The Equ.5 and the operate fold in the paper do not seem to be consistent.

The Equ.5:

In my opinion, this equ calculates the sum of features in the neighborhood corresponding to (i,j).
But in the code:
https://github.com/sail-sg/volo/blob/1f67923404d85cb8012a61b35d7eff782fe90cef/models/volo.py#L94-L95
F.fold(x, output_size=(H, W), ...) implements another operation.
Let's start with a simple example.
a = torch.randperm(18).float().reshape(1, 2, 3, 3)  # B=1, C=2, H=W=3

a
Out[33]:
tensor([[[[ 7., 14.,  0.],  # the first channel
          [ 8., 15., 16.],
          [ 6.,  4., 12.]],
         [[ 2., 17., 13.],  # the first channel
          [10.,  9., 11.],
          [ 5.,  3.,  1.]]]])

Collect the adjacent features in the local region 3x3 and stack the nine values along the channel dimension.
unfold_a = F.unfold(a, kernel_size=3, padding=1)  # 1 x C*K*K x H*W

The id of the row indexes the position of the HW space, the number of ids is HW=9
The id of the column indexes the position of the K*K neighbors in different channels.
For the column, it should be noted that this is channel-independent.
That is, first stack the data inside the channels, and then stack the data of different channels in sequence.
For example, the fourth line [ 0.,  7., 14.,  0.,  8., 15.,  0.,  6.,  4.] represents the fourth neighbor in the different windows from the first channel plane.
Specifically, for the first element 0, it represents the fourth value in the flattened K*K window ([[0, 0, 0], [0, 7, 4], [0, 8, 15]]) located at the upper left corner of the padded a.
unfold_a
Out[35]:
tensor([[
         # the first channel
         [ 0.,  0.,  0.,  0.,  7., 14.,  0.,  8., 15.],
         [ 0.,  0.,  0.,  7., 14.,  0.,  8., 15., 16.],
         [ 0.,  0.,  0., 14.,  0.,  0., 15., 16.,  0.],
         [ 0.,  7., 14.,  0.,  8., 15.,  0.,  6.,  4.],
         [ 7., 14.,  0.,  8., 15., 16.,  6.,  4., 12.],
         [14.,  0.,  0., 15., 16.,  0.,  4., 12.,  0.],
         [ 0.,  8., 15.,  0.,  6.,  4.,  0.,  0.,  0.],
         [ 8., 15., 16.,  6.,  4., 12.,  0.,  0.,  0.],
         [15., 16.,  0.,  4., 12.,  0.,  0.,  0.,  0.],
         # the second channel
         [ 0.,  0.,  0.,  0.,  2., 17.,  0., 10.,  9.],
         [ 0.,  0.,  0.,  2., 17., 13., 10.,  9., 11.],
         [ 0.,  0.,  0., 17., 13.,  0.,  9., 11.,  0.],
         [ 0.,  2., 17.,  0., 10.,  9.,  0.,  5.,  3.],
         [ 2., 17., 13., 10.,  9., 11.,  5.,  3.,  1.],
         [17., 13.,  0.,  9., 11.,  0.,  3.,  1.,  0.],
         [ 0., 10.,  9.,  0.,  5.,  3.,  0.,  0.,  0.],
         [10.,  9., 11.,  5.,  3.,  1.,  0.,  0.,  0.],
         [ 9., 11.,  0.,  3.,  1.,  0.,  0.,  0.,  0.]]])

the original data
a
Out[38]:
tensor([[[[ 7., 14.,  0.],
          [ 8., 15., 16.],
          [ 6.,  4., 12.]],
         [[ 2., 17., 13.],
          [10.,  9., 11.],
          [ 5.,  3.,  1.]]]])

Inconsistent with the equation of the paper.
fold_a = F.fold(unfold_a, output_size=(3, 3), kernel_size=3, padding=1)

fold_a
Out[40]:
tensor([[[[ 28.,  84.,   0.],
          [ 48., 135.,  96.],
          [ 24.,  24.,  48.]],
         [[  8., 102.,  52.],
          [ 60.,  81.,  66.],
          [ 20.,  18.,   4.]]]])

For simplicity, we only look at the first channel plane.
[[ 28.,  84.,   0.],
  [ 48., 135.,  96.],
  [ 24.,  24.,  48.]]

Comparing the previous unfold_a, we can find that the value of each element here is actually the result of the accumulation of different windows after returning to their original position in padded a:

In the first step, the values of different windows are placed back to their original corresponding positions in sequence.
In the second step, the values corresponding to the same element positions are accumulated.
3. For examples, fold_a[0, 0, 0, 1] = 84 = unfold_a[0, 5, 0] + unfold_a[0, 4, 1] + unfold_a[0, 3, 2] + unfold_a[0, 2, 3]+ unfold_a[0, 1, 4] + unfold_a[0, 0, 5]. These values come from different windows instead of the "same window" expressed in the equ. 5 of the paper.
The third step is to remove padding.

@lartpang Agree with you completely. And I also refer to the pytorch documentation

Fold calculates each combined value in the resulting large tensor by summing all values from all containing blocks. Unfold extracts the values in the local blocks by copying from the large tensor. So, if the blocks overlap, they are not inverses of each other.(https://pytorch.org/docs/stable/generated/torch.nn.Fold.html?highlight=fold#torch.nn.Fold)

Note the definition of  in equation 3.

It's a local window centered at (i,j). And here in equation 5

the summation is over (m,n) , which means gathering vectors from different windows but same original element location (i,j), same as step 1 and 2 in your comment @lartpang .
The notation is a little tricky, but it does not calculate the sum of features in the neighborhood corresponding to (i,j), but doing a fold op.

@zihangJiang
Ah oh, it looks like this is indeed the case, my understanding does have errors.
In my opinion, the paper lacks emphasis on this.
After all, such cross-window integration makes the Outlooker Attention proposed in this paper significantly different from other attention strategies.

@lartpang
Agree, some additional emphasis and explanation for the notation could be added for better understanding.

Interesting, I also thought we were summing over just the kernel, as in a convolution. This answers my question from the other thread, and explains why we need to aggregate for all pixels, not just the center. The fold makes the effective neighborhood size actually 2K-1 around the each pixel instead of just K.


Update HighLevelGraph documentation

I just came across this page of the docs which hasn't been changed much since Dec 2018. I think it would be useful to update it to include a runnable example and some information about the Layer class.
Once that page is updated, it will probably make sense to update https://docs.dask.org/en/latest/phases-of-computation.html and https://docs.dask.org/en/latest/graphs.html to make it clearer how HLGs fit in.
I am happy to take on this work, but just wanted to put this here in case I am missing something.
Some resources that I am planning to draw on:
Layer Issue
Blog post about scheduling
Scheduling workshop from summit
Pinging the people who I have seen working on HLG related things: @rjzamora @GenevieveBuckley @gjoseph92 @ian-r-rose @jrbourbeau

Totally agree that we should update our docs on HighLevelGraphs
FWIW I think it's okay for these update to be relatively...for lack of a better term...high-level for the time being. While the concept of layers is pretty established, specific APIs around them are still developing (thoughts from others are very welcome here).

I can help read over any drafts you make @jsignell

@freyam might also like to follow this discussion

@GenevieveBuckley This would be a great thing for me to work during the last week (16th to 23rd August).

Adding documentation about HLGs (dask docs)
A blogpost about my GSoC Project (dask blog)
Personal blogpost on my work (medium)

Linking https://github.com/dask/dask/pull/7417 as an example of a PR implementing a new HLG Layer and long discussion about the implications (cc @ian-r-rose ). That PR, once merged, might provide interesting insights into how to design a Layer.
Also of note, in https://github.com/ContinuumIO/dask-awkward/blob/main/src/dask_awkward/core.py we use existing layer-creating functions to manufacture HLGs, but could probably create our own ( cc @douglasdavis  ). This is like the prototypical "I want to make a new collection" topic that could be a great tutorial, as discussed in the dask devs meeting.

Also cc @rjzamora , who has developed a lot of Layers!

cc @madsbk

@martindurant @douglasdavis - The following gist is still very rough for now, but may be helpful for to-be layer developers: https://gist.github.com/rjzamora/3f76c6dcbde16a4185222eaadcd1d02f

Thanks very much, will give it a careful read. I wonder, though: would is not be easier to start with a layer that has no dependencies?

For what it's worth, I also recently wrote up some notes on HLG pain points. It's less detailed than Rick's but perhaps still interesting

Thanks @rjzamora!

I wonder, though: would is not be easier to start with a layer that has no dependencies?

Are you suggesting that how-to notes should consider a simpler example, or that the tree-reduction example should start with a dependency-free case?  If you are saying the latter, can you clarify what you mean by dependencies?

I meant the former

I meant the former

I probably agree. The official HLG-layer "how-to" docs should probably focus on a simple (contrived) example.  I was trying to come up with a "real" example that is less-complex, but I found it difficult to think of an algorithm that cannot be mapped onto a Blockwise layer, a shuffle, a join, a map_overlap call (still MaterializedLayer for now), or a tree reduction (targeted in #8468).

from_numpy (https://github.com/dask/dask/pull/7417) would be a good no-deps example, and maybe the best way to finish off that PR. Also, in dask-awkward we have a few of these, where the HLG should be a lazy dict and is based on a simple comprehension, but actually get materialised every time. That example is a lot like from_numpy, but here is another one - in this case reading parquet (!).

That is very useful @rjzamora, thank you for writing it!
I agree with the pain points you mention in the doc. Lots of parallels with discussions Ian and Gabe have had around this as well.

I wrote this. It's terrible, but I did promise Ian and Gabe I would try to write something.
I think the most helpful ideas from it are:

A focus on converting existing Dask functionality (I expect more people will be doing this, compared to creating entirely new functionality with high level graphs - at least at this stage of maturity)
Explaining where the code should live, and how to find the right places
Trying to focus on how you can do the development work incrementally.

Rick's document above is much, much better, but it is extremely hard to go from zero to 200-ish lines of code in step 2. Maybe separating out what is boilerplate code that can be copied over from somewhere, vs code you must implement, vs the nice to have code you could implement (like the _dict caching) would help.
"Trying" is the operative word here this is really hard to do because there is so much boilerplate, and because you need to implement several things at once before you can test them. Then if there is a problem, there's too many places to look and possible interactions between methods and it's hard to figure out what you did wrong. (I think Gabe suggested that if there were a more robust contract, where it was clear what the inputs and outputs of methods should be then it might become easier to test them in isolation)

Circling back to the original comment on this thread:

I just came across this page of the docs which hasn't been changed much since Dec 2018. I think it would be useful to update it to include a runnable example and some information about the Layer class.

I had a look at what would need to happen to make the code example runnable. I tried to change as little as possible about the example for this experiment, although we may find another type of example that could work better.
There are a few things that jump out:

Example data generation
Small changes needed so the code does not produce errors
Differences in terminology between layer names in example text vs runnable code.

1. Example data generation
This is the first hurdle for making the example actually runnable.
The example seemed closest to the accounts example datasets created and used in the dask-tutorial. To generate those csv files, we need the files prep.py, accounts.py, and sources.py from the tutorial repo.
2. Small changes needed so the code does not produce errors
These are generally easy enough to work around.
Lines like df = df + 100 don't work for dataframes including string columns, like the names column. That can be changed to something like df = df['amount'] + 100.
3. Difference in terminology between layer names
This potentially negatively affects the clarity of the documentation. For that reason, I think this is the biggest problem out of the three.
In the current docs, "filter" is used and is very clearly understandable. In a runnable example, we get a combination of getitem, eq (and sometimes try-loc, depending on what the exact computation is). This is likely to be a lot more confusing for people, because we've moved away from having one name for the filter operation.
It's possible that number 3 would be less of a problem with a more strategically chosen example, so we should strongly consider doing that. I haven't been able to think of a really good alternative yet, ideas are welcome.

Ref: https://github.com/dask/dask/pull/7417#pullrequestreview-833608482 (@gjoseph92 ) for an example of how this is all complex, or at least can be. I am more in the dark than before!


Move bottle to subdirectory if linkage or test failed

This would allow us to create artifacts of failed bottles that can't be accidentally published; i.e. successful bottles would be uploaded to the bottles artifact, while failed bottles could be uploaded to a bottles (failed) artifact
Closes #559.

Closes #559.

Closes #559.

Ninja edit 😉

Ninja edit 😉

I tried it as a separate comment... but it didn't get that dashed underline thing under "Closes". So I guess GitHub only recognises it if it's in the first post or in the commit message?

I tried it as a separate comment... but it didn't get that dashed underline thing under "Closes". So I guess GitHub only recognises it if it's in the first post or in the commit message?

Yes, I think that's correct

Yes, I think that's correct

Can we test this with a broken formula to see if it does what's expected?

Can we test this with a broken formula to see if it does what's expected?

Yes
$ brew edit homebrew/test-bot/testbottest # change test block to `system "false"`

$ mkdir test-bot-test-dir

$ cd test-bot-test-dir

$ brew test-bot --only-formulae --test-default-formula
==> Using Homebrew/homebrew-test-bot 027f369 (Move bottle to subdirectory if linkage or test failed)
...

$ ls -R
.:
failed	steps_output.txt

./failed:
testbottest--0.1.mojave.bottle.json  testbottest--0.1.mojave.bottle.tar.gz

That was helpful; I found an error and am now pushing a fix

Yes
$ brew edit homebrew/test-bot/testbottest # change test block to `system "false"`

$ mkdir test-bot-test-dir

$ cd test-bot-test-dir

$ brew test-bot --only-formulae --test-default-formula
==> Using Homebrew/homebrew-test-bot 027f369 (Move bottle to subdirectory if linkage or test failed)
...

$ ls -R
.:
failed	steps_output.txt

./failed:
testbottest--0.1.mojave.bottle.json  testbottest--0.1.mojave.bottle.tar.gz

That was helpful; I found an error and am now pushing a fix

Makes sense, thanks @SeekingMeaning!

Makes sense, thanks @SeekingMeaning!


Use run.join instead of run

I was having an issue where doing lots of makeList in a test caused more than 10 runloops to be created which caused an infinite rendering invalidation error.
A similar issue was reported here
https://github.com/ember-redux/ember-redux/issues/64#issuecomment-267053666
And fixed here using run.join to only create new loops as needed
https://github.com/ember-redux/ember-redux/pull/69

Interesting issue .. never ran into it myself ( yet )

Thanks!
Yeah likely something specific to my scenario but good as a safeguard either way.


feat: Add @events showRenderedSuggestions and hideRenderedSuggestions

New showRenderedSuggestions and hideRenderedSuggestions events to facilitate event handling when
suggestions appear and disappear
#178 enhancement

What:
feature #178 enhancement

Help control from the parent component when this suggestions are being shown/hidden, in case any more logic must be applied form the parent.

Checklist:

[ ] Documentation
[x] Tests
[x] Ready to be merged
[x] Added myself to contributors table

Didn't find how to add this 2 new  events in events table of the Readme.md file, is it referenced in another file?

Codecov Report

Merging #181 into master will increase coverage by 0.34%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #181      +/-   ##
==========================================
+ Coverage   85.11%   85.46%   +0.34%
==========================================
  Files           1        1
  Lines         168      172       +4
  Branches       47       48       +1
==========================================
+ Hits          143      147       +4
  Misses         11       11
  Partials       14       14

Impacted Files
Coverage Δ

src/Autosuggest.vue
85.46% <100.00%> (+0.34%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
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@BerniML btw, I added an events section very recently, so should be straightforward now on where to add these new events.

@darrenjennings  I made the changes requested:

Simplified names for the events
Moved the emitters in the isOpen watcher
Completed the reame with the new events information


Fix various typos in the classref

Random typos found when translating the class reference.

Thanks!

Cherry-picked for 4.0.3.


[LS] Update executor positions to not use module compilation

Purpose
$subject
Fixes #30750
Approach

Describe how you are implementing the solutions along with the design details.

Check List

[x] Read the Contributing Guide
[ ] Updated Change Log
[ ] Checked Tooling Support (#)
[ ] Added necessary tests

[ ] Unit Tests
[ ] Spec Conformance Tests
[ ] Integration Tests
[ ] Ballerina By Example Tests

[ ] Increased Test Coverage
[ ] Added necessary documentation

[ ] API documentation
[ ] Module documentation in Module.md files
[ ] Ballerina By Examples

Closing this as this was committed to beta 1 staging branch: https://github.com/ballerina-platform/ballerina-lang/commit/1f204a13479bbbe57292984a336c6bf558aefdcc


fix(typescript): resolve the shim used for tsc in Typescript v5.7 and up

This PR resolves issue #251.
I made the checks for detecting whether or not tscPath is pointed at a shim as resistant to change as I could think to make them (without trying to parse an AST). Because we rely on Typescript's source code, there's always a chance that a future update could break things, but this should be fairly resilient.
I tested this on a local repository and have verified that it fixes the issue when using Typescript v5.7.2. It also maintains backwards compatibility for older Typescript versions that don't use a shim for tsc.

I made a few modifications to your approach. Thanks for look into this!


Add csidriver object for cephfs and rbd

csidriver object can be created on the kubernetes for the below reason.
If a CSI driver creates a CSIDriver object, Kubernetes users can easily discover the CSI Drivers installed on their cluster (simply by issuing kubectl get CSIDriver)
Ref: https://kubernetes-csi.github.io/docs/csi-driver-object.html#what-is-the-csidriver-object
attachRequired is always required to be set to true to avoid issues on RWO PVC. more details about it at https://github.com/rook/rook/pull/4332
Signed-off-by: Madhu Rajanna<EMAIL_ADDRESS>

Warning: Permanently added 'n5.pufty.ci.centos.org,<IP_ADDRESS>' (ECDSA) to the list of known hosts.
Error from server (InternalError): Internal error occurred: resource quota evaluation timed out
script returned exit code 1

/retest ci/centos/mini-e2e-helm/k8s-1.20

@humblec PTAL


City/country name is not localised

URL
No response
How to reproduce the issue?

Change your locale Bulgarian (bg)
Go to 42.69093, 23.33091 and make some edit
Upload it
Notice the text on the left panel ("Благодарим ви за подобряването на картата около Sofia, Bulgaria.")

Screenshot(s) or anything else?
The text should be using the features' names in the selected locale. The text in this case should be "Благодарим ви за подобряването на картата около София, България"

Which deployed environments do you see the issue in?
Released version at openstreetmap.org/edit
What version numbers does this issue effect?
2.24.1
Which browsers are you seeing this problem on?
No response

The english part (Sofia, Bulgaria) comes from Nominatim, which uses your browser's locale, whereas the rest of iD uses the settings for your OSM account. I have a similar problem, text from Nominatim is in te reo māori or spanish, but the rest of iD is in english. This is fixed in #9501


bug fix for rendering correct layer 5 logo based on dark/light mode

Description
This PR fixes #
Notes for Reviewers
Signed commits

[x] Yes, I signed my commits.

@sudhanshutech here is the new PR.

@sudhanshutech @leecalcote here is the new PR.

@fardeenhasib Let's discuss this on Websites's call today 6:30 PM IST. Let's add this as an agenda item into the meeting minutes


Add a download page for v1.9.0

Proposed changes
Add a download page for v1.9.0
Types of changes
Please put an x in the boxes related to your change.

[ ] Minor Issues and Typos
[x] Major Content Contribution
[ ] Others

Checklist
Put an x in the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to reach out. We're here to help! This is simply a reminder of what we are going to look for before merging your code.

[x] I have read the CONTRIBUTING GUIDELINES
[x] I have signed the CLA
[x] I have added necessary documentation (if appropriate)
[x] Any dependent changes have been merged and published in downstream modules

recheck

I have read the CLA Document and I hereby sign the CLA


Disable waste water voiding

I think it would feel better to have to process waste before voiding.
Disable clarifier recipes for Sulfuric, Chloric, Nitric, and Fluoric waste water.
Make Water Treatment 1 a startup tech so it ignores tech cost modifier.

Make Water Treatment 1 a startup tech would not be necessary, if you had a good storage tank :) Currently the tiny inline tanks are quite bad for that

Make Water Treatment 1 a startup tech would not be necessary, if you had a good storage tank :) Currently the tiny inline tanks are quite bad for that

Fluid handling is a startup tech. That unlocks a 20k tank.
With a high tech cost modifier, this would probably still backup quickly.

i don't think i like this idea, mainly now that each of the waste water cleaning processes generate a solid.
While it is fine for a centralised reprocessing system, it takes away the benefits of onsite processing/voiding. Especially for things like Aluminium catalytic sorting. (chunk level)

Make Water Treatment 1 a startup tech would not be necessary, if you had a good storage tank :) Currently the tiny inline tanks are quite bad for that

Fluid handling is a startup tech. That unlocks a 20k tank.
With a high tech cost modifier, this would probably still backup quickly.

The bigger ones require steel

i don't think i like this idea, mainly now that each of the waste water cleaning processes generate a solid.
While it is fine for a centralised reprocessing system, it takes away the benefits of onsite processing/voiding. Especially for things like Aluminium catalytic sorting. (chunk level)

I always reprocess the waste water to get more water back. And I don't want to waste the sulfur/fluorite/nitrate... But others will curse the change and I already hear the streamer's rant about this... :D

If you search for a possibility to independently void by-products, in won't work. You have to consume them prioritized in other processes, and you have to increase usage of those processes if too little is consumed.
That is what I have in mind, when I say: "not voiding stuff is the next step in the puzzle, which would really drive complexity up insanely".
But it's probably not everyone's cup of tea...

That's more complexity than I want to add. I still want to have voiding options available, just with an additional step.
Sulfuric and nitric are easy to make work. The other two are too difficult for now. So I'm going to leave this idea for now.

To make this idea viable:

Disable calcium sulfate entirely
Either add a lower tier Water Treatment Plant that can be unlocked with Water Treatment 2. Or add a much slower salt > saline recipe that can be done in a liquifier.


The user guide and the cli disagree on the range of the sensitivity parameter

The user guide and the cli help say different things about the -s parameter.
The user guide says the following, both in the pdf bundled with the latest release and in the latest wiki version (https://github.com/soedinglab/mmseqs2/wiki#search-workflow)

-s [float] Target sensitivity in the range [1:8.5] (default=4).

Adjusts the sensitivity of the prefiltering and influences the prefiltering run time. 1.0 fastest -
8.5 sensitive. The sensitivity between 8 to 8.5 should be as sensitive as BLAST. For detailed
explanation see section Computation of Prefiltering Scores using mmseqs prefilter.

The cli help (mmseqs search --help) says:

-s FLOAT                     sensitivity: 1.0 faster; 4.0 fast default; 7.5 sensitive (range 1.0-7.5) [5.700]

As defined here:
https://github.com/soedinglab/MMseqs2/blob/5ae5503a923ec4338464d09cc1ff4bc3680727da/src/commons/Parameters.cpp#L30
I'm wondering about this since I'd like to search at a sensitivity similar to BLAST and since the cli doesn't reject values bigger than 7.5.
MMseqs2 Version: 6d92cd21676ccc36531f2852f7eb747f6389435f (Release 10-6d92c)

Thank you for pointing this out. Yes the parameter description is inconsistent. We will fix this.
I hope this plot helps to find the right -s setting for your use case. https://github.com/soedinglab/mmseqs2/wiki#set-sensitivity--s-parameter

We changed the description. Thank you.

@martin-steinegger
Hi，
I download the newest version of mmseqs2, the biggest value is 7.5 from software help information:
-s FLOAT                         Sensitivity: 1.0 faster; 4.0 fast; 7.5 sensitive [5.700]
but on the description from wiki is 8.5, so which one is correct?
And, I would like get same sensitive as PSI-BLAST, if the following parameter is OK:
mmseqs search -a -s 7 --num-iterations 2

mmseqs search --num-iterations 2 should be already more sensitive than PSI-BLAST. -s 7 helps mainly in the first iteration to build the initial profiles. 8.5 is incorrect. You can increase -s to 10 but there is no boost in sensitivity anymore.


fix typo in falco 0.35.1 blog post

What type of PR is this?

Uncomment one (or more) /kind <> lines:

/kind bug

/kind cleanup

/kind design

/kind user-interface

/kind content

/kind translation

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Uncomment one (or more) /area <> lines:

/area blog

/area documentation

/area videos

What this PR does / why we need it:
fix in a typo in the falco 0.35.1 blog post
Which issue(s) this PR fixes:

Fixes #
Special notes for your reviewer:

[APPROVALNOTIFIER] This PR is APPROVED
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[APPROVALNOTIFIER] This PR is APPROVED
This pull-request has been approved by: Issif, vjjmiras
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LGTM label has been added.  Git tree hash: b8871f2e6e01947d51adfcae1e2729dcebeac0b5


configs: revisit format and/or fix broken configs

Currently on 3018 branch. Changed cnc => motion, so at least some update is needed
Playing around with YAML/TOML etc since we are making a lot of breaking changes right now. I looked at a few options including StrictYAML, JSON5, and TOML. However I haven't been convinced any of them are so much better that its worth the switch.
JSON5: seems to be ok and would be backwards compatible while adding things like comment support and trailing newlines. Allegedly slow but our config files are very simple
I'm not super enthusiastic about implicit typing which both TOML and YAML have. See also: https://github.com/Labsmore/pyuscope/issues/30
StrictYAML: would have to define a DOM for best results which is both good and bad. Maybe more overhead than I want to deal with right now though

Moved to JSON5. Archived configs that aren't actively being used


Fix dependency scope

Coverage remained the same at 87.438% when pulling 9aa2e5b6125fe8a955bb5dba1b95bf823e617164 on christian-ertl:fix-dependency-scope into a7790167164183c1d9bf22d83404915528e0e400 on TNG:master.


xen-tools_git.bbappend: Disable installation of the python3-core inside the initrd

In order to minimize the size of the initrd
Signed-off-by: Vladyslav Goncharuk<EMAIL_ADDRESS>

Perfect, thanks! One question remains, so this limit here https://github.com/otyshchenko1/meta-xt-prod-devel-rcar/commit/f5acfef40933e2b74d2bcf240c0f4ceff6cbad82#diff-e78b63e574102e5f392ff67a928a6d7c926768b1cb99351fcf09fe007cb02501R176 is not actual and can be dropped? Could you re-check (and drop?) it?

And if this works well, the dom0 memory size could be reduced to it's previous size 256MB here https://github.com/otyshchenko1/meta-xt-rcar/commit/55341a375d5c8ede681d2e6957554f1c8169d830#diff-a4422f04d53193d309b47a945fa7c76fcfb1c6fa040a097a0868827e2d4dd58fR14 Could you re-check (and reduce) it?

Hi @otyshchenko1, the INITRAMFS_MAXSIZE was removed. The image was successfully built with the default value.


fix: Redis client configuration for RQ

Heroku Data for Redis premium plans only offer a TLS connection to Redis, which uses self-signed certificates, which require you to configure the verify_mode SSL setting of your Redis client.
This PR fixes the inability to configure this in JUDOSCALE["REDIS"] configuration.

@karls Thanks for the fix! Will we potentially have the same issue for Celery?


GUI: macOS shortcut to be CMD+F instead of CTRL+F

Fixes #165
@krokofant: please give it a try before merging.
This was done based on https://www.daniweb.com/programming/software-development/threads/494332/command-key-java-robot-meta

@sergey-wowwow: could you please check if this satisfies #165 in macOS?

Implemented in https://github.com/skylot/jadx/pull/616
Thanks @asashour


DRILL-4020: The not-equal operator returns incorrect results when used on the HBase row key

Added a condition that checks if the filter to the scan specification doesn't have NOT_EQUAL operator
Added testFilterPushDownRowKeyNotEqual() to TestHBaseFilterPushDown

Shoot, I mistyped my close message. Should have been 283 instead of 238. @nagix, can you reopen this pull request?

@jacques-n, I don't believe I can re-open this because I didn't close it. Can you do it or do l need to open a new request?

Maybe just submit new request. I can't reopen either.
On Dec 22, 2015 7:30 AM, "Akihiko Kusanagi"<EMAIL_ADDRESS>wrote:

@jacques-n https://github.com/jacques-n, I don't believe I can re-open
this because I didn't close it. Can you do it or do l need to open a new
request?
—
Reply to this email directly or view it on GitHub
https://github.com/apache/drill/pull/238#issuecomment-166647086.

Submitted a new request #309


PreRelease Support

I can't seem to get pre-release tags to show up... I am using the following format YY.MM.MICRO.MODIFIER but all I ever get is YY.MM.MICRO

@jtbairdsr I needed this as well, according to the node-calver docs the modifier would have to be passed in to the plugin here https://github.com/casmith/release-it-calver-plugin/blob/master/calver-plugin.js#L16, but it's being hard-coded to calendar. It would be easy to fork

@jtbairdsr I needed this as well, according to the node-calver docs the modifier would have to be passed in to the plugin here https://github.com/casmith/release-it-calver-plugin/blob/master/calver-plugin.js#L16, but it's being hard-coded to calendar. It would be easy to fork

Or someone could raise a pull request?

@jtbairdsr I added support for tags like alpha, dev etc (those supported to calver). Does this give you what you need?


Fixed check_reqs SyntaxWarning on tox by increasing tox to 3.1.0

No review needed.

coverage: 37.115%. remained the same
when pulling 88a97cc26d8d2196192efdffcafb8f9443fc4d48 on andy/fix-tox-warning
into cd67d2078864a738effc81c3182592d0b33ca2c9 on master.


Update macro_droid.md

As discussed in the ticket, here is an addition for the macrodroid docs

Thanks!


SceneTree: Fix reparent crash with animation tracks renaming disabled

This check was there since the first commit in 2014, but a later feature added in 2018
with #17717 did not properly update the code while adding non animation-related code
in perform_node_renames.
Fixes #40532.

@jesperkondrup Could you test this build from the 3.2 branch with this fix? https://github.com/akien-mga/godot/suites/1497512734/artifacts/26120581
Especially to check that it doesn't break when reparenting nodes which are used in animation tracks with the editors/animation/autorename_animation_tracks setting is false like in your case.

@akien-mga Everything works in that build. I can move the sprite1 into another node with the sprite1 name without problems (it just gets renamed now) and I can also add it to an Animation player and still move it back and forth between nodes without problems.

Thanks for testing!

Cherry-picked for 3.2.4.


Expose get_global_name() method to the editor

Thought this would be useful, as currently there isn't an easy way to get the global class name of a a given script.


Crosshair implementation

I attempted to create a temporary solution for implementing a crosshair.

changes look good besides the default hd position, will need appropriate integration into the configurator.

configurator commit https://github.com/BossHobby/Configurator/commit/401e40f0869e5bdb35d487038247cded1bd05a7f


use formatting to make command output clearer

Oghliner's output is quite simplistic, just plain text without any special formatting. By contrast, other popular command-line tools, like Yeoman (npm install -g yo && yo), use color, boldness, and other stylistic formatting to clarify the text they output to the console. (Yeoman even prints ASCII art, although that's a bit extraneous.)
We should evaluate the output of the various Oghliner commands for opportunities to use formatting to make them clearer.

[x] Use gutil.log to log messages (#131)
[x] Print colored warnings and errors (#131)
[x] Clarify output of configure (#148)
[x] Print large file warning in yellow (#151)
[x] Print all suggestions in blue (#156)
[x] Clarify output of bootstrap (#160)
[x] Clarify output of integrate (#161)
[x] Clarify output of offline (#162)
[x] Clarify output of deploy (#163)

We should also improve error messages, using console.error doesn't give much details.

#131 improves the situation.

It might be a bit further afield, but I see enhancements like #141 as keeping with the spirit of this issue.

All dependencies resolved, so this too is resolved!


implement iterator API

Maybe stick to existing Map signatures.

Map is a pure interface and thus does not play well with the side-effecting unqlite bindings. E.g.:
module type Map.S = sig
  (* how to do this? *)
  val empty : 'a t
end

Iterator was implemented in fd71c7c50119005f09c6d3872303ae968b437763


Add a config diretory and config file

Most coins don't require you to enter connection information every time you run the daemon. Instead all of that info is stored in a ~/.coinname/coinname.config file. I propose that we come up with a configuration file structure that will allow us to list node connection information, privacy settings for our node, default wallet location, etc.

we create a config file for the node (sushid) - we can keep the current cli options as overrides. but if not specified then it takes them from the config file? - a default config file would go in something like ~/.sushid.conf - and have a cli option to override the conf file location

Ideally I think we should follow suit with other coins and have a ~/.shushicoin directory with sushicoin.conf inside of it. The config file should definitely be overridable though. This way we have a single directory to store the config file, default wallet, and the database, as well as any other potential files we may need.
I also think the default configuration file, database, and default wallet should be created the first time sushid is launched.

directory structure could be ~/.sushicoin/config/{node.yml, cli.yml}
also we should create config for sushi client (most widely used by users) as well as config for the node (sushid) - I think there is not much reason to start a local node unless running a public one

Here's what I imagine the directory structure being eventually.

Done.


Complete gibberish produced by any and all models only when device_map="auto".

System Info
- `Accelerate` version: 0.29.3
- Platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35
- `accelerate` bash location: /root/miniconda3/envs/codevalet_ai/bin/accelerate
- Python version: 3.10.14
- Numpy version: 1.24.3
- PyTorch version (GPU?): 2.2.1+cu121 (True)
- PyTorch XPU available: False
- PyTorch NPU available: False
- PyTorch MLU available: False
- System RAM: 2015.56 GB
- GPU type: NVIDIA L40S
- `Accelerate` default config:
  Not found

Information

[ ] The official example scripts
[ ] My own modified scripts

Tasks

[ ] One of the scripts in the examples/ folder of Accelerate or an officially supported no_trainer script in the examples folder of the transformers repo (such as run_no_trainer_glue.py)
[ ] My own task or dataset (give details below)

Reproduction
System specs:

8 times L40S GPUs
Intel Xeon Gold 6558H

This:
import torch
from transformers import pipeline
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2"
pipe = pipeline("text-generation", model="HuggingFaceH4/starchat-beta", torch_dtype=torch.bfloat16, device_map='auto')
# We use a variant of ChatML to format each message
prompt_template = "<|system|>\n<|end|>\n<|user|>\n{query}<|end|>\n<|assistant|>"
prompt = prompt_template.format(query="How do I sort a list in Python?")
# We use a special <|end|> token with ID 49155 to denote ends of a turn
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.2, top_k=50, top_p=0.95, eos_token_id=49155)
print(outputs)

Prints:
[{'generated_text': '<|system|>\n<|end|>\n<|user|>\nHow do I sort a list in Python?<|end|>\n<|assistant|> to. Air1 (\nь\nInfo plit An che a\n the weьь Share Share\n aremobatar\n…We brain  be S jj jj'..., … …: no J\n,…AL more of… y they code lifefl\n --  B moreand.. L\nplitahph a after\n Ishare, E I I is L\n unel not Mid' I'’ …\n\n …" you a a   South  strength  I I S said "no\n\n\n E E11\n EASC not Sh English. of of E |isse\n as that said said of said reg of The The– n a… Open. The The for | A after After\n was M open open over in been\n\n into,onAR down :-)mad cos I you to E,( not "a001 that vis m44\n\n\n of3\n re1 T by so itack in inententancy of is  int Library to U U.. a a = ==Compression Itdata66 as111110 S'}]
While this:
import torch
from transformers import pipeline
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
pipe = pipeline("text-generation", model="HuggingFaceH4/starchat-beta", torch_dtype=torch.bfloat16, device_map='auto')
# We use a variant of ChatML to format each message
prompt_template = "<|system|>\n<|end|>\n<|user|>\n{query}<|end|>\n<|assistant|>"
prompt = prompt_template.format(query="How do I sort a list in Python?")
# We use a special <|end|> token with ID 49155 to denote ends of a turn
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.2, top_k=50, top_p=0.95, eos_token_id=49155)
print(outputs)

Prints:
[{'generated_text': '<|system|>\n<|end|>\n<|user|>\nHow do I sort a list in Python?<|end|>\n<|assistant|>\nThere are multiple ways to sort a list in Python. One of the most common ways is to use the sort() method. Here is an example:\n\n```\nmy_list = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]\nmy_list.sort()\nprint(my_list)\n```\n\nThis will sort the list in place and print the sorted list.\n\nAnother way to sort a list is to use the sorted() function. This function returns a new sorted list and does not modify the original list. Here is an example:\n\n```\nmy_list = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]\nsorted_list = sorted(my_list)\nprint(sorted_list)\n```\n\nIn this example, the sorted_list variable will contain the sorted list and the my_list variable will remain unchanged.\n\nThere are also other sorting algorithms available in the built-in sort module, such as quicksort, heapsort, and merge sort. You'}]
Expected behavior
Both should print coherent text. This happens no matter the model chosen. In the above reproduction steps, the model used is HuggingFaceH4/starchat-beta. The exact same thing happens with mistralai/Mixtral-8x7B-Instruct-v0.1, no matter if ran in bfloat16, float16, float32, or quantized / not quantized. The issue also occurs no matter the prompt.
The issue, however, does NOT occur when device_map="sequential" is set (tested with HuggingFaceH4/starchat-beta only).
Furthermore, the issue does NOT occur with device_map="auto" on my home 3x RTX 3090 / Threadripper 3960x setup.
However, I cannot use sequential in our current production environment without making significant changes.

Hi @FanaticPythoner, thanks for the detailed report ! This is indeed strange that sequential works while it fails with auto (using "balanced"). Could you check what is the output of model.hf_device_map ? Maybe you can try to allocate each layer to a specific device or set a max_memory when using sequential.

For the code:
import torch
from transformers import pipeline
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2"
pipe = pipeline("text-generation", model="HuggingFaceH4/starchat-beta", torch_dtype=torch.bfloat16, device_map='auto')
# We use a variant of ChatML to format each message
prompt_template = "<|system|>\n<|end|>\n<|user|>\n{query}<|end|>\n<|assistant|>"
prompt = prompt_template.format(query="How do I sort a list in Python?")
# We use a special <|end|> token with ID 49155 to denote ends of a turn
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.2, top_k=50, top_p=0.95, eos_token_id=49155)
print(outputs)

Doing:
import json
print(json.dumps(pipe.model.hf_device_map, indent=4))

Prints:
{
    "transformer.wte": 0,
    "lm_head": 0,
    "transformer.wpe": 0,
    "transformer.drop": 0,
    "transformer.h.0": 0,
    "transformer.h.1": 0,
    "transformer.h.2": 0,
    "transformer.h.3": 0,
    "transformer.h.4": 0,
    "transformer.h.5": 0,
    "transformer.h.6": 0,
    "transformer.h.7": 0,
    "transformer.h.8": 0,
    "transformer.h.9": 0,
    "transformer.h.10": 0,
    "transformer.h.11": 0,
    "transformer.h.12": 0,
    "transformer.h.13": 1,
    "transformer.h.14": 1,
    "transformer.h.15": 1,
    "transformer.h.16": 1,
    "transformer.h.17": 1,
    "transformer.h.18": 1,
    "transformer.h.19": 1,
    "transformer.h.20": 1,
    "transformer.h.21": 1,
    "transformer.h.22": 1,
    "transformer.h.23": 1,
    "transformer.h.24": 1,
    "transformer.h.25": 1,
    "transformer.h.26": 1,
    "transformer.h.27": 1,
    "transformer.h.28": 2,
    "transformer.h.29": 2,
    "transformer.h.30": 2,
    "transformer.h.31": 2,
    "transformer.h.32": 2,
    "transformer.h.33": 2,
    "transformer.h.34": 2,
    "transformer.h.35": 2,
    "transformer.h.36": 2,
    "transformer.h.37": 2,
    "transformer.h.38": 2,
    "transformer.h.39": 2,
    "transformer.ln_f": 2
}

And what is the hf_device_map with device_map="sequential" ?

@SunMarc
For the code:
import torch
from transformers import pipeline
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2"
pipe = pipeline("text-generation", model="HuggingFaceH4/starchat-beta", torch_dtype=torch.bfloat16, device_map='sequential')
# We use a variant of ChatML to format each message
prompt_template = "<|system|>\n<|end|>\n<|user|>\n{query}<|end|>\n<|assistant|>"
prompt = prompt_template.format(query="How do I sort a list in Python?")
# We use a special <|end|> token with ID 49155 to denote ends of a turn
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.2, top_k=50, top_p=0.95, eos_token_id=49155)
print(outputs)

Doing:
import json
print(json.dumps(pipe.model.hf_device_map, indent=4))

Prints:
{
    "": 0
}

Let me send you the same code for comparison, but instead of starchat, using mixtral, which is larger.

Oh makes sense why it works. It is because the model fits in a single gpu in the case of starchat. Yeah, let's check for mixtral.

For the code:
import torch
from transformers import pipeline
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2"
pipe = pipeline("text-generation", model="mistralai/Mixtral-8x7B-Instruct-v0.1", torch_dtype=torch.bfloat16, device_map='auto')
# We use a variant of ChatML to format each message
prompt_template = "<|system|>\n<|end|>\n<|user|>\n{query}<|end|>\n<|assistant|>"
prompt = prompt_template.format(query="How do I sort a list in Python?")
# We use a special <|end|> token with ID 49155 to denote ends of a turn
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.2, top_k=50, top_p=0.95, eos_token_id=49155)
print(outputs)

Doing:
import json
print(json.dumps(pipe.model.hf_device_map, indent=4))

Prints:
{
    "model.embed_tokens": 0,
    "model.layers.0": 0,
    "model.layers.1": 0,
    "model.layers.2": 0,
    "model.layers.3": 0,
    "model.layers.4": 0,
    "model.layers.5": 0,
    "model.layers.6": 0,
    "model.layers.7": 0,
    "model.layers.8": 0,
    "model.layers.9": 0,
    "model.layers.10": 1,
    "model.layers.11": 1,
    "model.layers.12": 1,
    "model.layers.13": 1,
    "model.layers.14": 1,
    "model.layers.15": 1,
    "model.layers.16": 1,
    "model.layers.17": 1,
    "model.layers.18": 1,
    "model.layers.19": 1,
    "model.layers.20": 1,
    "model.layers.21": 2,
    "model.layers.22": 2,
    "model.layers.23": 2,
    "model.layers.24": 2,
    "model.layers.25": 2,
    "model.layers.26": 2,
    "model.layers.27": 2,
    "model.layers.28": 2,
    "model.layers.29": 2,
    "model.layers.30": 2,
    "model.layers.31": 2,
    "model.norm": 2,
    "lm_head": 2
}

Now, for the code:
import torch
from transformers import pipeline
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2"
pipe = pipeline("text-generation", model="mistralai/Mixtral-8x7B-Instruct-v0.1", torch_dtype=torch.bfloat16, device_map='sequential')
# We use a variant of ChatML to format each message
prompt_template = "<|system|>\n<|end|>\n<|user|>\n{query}<|end|>\n<|assistant|>"
prompt = prompt_template.format(query="How do I sort a list in Python?")
# We use a special <|end|> token with ID 49155 to denote ends of a turn
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.2, top_k=50, top_p=0.95, eos_token_id=49155)
print(outputs)

Doing:
import json
print(json.dumps(pipe.model.hf_device_map, indent=4))

Prints:
{
    "model.embed_tokens": 0,
    "model.layers.0": 0,
    "model.layers.1": 0,
    "model.layers.2": 0,
    "model.layers.3": 0,
    "model.layers.4": 0,
    "model.layers.5": 0,
    "model.layers.6": 0,
    "model.layers.7": 0,
    "model.layers.8": 0,
    "model.layers.9": 0,
    "model.layers.10": 0,
    "model.layers.11": 0,
    "model.layers.12": 0,
    "model.layers.13": 0,
    "model.layers.14": 0,
    "model.layers.15": 0,
    "model.layers.16": 1,
    "model.layers.17": 1,
    "model.layers.18": 1,
    "model.layers.19": 1,
    "model.layers.20": 1,
    "model.layers.21": 1,
    "model.layers.22": 1,
    "model.layers.23": 1,
    "model.layers.24": 1,
    "model.layers.25": 1,
    "model.layers.26": 1,
    "model.layers.27": 1,
    "model.layers.28": 1,
    "model.layers.29": 1,
    "model.layers.30": 1,
    "model.layers.31": 1,
    "model.norm": 1,
    "lm_head": 1
}

I also looked at the result of outputs. For "auto", it doesn't even finish, throwing a nan/inf error. For "sequential", it does expected behavior, i.e., answers correctly.

The hardware/drivers has been triple checked by the bare metal provider. On my 3x 3090 setup, I don't use NVLink. Maybe that's the key. Or maybe it's something else.
As an update, I tested both Sequential and Auto on llama 2 70b, in bfloat16. Both are unable to run the inference and throw:
Exception has occurred: RuntimeError
probability tensor contains either `inf`, `nan` or element < 0
  File "/root/hwsrc/codeValet_AI/main.py", line 16, in <module>
    output = pipe("Hey how are you doing today?")
RuntimeError: probability tensor contains either `inf`, `nan` or element < 0

Here are the device maps and the code that was used.

The code:

import transformers
import torch
import json
model_id = "meta-llama/Meta-Llama-3-70B"

pipe = transformers.pipeline("text-generation",
                                 model=model_id,
                                 model_kwargs={
                                     "torch_dtype": torch.bfloat16,
                                     "max_memory": {0: "42GiB", 1: "42GiB", 2: "42GiB", 3: "42GiB"}
                                 },
                                 device_map="sequential")

print(json.dumps(pipe.model.hf_device_map, indent=4))

output = pipe("Hey how are you doing today?")

print(output)

outputs:
{
    "model.embed_tokens": 0,
    "model.layers.0": 0,
    "model.layers.1": 0,
    "model.layers.2": 0,
    "model.layers.3": 0,
    "model.layers.4": 0,
    "model.layers.5": 0,
    "model.layers.6": 0,
    "model.layers.7": 0,
    "model.layers.8": 0,
    "model.layers.9": 0,
    "model.layers.10": 0,
    "model.layers.11": 0,
    "model.layers.12": 0,
    "model.layers.13": 0,
    "model.layers.14": 0,
    "model.layers.15": 0,
    "model.layers.16": 0,
    "model.layers.17": 0,
    "model.layers.18": 0,
    "model.layers.19": 0,
    "model.layers.20": 0,
    "model.layers.21": 0,
    "model.layers.22": 0,
    "model.layers.23": 1,
    "model.layers.24": 1,
    "model.layers.25": 1,
    "model.layers.26": 1,
    "model.layers.27": 1,
    "model.layers.28": 1,
    "model.layers.29": 1,
    "model.layers.30": 1,
    "model.layers.31": 1,
    "model.layers.32": 1,
    "model.layers.33": 1,
    "model.layers.34": 1,
    "model.layers.35": 1,
    "model.layers.36": 1,
    "model.layers.37": 1,
    "model.layers.38": 1,
    "model.layers.39": 1,
    "model.layers.40": 1,
    "model.layers.41": 1,
    "model.layers.42": 1,
    "model.layers.43": 1,
    "model.layers.44": 1,
    "model.layers.45": 1,
    "model.layers.46": 1,
    "model.layers.47": 1,
    "model.layers.48": 1,
    "model.layers.49": 2,
    "model.layers.50": 2,
    "model.layers.51": 2,
    "model.layers.52": 2,
    "model.layers.53": 2,
    "model.layers.54": 2,
    "model.layers.55": 2,
    "model.layers.56": 2,
    "model.layers.57": 2,
    "model.layers.58": 2,
    "model.layers.59": 2,
    "model.layers.60": 2,
    "model.layers.61": 2,
    "model.layers.62": 2,
    "model.layers.63": 2,
    "model.layers.64": 2,
    "model.layers.65": 2,
    "model.layers.66": 2,
    "model.layers.67": 2,
    "model.layers.68": 2,
    "model.layers.69": 2,
    "model.layers.70": 2,
    "model.layers.71": 2,
    "model.layers.72": 2,
    "model.layers.73": 2,
    "model.layers.74": 2,
    "model.layers.75": 3,
    "model.layers.76": 3,
    "model.layers.77": 3,
    "model.layers.78": 3,
    "model.layers.79": 3,
    "model.norm": 3,
    "lm_head": 3
}

And the code:

import transformers
import torch
import json
model_id = "meta-llama/Meta-Llama-3-70B"

pipe = transformers.pipeline("text-generation",
                                 model=model_id,
                                 model_kwargs={
                                     "torch_dtype": torch.bfloat16,
                                     "max_memory": {0: "42GiB", 1: "42GiB", 2: "42GiB", 3: "42GiB"}
                                 },
                                 device_map="auto")

print(json.dumps(pipe.model.hf_device_map, indent=4))

output = pipe("Hey how are you doing today?")

print(output)

outputs:
{
    "model.embed_tokens": 0,
    "model.layers.0": 0,
    "model.layers.1": 0,
    "model.layers.2": 0,
    "model.layers.3": 0,
    "model.layers.4": 0,
    "model.layers.5": 0,
    "model.layers.6": 0,
    "model.layers.7": 0,
    "model.layers.8": 0,
    "model.layers.9": 0,
    "model.layers.10": 0,
    "model.layers.11": 0,
    "model.layers.12": 0,
    "model.layers.13": 0,
    "model.layers.14": 0,
    "model.layers.15": 0,
    "model.layers.16": 0,
    "model.layers.17": 0,
    "model.layers.18": 0,
    "model.layers.19": 1,
    "model.layers.20": 1,
    "model.layers.21": 1,
    "model.layers.22": 1,
    "model.layers.23": 1,
    "model.layers.24": 1,
    "model.layers.25": 1,
    "model.layers.26": 1,
    "model.layers.27": 1,
    "model.layers.28": 1,
    "model.layers.29": 1,
    "model.layers.30": 1,
    "model.layers.31": 1,
    "model.layers.32": 1,
    "model.layers.33": 1,
    "model.layers.34": 1,
    "model.layers.35": 1,
    "model.layers.36": 1,
    "model.layers.37": 1,
    "model.layers.38": 1,
    "model.layers.39": 1,
    "model.layers.40": 2,
    "model.layers.41": 2,
    "model.layers.42": 2,
    "model.layers.43": 2,
    "model.layers.44": 2,
    "model.layers.45": 2,
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    "model.layers.47": 2,
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    "model.layers.50": 2,
    "model.layers.51": 2,
    "model.layers.52": 2,
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    "model.layers.55": 2,
    "model.layers.56": 2,
    "model.layers.57": 2,
    "model.layers.58": 2,
    "model.layers.59": 2,
    "model.layers.60": 2,
    "model.layers.61": 3,
    "model.layers.62": 3,
    "model.layers.63": 3,
    "model.layers.64": 3,
    "model.layers.65": 3,
    "model.layers.66": 3,
    "model.layers.67": 3,
    "model.layers.68": 3,
    "model.layers.69": 3,
    "model.layers.70": 3,
    "model.layers.71": 3,
    "model.layers.72": 3,
    "model.layers.73": 3,
    "model.layers.74": 3,
    "model.layers.75": 3,
    "model.layers.76": 3,
    "model.layers.77": 3,
    "model.layers.78": 3,
    "model.layers.79": 3,
    "model.norm": 3,
    "lm_head": 3
}

@SunMarc

The hardware/drivers has been triple checked by the bare metal provider. On my 3x 3090 setup, I don't use NVLink. Maybe that's the key. Or maybe it's something else.
As an update, I tested both Sequential and Auto on llama 3 70b, in bfloat16. Both are unable to run the inference and throw:
Exception has occurred: RuntimeError
probability tensor contains either `inf`, `nan` or element < 0
  File "/root/hwsrc/project_name/main.py", line 16, in <module>
    output = pipe("Hey how are you doing today?")
RuntimeError: probability tensor contains either `inf`, `nan` or element < 0

Here are the device maps and the code that was used.

The code:

import transformers
import torch
import json
model_id = "meta-llama/Meta-Llama-3-70B"

pipe = transformers.pipeline("text-generation",
                                 model=model_id,
                                 model_kwargs={
                                     "torch_dtype": torch.bfloat16,
                                     "max_memory": {0: "42GiB", 1: "42GiB", 2: "42GiB", 3: "42GiB"}
                                 },
                                 device_map="sequential")

print(json.dumps(pipe.model.hf_device_map, indent=4))

output = pipe("Hey how are you doing today?")

print(output)

outputs:
{
    "model.embed_tokens": 0,
    "model.layers.0": 0,
    "model.layers.1": 0,
    "model.layers.2": 0,
    "model.layers.3": 0,
    "model.layers.4": 0,
    "model.layers.5": 0,
    "model.layers.6": 0,
    "model.layers.7": 0,
    "model.layers.8": 0,
    "model.layers.9": 0,
    "model.layers.10": 0,
    "model.layers.11": 0,
    "model.layers.12": 0,
    "model.layers.13": 0,
    "model.layers.14": 0,
    "model.layers.15": 0,
    "model.layers.16": 0,
    "model.layers.17": 0,
    "model.layers.18": 0,
    "model.layers.19": 0,
    "model.layers.20": 0,
    "model.layers.21": 0,
    "model.layers.22": 0,
    "model.layers.23": 1,
    "model.layers.24": 1,
    "model.layers.25": 1,
    "model.layers.26": 1,
    "model.layers.27": 1,
    "model.layers.28": 1,
    "model.layers.29": 1,
    "model.layers.30": 1,
    "model.layers.31": 1,
    "model.layers.32": 1,
    "model.layers.33": 1,
    "model.layers.34": 1,
    "model.layers.35": 1,
    "model.layers.36": 1,
    "model.layers.37": 1,
    "model.layers.38": 1,
    "model.layers.39": 1,
    "model.layers.40": 1,
    "model.layers.41": 1,
    "model.layers.42": 1,
    "model.layers.43": 1,
    "model.layers.44": 1,
    "model.layers.45": 1,
    "model.layers.46": 1,
    "model.layers.47": 1,
    "model.layers.48": 1,
    "model.layers.49": 2,
    "model.layers.50": 2,
    "model.layers.51": 2,
    "model.layers.52": 2,
    "model.layers.53": 2,
    "model.layers.54": 2,
    "model.layers.55": 2,
    "model.layers.56": 2,
    "model.layers.57": 2,
    "model.layers.58": 2,
    "model.layers.59": 2,
    "model.layers.60": 2,
    "model.layers.61": 2,
    "model.layers.62": 2,
    "model.layers.63": 2,
    "model.layers.64": 2,
    "model.layers.65": 2,
    "model.layers.66": 2,
    "model.layers.67": 2,
    "model.layers.68": 2,
    "model.layers.69": 2,
    "model.layers.70": 2,
    "model.layers.71": 2,
    "model.layers.72": 2,
    "model.layers.73": 2,
    "model.layers.74": 2,
    "model.layers.75": 3,
    "model.layers.76": 3,
    "model.layers.77": 3,
    "model.layers.78": 3,
    "model.layers.79": 3,
    "model.norm": 3,
    "lm_head": 3
}

And the code:

import transformers
import torch
import json
model_id = "meta-llama/Meta-Llama-3-70B"

pipe = transformers.pipeline("text-generation",
                                 model=model_id,
                                 model_kwargs={
                                     "torch_dtype": torch.bfloat16,
                                     "max_memory": {0: "42GiB", 1: "42GiB", 2: "42GiB", 3: "42GiB"}
                                 },
                                 device_map="auto")

print(json.dumps(pipe.model.hf_device_map, indent=4))

output = pipe("Hey how are you doing today?")

print(output)

outputs:
{
    "model.embed_tokens": 0,
    "model.layers.0": 0,
    "model.layers.1": 0,
    "model.layers.2": 0,
    "model.layers.3": 0,
    "model.layers.4": 0,
    "model.layers.5": 0,
    "model.layers.6": 0,
    "model.layers.7": 0,
    "model.layers.8": 0,
    "model.layers.9": 0,
    "model.layers.10": 0,
    "model.layers.11": 0,
    "model.layers.12": 0,
    "model.layers.13": 0,
    "model.layers.14": 0,
    "model.layers.15": 0,
    "model.layers.16": 0,
    "model.layers.17": 0,
    "model.layers.18": 0,
    "model.layers.19": 1,
    "model.layers.20": 1,
    "model.layers.21": 1,
    "model.layers.22": 1,
    "model.layers.23": 1,
    "model.layers.24": 1,
    "model.layers.25": 1,
    "model.layers.26": 1,
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    "model.layers.28": 1,
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    "model.layers.75": 3,
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    "model.layers.77": 3,
    "model.layers.78": 3,
    "model.layers.79": 3,
    "model.norm": 3,
    "lm_head": 3
}

@SunMarc

Would anyone care to look at it please? Let it be @SunMarc or someone else? I highly suppose it's an HF compatibility issue with NVLink, but I can't say with 100% certainty.

We really would appreciate any help on this roadblock....much thx!


Fix soft deleted doesn't work when upgraded Laravel 4.2

Fix #211
rebase commits from #212

+1
Is the project still mantained? Right now, the last commit is dated to 10 jul 2014 on the master branch.

Hey guys, I'm trying to catch up on the project. I'm really sorry for being gone, had academic + health issues.
If possible, please lend me a hand at #227, as this issue seems complicated and there are different fixes.
I'm closing this now as it seems that's the one that worked. I'm unsure, though (that's why I'm asking for help! haha)


Website [Lead space] Video and play-pause feature update

Objective

Provide Carbon for IBM.com adopters the most up-to-date best practices and guidance they need to adopt Carbon for IBM.com.
Useful resources

Design page mockup using Gatsby theme resources

Create images strictly using Image production guidelines. Find sketchfiles from same link above

Create thumbnail image on the Components overview page - use the master Sketch work file here to get started.

For general contribution - Please visit the Contributing page for information and process detail.

For Markdown best practices - Please visit the Production guideline to learn more.

To setup the local build of the website, follow Website edits via terminal

For how to create and submit PR
There are several ways to submit a PR. Use whichever method you are comfortable with:

Using command line / Terminal
Using VS Code
Using Github UI

This looks like a duplicate actually of #1323. Will copy issue description over and close this one.


Oes 93

New table & view to hold raws feed.

Incorrect pull request. Closing this.

Incorrect pull request. Closing this.


Performance issue when loading 50000 rows

Hi Paul,
I googled javascript spreadsheet and thankfully found this awesome project. :) After watching the document, i tried to create a simple demo project using VUE. Here is the codesandbox link.
There is some performance issue when i just simply increase the row size to 30000/40000/50000. It shows an empty page and i need to wait nearly 10s or mote to
get the table rendered in page. The page also freezes when i try to edit a cell value,  Do you have any suggestions on how to solve this issue?
After searching in the doc, i see there is  lazy loading  feature available. Is it possible to directly scroll to the end of the table? It spend a lot of time to do the scrolling which may not be user friendly. Thanks for creating this amazing project and hope get your reply. :)
jExcelOptions:
jExcelOptions() {
      let columns = _.map(["name", "title", "age"], columnName => {
        return {
          title: columnName,
          width: 150
        };
      });

      let rows = [];
      for (let i = 0; i < 30000; i++) {
        rows[i] = [];
        for (let j = 0; j < columns.length; j++) {
          rows[i].push("1000000");
        }
      }

      return {
        data: rows,
        columns: columns,
        minDimensions: [columns.length, 10],
        csvHeaders: true,
        columnDrag: true,
        allowInsertColumn: false,
        allowManualInsertColumn: false,
        allowDeleteColumn: false,
        onload: function() {
           // Looks like this function got executed before the table is finally rendered in the page.
           console.log('table got rendered..');
        }
        // tableOverflow:true,
        // lazyLoading:true,
        // loadingSpin:true,
      };
    }

You should use pagination or lazyLoading...
Check this example:
https://codesandbox.io/s/hopeful-einstein-yq5sc


riff system install --node-port error: stat /root/.kube/config: no such file or directory

I use this tutoral: https://projectriff.io/docs/getting-started/minikube/
And I run knative using riff on minikube.
riff system install --node-port could't work.
Install riff and Knative system components.

If an `istio-system` namespace isn't found, it will be created and Istio components will be installed.
Use the `--node-port` flag when installing on Minikube and other clusters that don't support an external load balancer.
Use the `--manifest` flag to specify the path or URL of a manifest file which provides the URLs of the kubernetes configuration files of the components to be installed. The manifest file contents should be of the following form:

    manifestVersion: 0.1
    istio:
    - https://path/to/istio-release.yaml
    knative:
    - https://path/to/build-release.yaml
    - https://path/to/serving-release.yaml
    - https://path/to/eventing-release.yaml
    namespace:
    - https://path/to/buildtemplate-release.yaml

Note: relative file paths or http/https URLs may be used in the manifest.

Usage:
  riff system install  [flags]

Flags:
      --force             force the install of components without getting any prompts
  -h, --help              help for install
  -m, --manifest string   manifest of kubernetes configuration files to be applied; can be a named manifest (latest, nightly, stable) or a path of a manifest file (default "stable")
      --node-port         whether to use NodePort instead of LoadBalancer for ingress gateways

Global Flags:
      --kubeconfig path   the path of a kubeconfig (default "~/.kube/config")
      --master address    the address of the Kubernetes API server; overrides any value in kubeconfig

Error: stat /root/.kube/config: no such file or directory```

@reachyunsong The riff cli needs access to your kubernetes cluster and it expects to find ~/.kube/config. Are you running riff in a container?

I just install riff via
curl -Lo riff-linux-amd64.tgz https://github.com/projectriff/riff/releases/download/v0.3.1/riff-linux-amd64.tgz
tar xvzf riff-linux-amd64.tgz
sudo mv riff /usr/local/bin/```
How do I check whether `riff` running in a container?

do you have kubectl installed and are able to use it to connect to your cluster?

yes, I think so. @trisberg
$ sudo kubectl get nodes
NAME       STATUS   ROLES    AGE     VERSION
minikube   Ready    <none>   7h57m   v1.14.0

I wonder why you run kubectl with sudo? Look for where the .kube/config is created.

I first installed kubectl following the official guide, but met this error:
The connection to the server localhost:8080 was refused - did you specify the right host or port?

I haven't find solution so I use another tutorial but it always need sudo.
And .kube/config is in my root directory.
locate .kube/config
/users/yunsong/.kube/config

@reachyunsong not ideal, but if you sudo the riff command, it will be able to find kube/config.
I would highly recommend that you re-install minikube & kubectl cli by following official instructions  and then start the minikube cluster using instructions from projectriff

@sbawaska I re-install minikube & kubectl, so I can use kubectl without sudo.
$ kubectl get nodes
NAME       STATUS   ROLES    AGE     VERSION
minikube   Ready    master   8m22s   v1.14.0

But now I can't find .kube/config...
$ locate .kube/config

I can install knative successfully, but why cannot create function?
$ kubectl get pod --all-namespaces
NAMESPACE          NAME                                            READY   STATUS    RESTARTS   AGE
istio-system       cluster-local-gateway-5bf5488bb-2jfws           1/1     Running   0          4m39s
istio-system       istio-citadel-78fd647cf-zm5fn                   1/1     Running   0          4m46s
istio-system       istio-egressgateway-5547468b8d-62fww            1/1     Running   0          4m49s
istio-system       istio-galley-64ddbbff8b-djp7s                   1/1     Running   0          4m49s
istio-system       istio-ingressgateway-686d54b4bf-zdpqs           1/1     Running   0          4m49s
istio-system       istio-pilot-7c86c7cb8b-7hzmd                    2/2     Running   0          4m47s
istio-system       istio-policy-64b5ff6bd8-m268x                   2/2     Running   0          4m48s
istio-system       istio-sidecar-injector-6956c47586-k7dmq         1/1     Running   0          4m46s
istio-system       istio-telemetry-55b97c59c4-5cpw8                2/2     Running   0          4m48s
knative-build      build-controller-77cbbc9888-rcq25               1/1     Running   0          119s
knative-build      build-webhook-64f9bbc7c9-t5c57                  1/1     Running   0          119s
knative-eventing   eventing-controller-8b87fcbb5-5jzf8             1/1     Running   0          104s
knative-eventing   in-memory-channel-controller-c48986657-rh5fd    1/1     Running   0          94s
knative-eventing   in-memory-channel-dispatcher-5f68fff98d-hspr8   2/2     Running   1          91s
knative-eventing   webhook-6dc88dbfb4-kg2bg                        1/1     Running   0          104s
knative-serving    activator-5956447886-dtjz7                      2/2     Running   0          115s
knative-serving    autoscaler-5cb94cdb69-rczg9                     2/2     Running   0          115s
knative-serving    controller-c4c56dd6d-6wnvr                      1/1     Running   0          114s
knative-serving    webhook-6cf887c686-vjmfw                        1/1     Running   0          113s
kube-system        coredns-fb8b8dccf-7dfpc                         1/1     Running   0          9m8s
kube-system        coredns-fb8b8dccf-mbg8v                         1/1     Running   0          9m8s
kube-system        etcd-minikube                                   1/1     Running   0          8m21s
kube-system        kube-addon-manager-minikube                     1/1     Running   0          8m8s
kube-system        kube-apiserver-minikube                         1/1     Running   0          7m58s
kube-system        kube-controller-manager-minikube                1/1     Running   0          8m15s
kube-system        kube-proxy-hzvwl                                1/1     Running   0          9m7s
kube-system        kube-scheduler-minikube                         1/1     Running   0          8m17s
kube-system        storage-provisioner                             1/1     Running   0          8m57s

$ riff function create square \
>   --git-repo https://github.com/projectriff-samples/node-square  \
>   --artifact square.js \
>   --verbose
Applied default --image="docker.io/dockeryunsong/square"
Waiting for LatestCreatedRevisionName
Waiting on function creation: checkService failed to obtain service status for observedGeneration 1
Waiting on function creation: function creation incomplete: service status unknown: RevisionMissing
LatestCreatedRevisionName available: square-gsj2k
default/square-6s262-pod-dc50b6[build-step-git-source-0]: {"level":"warn","ts":1561938341.9878285,"logger":"fallback-logger","caller":"logging/config.go:65","msg":"Fetch GitHub commit ID from kodata failed: \"ref: refs/heads/upstream/release-0.5\" is not a valid GitHub commit ID"}
default/square-6s262-pod-dc50b6[build-step-git-source-0]: {"level":"error","ts":1561938347.0181088,"logger":"fallback-logger","caller":"git-init/main.go:52","msg":"Unexpected error running git [fetch --depth=1 --recurse-submodules=yes origin master]: exit status 128\nfatal: unable to access 'https://github.com/projectriff-samples/node-square/': Could not resolve host: github.com\n","stacktrace":"main.runOrFail\n\t/go/src/github.com/knative/build/cmd/git-init/main.go:52\nmain.main\n\t/go/src/github.com/knative/build/cmd/git-init/main.go:91\nruntime.main\n\t/usr/local/go/src/runtime/proc.go:200"}
default/square-6s262-pod-dc50b6[build-step-git-source-0]: {"level":"error","ts":1561938352.0422978,"logger":"fallback-logger","caller":"git-init/main.go:41","msg":"Error running git [pull --recurse-submodules=yes origin]: exit status 1\nfatal: unable to access 'https://github.com/projectriff-samples/node-square/': Could not resolve host: github.com\n","stacktrace":"main.run\n\t/go/src/github.com/knative/build/cmd/git-init/main.go:41\nmain.main\n\t/go/src/github.com/knative/build/cmd/git-init/main.go:95\nruntime.main\n\t/usr/local/go/src/runtime/proc.go:200"}
default/square-6s262-pod-dc50b6[build-step-git-source-0]: {"level":"error","ts":1561938352.0445173,"logger":"fallback-logger","caller":"git-init/main.go:52","msg":"Unexpected error running git [checkout master]: exit status 1\nerror: pathspec 'master' did not match any file(s) known to git.\n","stacktrace":"main.runOrFail\n\t/go/src/github.com/knative/build/cmd/git-init/main.go:52\nmain.main\n\t/go/src/github.com/knative/build/cmd/git-init/main.go:96\nruntime.main\n\t/usr/local/go/src/runtime/proc.go:200"}
default/square-6s262-pod-dc50b6[build-step-git-source-0]: {"level":"info","ts":1561938352.0445998,"logger":"fallback-logger","caller":"git-init/main.go:101","msg":"Successfully cloned \"https://github.com/projectriff-samples/node-square\" @ \"master\" in path \"/workspace\""}

@skeeey can you help check and give some comments here?

@reachyunsong i appears from the error message that your environment could not resolve github.com to pull the source code for the function.
Could not resolve host: github.com

Instead of building directly from GitHub you could try to clone the repo to your own machine and then create the function using '--local-path' instead of '--git-repo'
git clone https://github.com/projectriff-samples/node-square.git
cd node-square

riff function create square \
--local-path .  \
--artifact square.js \
--verbose

The local-path option assumes that you have initialized the namespace with your docker credentials, and are running a local docker daemon which is logged-in using those credentials.

@reachyunsong I think @jldec is right, you should make sure your environment can visit the  github.com successfully, in my environment, I can run the example successfully, here is my log
root@perftest4:~# riff function create square \
>   --git-repo https://github.com/projectriff-samples/node-square  \
>   --artifact square.js \
>   --verbose
Applied default --image="docker.io/skeeey/square"
Waiting for LatestCreatedRevisionName
Waiting on function creation: checkService failed to obtain service status for observedGeneration 1
Waiting on function creation: function creation incomplete: service status unknown: RevisionMissing
LatestCreatedRevisionName available: square-5pflg
default/square-twqnb-pod-386787[build-step-git-source-0]: {"level":"warn","ts":1562564734.4276793,"logger":"fallback-logger","caller":"logging/config.go:65","msg":"Fetch GitHub commit ID from kodata failed: \"ref: refs/heads/upstream/release-0.5\" is not a valid GitHub commit ID"}
default/square-twqnb-pod-386787[build-step-git-source-0]: {"level":"info","ts":1562564734.8910928,"logger":"fallback-logger","caller":"git-init/main.go:101","msg":"Successfully cloned \"https://github.com/projectriff-samples/node-square\" @ \"master\" in path \"/workspace\""}
default/square-twqnb-pod-386787[build-step-analyze]: WARNING: image 'docker.io/skeeey/square' not found or requires authentication to access
default/square-twqnb-pod-386787[build-step-analyze]: WARNING: image 'docker.io/skeeey/square' has incompatible 'io.buildpacks.lifecycle.metadata' label
default/square-twqnb-pod-386787[build-step-build]: -----> Node.js Buildpack 0.0.4
start to build and export image ...
default/square-5pflg-deployment-5968f87b9c-6xg9l[user-container]: Node started in 148ms
start the container and invoke it ...
riff function create completed successfully
Deployed image "index.docker.io/skeeey/square@sha256:edaea2004c982afdfd62e57196e5f90694347e63de323f24702db4b8d3b960ec"

@jldec Thank you, I followed step you mentioned, but met this error, is this due to docker configuration?
~/node-square$ riff function create square \
> --local-path .  \
> --artifact square.js \
> --verbose

Applied default --image="docker.io/dockeryunsong/square"
Using user-provided builder image projectriff/builder:0.2.0
Pulling builder image projectriff/builder:0.2.0 (use --no-pull flag to skip this step)
2019/07/16 21:13:27 Unable to read "/users/yunsong/.docker/config.json": open /users/yunsong/.docker/config.json: no such file or directory
2019/07/16 21:13:28 Unable to read "/users/yunsong/.docker/config.json": open /users/yunsong/.docker/config.json: no such file or directory

Error: Got permission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Post http://%2Fvar%2Frun%2Fdocker.sock/v1.38/images/create?fromImage=projectriff%2Fbuilder&tag=0.2.0: dial unix /var/run/docker.sock: connect: permission denied

@skeeey Thank you~~~
I‘ll check my environment again.

as i mentioned above,

The  --local-path option assumes that you have initialized the namespace with  your docker credentials, and are running a local docker daemon which is  logged-in using those credentials.

To install docker, please see here

@reachyunsong please reopen if you still having issues


Lazy loading fails in IE10

Likely due to this bug: https://connect.microsoft.com/IE/feedback/details/792880/document-readystat
We need to check for readyState !== 'interactive' as well in the ready method for script-loader.js
  var ready = function (fn) {
    if (document.readyState !== 'loading' && document.readyState !== 'interactive') {
      fn();
    } else if (document.addEventListener) {
      document.addEventListener('DOMContentLoaded', fn);
    } else {
      document.attachEvent('onreadystatechange', function() {
        if (document.readyState !== 'loading') {
          fn();
        }
      });
    }
  };

@drewcovi would you be interested in submitting a PR for this? Would be interested in seeing one.

Hey, it would be cool if this issue'd be solved. :) It's a blocker for me.


Not able to make mutual auth REST calls

When trying to make mutual auth REST calls (requires client cert), the call is failing with error "There was an error during the request. An SSL protocol error occurred". In the earlier version, it was using the certification I had in Personal store via chrome. That does not work anymore.
Expected outcome
Mutual auth REST call should use certificate from Personal store
Actual outcome
Displays error "There was an error during the request. An SSL protocol error occurred"
Versions
App: <IP_ADDRESS>-stable
Chrome: 49.0.2623.110
Platform: Windows (7)
Steps to reproduce

Make mutual auth REST call which requires client cert

Duplicate of #432


Make partner profile information consistent in both bank and partner views.

Resolves #4791
Description

I only updated the descriptions in the views. I searched for them in the editor and made sure all instances were changed.
Type of change

Bug fix (non-breaking change which fixes an issue)
This change requires a documentation update

How Has This Been Tested?

It appears that there are no tests for the file upload function. If necessary, I can write some tests for it.
Screenshots

@nozomirin can you fix the lint errors?

I noticed that there is a space after every colon, so I added one as well. However, I will remove it.
Additionally, I realized there is a (Link): in the condition. Should the colon after 'Agency Status' be removed as well?
@dorner
<p>501(c)(3) IRS Determination Letter or other Proof of Agency Status:
    <% if partner_profile.proof_of_partner_status.attached? %>
      <!-- NOTE: The actual download link may not work in local storage mode due to file locations being seperate locally. -->
      (Link): <%= link_to partner_profile.proof_of_partner_status.filename, rails_blob_path(partner_profile.proof_of_partner_status, disposition: 'inline') %>
  <% end %>

The colons in displayed text wouldn't be affected by the linter. It only cares about code.


Dockerfile Tweaks and Cleanup

Addressing issue #144:

I corrected the variable expansion issue with WORKDIR in the Dockerfile.
Did some light "copy editing".
Deleted the entrypoint.sh script.
Corrected some of the flags in run.

I love deleting code! And it looks good to me, but deferring to @jsf9k as a better Docker reviewer.

@egyptiankarim, thanks for catching the error and thanks for getting rid of entrypoint.sh!

@egyptiankarim You should be able to check a box somewhere that lets @jsf9k make changes on the PR directly. I know it lets you do at post-time, not as certain about after posting.

@konklone @jsf9k it's strange because I already have the little "allow edits from maintainers" box checked. Hopefully the latest commit addresses the requested change. Let me know if I need to make any more :)


Assembly is updated

Hi,
I've updated the assembly code.
There was a small mistake in the multiply function.
At least in the part of it that I left in.
I had to remove some since I could not confirm it working at the moment. I commented it out.
I was able to confirm the rest of the code working.
After I reduced the numbers from the example since I only handle integers and just multiplying every number by 10 would already create an overflow.
I'm not sure about my commit procedure.
I'm relatively new to git.
At the beginning I forked your repo. Then I added the AVR folder, commited and created a pull request. So far so good.
This time I first created a pull request on my fork to get up to date with your repo and then made my changes. Is that correct? Is there a better way to keep my fork up to date?
MxFxM

Paging @daniel-kukiela  =]

This way looks ok, but the proper one would be: https://help.github.com/en/github/collaborating-with-issues-and-pull-requests/syncing-a-fork so something like:
git merge upstream/master

Where upstream is however this repository is named on your side.
Also I strongly encourage you to create README.md file with some description how to run your code. I have pretty many different AVR microcontrollers and might run your code, but you might save me the part about researching how to compile and flash asm code, thank you!
Also thank you for your contribution!


Drop karma tests

Since we're relying on React handles cross-browser inconsistencies, so neither we nor userland need to, so we can remove it from all the packages as well as skip developing for it. This should make testing faster and more reliable, and we could explore integrating with alternative testing frameworks.

As we drop these tests to be run in node alone, we should double check our code coverage as well.


Prompted to re-answer join questions once my request to join a group approved

Another thing, I requested access to join BioFi. I answered the join questions and requested access. Once my request was approved, I'm taken to the Explore page and immediately I'm prompted to re-answer the join questions. It won't let me hop in until I do so.
This is happening on my Macbook Air, on Chrome

Update: once I refresh, I'm taken back to the screen to re-agree to group agreements and I'm let into the group

Bug replicated, at least until the second set of join questions popping up. The third time around for agreements I will have to confirm later.
The joinQuestionsAnsweredAt value is null instead of being a date-time stamp
The value comes from
const { agreementsAcceptedAt, joinQuestionsAnsweredAt } = currentMembership?.settings || {}
Which comes from currentMembership = useSelector(state => getMyGroupMembership(state, props))
If you receive a notification (over web sockets), sharing that you've been accepted into a group, you have somewhere to click on getting access for that group. Looking in the console, at the redux debugging information, FETCH_CURRENT_USER does happen, and it had a membership for the group! But it appears that the membership doesn't have the joinQuestionsAnsweredAt value. But it is requested and present in the graphql query.
So, my current theory is that the 'joinQuestionsAnswerAt' isn't updated if someone answers them as part of their request to join and that this is a node issue....
Off to validate that

Nah, node is fine.
It is that its missing a up to date membership. Once we have everything running off graphQL subscriptions these sorts of bugs will all go away :D

OK... back to comment on this just before I go to bed. Now I'm just getting a variation of this bug where I have been approved but there is no way for me to trigger receiving the membership object in the browser without just hitting refresh.

@tibetsprague, thoughts on what makes sense here...
Once we have graphql subscriptions, this will be straightforward. until then its...

Socket updates for memberships (is there a user socket?)
Have the group-view for non-members re-request membership info on load... and then maybe periodically

Leaning towards the second, since I am not so familiar with the socket setup

no user socket right now, I started working on that at some point. There used to be one. yes we definitely need some kind of re-request of membership for sure, why not just when you go to the group?


ci: improvements on the renovate changeset workflow

When pushing the changeset, the PR checks were disappearing. We need to use another PAT so it re-triggers the CI workflow. It does then make more sense to separate the CI and renovate workflows
An empty changeset was pushed when the renovate version bump had no impact on any npm package (e.g. non-node renovations). It now checks if any npm package changed before creating the file
the changeset was including dependent packages. It is confusing as we can't easily determine which package is responsible for the bump in reading the changeset, and it is unnecessary as the changeset action already determines the bumps of the dependents

Codecov Report

Merging #1269 (fab330c) into main (5638b5e) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##             main    #1269   +/-   ##
=======================================
  Coverage   94.74%   94.74%
=======================================
  Files          48       48
  Lines        6931     6931
  Branches      450      450
=======================================
  Hits         6567     6567
  Misses        364      364

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

@szilarddoro I'm going to merge this one - all the oncoming renovate PRs don't have mandatory checks activated because of this


Use conversion protocol to ensure input types on connection init

Protect borders :shield: earlier then it will be passed to SSL with few extra characters.
Fix double quotes in README.

@witkwski why do we need to convert certificate data to a string?

@dankimio for example? OpenSSL::X509::Certificate#new expects a string as a certificate and coerces input data with #to_s . OpenSSL::PKey::RSA#new in that case expects a pair of strings as well (cert and passphrase). So will be better to ensure needed types on connection building instead of catching errors from OpenSSL entrails.

@dankimio for example? OpenSSL::X509::Certificate#new expects a string as a certificate and coerces input data with #to_s . OpenSSL::PKey::RSA#new in that case expects a pair of strings as well (cert and passphrase). So will be better to ensure needed types on connection building instead of catching errors from OpenSSL entrails.

@witkwski That's a valid point! Thank you for the PR.


running in browser

I think it must be possible by using wasm in xterm.js?

Someone created an example here, haven't tried it myself though https://github.com/BigJk/bubbletea-in-wasm

Someone created an example here, haven't tried it myself though https://github.com/BigJk/bubbletea-in-wasm

I tried, thanks, it works very well

@7flash Awesome, thanks for letting us know!


Filter for issues without milestone

Feature Description
IMHO it would be very helpful if the select field "Milestone" for selecting issue filters based on milestones would also provide an option "no milestone" for filtering all issues which do not have a milestone assigned.
Screenshots
No response

duplicated with #3407


Connected Next.js with chrome extension

Overview
Issue Type

[ ] Bug
[x] Feature
[ ] Tech Debt

Description
Implemented Node event emitters to create SSE events when next.js endpoint is met with a request.
Implemented consumption of SSE events on the chrome extension front end with EventSource API.
Replaced mock data on frontend with actual Otel data.
Ticket Item
Feature 2: Replace mock data on frontend with actual data
Steps to Reproduce Bug / Validate Feature / Confirm Tech Debt Fix

Clone the Next Inspect Testing App repo at 'https://github.com/wnguye03/next-inspect-testing-app'
ensure that line 15 on instrumentation.node.js has the url value set to 'http://localhost:3002/stream/otel' and ensure the endpoint is wrapped in quotes, such that it is a string.
start up the next.js app by running npm run dev
Go to Chrome and manage extensions.
Ensure that dev mode is switched on in the top right.
Click 'Load Unpacked' in the top left and select the dist folder within the NextInspect repo under /chrome-extension/dist
Go to the NextInspect repo root directory and run the express server by changing directories to npm-package and running npm run dev
navigate to http://localhost:3000 in the browser
inspect the page and open dev tools
Click the double right arrows in the devtool top tab. A picture will be attached to show the right arrows.
Select NextInspect
Refresh the localhost page if needed
Network information should be loaded

Screenshots & Videos

Yourui, is the data that you are sending reduced or is that the complete data that we are recieveing from OTEL, from memory I think there were more spans and traces on initial page load.


PublishSymbols default SearchPattern (and doc) is a poor choice leading to not being able to analyze crashes and other reliability issues

SearchPattern in PublishSymbols@2 has a bad default that will result in not able to properly analyze Reliability issues including crashes, hangs, memory leaks, etc. Since the ability to analyze is the MAIN purpose of publishing symbols, this is clearly a bad default.
I even worked in the crashdump analysis area for Microsoft, and did not realize right away these were poor defaults, until I was not able to analyze crash dumps for my own process.
Backstory: Almost all modern binaries x64, arm64, .NET REQUIRE binaries (.exe, .dll) to also be uploaded to the symbol server along with .pdbs files. Without these files, stack unwinding cannot happen and analysis will be messed up in WinDbg, VS, or other analysis tools.
SearchPattern - Search pattern
string. Required. Default value: /bin//*.pdb  <--- Bad default
Specifies the pattern used to discover the PDB files to publish. See File matching patterns reference for more information.
The task defaults for PublishSymbols and docs should change to this which properly publish symbols for all 3 file types.
            SearchPattern: |
              **/bin/**/*.pdb
              **/bin/**/*.exe
              **/bin/**/*.dll

Also, this SearchPattern syntax is not intuitive if you read the file matching pattern docs. I got it wrong the first time resulting in no files published

Document Details
⚠ Do not edit this section. It is required for learn.microsoft.com ➟ GitHub issue linking.

ID: 4d97490d-94e9-7c19-f87a-0594ff604c3e
Version Independent ID: 4d97490d-94e9-7c19-f87a-0594ff604c3e
Content: PublishSymbols@2 - Index sources and publish symbols v2 task
Content Source: task-reference/publish-symbols-v2.md
Service: azure-devops-pipelines
Sub-service: azure-devops-pipelines-tasks
GitHub Login: @steved0x
Microsoft Alias: sdanie

Product issue: https://github.com/microsoft/azure-pipelines-tasks/issues/19691

Thank you for your feedback. We are migrating this issue to our new documentation feedback system, and closing this issue.
As we phase out GitHub issues for this repository, we encourage you to propose changes using public PRs or submit feedback through our updated control at the top of the page. For more information on our feedback systems, see https://aka.ms/contentuserfeedback.


Updating service topology to a higher weight due to deprecation

Follow up to https://github.com/kubernetes/website/pull/37494; contributes to https://github.com/kubernetes/website/issues/35093
Updating service topology to a higher weight than any other page in its section as it is a deprecated feature.
/cc @haosdent @sftim

deploy preview: https://deploy-preview-37678--kubernetes-io-main-staging.netlify.app/docs/concepts/services-networking/

/lgtm

/lgtm
/approve


Can't add a constructor to a class

There's a block for creating a class, but no way to add a constructor for the class.
If you try to add it manually, like this:
class Name {
constructor(name) {
}
}
It creates a 'method constructor' block and round trips to:
class Name{
methodconstructor(name){
}
}

Fixed on version 0.3.8


Auto-discovery fails on Laravel 5.5 due to incorrect path

Path is wrong, so the service provider autodiscovery call fails. Not quite seeing this locally but for still fails on builds for completely fresh no vendor installs.
Fatal error: Illuminate\Support\ServiceProvider::loadRoutesFrom(): Failed opening required '/project/path/vendor/rachidlaasri/laravel-installer/src/Providers/../routes/web.php' (include_path='.:/home/travis/.phpenv/versions/7.0.22/share/pear') in /project/path/vendor/laravel/framework/src/Illuminate/Support/ServiceProvider.php on line 71

Stack trace/build log here:
https://travis-ci.org/nabeelio/phpvms/jobs/311455947

I've made same pull request: https://github.com/RachidLaasri/LaravelInstaller/pull/131
Can mantainer pleasse tell us why it's not accepted?


plural class name

Describe the bug
models from array struct are generated in plural forms
To Reproduce
given the json
{
    "__className": "Document",
    "title": "INSURANCE",
    "ownerOrganizationKey": "778a69f7-d98c-4464-859c-f700c7a33162",
    "status": "approved",
    "pages": [
      {
        "key": "5621f8a9-f05a-4469-bddf-0cdb56b24771-3",
        "image": null,
        "local_uri": "/var/mobile/Containers/Data/Application/2D3D40E2-4DBD-4364-A9D5-3F50732A63A0/Documents/camera/pictures/CAP_8C794E18-11AE-43CE-B8A8-B8395ED1F06A.jpg",
        "documentTitle": "INSURANCE",
        "documentKey": "5621f8a9-f05a-4469-bddf-0cdb56b24771"
      }
]
}

and using json generation the model generated is
class Pages{
....
}

Expected behavior
Class name should be Page
Screenshots
If applicable, add screenshots to help explain your problem.
Version
3.2.5
Json
see above
Additional context
using Jsonc file generation

@Miamoto-Musashi Hi.
I would not say that it's a bug. In this case JSON key pages for list object used for value name for type names as List<Pages> and for unnamed list object inside the pages list. It possible to remove s letter but I don't know if not defect names and I'm not sure if all plural have s at the end? Need to test.

yes Is in the middle from a bug and an enhancement, let's say the expected behavior is to have List objects in the array not Pages, probably a simple implementation can start removing s at the end but then you need to consider noun like man/men, child/children and so on.
Probably introducing references between objects (see task #45 ) can solve both
Best

@Miamoto-Musashi I have consulted with a friend who speaks English. And he said that it would work 99% to remove only s at the end for the rest 1% he not garante 😁
I will fix it as soon as possible.

Just would like to add that there's some cases where trimming s isn't enought. Imagine countries for example, it should be changed to country, but then there might be i18n issues because I'm not sure if it's always enough to replace ies with y.

Just would like to add that there's some cases where trimming s isn't enough. Imagine countries for example, it should be changed to country, but then there might be i18n issues because I'm not sure if replacing ies by y always solves the problem.

@Ascenio Thanks for the correction. You are right.


Is tcgetattr supported?

I don't see it on http://docs.go-mono.com/?link=N%3AMono.Unix or in grep
I wrote a console app using Tmds.Linux, and it works great on Linux/WSL, but is not portable to Mac currently.
And the .net built-in console support does not seem sufficient.  I don't see how to force the tty back to 'echo' mode right before an execve.

It looks like this was using an ioctl under the hood.  Never mind.  I was confused because Tmds.Libc chooses to expose the tc* wrappers.

It is not supported right now, it'd need to be added in Syscall.cs and presumable some native wrappers for the termios struct.
https://github.com/mono/mono.posix/blob/062156d94302990cf742883bc688a1c9a1982a9f/src/Mono.Unix/Mono.Unix.Native/Syscall.cs#L5025

I'm hacking around this limitation as follows:
execve("sh -c 'stty sane; exec $my_target_prog $my_args'")


Add Wiesbaden, Germany

Hi, I'd like to add Wiesbaden, Germany to this wonderful project. The repo can be found here: https://github.com/mattsches/equalstreetnames-wiesbaden

Hello @mattsches, you should have received an invite to join @EqualStreetNames/wiesbaden.
Once you've joined you should be able to transfer your repository.

Repository transfered!

Perfect, I'll take care of the next steps when I have some free time.

Thank you! :smiley:

🚀 Deployed: https://wiesbaden.equalstreetnames.eu/


Markdown pages

Add a donation page
Rewrite the Opera page with markdown

Deploy preview for bettertw ready!
Built with commit 7f8a615b86f766722de15cde20553744f9507142
https://deploy-preview-9--bettertw.netlify.com


[WIP] website setup

Needs to merge https://github.com/runtimeverification/k-web-theme/pull/15 first
Demo website: https://shd101wyy.github.io/kore

I think the performance workflow is failing because this PR comes from a fork. There's no need to worry about that, since the PR doesn't touch any Haskell code it's safe to merge without it.
Let me know when it's ready for review. Thanks!