show current location

Would like to be able to center the map around my current location. I wrote location for this.
Will submit a PR if you don't mind.

lovely idea, go ahead!

would you like to have a specific key to query the location? what about showing a progress indicator?

on the current-location branch, it will now query the current location after startup. rendering it is still missing.

would you like to have a specific key to query the location?

like the idea, choose any one that feels good for you :)

what about showing a progress indicator?

👍 _notify will help
would love to include a simple UI at some point to display information like progress/meta/search/*

what about setting the zoom level?

hum..., maybe on initial load keeping the minimal zoom, when pressing the corresponding key street/block-level-ish?
thanks for your work!

would you like to have a specific key to query the location?

like the idea, choose any one that feels good for you :)

i picked l
current-location will show a notification now.

:heart: tried and works beautifully!
just one question came to my mind:
in terms of user control & privacy, should we maybe ask before sending the related data?
we could / i would implement a small info-footer with all keys on startup - with [l] being the first.
thoughts?

in terms of user control & privacy, should we maybe ask before sending the related data?

good point. macOS will automatically ask if the helper tool (that location uses underneath) should be able to access your location. on Linux and Windows, this warning is currently missing.
from the perspective of location, we have two choices:

let consuming tools such as mapscii ask for permission. this is easy to implement, as the prompt can be shown in the best context possible (web, cli, gui)
let location ask for permission. this would have the advantage that we can use native system prompts.


rustfmt always insert a string at the start of file using neovim on arch linux

I'm using same nvim config file on both my windows and arch linux device. It works fine on windows but would insert a string(I don't know what it means) at the start of file after formatting.

I'm using formatter.
After removing this tool and just use cargo fmt in command line, it works fine. Strange.

@fristzzz given that running cargo fmt directly didn't produce the error, I'm assuming this is an issue with formatter, and you should probably file an issue with that project.


[A11Y] Android: Focus goes to top of browser window instead of webpage when user navigates from one page to another

ENVIRONMENT:
OS (number): N (7.0)
Build number: NRD91R
Form factor (Tablet):  Nexus 9
Browser: Chrome Dev 59.0.3062.4
Pre-requisite:

Talkback is ON

STEPS TO REPRODUCE:

Open https://ampstart.com
Linearly Navigate to COMPONENTS link and double tap on it.
When Components page is loaded, try to swipe linearly forward.

ACTUAL RESULTS:
Focus goes to the top of browser window and linear navigation happens through Tab name, URL, toolbar etc.
EXPECTED RESULTS:
Focus should go to the top of page opened and linear navigation should happen as per the page reading order from top.
ATTACHMENT(S):
PageToPageNav_FocusIssue.mp4.zip

Dont think this can be fixed , this seems to be a browser thing.


Android Basics issue:

URL of codelab
https://developer.android.com/codelabs/android-basics-kotlin-write-instrumentation-tests?continue=https%3A%2F%2Fdeveloper.android.com%2Fcourses%2Fpathways%2Fandroid-basics-kotlin-unit-2-pathway-2%23codelab-https%3A%2F%2Fdeveloper.android.com%2Fcodelabs%2Fandroid-basics-kotlin-write-instrumentation-tests#3
In which task and step of the codelab can this issue be found?
3
Describe the problem
There's a space missing in the following code line
@get:Ruleval activity = ActivityScenarioRule(MainActivity::class.java)
@get:Rule val activity = ActivityScenarioRule(MainActivity::class.java)
Steps to reproduce?

Go to...
Click on...
See error...

Versions
Android Studio version:
API version of the emulator:
Additional information
Include screenshots if they would be useful in clarifying the problem.

@programify
Thank you for reaching out to us. The issue is fixed and published:


VPS & Tor

Hello,
I configured my Raspiblitz in Clearnet with a public ip from DigitalOcean
Tutorial: https://www.mobycrypt.com/turn-your-self-hosted-lightning-network-node-to-public-in-10-minutes/
Is it possible to run the node in Clearnet for requests etc. and activate Tor only for Applications like LNBits, Zeus Wallet, Sphinx Chat, Bos Telegram Bot.... to have better security or is it better with dyndns?

It is possible, but corrently not implemented. Tor only is default and you could manually activate the clearnet access for LND.
DynDNS does not provide any security or privacy since it is just resolves to the given IP address.
See: https://github.com/rootzoll/raspiblitz/issues/2787

Yeah, but I deactivate ''run behind tor'' in the menu and configure my node with the tutorial above to a public ip...
To get access with applications like lnbits, zeus..... I need DynDNS and open ports in the VPS droplet (those are my security concerns)
My thoughts are to connect only the Applications over a Tor Adresse.
Maybe with Hybrid Mode....idk

aah ok thx. you are the man


Subquery and aggreagation supports

Following features were added;

Subquery support (inline query for 'from' clauses).
Sum, Avg, CountExp aggreagation methods.
GroupBy method accessor in SimpleQueryProvider
SubQueryWithAggregationTest unit test

And  'Select' method is modified to use with aggreagtion methods.
Example:
SELECT [CUT].[House__Address] as [HomeAddress], SUM([CUT].[ExtraUserInfo__Children])....

Any plans for this PR to be merged?

Is this something we can expect to become part of NPoco? It would be something very useful to replace more complex SQL queries with.


logo title fixing GSSoC'2023

Description
I want to add "shortly" just after right side of the logo so, that the UI will improve. I have also marked in the screenshots.
Screenshots

Additional information
No response

Hi Please assign this issue to me for GSSOC 23

Already assigned to someone in other issue


Succeeded  [False] but Violations  [0]

2016-11-11T19:52:56.4958750Z VERBOSE: Processing the folder
 2016-11-11T19:52:56.4958750Z [C:\****\_work\1\s\src\****.Models]
 2016-11-11T19:52:56.4958750Z VERBOSE: The settings.stylecop passed the parameter
 2016-11-11T19:52:56.4958750Z [C:\******\_work\1\s\src\Settings.StyleCop]
 2016-11-11T19:52:56.4958750Z VERBOSE: The IsNullOrEmpty check returned [False]
 2016-11-11T19:52:56.4958750Z VERBOSE: The Test-Path check returned [True)]
 2016-11-11T19:52:56.4958750Z VERBOSE: Loading from folder from [C:\******\tasks\StyleCop\1.8.1]
 2016-11-11T19:52:56.4958750Z VERBOSE: Loading DLLs from
 2016-11-11T19:52:56.5115000Z [C:\******\tasks\StyleCop\1.8.1\StyleCopWrapper.dll]
 2016-11-11T19:52:56.5271250Z VERBOSE:
 2016-11-11T19:52:56.5271250Z VERBOSE: Base folder [C:\******\_work\1\s\src\***.Models]
 2016-11-11T19:52:56.5271250Z VERBOSE: Settings  [C:\******\_work\1\s\src\Settings.StyleCop]
 2016-11-11T19:52:56.5271250Z VERBOSE: Succeeded  [False]
 2016-11-11T19:52:56.5271250Z VERBOSE: Violations  [0]
 2016-11-11T19:52:56.5271250Z VERBOSE: Log file  [C:\******\_work\1\a\***.Models.stylecop.log]
 2016-11-11T19:52:56.5271250Z VERBOSE: XML results
 2016-11-11T19:52:56.5271250Z [C:\******\_work\1\a\****.Models.stylecop.xml]

2016-11-11T19:52:56.5271250Z VERBOSE: Succeeded  [False]
2016-11-11T19:52:56.5271250Z VERBOSE: Violations  [0]

Thanks strange, could you share with me the ***.Models.stylecop.log? Are there any warnings?
Note that this task actually use the DLL from the project https://github.com/rfennell/StyleCopCmdLine so there is a chance the issue is in there. Thought I have not had problems reported before

Sorry.
After clean build repository problem is gone

No problem, glad you are sorted


query-balance -> get-balance

casper-client query-balance does not exist, changed it to get-balance and tested successful.

Thanks for the PR, however the query-balance exists in the Rust client on the dev branch.  Generally the casper-client's dev branch is kept aligned with the casper-node's dev one and once the node undergoes an upgrade, the client's dev branch will be merged to main and a new client version published.
Thanks anyway, but I'll close this unmerged.


Trademark usage of Spinnaker

Hey, can someone look into the trademark usage demonstrated in https://marketplace.redhat.com/en-us/products/spinnaker and reach out to OpsMX about usage of the Spinnaker mark? Per a prior conversation with @caniszczyk and @brianwarner, Armory has updated our product name and we're nearly done the process of updating all the assets on our website (started with the most prominent) to comply with the guidelines from the LF https://www.linuxfoundation.org/trademark-usage/. So, now we're extra aware of those guidelines. Thanks!

@dnilasor I notified @tracymiranda who now is the CDF lead and is working to rectify the situation and kickstart a conformance working group for Spinnaker + put together branding guidelines.

Hi. Any movement on this? Does the Linux Foundation actually own the trademark for Spinnaker at this juncture? @tracymiranda can you please look into this or refer us elsewhere? We are still unable to use the word Spinnaker in Google advertisements because of a conflict with Spinnaker Support, who owns a relevant mark. We are unable to resolve this on our own as we are not the mark owner. Our competitors are still able to use the mark because of the timing of the complaint.

for sure the LF owns the mark, I just looked it up in USPTO
 along with it being here: https://www.linuxfoundation.org/trademarks
@tracymiranda leads CDF so should be working to resolve this issue with you and the community

Great, looks like the filing was finalize and approved in November, since the last time I pinged on this. Thanks for the update @caniszczyk. I am reaching out to the complainant at Spinnaker Support now, Michelle, whose contact information I got from Google Ads. If there are any additional disputes about this, I will likely need support from the CDF/LF since you are the owner of the mark and have authorized to use it (they may want verification).
I'll reach out to Tracy in that case and request expedient attention. Thanks!


feat(automod): refactor slur processing

The old automod code relied upon cut-pasting a bunch of [hhhhhh][eeeeeee][iiiiiiil]{2}[oooooooooo0] strings around when the regexes could be a lot more readable by separating the unicode substitution and badword checking steps. This attempts to unify the code into one place.

this looks interesting/promising, but it will probably be January (2025) before we can take a real look

this looks interesting/promising, but it will probably be January (2025) before we can take a real look

Enjoy your holiday break! There's no urgency, this is just maintainability of future badword detection rather than any urgent need to add more badwords.


HD5 Exception in unittests

On my windows laptop, some unittests throw exceptions HDF5 exceptions. The CI seems to be unaffected.
Output of TestSaveResult.compareResultWithH5 on my msvc build:
[ RUN      ] TestSaveResult.compareResultWithH5
[2021-09-06 15:06:02.349] [error] Constraint check: Parameter InfectiousTimeAsymptomatic not set as fully dependent on tinc, tserint and tinfmild. See HZI paper.
HDF5-DIAG: Error detected in HDF5 (1.12.0) thread 0:
  #000: C:\autotest\hdf5112-StdRelease-dist-10vs14\build\hdfsrc\src\H5F.c line 793 in H5Fopen(): unable to open file
    major: File accessibility
    minor: Unable to open file
  #001: C:\autotest\hdf5112-StdRelease-dist-10vs14\build\hdfsrc\src\H5VLcallback.c line 3500 in H5VL_file_open(): open failed
    major: Virtual Object Layer
    minor: Can't open object
  #002: C:\autotest\hdf5112-StdRelease-dist-10vs14\build\hdfsrc\src\H5VLcallback.c line 3465 in H5VL__file_open(): open failed
    major: Virtual Object Layer
    minor: Can't open object
  #003: C:\autotest\hdf5112-StdRelease-dist-10vs14\build\hdfsrc\src\H5VLnative_file.c line 100 in H5VL__native_file_open(): unable to open file
    major: File accessibility
    minor: Unable to open file
  #004: C:\autotest\hdf5112-StdRelease-dist-10vs14\build\hdfsrc\src\H5Fint.c line 1564 in H5F_open(): unable to open file: name = 'XÏ¤ÄM', tent_flags = 0
    major: File accessibility
    minor: Unable to open file
  #005: C:\autotest\hdf5112-StdRelease-dist-10vs14\build\hdfsrc\src\H5FD.c line 741 in H5FD_open(): open failed
    major: Virtual File Layer
    minor: Unable to initialize object
  #006: C:\autotest\hdf5112-StdRelease-dist-10vs14\build\hdfsrc\src\H5FDsec2.c line 346 in H5FD_sec2_open(): unable to open file: name = 'XÏ¤ÄM', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0
    major: File accessibility
    minor: Unable to open file
unknown file: error: SEH exception with code 0xc0000005 thrown in the test body.

and TestSaveParameters.ExtrapolateRKI
[ RUN      ] TestSaveParameters.ExtrapolateRKI
....
HDF5-DIAG: Error detected in HDF5 (1.12.0) thread 0:
  #000: C:\autotest\hdf5112-StdRelease-dist-10vs14\build\hdfsrc\src\H5G.c line 355 in H5Gcreate2(): name parameter cannot be an empty string
    major: Invalid arguments to routine
    minor: Bad value
unknown file: error: SEH exception with code 0xc0000005 thrown in the test body.
[  FAILED  ] TestSaveParameters.ExtrapolateRKI (148 ms)

probably an encoding issue. (maybe related to https://stackoverflow.com/questions/32072272/using-std-string-in-hdf5-creates-unreadable-output)
only happens in debug builds, which explains why CI currently doesn't complain (see #29) but also means it needs to be fixed, since it's not just a problem on my system.


[FEAT]: Fix camera in position to get correct bottle pictures

Done.
TOBE done is the CAD version, but it need too much time and this MOC will go to @gteti to do the image processing.
In these images the camera position on the MOC
A dedicated angle regulation system is present.


increase input image size

hi nice work on the repo, thank you for these great examples.
I'm trying to increase the size and getting tensor mismatch errors, cannot really see a way around it.
Is there a way to not hard code the FC layer input size and get it from the convnet somehow ?
 RuntimeError: size mismatch, m1: [256 x 179776], m2: [1024 x 256] at /pytorch/aten/src/THC/generic/THCTensorMathBlas.cu:268

No, the linear layers need to have their weights initialized so they need to know the input shape. You need to change it accordingly.
To avoid this you could use a network that uses global average pooling after the last spatial output (e.g. after the last convolutional layer), then your input vector has the size of number of channels which doesn't rely on input size. Then you can reshape and apply one last linear layer. You can look at ResNet or Inception networks as an example.

Could you give an example for the modification? Thank you.


Keep top border only on action buttons for on-chain actions

To remove clutter from UI, would be nice just keep top-border on action buttons.

change it for

BUY

GIFT

BURN

LIST

SHARE JOY

remove Download button from actions and download functionality with icon https://fontawesome.com/icons/download?s=solid next to sharing icons as Download is not on-chain action.

👋

@roiLeo got a better idea?

That's a lot of border top in one screen, I would try something new.
maybe remove colors; add corresponding emoji; "BUY" button as a CTA;  rename "MAKE OFFER" to "BID"

I mean till we get someone who would help us to make great components or rehaul the whole design, it's just a small minor fix, it's not permanent 😄 just realized we have buttons on gallery item everywhere with border top

as you wish 🏎


Home page should talk about NuGet 1.5, not 1.6

The home page mentions NuGet 1.6, which hasn't been released yet.

We made thos choice along time ago... Are we not going to release them at the same time?

The current plan is to have the gallery up for a day or two to make sure it's stable and to address any data issues before we release 1.6.


Allow SpinGroup tasks to report failure by returning special symbol

At the moment, the only way a SpinGroup task can report failure is by
raising an excepting. Since SpinGroup generates a backtrace from the
exception, task failures are very noisy.
This PR allows tasks to return a special symbol :task_failed to indicate
to the SpinGroup that it failed. During debrief, SpinGroup doesn't generate
a backtrace for these kind of failure.

I thought I wrote it so that returning false would do something like this. I meant to anyway.

I like this because it's more explicit. Someone not familiar with the library could place a call to something that happens to return false at the end of the block and that's a bit confusing


scrubber: more robust metadata consistency check

The scrubber's scan_metadata command will flag some inconsistencies, but it's not quite robust enough to trust at scale:

It needs to handle objects being deleted while it scans, by re-reading the index after scan and checking that any objects that vanished have also vanished from the index.
It needs a way of reporting results that we can alert on at scale.  Perhaps this is a log, perhaps it's a write to a database, or a write to a scrub report in S3.

Basically the code in branch_cleanup_and_check_errors is somewhat old and crufty and needs a fresh set of eyes to make sure we are robustly checking a well understood set of things, before we can use it at scale to increase confidence that our metadata's integrity is okay.
### Tasks
- [ ] #8344
- [ ] https://github.com/neondatabase/neon/pull/8424
- [ ] https://github.com/neondatabase/neon/issues/8421
- [ ] https://github.com/neondatabase/neon/pull/8480
- [ ] https://github.com/neondatabase/neon/pull/8502
- [ ] https://github.com/neondatabase/neon/pull/8565
- [ ] https://github.com/neondatabase/neon/pull/8635
- [ ] Wire the check into a command suitable for running along with physical GC (a la https://github.com/neondatabase/cloud/issues/14024)
- [ ] Setup alert on metadata health status
- [ ] scrubber: invoke storage controller to learn about timeline existence (blocked until storage controller is timeline-aware)

Last week:

write out race conditions between RemoteTimelineClient and scrubber.

This week:

implement changes to scan_metadata to make the checks robust.

Last week:

implemented the check (without considering parallelism to head object calls).

This week:

add some helper functions for creating corrupted S3 state + check if scrubber actually detect errors
add it to the same cronjob as Physical GC (or maybe a seperate cronjob?)

Last week:

Opened  #8480
Opened #8502

This week:

Merge existing PRs
Wire scan_metadata command into scrubber cronjob.

Last week:

Opened #8565

This week:

Wire scan_metadata command into scrubber cronjob.

Last week:

Merged #8635

This week:

Update helm-charts to use unified command.

Last week:

Found a new transient error as a result of race between scrubber listing and timeline deletion [Grafana].

Classify errors and see if any are non-fatal
We will switch to and exit-code based alerting (@skyzh set up the alert here).

This week:

Merge #8873

We will switch to and exit-code based alerting

already done, let's refine the exit code within scrubber to make the alert more informative

Last week:

Handle concurrent list_timeline_blobs and timeline deletion: https://github.com/neondatabase/neon/pull/8873

This week:

Look into scrubber logs to see if there are any failures.


add [PUB] points badge

Add a badge for PUB to show the points for Dart/Flutter packages and plugins.
Fix #7917.

Messages

:book:
:sparkles: Thanks for your contribution to Shields, @G1Joshi!

  Generated by :no_entry_sign: dangerJS against e2925c0290ebca7f4ceb9ae15a85222fc91e7b60

This PR depends on #7921.
All tests will pass after merging the above-mentioned PR.

Cheers for working on these

Cheers for working on these

Thanks for your cooperation.


Add doris exporter to otelcol-contrib releases

Related PR: https://github.com/open-telemetry/opentelemetry-collector-contrib/pull/36448

Can we add a changelog note?

Can we add a changelog note?

Done.


Digsam On "For Bedrifter" Page

What happened?
The section about Digial Transformasjon study at the page "For Bedrifter" shows Digital Samhandling. This must be changed
What browsers are you seeing the problem on?
Chrome
What device are you seeing the problem om?
PC
Relevant log output
No response

Anton has a fix for this already, but he needs to fix the merge conflicts before we merge it, and we must double check that he hasnt switched any of the links as well.

@antontveito we will fix it together during the meeting


gdbus-codegen-glibmm: bump to latest master

Contains fixes and new API needed for first version of connectivity-manager.
Shortlog:

Add missing return 0 for when Gio::DBus::NodeInfo::create_for_xml() fails
Add usage_count() method to stub
Use object id to check if object is already registered in stub
Improve logging in register_object() of stub
Add unregister_object() to stub and call it in destructor
Make stub inherit from sigc::trackable
Make stub follow rule of five
Remove deprecated connect() method in stub
Add missing return 0 to main() of integration test sources
proxy.cpp.templ: call proxy's call_finish() in *_set_finish()

The commits related to making the stub handle deletion and unregistering from the bus properly are especially important since connectivity-manager creates/removes objects dynamically on the bus for Wi-Fi access points.

Pushed a fix for the SRC_URI as well.


Fix gnote.text issue

Resolves #22

@davenicoll - this was already fixed in the develop branch - so I will close this out.  See issue #25 notes


[bn] Maintainers alert for the dev-bn branch

hey @ikramulkayes  and @Mouly22 , are you guys eager to maintain this repository?
Kindly respond within next 1 week (Deadline 10th February) if you want to continue.
Or else, we will be editing the approvers.
Approvers responsibilities:

Approvers need to attend the monthly meeting if possible and check PR's and check in their local system
Approvers might also need to attend the monthly meetup we have on the CNCF Chattogram's page

If you agree to these, kindly response.

Due to no response within almost 2 weeks, we can not process with you guys @Mouly22  @ikramulkayes .
It was great working with you guys as a maintainer.

@Mouly22  after creating the PR, this issue will be closed. We have some PRs to make regarding this issue. If you guys are intended to remain the maintainer , you can share your interest in the comment section or else, we will create the PR soon and look for maintainers.


Deny-all network policy for CAPA

After https://github.com/giantswarm/giantswarm/issues/27266, we found that the newly introduced deny-all policy, together with removal of cilium-app's defaultPolicies.enabled=true means some operators cannot reach the API server nodes anymore. Those operators have a NetworkPolicy with the correct CIDR range allowed, but Cilium has a known issue (https://github.com/cilium/cilium/issues/20550) which renders the allow rules ineffective. While the fix is not released and Cilium not upgraded on our side, we have to set defaultPolicies.enabled=true again in order to keep things working. We can expect the Cilium fix to be released quite soon.
We could also instrument all our apps with a CiliumNetworkPolicy allowing toEntities: [ kube-apiserver ], but that's a lot of effort.

We will have to update cilium-app to get this feature, cc @giantswarm/team-turtles maybe if you have some time, if not we will try to make it

Btw...we got another ticket just like that in our backlog that's currently being worked on by rocket: #2815
So maybe you can check with @gawertm for cooperation on it here aswell :)

are we talking about MC or WC deny all policies? Rocket is working to make this work as discussed in Kaas sync for panamax WCs. (because they are already very far with capvcd and a later migration would could hurt us). I would need to recall the exact approach, but I believe once we have it, it will be very easy for you to adopt the same for CAPA @T-Kukawka
cc @jkremser

It's both MC and WC stuff. Any operator that uses NetworkPolicy to reach the k8s API, such as metrics-server which goes into all clusters.

The fix is in release cilium v1.15.0-pre1, not in a stable release yet. We should discuss whether we want to try for CAPA only, for instance.

@whites11 and me checked that apps belonging to default-apps-aws (= the most important ones that must work) can be adapted to include a CiliumNetworkPolicy. That's a quick win to get things working. Once that's done, we can introduce the deny-all policy (and remove defaultPolicies.enabled again).

After checking with Andreas, we believe the best way forward to finally fix this issue is:

disable default cilium NPs in cilium app config in cluster-aws PR
set ciliumNetworkPolicy.enabled = true to all relevant apps in default-apps-aws
add back the deny all network policies as we have in vintage

This way vintage and capa will be aligned in terms of network policies and we don't need to wait for cilium 1.15


CacheRead: clear dir entry if doc is found to be truncated

We were seeing document corruption errors which kept on repeating over and over again.
This modifies the logic inside iocore/cache/CacheRead.cc function CacheVC::openReadReadDone to remove the cache directory entry not only on IO fail but on other detected document errors.

[approve ci autest]

What is the document corruption means ? Which error is repeating over an over again .
This code looks good to me but still need more information.

https://github.com/apache/trafficserver/blob/18042049ee31fdb1d7063a197787c61d4c3e471c/iocore/cache/CacheRead.cc#L605

In this case, we don't need to delete earliest_dir because dir is already cleared by writer. But it is ok to delete earliest_dir again (It is do nothing for earliest_dir).

Sorry about that I pulled up the old ticket that this patch was attached to.  For some reason on a server an asset got "stuck" in this state and we ended up with clients being stuck on this server and asset, enough that a cdn user was able to track down the specific machine that was causing their clients to stick.
[Jun 30 19:34:18.903] [ET_NET 3] WARNING: <CacheRead.cc:626 (openReadReadDone)> Document CCC9640029DCE88B5589176CB010DBEB truncated, <anonymized>
[Jun 30 19:34:22.257] [ET_NET 21] WARNING: <CacheRead.cc:626 (openReadReadDone)> Document CCC9640029DCE88B5589176CB010DBEB truncated, <anonymized>
[Jun 30 19:34:26.055] [ET_NET 9] WARNING: <CacheRead.cc:626 (openReadReadDone)> Document CCC9640029DCE88B5589176CB010DBEB truncated, <anonymized>

https://github.com/apache/trafficserver/blob/18042049ee31fdb1d7063a197787c61d4c3e471c/iocore/cache/CacheRead.cc#L605

In this case, we don't need to delete earliest_dir because dir is already cleared by writer. But it is ok to delete earliest_dir again (It is do nothing for earliest_dir).

I could narrow down the logic or else add a comment that this line already clears the entry if that would help make things clearer in the future.

Another question . Is truncated asset still in cache before your change when you get next request for same asset ?

Another question . Is truncated asset still in cache before your change when you get next request for same asset ?

Yes the truncated asset is stuck in cache.

[approve ci docs]

[approve ci]

[approve ci]

Cherry-picked to v9.1.x branch.

I'm slightly uncomfortable with this in 9.0.x, how well tested is it? @SolidWallOfCode @bryancall  wdyt?

Cherry-picked to v9.0.x branch.
Thanks @vmamidi  for convincing me.

Can we get a backport PR for 8.1.x for this?


No way to return an error with arbitrary message

I have the "catch all panics" wrapper around the code and return a JNI error in this case. With the introduction of errors enum in 0.2.1 this stopped working. Right now JniError::Unknown looks like the best type for this case but there is no way to also provide the error message.

Might be related to #25?

This can be an implementation example


pwsafe: extend to Darwin platform

Motivation for this change
Fixes #109957
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
22.05 Release Notes (or backporting 21.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[x] Fits CONTRIBUTING.md.

It's been a while since you opened the issue @nxg
But if you can retest building pwsafe on macOS with those changes that would be nice. :)

I don't think this works, but I'm not at all sure I'm doing the right thing...
% nix-channel --update
unpacking channels...
created 1 symlinks in user environment
% nix-env -qa --drv-path --out-path pwsafe
pwsafe-1.14.0  /nix/store/bwa32mb3db6ikdxya7z1f38xz7hbcyav-pwsafe-1.14.0.drv  /nix/store/ba1i9v1mnmf6s3qzpqdmb0agkvvymq7a-pwsafe-1.14.0
% nix-shell -p pwsafe
these derivations will be built:
  /nix/store/nd33a5kzpr3j6fxk22b95p7jnvyg2h18-wxwidgets-3.0.5.drv
  /nix/store/bwa32mb3db6ikdxya7z1f38xz7hbcyav-pwsafe-1.14.0.drv
these paths will be fetched (5.14 MiB download, 32.73 MiB unpacked):
  /nix/store/2826q8vlldv59hcllxr75wjkbmbpjlli-libGL-1.4.0
  /nix/store/66yxgp673p3pz2mnh8rfwwgwg9831ac9-mesa-21.3.5-drivers
  /nix/store/6wrgi1cbazbr5cyc8hwac58pk9jm8hhh-mesa-21.3.5-dev
  /nix/store/b5zsafzr5nrgw7asr1xwhihc0hr5a8pf-qrencode-4.1.1-bin
  /nix/store/g4r29y89hx86rla7nnbr655n20vdj3fk-libGL-1.4.0-dev
  /nix/store/h9g1hl37cjf8if28icq8qfjqrcs2b4h9-glu-9.0.2-dev
  /nix/store/id5khcw2q9mhdirklciy0xhz4a8fvlhf-qrencode-4.1.1-dev
  /nix/store/jsmn3b3ifc9qdfwmwwygk5gl2138cxsz-mesa-21.3.5
  /nix/store/k4mb7b2vaxi9nzcdldmv0vns6d7i2rn7-glu-9.0.2
  /nix/store/l9s25vzy0ycv5gpwd9gp8pqqz4vvppqj-qrencode-4.1.1
  /nix/store/n2llvwal5wfwm3spdgiw05ld7wh717l1-gst-plugins-base-1.18.5-dev
  /nix/store/vvgykbdb6p6yj01lk1n3gdsqw40h2vj0-gst-plugins-base-1.18.5
copying path '/nix/store/l9s25vzy0ycv5gpwd9gp8pqqz4vvppqj-qrencode-4.1.1' from 'https://cache.nixos.org'...
copying path '/nix/store/vvgykbdb6p6yj01lk1n3gdsqw40h2vj0-gst-plugins-base-1.18.5' from 'https://cache.nixos.org'...
[...]
clang++ -mmacosx-version-min=10.7 -c -o htmldll_helpdlg.o  -D__WXOSX_COCOA__      -DWXBUILDING      -I./src/regex  -DWXUSINGDLL -DWXMAKINGDLL_HTML -dynamic -fPIC -DPIC -Wall -Wundef -Wunused-parameter -Wno-ctor-dtor-privacy -Woverloaded-virtual -Wno-deprecated-declarations -D_FILE_OFFSET_BITS=64 -I/private/tmp/nix-build-wxwidgets-3.0.5.drv-0/source/lib/wx/include/osx_cocoa-unicode-3.0 -I./include -D__ASSERT_MACROS_DEFINE_VERSIONS_WITHOUT_UNDERSCORES=1 -O2 -fno-strict-aliasing -fno-common -fvisibility=hidden -fvisibility-inlines-hidden ./src/html/helpdlg.cpp
./src/osx/cocoa/mediactrl.mm:470:9: fatal error: 'AVFoundation/AVFoundation.h' file not found
#import <AVFoundation/AVFoundation.h>
        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
1 error generated.
make: *** [Makefile:39581: mediadll_osx_cocoa_mediactrl.o] Error 1
make: *** Waiting for unfinished jobs....
builder for '/nix/store/nd33a5kzpr3j6fxk22b95p7jnvyg2h18-wxwidgets-3.0.5.drv' failed with exit code 2
cannot build derivation '/nix/store/bwa32mb3db6ikdxya7z1f38xz7hbcyav-pwsafe-1.14.0.drv': 1 dependencies couldn't be built
error: build of '/nix/store/bwa32mb3db6ikdxya7z1f38xz7hbcyav-pwsafe-1.14.0.drv' failed
%

I'm rather confused that the version of the pwsafe derivation appears to have gone from 3.53 to 1.14.0.  Am I doing something terribly wrong? (I confess that my usage of Nix is largely voodoo, rather than the result of deep understanding!)
% nix search -u nixpkgs.pwsafe
* nixpkgs.pwsafe (pwsafe-1.14.0)
  A password database utility

This is on Darwin jellicle.home 20.6.0 Darwin Kernel Version 20.6.0: Mon Aug 30 06:12:21 PDT 2021; root:xnu-7195.141.6~3/RELEASE_X86_64 x86_64 (ie, macOS 11.6).  Tomorrow I should be able to try also on 12.1 on M1.

Yes the version "downgrade" is explained in #151601
3.x are the Windows versions ; but Unix builds with wxWidgets are 1.x versions.

Ah – thanks for the explanation.
I've also, as promised, had a chance to run on M1, and this fails (but it looks like you were expecting that).
% nix-channel --update
unpacking channels...
created 1 symlinks in user environment
% nix-shell -p pwsafe
error: Package ‘pwsafe-1.14.0’ in /nix/store/dg2x0651qjjlynnfs2997ggd5f71lxgi-nixpkgs-22.05pre352151.18a062b02d6/nixpkgs/pkgs/applications/misc/pwsafe/default.nix:57 is not supported on ‘aarch64-darwin’, refusing to evaluate.

Yes with nix-shell -p you're trying to install or build pwsafe from the current unstable channel.
But there is several point with the current package definition that makes it nok for Darwin:

wxGTK30 is not working on Darwin, wxmac must be used instead
it needs Darwin-specific frameworks like Carbon, etc...

This PR is trying to address those 2 points.
Currently failing on ofBorg builders, it seems there is a problem with upstream CMake rules.

...and these changes aren't in the current unstable channel – right, I think I see.  Is there anything I can usefully test here?  As I say, I'm a pretty naive user of NixPkgs, so if I'm to test with something not in that channel, I'm afraid you'll have to walk me through the process.


QAT

hi there
according to the documentation
https://github.com/analogdevicesinc/ai8x-training#quantization-aware-training-qat
we can use either QAT or post quantization but can I use both of them? if yes for using both of them after training which file should I choose qat-checkpoint or qat-best?
while is training it is writing "save checkpoints to qat_checkpoint.pth.tar"  but in the documentation is written we have to choose qat-best.pth.tar.

Hello,
QAT is a method to train a model while optimizing the performance of its quantized version. So at QAT, all the model parameters are stored as floating points but the forward pass of the model is executed after quantizing the parameters. At the model synthesis stage, you still have to quantize the model checkpoint whether you use QAT or not. This is why you can observe two scripts for each pretrained model in our [synthesis repo] (https://github.com/analogdevicesinc/ai8x-synthesis/tree/develop/scripts); the first one to quantize the model and the second one to synthesize the model for the MCU.
We always advice you to train the models using QAT as the quantized model's performance is always better with respect to the models trained without QAT. In our framework, two model checkpoints are saved to the disk. 'qat_checkpoint.pth.tar' is the checkpoint fie that is saved at the last epoch of the training where 'qat_best.pth.tar' is for the epoch when the validation set accuracy is maximum. So it is recommended to use 'qat_best.pth.tar' in our documentation.

There are 4 checkpoint files in the log folder. checkpoint.pth.tar & best.pth.tar are related to the floating point model training. These files are updated until QAT starts (epoch 240 for your case). After QAT is initiated, only the qat_checkpoint.pth.tar & qat_best.pth.tar are updated. Therefore, if you want to use QAT models, you need to use the model checkpoints with qat prefix.

hi
thanks a lot for your clear answer;))


Ensure services use internal methods

Accompanying test for feathersjs/feathers-knex#51, has not been tested against other services though.

Woot! Thanks @t2t2


URL not displayed in publication entry

Describe the bug
When adding the field url to a PublicationEntry, no URL is displayed. I would expect to see a hyperlinked URL here, similar to when using a DOI. If disable_external_link_icons: true, then the link dissappears entirely.
To Reproduce
    publications:
      - title: 3D Finite Element Analysis of No-Insulation Coils
        authors:
          - Frodo Baggins
          - '***John Doe***'
          - Samwise Gamgee
        url: https://github.com/
        date: 2004-01

Screenshots

It might also be nice to have the option to hide the link but make the publication title clickable instead

Thank you! This has been addressed in #128. It will be fixed in v1.13 (I plan to release it today.)

It might also be nice to have the option to hide the link but make the publication title clickable instead

This can be achieved by using Markdown links as shown below:
- title: [This is a title](https://example.com)
...

Although for your second suggestion I would prefer a configuration option. It would be much cleaner on the yaml side and also would avoid mixing up DOIs and URLs if a DOI field is defined. It would also be nice to have the abilty to display the external link icon next to the publication title. What do you think?

Although for your second suggestion I would prefer a configuration option.

I wouldn't say I like using configuration options because they increase the size of the templates and make tests even more difficult. Even the 'url' field was not properly tested, as this issue demonstrates.
Of course, I always prioritized the user experience over development issues; therefore, in v1.9, I took a new approach to allow users to tweak their entries: I gave the users complete control of the templates. You can quickly achieve what you want by tweaking the PublicationEntry.j2.tex file that comes from the rendercv new command (see here.) Overriding built-in themes is described here.

It would also be nice to have the abilty to display the external link icon next to the publication title.

This can be achieved with a blank Markdown link:
- title: This is a title [](https://example.com)
...

Thanks for the explaination and solutions!


Create a privacy policy

Again just like in #42 i like nebula's as a starting point:

Nebula privacy policy
Privacy Policy
We will not collect any more information than needed to provide you with a great experience.
Whatever information we collect, we won’t share with third parties beyond the technical requirements of third-party services.
Whenever possible, we’ll anonymize whatever data we have.
We won’t sell your data under any circumstances.
Someone may someday acquire us, and they’ll get your data as a result. If that happens, they won’t be allowed to sell it either. Unless they get your permission. Don’t give it to them unless they offer something really cool.
If someone acquires us, they'll have the ability to change this policy. They'll have to notify you first, though.
We might email you to tell you about cool stuff. We’ll do our best to keep it interesting and not annoy you.
Some people just hate getting email at all. We get that. If you want us to stop, let us know and we’ll stop.
We’ll never subject you to a passive-aggressive guilt trip about unsubscribing to marketing emails. Ew.
If you want to cancel your subscription, that’s okay. No hard feelings. We’ll remove your data as soon as possible. It may take a while because backups, but we won’t put any artificial delays in place.
 That’s not us. We won’t do that.
If we ever accidentally do that, we’ll understand if you send a grumpy email. We'll deserve it.
We won’t share any data with government or law enforcement unless required to by law.
We have never shared any user information with a government or law enforcement agency. We won’t be able to tell you if we have, so keep an eye out for future versions of this privacy policy with this line missing.
We don't have your credit card information. Our processing partner, Stripe, does. We trust them to keep it safe.
We’ll only use that information to bill you for service, charge you for merchandise that you’ve chosen to buy, or otherwise charge you for things that you explicitly request.
We can’t think of any reason we’d need your phone number, but if we ever get it, we promise not to sell it to anyone.
We may anonymize data about trends and share that with the press or with partners. This will always be done in the spirit of improving the service, and never at the expense of your privacy.
We will not use any kind of technology that utilizes your microphone or camera to gather data about you for marketing purposes. Weird that this would even be a concern, right?
The videos we present may contain advertisement materials from sponsors. The presence of these sponsors is up to the individual creator.
We’ll do our best to stick to sponsors we really think you’ll like.
Sponsors will always be disclosed.
We may occasionally need to change this policy. We’ll be sure to let you know. This might require us sending you an annoying email. We’re sorry in advance.

This needs to be evaluated for inclusion in the launch
See : https://docs.google.com/document/d/1bfoYhmwfImSCrlXe7v4DbH4MGnkjcNKU/edit

Completed with #42


41 delete users

IMPORTANT: Please do not create a Pull Request without creating an issue first.
Please provide enough information so that others can review your pull request:
/users shows the create user form and the list of all users. Each of these can be deleted (note the current logged in user isn't shown)
Explain the details for making this change. What existing problem does the pull request solve?
Adds feature to be able to delete users.
Gives chance to see all users.
Test plan (required)
Demonstrate the code is solid. Example: The exact commands you ran and their output, screenshots / videos if the pull request changes UI.

php artisan test - tests backend features
npm run test  - runs jest tests
Closing issues
List all issues this PR resolves.

closes #41

Pre-Merge checklist
Complete these items before requesting reviews

[x] Static Analysis Rules Validated
[x] All commits follow naming conventions

Sub-tasks Checklist

[x] UI Implementation
[x] UI Test
[x] Backend Implementation
[x] Backend Tests
[x] Integration Tests
[x] System Tests

Validated via http://csu-bp-41-delete-users-193ppcs.herokuapp.com/users and it worked! Nice job


Linkify Addresses

Would it be possible to add default text rules to automatically linkify addresses?

Hello @Calvin-LL, actually there is.
There was this deprecated flag: https://developer.android.com/reference/android/text/util/Linkify#MAP_ADDRESSES and how there's this https://developer.android.com/reference/android/view/textclassifier/TextClassifier#TYPE_ADDRESS which support addresses but also other things like flights, that could also be an option to be added.
Can you take a look and see if it's worth to reopen this issue? Thanks!

Oh I see, thanks for digging into it. I'll take a look when I have time next week.


Change default target framework to netstandard2.1

Default to netstandard2.1 instead of the net46 from SqlTasks.target, also allows it to be overridable with anything like net6.0 or net8.0 - fixes #330
Import Microsoft.NET.Sdk.targets which adds more features as supported by .NET such as transitive project dependencies - fixes #278

What will our story be for .net framework?

What will our story be for .net framework?

Since sqlproj doesn't really care about .NET version, you can set the target framework to net46 if you want. The test confirms that.
If you're asking about using the .NET Framework version of msbuild, nothing is changed in that path since we need the targets from the .NET SDK.


feat(header/p2p): implement GetVerifiedRangeByHeight

Resolves:

https://github.com/celestiaorg/celestia-node/issues/1201
https://github.com/celestiaorg/celestia-node/issues/1078

Codecov Report

Merging #1305 (4fdd06f) into main (c71c036) will increase coverage by 0.51%.
The diff coverage is 69.88%.

@@            Coverage Diff             @@
##             main    #1305      +/-   ##
==========================================
+ Coverage   55.35%   55.87%   +0.51%
==========================================
  Files         182      186       +4
  Lines       11072    11463     +391
==========================================
+ Hits         6129     6405     +276
- Misses       4328     4429     +101
- Partials      615      629      +14

Impacted Files
Coverage Δ

header/core/exchange.go
40.90% <0.00%> (-9.10%)
:arrow_down:

header/interface.go
0.00% <ø> (ø)

header/local/exchange.go
61.90% <0.00%> (-6.52%)
:arrow_down:

header/store/store.go
62.26% <0.00%> (-3.74%)
:arrow_down:

header/p2p/peer_tracker.go
57.35% <57.35%> (ø)

header/p2p/session.go
72.48% <72.48%> (ø)

header/p2p/exchange.go
67.95% <89.28%> (-1.23%)
:arrow_down:

header/p2p/peer_stats.go
93.54% <93.54%> (ø)

nodebuilder/header/constructors.go
79.16% <100.00%> (+7.73%)
:arrow_up:

header/p2p/server.go
66.37% <0.00%> (-5.31%)
:arrow_down:

... and 5 more

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

@renaynay, check the top comment on my previous review to answer the your question

ack @Wondertan

can be done in a subsequent pr

I'd suggest to keep everything together if you don't mind


input_binding_thumbstick_position

input_binding_thumbstick_position(gp_stickl|r, [minMagnitude = 0], [maxMagnitude = 1], [minAngle = 0], [maxAngle = 360], [ignoreDeflection = true], [playerIndex])
'pressed' when engaged within specified min and max angle and magnitude
ideally should work with all checkers and be chord and combo compatible

#583


Update font name; Add PAT token as authentication.

This pull request includes changes to the init.lua file, primarily focusing on the modification of icon fonts and the addition of a new authentication method. The most significant changes are:
Icon Font Modification:

init.lua: The show_warning(status, body) function has been updated to use the 'icomoon' font instead of the 'feather' font for both user_icon and ticket_icon.

Authentication Method Addition:

init.lua: In the setup(args) function, a new authentication method has been added. If an API token is provided, it will be used for authentication. Otherwise, a PAT token will be used.

Hello @streetturtle, apologies for the tag, I wanted to do it by adding as reviewer. But it seems I can't do it.

Hey-hey! Thank you for this PR!
Could you please add to the readme how to install icomoon font please.

Could you please also bump the version to 1.3.

@streetturtle regarding the icomoon font - When I click on the link for 'feather.ttf' from your readme and attempt to install it, it says the name is 'icomoon' and not 'feather'.

It looks like icomoon is a software to create fonts. Maybe it was used to generate the font, and it automatically overrode the original font name. I'll do few tests and will post here.

Yeah, when I download version c51fe7c from https://github.com/AT-UI/feather-font it goes back to the name "feather".


F3, ignore when measure is hidden in refinement (version 3.0.0-beta.0)

Hello, when using version 3.0.0-beta.0, we are still receiving F3-issues on autogenerated count-measures, that are hidden in refinement.
We are getting autogenerated views by using Looker's "Create View From Table", and fetching all our tables from BigQuery, which auto-populates the dimensions with types and descriptions for us, and it also adds a default "count" measure, without any filters. We then refine the views, where we add primary-keys, hide unwanted dimensions/measures, and add new ones.
Since there is no way to delete the auto-generate measure (without editing the auto-generated file, which will be overwritten the next time it is auto-generated), we hide it. LAMS rule F4 ignores the hidden fields, but rule F3 does not ignore hidden measures.
Can F3 safely ignore all measures that are hidden, or are there some reasons that we are unaware of to still report F3-issues on hidden measures? Is there a way to delete a measure in a refined view?

Hidden measures can still be surfaced, for example by users explicitly typing them into the URL, or by drill_fields.
Would it be reasonable to apply the LAMS extension in the refinement?

Then I guess it would be reasonable to use exemptions, or create a custom rule that satisfies our use of hiding autogenerated count-measures.


CI/CD?

Should we set up a CI? Travis perhaps? We could make this nice 'n strict by failing builds which clippy errors on and rustfmt finds weird formatting in.

@gegy1000 should we use travis? Perhaps your jenkins?

Travis is probably simpler for now -- if we get to a stage where we need artifacts to be available, we could move to Jenkins. What do you think? Maybe we should just go for Jenkins right away?

Hmm... I've only used Travis, and don't really know how Jenkins works. What would be the difference?

Travis simply tests build success. Jenkins does this and hosts built artifacts. The builds also have to be managed on the Jenkins server.

Hmm... What do you think? Jenkins might be easier since it Flower requires quite a few build dependencies.

They're probably about the same when it comes to setting up.

@gegy1000 perhaps we could use Jenkins, so we could also allow people to download builds.

@gegy1000 this is done, so if you could just add badges, links, and integrate this with github (or tell me what I need to do for that to be done) then that would be great and we can close this.

Namely, this commit


Remove pages that duplicate handbook content

We should just link to handbook content. When both the wiki and handbook are in flux, keeping them in sync can be a bit of a pain.

Ideally the website would pull the handbook content directly from GitHub.  We're working on it.

Right, but this is for the wiki, not necessarily the website.


Model unable to take input from dictionary(with input layer names as key) after loading it using tf.keras.models.load_model

System information

OS Platform and Distribution (Linux Ubuntu 16.04):
device:
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): 2.0 rc
Python version: 3.6

My model works fine the first time when i create the architecture and train it, but once i save the model using tf.keras.model.save_model  and then load it again using tf.keras.models.load_model it fails to take input from the  dictionary(with input layer names as key) as if the names of layers are changed.
Example:
training_mask = tf.keras.layers.Input(shape=(None, None, 1), name='training_mask')
target_score_map = tf.keras.layers.Input(shape=(None, None, 1), name='target_score_map')
target_geo_map = tf.keras.layers.Input(shape = (None,None,5), name='target_geo_map')
These are three input layers that i am using to take input for training but once i save the model and later load it again to train it gives me the error " No data provided for "input_1". Need data for each key in: ['input_1', 'input_2', 'input_3']"
I am feeding data by specifying layer names :
    inputs = {
            'target_score_map': score_maps,
            'target_geo_map': geo_maps,
            'training_mask': training_masks
        }

Therefore, it works the first time when create I the architecture from code then train and save it but later when i load the model from disk it fails.
Regards
Shubham

In order to expedite the trouble-shooting process, please provide a minimal standalone code to reproduce the issue reported here. Thanks!

Hey ravikyram,
On more trouble-shooting i found out that the name of the layers are not changing, but something else is going on, layers are connected.
Following is the code to reproduce the issue:
**import tensorflow as tf
import os
import numpy as np
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
def get_data():
images = np.zeros((64,224))
labels = np.zeros((64,5))
inputs = {
'Image_input':images
}
outputs = {
'output-softmax':labels
}
return inputs, outputs
def create_model():
input_layer = tf.keras.layers.Input(name='Image_input', shape=(224), dtype='float32')
model = tf.keras.layers.Dense(5)(input_layer)
model = tf.keras.layers.Activation('softmax', name = "output-softmax")(model)

model = tf.keras.models.Model(inputs=input_layer, outputs=[model])
return model

model = create_model()
optimizer = tf.keras.optimizers.Adadelta(lr=1.0, rho=0.95, epsilon=None, decay=0.0)
print (model.summary())
model.compile(loss='categorical_crossentropy', optimizer=optimizer)
data = get_data()
model.fit(data[0], data[1], batch_size=16, epochs=10)
tf.keras.models.save_model(model,"model")
model1 = tf.keras.models.load_model("model")
model1.fit(data[0], data[1], batch_size=16, epochs=10)**
model.fit() works well but model1.fit() fails.
Also if you provide input without dictionary
def get_data():
images = np.zeros((64,224))
labels = np.zeros((64,5))
return images,labels
both model.fit() and model1.fit() runs successfully.
Thanks

I have tried on colab with TF version 2.0 rc0 and was able to reproduce the issue.Please, find the gist here.Thanks!

I believe that this is fixed with commit: https://github.com/tensorflow/tensorflow/commit/6a26d679113105820cf83a2447863a6a32488c47#diff-29e6348914dee326daf67d86aa5075db.
Ran the colab (thanks @ravikyram!) with tf-nightly-2.0-preview, and it worked.

Hello Everyone
I am still facing this issue with stable release of tensorflow-2 i.e tf-2.0.0.
Also, I am unable to use "model.summary()" after loading the model. It gives error:
You tried to call count_params on Image_input, but the layer isn't built. You can build it manually via: Image_input.build(batch_input_shape)

@k-w-w Can you reopen this issue?

@Shubham3101 As mentioned by @k-w-w this was already resolved in tf-nightly. Please check the gist here. Thanks!

Thanks @jvishnuvardhan, it is working with tf-nightly-2.1.0 version.


Migrate dependency checker and add support for LTS branches

Description
This PR moves the dependency checker from https://github.com/nodejs/node/tree/main/tools/dep_checker to this repo, and adapts it so that it can run on the v16.x and v14.x branches. The corresponding workflows are added to run the script daily for those branches.
Fixes https://github.com/nodejs/nodejs-dependency-vuln-assessments/issues/58
Details

The script now takes two new parameters: the path for Node's repo, and the checked out branch for that repo
The supported branches are main, v18.x, v16.x and v14.x
The logic for querying vulnerabilities is the same, except that now the dependencies checked are tied to the checked out branch. For example v16.x searches for undici vulns, whereas v14.x does not.

TODO

[ ]  After this branch is merged, remove the dep_checker script from Node's repo (both main and v18.x)

Shouldn't we have a v18x-main.yml too?

Yeah, it's already part of the repo (created by @mhdawson). See here


Changed data to be an NSArray instead of NSMutableArray

Hi!
I was integrating this library in my project. I'm want to initialize the DownPicker with an NSArray.
The picker doesn't modify the data array it's given, so I think it should accept an NSArray instead forcing the caller to initialize it with an NSMutableArray.
Thanks!

Done in 0.1.32

Also added most of your valuable fixes implemented in your fork.


Print Picking List

[Enter feedback here]
The first line of Print a picking list from a sales order states:
" You can print an inventory picking document from a sales order, sales invoice or any other document that initiates shipment of items. "
HOWEVER, there is no Print Picking List from a Sales Invoice. It is a billing document, so the Help is incorrect and misleading.
Thank you.
Tom

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

ID: b2f6f97c-3fad-dbfd-e0d3-54318b7ae8d1
Version Independent ID: 955ac75d-d4e0-6e6c-c7ad-adef1074aba4
Content: How to Print an Inventory Picking List from a Sales Order - Business Central
Content Source: business-central/sales-how-print-picking-list.md
Service: dynamics365-business-central
GitHub Login: @SorenGP
Microsoft Alias: edupont

Hello,
Thank you for your feedback! You're right that you cannot create a picking list from a sales invoice. This will be fixed in the next doc update.

Hello again,
The article has now been updated accordingly.


How can I draw perturbation effect heatmap manuel?

Hi @BinDuan,
I was wondering how can I draw perturbation effect size heatmap manuel? I want to obtain heatmap like default one. Which column of Diff_topic_distri() function's output should be used in drawing heatmap to see perturbation effects on each topic?
Thank you for your help.
Best regards.

@MichaelChuai  and @BinDuan Hi,
First of all, I'd like to thank you for developing such nice tool for Perturb-seq data.
I was wondering how to interpret negative and positive topic distribution values across perturbations. Could you explain this? In addition to that, it would be nice to answer my question titled "How can I draw perturbation effect heatmap manuel?".
Thank you for your interest!


Add variable fee structure

Description
Create fees payable in collateral token or MKT.  Differing rates set for each of these options, and the ability to for us to turn those fees off or on.
Solution

Definition of Done

[ ] ability to pay fees just in MKT
[ ] ability to pay fees just in CollateralToken
[ ] ability to pay no fees
[ ] ability for user to choose between paying the MKT fee or the Collateral Token fee
[ ] ability to withdraw fees

COLLATERAL_TOKEN_FEE_PER_UNIT;
MKT_TOKEN_FEE_PER_UNIT;
IF both zero === no fees charged
IF both non zero === user decides which to pay
IF one zero (other not zero) === fees must be paid in non zero token.


Adding option to specify a connectTimeout duration

Fixes  #57 in conjunction with #58

Hi @sanders41,
Thanks, for the PR! Sorry for the delay I did not think to launch your GA but do not hesitate to ping me if needed.
For the merge, we will wait for @curquiza's return.

No worries, I knew she was out and wasn’t expecting to hear anything before she got back.


default recvWindow value

What do You think?

We can add a default, but I think we should use the value currently defined by Binance Rest API documentation (5000).

Sure if work. I didnt read this.


chore: cleanup initial tooling

When we started this project we hadn't a good idea of how to build it, but I think we have now.
So I propose to delete all those extra things we have now, because they add no real value to the project at this stage (Sorry Rob).
Since we start fresh, I would like to have the project under control and not having extra folders / configuration that does nothing for the time being.
So, no JSPM (we don't need that for a library), no examples folder (we haven't decided what to do with the demos, but is not going to be that at least). The tsconfig is not needed if we merge my new tooling.
So if you don't mind, I prefer to start as clean as possible and I promise that if any of this is needed in 1 month, I will code that again, but for now, it is adds no value.
There is still more tidy up to do, but I will create more PRs for that.

Some editors like Webstorm seems to also rely on tsconfig.js for highlight (when it should only worry about typings) so I am not sure if it is crying for me (in another unrelated project) because I am importing a library without d.ts or not.
If all editors have a different way of working with TS, we are going to have a problem :P

LGTM

I removed some reference things.
@robwormald Could this tsconfig.json be enough for Atom?

Some of the errors are on Angular 2's side from what I remember.

Oh yeah, I am mostly interested to have the tooling working perfectly for non webstorm users. Error fixing comes next.


[BUG]Issue with Zero Optimization for Llama-2-7b Fine-Tuning on Intel GPUs

Describe the bug
I’m experiencing an issue when fine-tuning the Llama-2-7b model from Hugging Face with Zero optimization enabled. I am running on 8 Intel Max 1550 GPUs using the code from the examples provided in Intel Extension for DeepSpeed.
The model loads and runs successfully without Zero optimization, but when I enable Zero optimization (particularly with stage 3), I encounter the following errors:
[rank0]: RuntimeError: could not create an engine
2024:11:05-02:39:09:(678567) |CCL_INFO| finalizing level-zero
2024:11:05-02:39:09:(678567) |CCL_INFO| finalized level-zero
0%| | 0/50 [00:00<?, ?it/s]
2024:11:05-02:39:09:(678572) |CCL_INFO| finalizing level-zero
2024:11:05-02:39:09:(678566) |CCL_INFO| finalizing level-zero
...
[2024-11-05 02:39:10,447] [INFO] [launch.py:319:sigkill_handler] Killing subprocess 678572
**System info **
Model: Llama-2-7b from Hugging Face
GPUs: 8x Intel Max 1550 GPUs
Software:
•	Intel Extension for pytorch
•	DeepSpeed with Zero Optimization (Stage 3)
•	oneCCL for communication backend
Launcher context
cd transformers
deepspeed --num_gpus=8 examples/pytorch/language-modeling/run_clm.py
--deepspeed tests/deepspeed/ds_config_zero3.json
--model_name_or_path meta-llama/Llama-2-7b-hf
--dataset_name wikitext
--dataset_config_name wikitext-2-raw-v1
--dataloader_num_workers 0
--per_device_train_batch_size 1
--warmup_steps 10
--max_steps 50
--bf16
--do_train
--output_dir /tmp/test-clm
--overwrite_output_dir

@delock, can you please help? Thanks!

@molang66 Hi, I reran the cmd that you pasted in this issue and found that no such error appeared. So I think that must be some version mismatch or outdated.
I verify the cmd with following versions:
Ubuntu 22.04.2 LTS
torch 2.3
intel-extension-for-pytorch 2.3.110
oneccl-bind-pt 2.3.0+gpu
(torch/ipex/onecclbindpt wheels can be found at https://pytorch-extension.intel.com/release-whl/stable/xpu/us/)
oneAPI 2024.2.1
GPU Driver 950.13 (rolling stable version)
Can you provide more details about your development environment?  Or you can try using my verified versions :)

@delock, can you please help? Thanks!

Hi @tjruwase, @Liangliang-Ma will followup with this issue.  Thanks!

Thank so much for help. I have updated my CCL version, and now I am encountering this issue：

[rank0]: Traceback (most recent call last):
[rank0]:   File "/work2/09250/molang66/stampede3/transformers/examples/pytorch/language-modeling/run_clm.py", line 657, in
[rank0]:     main()
[rank0]:   File "/work2/09250/molang66/stampede3/transformers/examples/pytorch/language-modeling/run_clm.py", line 605, in main
[rank0]:     train_result = trainer.train(resume_from_checkpoint=checkpoint)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/trainer.py", line 2141, in train
[rank0]:     return inner_training_loop(
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/trainer.py", line 2495, in _inner_training_loop
[rank0]:     tr_loss_step = self.training_step(model, inputs, num_items_in_batch)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/trainer.py", line 3613, in training_step
[rank0]:     loss = self.compute_loss(model, inputs, num_items_in_batch=num_items_in_batch)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/trainer.py", line 3667, in compute_loss
[rank0]:     outputs = model(**inputs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/deepspeed/utils/nvtx.py", line 18, in wrapped_fn
[rank0]:     ret_val = func(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/deepspeed/runtime/engine.py", line 1899, in forward
[rank0]:     loss = self.module(*inputs, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 1199, in forward
[rank0]:     outputs = self.model(
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 926, in forward
[rank0]:     position_embeddings = self.rotary_emb(hidden_states, position_ids)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank0]:     return func(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 160, in forward
[rank0]:     freqs = (inv_freq_expanded.float() @ position_ids_expanded.float()).transpose(1, 2)
[rank0]: RuntimeError: could not create an engine

I was running on  Stampede3 cluster, and my environments are as follows
OS:  centos
conda python = 3.9
intel_extension_for_pytorch   2.3.110+xpu
oneccl-bind-pt                2.3.100+xpu
torch                         2.3.1+cxx11.abi
oneAPI  2024.2.1

GPU driver:
[level_zero:gpu][level_zero:7] Intel(R) Level-Zero, Intel(R) Data Center GPU Max 1550 1.3 [1.3.27642]

Thank so much for help. I have updated my CCL version, and now I am encountering this issue：

[rank0]: Traceback (most recent call last):
[rank0]:   File "/work2/09250/molang66/stampede3/transformers/examples/pytorch/language-modeling/run_clm.py", line 657, in
[rank0]:     main()
[rank0]:   File "/work2/09250/molang66/stampede3/transformers/examples/pytorch/language-modeling/run_clm.py", line 605, in main
[rank0]:     train_result = trainer.train(resume_from_checkpoint=checkpoint)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/trainer.py", line 2141, in train
[rank0]:     return inner_training_loop(
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/trainer.py", line 2495, in _inner_training_loop
[rank0]:     tr_loss_step = self.training_step(model, inputs, num_items_in_batch)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/trainer.py", line 3613, in training_step
[rank0]:     loss = self.compute_loss(model, inputs, num_items_in_batch=num_items_in_batch)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/trainer.py", line 3667, in compute_loss
[rank0]:     outputs = model(**inputs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/deepspeed/utils/nvtx.py", line 18, in wrapped_fn
[rank0]:     ret_val = func(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/deepspeed/runtime/engine.py", line 1899, in forward
[rank0]:     loss = self.module(*inputs, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 1199, in forward
[rank0]:     outputs = self.model(
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 926, in forward
[rank0]:     position_embeddings = self.rotary_emb(hidden_states, position_ids)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank0]:     return func(*args, **kwargs)
[rank0]:   File "/work2/09250/molang66/stampede3/miniconda3/envs/intel_xpu/lib/python3.9/site-packages/transformers/models/llama/modeling_llama.py", line 160, in forward
[rank0]:     freqs = (inv_freq_expanded.float() @ position_ids_expanded.float()).transpose(1, 2)
[rank0]: RuntimeError: could not create an engine

I was running on Stampede3 cluster, and my environments are as follows
OS:  centos
conda python = 3.9
intel_extension_for_pytorch   2.3.110+xpu
oneccl-bind-pt                2.3.100+xpu
torch                         2.3.1+cxx11.abi
oneAPI  2024.2.1

GPU driver: [level_zero:gpu][level_zero:7] Intel(R) Level-Zero, Intel(R) Data Center GPU Max 1550 1.3 [1.3.27642]

Do you have the latest version of deepspeed? I have seen similar issue for outdated deepspeed.

@Liangliang-Ma  My deepspeed version is 0.15.3.  I don't know what the latest version of the drive is

@molang66 I think the gpu driver version is different. Can you try the gpu verison: GPU Driver 950.13 (rolling stable version) and test again?

@Liangliang-Ma  Thank you for your response. I’d like to know which command can check the GPU driver; I didn’t see any indication for the rolling stable version.
Additionally, I tried updating oneAPI to 25.0 and DeepSpeed to 0.15.4, but encountered the following error when compiling FusedAdam:
Using /home1/09250/molang66/.cache/torch_extensions/py39_xpu as PyTorch extensions root...
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/intel_extension_for_pytorch/utils/_logger.py:67: UserWarning: [MissingDependency]
                               !! WARNING !!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Your compiler (/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/icpx 1.9.0) may be ABI-incompatible with PyTorch!
Please use a compiler that is ABI-compatible with GCC 5.0 and above.
See https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html.
See https://gist.github.com/goldsborough/d466f43e8ffc948ff92de7486c5216d6
for instructions on how to install GCC 5 or higher.
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
                              !! WARNING !!

  warnings.warn(msg)
2024-11-14 01:20:59,864 - _logger.py - IPEX - WARNING - [MissingDependency]
                               !! WARNING !!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Your compiler (/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/icpx 1.9.0) may be ABI-incompatible with PyTorch!
Please use a compiler that is ABI-compatible with GCC 5.0 and above.
See https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html.
See https://gist.github.com/goldsborough/d466f43e8ffc948ff92de7486c5216d6
for instructions on how to install GCC 5 or higher.
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
                              !! WARNING !!

Emitting ninja build file /home1/09250/molang66/.cache/torch_extensions/py39_xpu/fused_adam/build.ninja...
Building extension module fused_adam...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
[1/2] /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/icpx -MMD -MF multi_tensor_adam.dp.o.d -DTORCH_EXTENSION_NAME=fused_adam -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1016\" -I/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/includes -I/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam -isystem /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include -isystem /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/torch/csrc/api/include -isystem /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/TH -isystem /scratch/projects/compilers/intel25.0/compiler/2025.0/linux/include -isystem /scratch/projects/compilers/intel25.0/compiler/2025.0/linux/include/sycl -isystem /scratch/projects/compilers/intel25.0/mkl/2025.0/include -isystem /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/intel_extension_for_pytorch/include -isystem /work2/09250/molang66/stampede3/miniconda3/envs/intel/include/python3.9 -D_GLIBCXX_USE_CXX11_ABI=1 -fPIC -std=c++17 -fsycl -fsycl-targets=spir64_gen -g -gdwarf-4 -O3 -std=c++17 -fPIC -DMKL_ILP64 -fno-strict-aliasing -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DVERSION_GE_1_5 -fsycl -c /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp -o multi_tensor_adam.dp.o
FAILED: multi_tensor_adam.dp.o
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/icpx -MMD -MF multi_tensor_adam.dp.o.d -DTORCH_EXTENSION_NAME=fused_adam -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1016\" -I/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/includes -I/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam -isystem /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include -isystem /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/torch/csrc/api/include -isystem /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/TH -isystem /scratch/projects/compilers/intel25.0/compiler/2025.0/linux/include -isystem /scratch/projects/compilers/intel25.0/compiler/2025.0/linux/include/sycl -isystem /scratch/projects/compilers/intel25.0/mkl/2025.0/include -isystem /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/intel_extension_for_pytorch/include -isystem /work2/09250/molang66/stampede3/miniconda3/envs/intel/include/python3.9 -D_GLIBCXX_USE_CXX11_ABI=1 -fPIC -std=c++17 -fsycl -fsycl-targets=spir64_gen -g -gdwarf-4 -O3 -std=c++17 -fPIC -DMKL_ILP64 -fno-strict-aliasing -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DVERSION_GE_1_5 -fsycl -c /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp -o multi_tensor_adam.dp.o
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:18:
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_apply.dp.hpp:192:70: warning: 'constant_buffer' is deprecated: use 'target::device' instead [-Wdeprecated-declarations]
  192 |                                                        sycl::target::constant_buffer>(cgh);
      |                                                                      ^
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/access/access.hpp:24:19: note: 'constant_buffer' has been explicitly marked deprecated here
   24 |   constant_buffer __SYCL2020_DEPRECATED("use 'target::device' instead") = 2015,
      |                   ^
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/detail/defines_elementary.hpp:62:40: note: expanded from macro '__SYCL2020_DEPRECATED'
   62 | #define __SYCL2020_DEPRECATED(message) __SYCL_DEPRECATED(message)
      |                                        ^
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/detail/defines_elementary.hpp:53:38: note: expanded from macro '__SYCL_DEPRECATED'
   53 | #define __SYCL_DEPRECATED(message) [[deprecated(message)]]
      |                                      ^
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:18:
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_apply.dp.hpp:199:17: warning: expression result unused [-Wunused-value]
  199 |                 0;
      |                 ^
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:19:
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/includes/type_shim.h:91:54: warning: 'this_nd_item<3>' is deprecated: use sycl::ext::oneapi::this_work_item::get_nd_item() instead [-Wdeprecated-declarations]
   91 |     auto item_ct1 = sycl::ext::oneapi::experimental::this_nd_item<3>();
      |                                                      ^
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/ext/oneapi/free_function_queries.hpp:50:1: note: 'this_nd_item<3>' has been explicitly marked deprecated here
   50 | __SYCL_DEPRECATED(
      | ^
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/detail/defines_elementary.hpp:53:38: note: expanded from macro '__SYCL_DEPRECATED'
   53 | #define __SYCL_DEPRECATED(message) [[deprecated(message)]]
      |                                      ^
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:45:58: warning: 'this_nd_item<3>' is deprecated: use sycl::ext::oneapi::this_work_item::get_nd_item() instead [-Wdeprecated-declarations]
   45 |         auto item_ct1 = sycl::ext::oneapi::experimental::this_nd_item<3>();
      |                                                          ^
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/ext/oneapi/free_function_queries.hpp:50:1: note: 'this_nd_item<3>' has been explicitly marked deprecated here
   50 | __SYCL_DEPRECATED(
      | ^
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/detail/defines_elementary.hpp:53:38: note: expanded from macro '__SYCL_DEPRECATED'
   53 | #define __SYCL_DEPRECATED(message) [[deprecated(message)]]
      |                                      ^
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:11:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/ATen.h:7:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/Context.h:3:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/CPUGeneratorImpl.h:3:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/core/Generator.h:21:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/GeneratorImpl.h:8:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/TensorImpl.h:11:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/ScalarType.h:7:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_e4m3fnuz.h:136:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_e4m3fnuz-inl.h:4:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_fnuz_cvt.h:4:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/sycl.hpp:25:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/detail/core.hpp:21:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/accessor.hpp:15:
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/buffer.hpp:174:17: error: static assertion failed due to requirement 'is_device_copyable_v<multi_tensor_apply_kernel<TensorListMetadata<4>, AdamFunctor<double>, float, float, float, float, float, float, adamMode_t, float>>': Underlying type of a buffer must be device copyable!
  174 |   static_assert(is_device_copyable_v<T>,
      |                 ^~~~~~~~~~~~~~~~~~~~~~~
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_apply.dp.hpp:187:34: note: in instantiation of template class 'sycl::buffer<multi_tensor_apply_kernel<TensorListMetadata<4>, AdamFunctor<double>, float, float, float, float, float, float, adamMode_t, float>>' requested here
  187 |                     sycl::buffer params(const_cast<const decltype(capture)*>(&capture),
      |                                  ^
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:146:36: note: in instantiation of function template specialization 'multi_tensor_apply<4, AdamFunctor<double>, float, float, float, float, float, float, adamMode_t, float>' requested here
  146 |                                    multi_tensor_apply<4>(BLOCK_SIZE,
      |                                    ^
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:18:
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_apply.dp.hpp:199:17: warning: expression result unused [-Wunused-value]
  199 |                 0;
      |                 ^
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:146:36: note: in instantiation of function template specialization 'multi_tensor_apply<4, AdamFunctor<double>, float, float, float, float, float, float, adamMode_t, float>' requested here
  146 |                                    multi_tensor_apply<4>(BLOCK_SIZE,
      |                                    ^
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:11:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/ATen.h:7:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/Context.h:3:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/CPUGeneratorImpl.h:3:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/core/Generator.h:21:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/GeneratorImpl.h:8:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/TensorImpl.h:11:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/ScalarType.h:7:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_e4m3fnuz.h:136:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_e4m3fnuz-inl.h:4:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_fnuz_cvt.h:4:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/sycl.hpp:25:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/detail/core.hpp:21:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/accessor.hpp:15:
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/buffer.hpp:174:17: error: static assertion failed due to requirement 'is_device_copyable_v<multi_tensor_apply_kernel<TensorListMetadata<4>, AdamFunctor<float>, float, float, float, float, float, float, adamMode_t, float>>': Underlying type of a buffer must be device copyable!
  174 |   static_assert(is_device_copyable_v<T>,
      |                 ^~~~~~~~~~~~~~~~~~~~~~~
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_apply.dp.hpp:187:34: note: in instantiation of template class 'sycl::buffer<multi_tensor_apply_kernel<TensorListMetadata<4>, AdamFunctor<float>, float, float, float, float, float, float, adamMode_t, float>>' requested here
  187 |                     sycl::buffer params(const_cast<const decltype(capture)*>(&capture),
      |                                  ^
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:146:36: note: in instantiation of function template specialization 'multi_tensor_apply<4, AdamFunctor<float>, float, float, float, float, float, float, adamMode_t, float>' requested here
  146 |                                    multi_tensor_apply<4>(BLOCK_SIZE,
      |                                    ^
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:18:
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_apply.dp.hpp:199:17: warning: expression result unused [-Wunused-value]
  199 |                 0;
      |                 ^
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:146:36: note: in instantiation of function template specialization 'multi_tensor_apply<4, AdamFunctor<float>, float, float, float, float, float, float, adamMode_t, float>' requested here
  146 |                                    multi_tensor_apply<4>(BLOCK_SIZE,
      |                                    ^
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:11:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/ATen.h:7:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/Context.h:3:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/CPUGeneratorImpl.h:3:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/core/Generator.h:21:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/GeneratorImpl.h:8:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/TensorImpl.h:11:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/ScalarType.h:7:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_e4m3fnuz.h:136:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_e4m3fnuz-inl.h:4:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_fnuz_cvt.h:4:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/sycl.hpp:25:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/detail/core.hpp:21:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/accessor.hpp:15:
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/buffer.hpp:174:17: error: static assertion failed due to requirement 'is_device_copyable_v<multi_tensor_apply_kernel<TensorListMetadata<4>, AdamFunctor<c10::Half>, float, float, float, float, float, float, adamMode_t, float>>': Underlying type of a buffer must be device copyable!
  174 |   static_assert(is_device_copyable_v<T>,
      |                 ^~~~~~~~~~~~~~~~~~~~~~~
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_apply.dp.hpp:187:34: note: in instantiation of template class 'sycl::buffer<multi_tensor_apply_kernel<TensorListMetadata<4>, AdamFunctor<c10::Half>, float, float, float, float, float, float, adamMode_t, float>>' requested here
  187 |                     sycl::buffer params(const_cast<const decltype(capture)*>(&capture),
      |                                  ^
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:146:36: note: in instantiation of function template specialization 'multi_tensor_apply<4, AdamFunctor<c10::Half>, float, float, float, float, float, float, adamMode_t, float>' requested here
  146 |                                    multi_tensor_apply<4>(BLOCK_SIZE,
      |                                    ^
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:18:
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_apply.dp.hpp:199:17: warning: expression result unused [-Wunused-value]
  199 |                 0;
      |                 ^
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:146:36: note: in instantiation of function template specialization 'multi_tensor_apply<4, AdamFunctor<c10::Half>, float, float, float, float, float, float, adamMode_t, float>' requested here
  146 |                                    multi_tensor_apply<4>(BLOCK_SIZE,
      |                                    ^
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:11:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/ATen.h:7:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/Context.h:3:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/CPUGeneratorImpl.h:3:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/ATen/core/Generator.h:21:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/GeneratorImpl.h:8:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/TensorImpl.h:11:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/core/ScalarType.h:7:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_e4m3fnuz.h:136:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_e4m3fnuz-inl.h:4:
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/torch/include/c10/util/Float8_fnuz_cvt.h:4:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/sycl.hpp:25:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/detail/core.hpp:21:
In file included from /scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/accessor.hpp:15:
/scratch/projects/compilers/intel25.0/compiler/2025.0/bin/compiler/../../include/sycl/buffer.hpp:174:17: error: static assertion failed due to requirement 'is_device_copyable_v<multi_tensor_apply_kernel<TensorListMetadata<4>, AdamFunctor<c10::BFloat16>, float, float, float, float, float, float, adamMode_t, float>>': Underlying type of a buffer must be device copyable!
  174 |   static_assert(is_device_copyable_v<T>,
      |                 ^~~~~~~~~~~~~~~~~~~~~~~
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_apply.dp.hpp:187:34: note: in instantiation of template class 'sycl::buffer<multi_tensor_apply_kernel<TensorListMetadata<4>, AdamFunctor<c10::BFloat16>, float, float, float, float, float, float, adamMode_t, float>>' requested here
  187 |                     sycl::buffer params(const_cast<const decltype(capture)*>(&capture),
      |                                  ^
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:146:36: note: in instantiation of function template specialization 'multi_tensor_apply<4, AdamFunctor<c10::BFloat16>, float, float, float, float, float, float, adamMode_t, float>' requested here
  146 |                                    multi_tensor_apply<4>(BLOCK_SIZE,
      |                                    ^
In file included from /work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:18:
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_apply.dp.hpp:199:17: warning: expression result unused [-Wunused-value]
  199 |                 0;
      |                 ^
/work2/09250/molang66/stampede3/miniconda3/envs/intel/lib/python3.9/site-packages/deepspeed/ops/csrc/xpu/adam/multi_tensor_adam.dp.cpp:146:36: note: in instantiation of function template specialization 'multi_tensor_apply<4, AdamFunctor<c10::BFloat16>, float, float, float, float, float, float, adamMode_t, float>' requested here
  146 |                                    multi_tensor_apply<4>(BLOCK_SIZE,
      |                                    ^
8 warnings and 4 errors generated.
ninja: build stopped: subcommand failed.

Is this normal? Compilation worked fine with version 24.2.1.

@molang66  You can check with dpkg -l | grep -P "intel|level-zero|libigc|libigd|libigf|opencl" to see installed components. And we suggest you keep using oneAPI 2024.2.1 with ipex2.3.110 because it currently matching each other for usage.