > <br> >>
>  > > > <br> >> >
> > >> or unsubscribe <br>  >
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> > < <br> >> > >
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 >
https://github.com/prov-gigapath/prov-gigapath/issues/31#issuecomment-2441585416&gt;,
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Dear Hanwen,
I know you must be busy so I am just pinging you again in case you've
missed my message.
Best
Gil
On Tue, Nov 19, 2024 at 2:12 PM Gil Shamai @.***> wrote:

Dear Hanwen,
I haven't received an email from you yet.
Please let me know if you sent an email so that I can see it did not go to
the spam folder.
Best,
Gil
On Tue, Nov 5, 2024 at 5:56 PM Gil Shamai @.***> wrote:

sure,
@.***
OR
@.***
On Tue, Nov 5, 2024 at 5:43 PM Hanwen Xu @.***>
wrote:

Yes it's ready. Can you provide me with your email address? Then I
will  share it with you.   Regards,   Hanwen
On Sun, Nov 3, 2024 at 4:23 AM Dr. Gil Shamai @.>  wrote:
  > Dear Hanwen, <br> <br> I wanted to follow up on
my previous email in case  > it may have been missed. <br>
Your assistance would be invaluable in  > helping us expedite our
study, and I <br> would greatly appreciate any  > guidance or
support you can provide. <br> <br> Thank you very much for your
 > time and consideration. <br> <br> Best, <br>
Gil <br> <br> <br> On Tue, Oct  > 29, 2024 at
11:03 AM Gil Shamai @.> wrote: <br> <br>
> Dear  > Hanwen, <br> > Thank you, that sounds
exactly like what we need! We  > appreciate the help. <br>
> What kind of slide formats does your code  > accept?
<br> > CC-ing Hen again so you can communicate directly.
<br>  > > Best, <br> > Gil <br>
> <br> > On Tue, Oct 29, 2024 at  > 12:48 AM
Hanwen Xu @.> <br> > wrote: <br>
> <br> >>  > Yes, I'm happy to
help with setting up the option (1). Is your task the  > <br>
>> classification task? If so, I can provide the finetuning
 > script taking <br> >> the <br>
>> train.csv and test.csv as  > input. Each csv has
the "image_path" and <br> >>
> "labels" <br> >> as columns. You
can then finetune by  > directly replacing the csv with your
<br> >> customized csv files.  > <br>
>> <br> >> Best, <br>
>> <br> >> Hanwen <br>  >
>> <br> >> On Mon, Oct 28, 2024 at
3:37 PM Dr. Gil Shamai  > @.> <br>
>> wrote: <br> >> <br>
>> > Dear  > Hanwen, <br>
>> > Thank you for the detailed response. <br>
 > >> > I am CC-ing Hen Davidov who is our deep
learning expert and  > would be <br> >> able
<br> >> > to follow up with more  >
details on what we need. <br> >> > <br>
>> > Option (1)  > sounds like an appropriate
solution for our problem. We <br> >>  >
weren't <br> >> > aware that the DINOv2
finetuning code was  > still compatible with your <br>
>> tile <br> >> > encoder.
> We'd very much appreciate help with setting that up,
<br> >>  > especially <br>
>> > if <br> >> > some
modifications to  > the relevant open source code are necessary. Is
<br> >> that <br>  > >>
> the case? <br> >> > Best, <br>
>> > Gil  > <br> >>
> <br> >> > On Mon, Oct 28, 2024, 19:21
Hanwen Xu  > @.> wrote: <br> >>
> <br> >> > > Ah I see.  >
Unfortunately I didn't have existing codes for end-to-end
<br> >>  > > > finetuning because
end-to-end finetuning will be computationally  > <br>
>> > > intensive. <br> >>
> > But I do have  > the code for DINOv2 finetuning
and that's only for <br> >> >  >
> tile-level <br> >> > > tasks.
Does the following work: (1)  > Finetune tile encoder on your
<br> >> large <br> >> >
>  > cohort by distributing the slide-level labels to tile
level. (2) <br>  > >> Freeze <br>
>> > > the <br> >> >
> tile  > encoder from stage 1, and then finetune the slide
encoder. If <br> >>  > this <br>
>> > > works, I can set up this pipeline for
you.  > I'm a bit busy these days <br>
>> so <br> >> > >  >
sorry for the late response. If this works, I will set it up for you
<br>  > >> > > before <br>
>> > > Friday. <br> >>
> > > <br> >> > > On
Mon, Oct 28, 2024 at 6:25 AM Dr. Gil  > Shamai @.>
<br> >> > > wrote: <br>
>> >  > > <br> >>
> > > Dear Hanwen, <br> >>
> > >  > I hope this message finds you well. I
just wanted to follow up with <br>  > >>
> you <br> >> > > on <br>
>> > > >  > my previous email
about the tile encoder. <br> >> > >
>  > Given our large cohort size and its distinctive
features, we'd like  > <br> >> to
<br> >> > > > finetune the tile
extractor.  > Thus, I just wanted to clarify and <br>
>> > suggest <br> >>  >
> > > two <br> >> >
> > things that either of them  > would help us:
<br> >> > > > 1) Could you share
the code for  > training the tile encoder? <br>
>> > > > 2) Or, if an  > existing
framework was used, could you clarify how it <br> >>
was  > <br> >> > > >
implemented? <br> >> > > > This
 > would be very helpful for our current study and may <br>
>>  > significantly <br> >>
> > > accelerate our submission to  > Nature
Medicine. <br> >> > > > <br>
>> > > >  > Thank you for your
time, <br> >> > > > Best,
<br> >>  > > > > Gil
<br> >> > > > <br>
>> > >  > > On Mon, Oct 14, 2024
at 4:08 PM Gil Shamai @.> wrote: <br>  >
>> > > > <br> >>
> > > > Dear Hanwen, <br>  >
>> > > > > Thank you for your
email. <br> >> >  > > >
> Sure, in this task, we would like to perform a slide-level
> task <br> >> to <br> >>
> > > predict <br> >>  >
> > > > a molecular marker from H&E
images. We fine-tuned  > your slide <br> >>
encoder <br> >> > > for <br>
>>  > > > > > this task.
However, our cohort is large (10K patients),  > and thus <br>
>> we <br> >> > > >
believe <br>  > >> > > >
> that the training can be improved by  > finetuning not only
the <br> >> slide <br> >> >
> >  > encoder <br> >> >
> > > but also your frozen tile  > encoder.
<br> >> > > > > This
potential improvement may  > be critical for proving a new
<br> >> > > hypothesis <br>
> >> > > > we <br>
>> > > > > are studying.
> <br> >> > > > > Does
this make any sense? <br> >>  > >
> > > Best, <br> >> >
> > > Gil <br>  > >>
> > > > <br> >> >
> > > <br>  > >> >
> > > <br> >> > >
> > On Mon, Oct  > 14, 2024 at 10:42 AM Hanwen Xu
@.> <br> >> > > >
 > > wrote: <br> >> > >
> > <br> >> > > >
 > >> Hi Dr.Gil, yes I feel excited that
you're interested in <br>  > >>
fine-tuning <br> >> > > our <br>
>> > >  > > >>
model. Can I get more background of this task? Is it a <br>  >
>> slide-level <br> >> > >
> >> prediction task  > or tile-level? Our
current pipeline is (1) <br> >> extract <br>
> >> > > the <br> >>
> > > >> features with  > a
frozen tile-encoder (2) fine-tune the slide <br> >>
encoder <br>  > >> > > to
<br> >> > > > >>
adapt to  > specific tasks. If our task here could accept this
<br> >> >  > pipeline, <br>
>> > > > then <br>
>> > > >  > >> the
answer is yes and I'm happy to help set up your  >
experiments. <br> >> > > Also, <br>
>> > > >  > feel <br>
>> > > > >> free to
directly email me at  > @., I'm looking forward
<br> >> > > > >>
 > to your work! <br> >> > >
> >> <br> >> > >
 > > >> — <br> >> >
> > >> Reply to this email  > directly,
view it on GitHub <br> >> > > >
>> < <br>  > >> >
> > <br> >> > > <br>
>> > <br>  > >>  >
https://github.com/prov-gigapath/prov-gigapath/issues/31#issuecomment-2410304763&gt;,
 > <br> >> <br> >> >
<br> >> > > <br> >>
>  > > > <br> >> >
> > >> or unsubscribe <br>  >
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>  > > > <br> >> >
> > >> . <br> >> >
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you authored the  > thread.Message <br> >> ID:
<br> >> > > > >>
 > @.> <br> >> > >
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 > <br> >> <br> >> >
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Support for the new "Native Javascript Modules" ( /** @odoo-module **/ ) without filename globs

Support for the new js files has been added here:

https://github.com/OCA/oca-addons-repo-template/pull/86

At least to me, having to name a file .esm.js is not intuitive and finding this information took me a while
Ideally we'd want eslint to be smart enough to choose the right sourceType when parsing a file, and so we could drop this glob matching.
Here's a stackoverflow answer that claims it's possible:

https://stackoverflow.com/a/69310095

It requires creating a custom eslint plugin to identify ("disambiguate") the files.
In our case, all this plugin would need to do is try to find  /** @odoo-module **/ in the file header

finding this information took me a while

FTR It's in the migration guide: https://github.com/OCA/maintainer-tools/wiki/Migration-to-version-15.0


tarpit malicious requests

https://news.ycombinator.com/item?id=33055704
https://github.com/mickael-kerjean/filestash/blob/master/server/plugin/plg_security_scanner/index.go#L198-L217

This is not something for ong to do, instead it is for users of ong to implement in their apps.

good idea, but needs to be implemented in apps not in this lib.


bytearray needs an encoding in Python 3.6.2

In the Python bindings, class Run.parse_file is doing a:
bytes = bytearray(file.read())
But it needs to pick an encoding, at least in my Python 3.6.2 just installed from python.org, such as:
bytes = bytearray(file.read(), 'utf8')

Is that compatible with older versions too? If there's a way to support old versions too, feel free to fix it and do a PR.

Looks like bytearray was added in 2.6 and had that argument all along. Will do the PR.

Wait, why do you need an encoding for a byte array? That seems super weird O.o

Good question.  So I have the real fix figured out.  I was slightly thrown off here by a subtle change in read() semantic porting my code from python 2 to python 3.
(Yes you may laugh from rust land :)

PR #69 sent.


Tracking correction (demo/pom.xml)

The tracking of the demo-pom.xml was corrected.
The changes need to be propagated correctly to the nested projects.

Done, git detected the changes automatically and fixed them correctly when merging 👍


How to update the packages?

How can I test my packages?
I am trying to add some modules in the Existing package. I have added the quotes module in the leon package.
I added this in leon/data/expressions/en.json

"quote": [
		"Tell me a Quote",
		"Give me a Quote",
	]

Then I have updated the below in ` leon/data/expressions/en.json

"quote":{
  	  "quotes":
  	   [
		  "Design is the silent ambassador of your brand. ",
		  "If there is one word I’d like to remove from any conversation about design, it’s “pretty.",
	   ]
    }

Then I create a new python file named  quote.py. Please see the below code.
import utils

def quote(string):
	"""Leon says some quote"""

	return utils.output('end', 'quotes', utils.translate('quotes'))

I also created a new test python file in the test folder.
But it seems it breaks leon. Wheneve I ask question it gives reply as "Sorry, I don't work correctly!"
How can I test the modules?  Do I need to add anything else?

check the error logs get in console

I am running it through docker. Can you please tell me the code to get the logs in console?

npm run dev:server
npm run dev:app

@jtorresdev  I got this below error when I tried  npm run dev:server

><EMAIL_ADDRESS>dev:server /home/emperoreby/sideprojects/leon
> npm run train expressions && nodemon --watch server ./server/src/index.js --exec babel-node

><EMAIL_ADDRESS>train /home/emperoreby/sideprojects/leon
> babel-node scripts/run-train.js "expressions"

sh: 1: babel-node: not found
npm ERR! file sh
npm ERR! code ELIFECYCLE
npm ERR! errno ENOENT
npm ERR! syscall spawn
npm ERR<EMAIL_ADDRESS>train: `babel-node scripts/run-train.js "expressions"`
npm ERR! spawn ENOENT
npm ERR!
npm ERR! Failed at the<EMAIL_ADDRESS>train script.
npm ERR! This is probably not a problem with npm. There is likely additional logging output above.
npm WARN Local package.json exists, but node_modules missing, did you mean to install?

npm ERR!  Exit status 1
npm ERR!
npm ERR! Failed at the<EMAIL_ADDRESS>dev:server script.
npm ERR! This is probably not a problem with npm. There is likely additional logging output above.
npm WARN Local package.json exists, but node_modules missing, did you mean to install?

npm ERR! A complete log of this run can be found in:
npm ERR!     /home/emperoreby/.npm/_logs/2019-02-27T02_45_26_870Z-debug.log

@menporulporiayalan run npm install

@jtorresdev  Got this error, while installing.

✖ Failed to install the Python packages: Error: Command failed: /bin/sh -c pipenv install
Traceback (most recent call last):
  File "/usr/local/bin/pipenv", line 11, in <module>
    sys.exit(cli())
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 764, in __call__
    return self.main(*args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 717, in main
    rv = self.invoke(ctx)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 1137, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 956, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 555, in invoke
    return callback(*args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/decorators.py", line 64, in new_func
    return ctx.invoke(f, obj, *args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 555, in invoke
    return callback(*args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/decorators.py", line 17, in new_func
    return f(get_current_context(), *args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/cli/command.py", line 254, in install
    editable_packages=state.installstate.editables,
  File "/usr/local/lib/python2.7/dist-packages/pipenv/core.py", line 1741, in do_install
    pypi_mirror=pypi_mirror,
  File "/usr/local/lib/python2.7/dist-packages/pipenv/core.py", line 574, in ensure_project
    pypi_mirror=pypi_mirror,
  File "/usr/local/lib/python2.7/dist-packages/pipenv/core.py", line 494, in ensure_virtualenv
    python = ensure_python(three=three, python=python)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/core.py", line 397, in ensure_python
    path_to_python = find_a_system_python(python)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/core.py", line 350, in find_a_system_python
    from .vendor.pythonfinder import Finder
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/pythonfinder/__init__.py", line 14, in <module>
    from .pythonfinder import Finder
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/pythonfinder/pythonfinder.py", line 6, in <module>
    from .models import SystemPath
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/pythonfinder/models/__init__.py", line 11, in <module>
    from ..utils import KNOWN_EXTS, unnest
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/pythonfinder/utils.py", line 27, in <module>
    from backports.functools_lru_cache import lru_cache
ImportError: No module named functools_lru_cache

✖ Error: Command failed: /bin/sh -c pipenv install
Traceback (most recent call last):
  File "/usr/local/bin/pipenv", line 11, in <module>
    sys.exit(cli())
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 764, in __call__
    return self.main(*args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 717, in main
    rv = self.invoke(ctx)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 1137, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 956, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 555, in invoke
    return callback(*args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/decorators.py", line 64, in new_func
    return ctx.invoke(f, obj, *args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/core.py", line 555, in invoke
    return callback(*args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/click/decorators.py", line 17, in new_func
    return f(get_current_context(), *args, **kwargs)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/cli/command.py", line 254, in install
    editable_packages=state.installstate.editables,
  File "/usr/local/lib/python2.7/dist-packages/pipenv/core.py", line 1741, in do_install
    pypi_mirror=pypi_mirror,
  File "/usr/local/lib/python2.7/dist-packages/pipenv/core.py", line 574, in ensure_project
    pypi_mirror=pypi_mirror,
  File "/usr/local/lib/python2.7/dist-packages/pipenv/core.py", line 494, in ensure_virtualenv
    python = ensure_python(three=three, python=python)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/core.py", line 397, in ensure_python
    path_to_python = find_a_system_python(python)
  File "/usr/local/lib/python2.7/dist-packages/pipenv/core.py", line 350, in find_a_system_python
    from .vendor.pythonfinder import Finder
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/pythonfinder/__init__.py", line 14, in <module>
    from .pythonfinder import Finder
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/pythonfinder/pythonfinder.py", line 6, in <module>
    from .models import SystemPath
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/pythonfinder/models/__init__.py", line 11, in <module>
    from ..utils import KNOWN_EXTS, unnest
  File "/usr/local/lib/python2.7/dist-packages/pipenv/vendor/pythonfinder/utils.py", line 27, in <module>
    from backports.functools_lru_cache import lru_cache
ImportError: No module named functools_lru_cache

@louistiti  Could you please let me know what I did wrong? Why the Leon breaks?

Hello @menporulporiayalan,
First of all, thanks for contributing by creating a Leon's module.
It's normal you have these errors as you are using Python 2.7 outside of Docker.
Try to do a docker logs -f <CONTAINER>, with the ID of your running container, that will show you a log in real time.

@louistiti  In the Logs, I have got this below error.
✖ The expressions classifier is missing, please rebuild the project or if you are in dev run: npm run train expressions

To develop a Leon's module, I do not recommend you to use Docker, as the Dockerfile and the npm scripts were prepared for an "easy to go" setup.
For the moment, the best shot would be to install Leon as mentioned in the documentation without Docker. To do so, you firstly need to use Python 3.6.x as your machine is using Python 2.7 according to your previous log messages.
But now, to have a better understanding of the situation, please:

Run: npm run docker:build
Run: npm run docker:run
Run: docker logs -f <YOUR_CONTAINER>
Paste the full output of your terminal in a Pastebin
Share this Pastebin here

@louistiti  Here it is ->  Pastebin link

The Pastebin is private, I cannot see it. Please switch to public.

I am sorry, Kindly check now.

 Because it should generate your classifier on that moment.
But as I said, don't use Docker for development purposes as the Leon's workflow is not ready for that (yet).

Yes, I Built. I figured out the issue. The Issue is with the JSON file. Thanks for your time @louistiti :)


automatically start translating with CMD + C + C like DeepL

Hi!
Thank you for creating this.
If we can start translating with CMD + (C + C) like DeepL app, it makes our life easier

Oh, maybe adding shortcut for service is good enough!!!
Thanks


feat: 3657 - blue banner on bottom end when in "TEST ENV"

Impacted file:

page_manager.dart: blue banner on bottom end when in "TEST ENV"

What

blue banner on bottom end when in "TEST ENV"

Screenshot

Fixes bug(s)

Closes: #3657

Codecov Report

Merging #3660 (f17dc8c) into develop (b013a9a) will decrease coverage by 0.01%.
The diff coverage is 0.00%.

:exclamation: Current head f17dc8c differs from pull request most recent head be96bd7. Consider uploading reports for the commit be96bd7 to get more accurate results

@@             Coverage Diff             @@
##           develop    #3660      +/-   ##
===========================================
- Coverage    10.64%   10.63%   -0.01%
===========================================
  Files          270      270
  Lines        13484    13487       +3
===========================================
  Hits          1435     1435
- Misses       12049    12052       +3

Impacted Files
Coverage Δ

packages/smooth_app/lib/pages/page_manager.dart
1.66% <0.00%> (-0.09%)
:arrow_down:

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more

Thank you @teolemon for the review!

Thank you @monsieurtanuki !


Allow the user to require that FHIR Base URLs use HTTPS

Right now, we'll default require_https to false, so that this PR can be non-breaking.
Then, in the future, we'll make a breaking release of FHIRClient.jl in which we change the default to require_https = true.

Bump @Vaibhavdixit02

Then, in the future, we'll make a breaking release of FHIRClient.jl in which we change the default to require_https = true.

#122


is it possible to get overId and activeId on dndcontext modifiers ?

hey, awesome library! really smooth transitions
is it possible to get the overId and activeId on a custom modifier context ? I would like to apply custom restrictions based on the type of the element i'm dragging rather than its position.
thanks

Hey, not currently, but this would be a fairly straightforward change. If you'd like to and have time to do so, PRs are welcome 🙏

Hey, not currently, but this would be a fairly straightforward change. If you'd like to and have time to do so, PRs are welcome 🙏

This would be cool to have!

Added in this PR #207


Discussion about the files in the /boot and initrd

This PR was opened to have a place where to discuss line by line on the files that we can or cannot remove from the /boot partition and initrd. Or maybe move them into the /usr.
This is a follow up on @pothos suggestion to cut things we do not need: https://github.com/flatcar/Flatcar/issues/1381#issuecomment-1969285023
How the data was compiled:
# Content of the /boot partition for AMD64 built from
# flatcar/scripts commit a842366ed9a2c2b1204a87f8563ef09e2950e5e3
tree -sifF  /boot | sort -k2 -rn

# Main data
$: df | grep '/boot'
/dev/vda1          129039      64135      64905  50% /boot

$: file flatcar_production_image.vmlinuz
flatcar_production_image.vmlinuz: Linux kernel x86 boot executable bzImage, version 6.6.17-flatcar<EMAIL_ADDRESS>#1 SMP PREEMPT_DYNAMIC Mon Mar  4 18:50:2A

$: du flatcar_production_image.vmlinuz
56124   flatcar_production_image.vmlinuz

Added another commit with the initrd contents.
How the data was compiled:
bash extract-initramfs-from-vmlinuz.sh flatcar_production_image.vmlinuz vmlinuz
cd vmlinuz/
tree -sifF . | sort -k2 -rn

Thanks, we can also discuss the kernel config: https://alpha.release.flatcar-linux.net/amd64-usr/current/flatcar_production_image_kernel_config.txt

My impression is that we should start with the big stuff: find a way to load network firmware and kernel modules, and CPU microcode update from /sysusr/usr/.

Thanks, we can also discuss the kernel config: https://alpha.release.flatcar-linux.net/amd64-usr/current/flatcar_production_image_kernel_config.txt

Added this file for discussion.

I will keep in this updated comment a log of the AMD64 /boot partition size history, to have a clear picture on the size increase over time:
# 2024-03-18, Flatcar ALPHA 3913.0.0 https://alpha.release.flatcar-linux.net/amd64-usr/3913.0.0/
TBD
# 2024-03-25, Flatcar HEAD https://github.com/flatcar/scripts/commit/6ebffa7a4fde3a1b2c8d362b065b35b4ce3a43e4
/dev/sda1<PHONE_NUMBER>3     66536  49% /boot


Support over BT

Hi, great feature here!
Any way this can work over bluetooth (BT-1 and BT-2) instead of using the cable? Like Raspberry Pi blupy as the data logger?

Hi, just wanted to follow up on this, looks like there is a way to get this work over the bluetooth module, BT-1. Please see this thread:
https://diysolarforum.com/threads/renogy-devices-and-raspberry-pi-bluetooth-wifi.30235/#post-402147
Seems to work well with the Rover and BT-1. Any ides how to get this to work with BT-2 modules (i.e. battery/inverters)? Your input would be greatly apprecaited on the forum.

That's cool that people are figuring out how to read from the bluetooth. I didn't realize someone already reverse engineered that for Rengoy BT.
I don't know how to get it to work with BT-2 modules. Like I said, I don't know if the BT-1 and BT-2 modules do the same thing (just with a different connection). I would have guessed that BT-1 and BT-2 modules are pretty similar, but if people cannot get BT-2 modules to work with software that works with BT-1 then I guess that might prove that wrong.
I've had brief looks at the Renogy DC Home's decompiled code, and from what I can tell, BT-1 and BT-2 modules are treated the same in the code. I'm only aware of the app treating some registers differently for the DCDC Dual Input Charger, but that isn't bluetooth related. SolarThing also has to treat some of the registers differently for DCDC controllers.
I imagine that once you establish connection with a bluetooth module, you don't have to treat it differently based on if it is a battery, inverter or charge controller. From what I can tell, the bluetooth module is just an interface around making modbus requests to the controller. Batteries, inverters, and charge controllers all have different modbus documents, meaning that most of their registers are different from each other. Again, this isn't bluetooth related, but I figured it's worth mentioning.
Also the decompiled Renogy DC Home code is some of the ugliest code I've ever seen (I think some of it is obfuscated), so I could have easily missed something.
Thanks for asking for my input. This is interesting stuff. I'll be watching that thread and might reply if I think there's anything useful I can add.

Sounds good, even your reply already helped! Hopefully, with enough brain-power and expertise like yours, we can get it to work!


Add more benchmarks to the suite

Now we have an asv benchmark suite (https://github.com/pygeos/pygeos/pull/96), we should add more benchmarks, covering the full functionality of pygeos.

I'd be happy to work on this. Two benchmarks that come to mind are:

Copying the README example of calculating the area of the intersection of polygons (with larger sets)
Computing a voronoi diagram

Any other suggestions?

I think we eventually want to have benchmarks covering almost all functions, but so those you mention certainly sound useful to start with!


Complete migration to Vox Pupuli

[x] Perform label sync
[x] Update metadata.json
[x] Add README badges
[x] Add note to README https://github.com/voxpupuli/puppet-firewalld/commit/e11ebbceca6ba7afa75740a0950acead54ed19f5#diff-04c6e90faac2675aa89e2176d2eec7d8
[x] Create release summary ticket
[x] Review open PRs/tickets for low hanging fruit and/or release critical issues
[x] Rubocop
[x] Add module to plumbing/modulesync_config
[x] Modulesync
[x] Release 4.0.0
[x] Open Puppetlabs JIRA ticket to deprecate old module and move approved status

See https://tickets.puppetlabs.com/browse/FORGE-524


Support for Django 1.11

Hi, when do you plan to integrate this pr to master?

Looks like something needs doing with url patterns (Django 1.11 moved to a python list rather than a patterns object). Been meaning to have a look but haven't had the time. May try today.

Scratch that, looks like urlpatterns as a Python list is in 1.8. PR #86 has already fixed this. @philippbosch Can you merge that PR into this one? All should be green and you'll be good for a release.


#9196: Merge new op: Fast reduce nc into main

Currently, there are two ways to perform reduction on device. The ttnn.experimental.tensor.sum api performs transposes of dim0 and dim1 into row and column dims, and perform row/col reduction. This approach is very slow and creates extra ops. On the other hand, the moreh_sum api performs reduction on dim0 and dim1 much more efficiently, with dedicated kernels for those operations. A comparison of two ops can be found #9126  However, more optimization could be done on moreh_sum op by increasing its granularity, using dst accumulation for add_tiles (new feature), and support bfp8_b reduction, which is being used in Mixtral8x7b model.
Hence, I created this new op called fast_reduce_nc which dedicates an optimized reduction on dim0 and 1, and supports bfp8_b precision.
A perf comparison of the fast_reduce_nc op and moreh sum op on Mixtral8x7b use cases is below:

FYI @cglagovich @cglagovichTT @sraizada-tt

Great work @caixunshiren !

all post commit tests passed. Merging to Main


Cannot change max size of attachments via env variables on docker

Gitea version (or commit ref):
Git version: 1.13.2
Operating system: docker on centos
Database (use [x]):

[x] MySQL

Description
setting the env var GITEA__ATTACHMENT__MAX_SIZE=40 in docker-compose is ignored and the limit is still 4MB
Screenshots

most of the env vars passed to docker are only used to cerate the app.ini if it doesn't yet exist. If app.ini already exists then you'll need to configure it there. You appear to be using the format for the contrib helper script https://github.com/go-gitea/gitea/tree/master/contrib/environment-to-ini however that is not built into the default docker image.

This would be a nice addition though, no ? :)


JSON Format

Thanks for putting this list together. Would be great to have it in JSON format.

Hello @shellscape ,
Thank you for your request regarding the conversion of an MD file to a JSON file. I have successfully converted the MD file to a JSON file named 'device.json.' If you have any feedback, please inform me.

thanks!


Consider alterantives

BTW, https://github.com/a8m/envsubst supports "fail on unset var".

There's also https://github.com/containeroo/renvsubst


bump build number in preparation for automatic re-rendering

Checklist

[x] Used a personal fork of the feedstock to propose changes
[x] Bumped the build number (if the version is unchanged)
[ ] Reset the build number to 0 (if the version changed)
[x] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[ ] Ensured the license file is being packaged.

Creating a pull request for automatic re-rendering

@conda-forge-admin, please re-render

@conda-forge-admin, please rerender

Looks like there is an issue with the new C compilers and the KIM API, all the builds are giving the same error:
/Users/runner/miniforge3/conda-bld/kim-api_1706245648194/work/kim-api-2.3.0/build/examples/model-drivers/ex_model_driver_P_LJ/item-compiled-with-version.txt.c:5:1: error: unknown type name 'size_t'
I feel like I've seen this error before, but don't remember where I saw it or how I fixed it, does anyone else?
I don't think it's urgent to get this built with the new compilers, I will take a closer look later when I get a chance.


/var/lib/jenkins folder empty

Hi,
I am new to AWS and was trying to implement CI/CD pipeline in AWS. I got stuck on  Step 2 => 4nd Point.
In EC2 instance /var/lib/jenkins was empty and curl to localhost:8080 gives :-
HTTP ERROR: 503
Problem accessing /. Reason:
Service Unavailable
I am unable to figure out the reason why it is happening.
Thanks .

Hi Amit,
Sorry you're having trouble.  Sounds like Jenkins wasn't.  I'll try running through this again later this week.  Meanwhile, try running the CFN stack template for Jenkins again.
The formatting for the README is all messed up.  Not sure it contributed to this problem, but I need to fix that too.

Thankyou Jeremy,
The issue was solved by reinstalling Jenkins.
I have tried running the template 4 times but each time I got same result.

Hi Amit,
I fixed the CFN template so that it installs Java 1.8.0.  It should work now.  This getting started guide was published on http://docs.aws.amazon.com/AWSGettingStartedContinuousDeliveryPipeline/latest/GettingStarted/CICD_Jenkins_Pipeline.html.  The formatting is fixed on that site.


As a master I want to create the list of inventory so event's participants can see needs equipment

[ ] Expand the DB and correspondive repo

[ ] Implement the logic of creating an inventory list

[ ] Create form on UI

Uploading sch_10_29_20.pdf…


Enabling ADR (  LoRaWAN Adaptive Data Rate)

Hello all, i would like to thank the author of this library it’s supper easy to use without any complexity, so now i have two questions one is instead of setting a specific DataRate like lora.setDataRate(SF8BW125) is there a way we can let a node decided which DataRate is best for it according to the distance between node and Gateway.
My second question is i was checking in the library function but i haven’t seen any way we can put a node into sleep mode without putting the whole microcontroller into sleep mode. Thanks

Hi lambertoo, ADR is set by server and sent to the node using MAC commands  I have plans to implement it in this library if the authors aren't already doing it but first need to add MAC commands functionality. I'm still checking differences in regional parameters implying changes in functionality from EU868 (my region) and US915  (original library region)

@mr3188 .. do you have some news on ADR enhancement?
It's a very useful feature ;)

I'm sorry  I have been busy looking at confirmed downlink/uplink issues but I will try to work on MAC commands common code to be able to have ADR on top.
With ADR the server ask the node to change DR but there are some SX12... registers that give us information of last messages signal strength. i haven't used it before  but I suppose it can help the to the node decide which DR to use.
I will first try with LinkCheck MAC command that seems to be simpler and then go forward with ADR.

I have successfully sent LinkCheckReq command from the node to the ChirpStack server as a single uplink with port=0 and 0x02 in payload. ChirpStack recognises the command but I can't see any downlink with LinkReqAns from the server.
I don't know if the problems is the ChirpStack server or the gateway (RAK831), and I will not have another gateway to test until next week.
With TTN v2 I don't see any information about the command, just an uplink without payload.
I will try sending the command together with a regular uplink using Frame options field.
Does any body know how to trace communication between ChirpStack server and the gateway?

I have changed the gateway to a Dragino LPS8 and know I can see LickCheckAns dow links. I will confirm I'm handling LinkCheckAns correctly before pushing changes to repo.

I have created #75 as a base to implement ADR support.
It has some MAC commands already working and tested and I will commit changes to be able to discuss if it meets al regional requirements we need to change frequencies, active channels and data rates now stored in static structures.


remove 1 - cosine similarity.

by wikipedia definiton:
https://en.wikipedia.org/wiki/Cosine_similarity
a.dot(b) / (norm(a) * norm(b))
this gives normalized results in the range -1 to 1

@@            master   #5857   diff @@
======================================
  Files          237     237
  Stmts        43374   43358    -16
  Branches      8135    8134     -1
  Methods          0       0
======================================
- Hit          33832   33816    -16
  Partial       2586    2586
  Missed        6956    6956

Review entire Coverage Diff as of 106f1d4

Powered by Codecov. Updated on successful CI builds.

Sorry, but this isn't the sort of change we can (or would like to) accept. scipy.spatial.distance defines distances, whereas the Wikipedia definition you cite is for cosine similarity.

-1.  We can't just change this because it will likely break other peoples code.  Beyond that, the page you linked even points out that cosine distance, which is what is being calculated here, uses  the 1-.

Too slow!

@ewmoore You are right, it does say that :)
I got confused when the function returned values larger than 1.
Sorry


Data leak for self-created users

Hello,
I use CVAT and am very happy with it. So I want to give some feedback to improve the software.
This Issue does not need to be solved. I found a workarround.
I use CVAT on an AWS server and everyone has access to it. I also use a shared path:
https://openvinotoolkit.github.io/cvat/docs/administration/basics/installation/#share-path
The problem is that anyone who creates their own account, is assigned to the group user and has access to the shared path and can steal my data.
If that's the way it should be, I think it should be changed.
If this post is somehow redundant, wrong or incomprehensible, you can simply delete it.
Siccerelly,
xXxTheUserxXx

@xXxTheUserxXx , thanks for the feedback. Need to think how to protect share-path. Did you try Cloud Storages: https://openvinotoolkit.github.io/cvat/docs/manual/basics/attach-cloud-storage/?

@nmanovic,
currently the files are stored on a private AWS FSx file server. But we will think about using cloud storage. Thank you for this advice.
Maybe another possible improvement would be that an account assigned to the group worker doesn't even see that there are "shared files". At the moment, if he tries to create a new task, he can see that there are shared files and folders, but he cannot create a task.

The problem is that anyone who creates their own account, is assigned to the group user.

How can I change this behaviour? I don't want new users to have any rights.
@nmanovic


Add Zilliqa information

Hello. Zilliqa core team member here. This PR adds Zilliqa token information to Metamask.
Etherscan url: https://etherscan.io/token/0x05f4a42e251f2d52b8ed15e9fedaacfcef1fad27

Hi @bb111189, could you link to an official Zilliqua source that cites this contract address?

The official source is at https://www.youtube.com/watch?v=gW0Hd8VQlq0


⚠ ClamAV has degraded performance

In 09b9e5b, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 253 ms

Resolved: ClamAV performance has improved in a677408 after 15 minutes.