[Feature Request] [Question] Dialog Component - How to disable close modal when click outside

Existing Component
Yes
Component Name
Dialog
Description
Dialog Component - How to disable close modal when click outside? (like propertie: allowOutsideClick of sweetalert2)

found this attribute: close-on-click-modal
Thanks.


Set spanId in TracingResponderRSocketProxy

also respect traceIdHigh and debug flag in TracingMetadata

Thanks, great work as usual @making !


In version 1.1.0 all types have become private

Quote, YahooError, etc and others have become private, making impossible to use them in fn dеfinitions
pub fn test(a: &yahoo_finance_api::quotes::YResponse) {}
    |                                      ^^^^^^ private module

Oh yes, thanks for the hint, fill fix that soon.

Just pushed/published and update

confirming, this is fixed in 1.1.3
thank you!


Hopefully fixing documentation generation.

This will hopefully prevent issues like #411 , #360 , and #268 in the future by automatically running a re-build on the style guide before deploying to GitHub pages.

Hey @AaronCoplan are you around to fix up the conflict so I can merge this?


OOM Issue

Hi! I am running evaluations but keep getting OOM errors.  I have already decreased the gpu_memory_utilization and max_model_len, but the problem persists. I have tried Llama3-8b with the same hyperparameters and everything was just fine. Can anyone please tell me why this happens and how I can solve it? Thanks!

https://github.com/EleutherAI/lm-evaluation-harness/issues/1894 check this one too

not sure why but my vram usage does not seem to imply that gpu_memory_utilization is being respected - i also have issues running a 7B model on an A40 (40GB vram) despite having no issues in using the HF backend (~28gb vram utilized there). specifically: it OOMs even before running any requests. Have verified that there is nothing else running on the GPU.
However, passing enforce_eager=True in model_args into the vllm backend fixes this issue for me by preventing cuda graphs being built.

@johnwee1 when you pass enforce_eager=True to vllm, does it seem then like gpu_memory_utilization is being respected?

@johnwee1 confirmed on Discord that when using enforce_eager=True, vllm seems to respect the gpu_memory_utilization value. Am intending to create an FAQ docs page, and will include this fact when I do


vectored environments

Hi,
Does this work with vectorized environments (such as using gym.vector.AsyncVectorEnv function)?
Best,
Raymond

Not out of the box since DQN and variants expect a single stream of experience. One could get something working reasonably quickly by adapting TransitionAccumulator so it accepts a batch of time steps.

Awesome, thanks @jqdm !


Add support for Optical Duplicate tracking to MarkDuplicatesDataflow

Reverts broadinstitute/hellbender#748

Sorry about all the back and forth! This should be ready for review. @akiezun

Since we never actually look to see if something IS an optical duplicate and only care about the total number, we could just output a single annotation on one read in the best read pair with the number of optical duplicates found for that set of reads.  It would make the code simpler but maybe not make as much sense logically?

@tovanadler Review complete.  Looks good, just a few comments.
I have a few comments about the organization of duplicate marking.  I think you've inherited some very old style code that could maybe use some refactoring.
I think we do need to also include the histogram and the metrics headers.  Those could be done in a separate ticket though.
I'm a bit worried that the test is indeterministic.  Unless I overlooked something which is likely, it seems like it might depend on the ordering of a PCollection which is undefined.  This isn't problematic for the actual metric file, but might be for the tests.
What do you think about reorganizing to output an annotation on only 1 of the "best" reads with the count of all optical duplicates in it's group.  That would simplify the code, and since we only care about the global count it wouldn't change the information content.

Thanks for the review.
Regarding the code complexity, I definitely agree. I was trying to not do too much code surgery. For your suggestion regarding just outputting the total, perhaps if I name it something like total optical duplicates? The issue is that you could have two optical duplicate clusters, but I guess we don't really care, right? We just need the total?
Also, I can rewrite the test to load the information in as a map and then just make sure the sizes are the same and query the map. Would that be better?

I just commited some changes based on your comments and also fixed the tests. Can you see them as part of this PR or should I make a separate PR? I am waiting to rebase until we agree on everything in this CL.

OK, things have become sufficiently complicated here with my revert branches and my difference from master that I am just going to rebase everything now. I will probably have to send you a new PR with the updated changes, if that is ok.

Rebasing sooner rather than later is a good idea.  Easiest thing to do is to make a copy of your branch and do the rebase in that which seems like what you're planning.  When you're sure it's gone right you can always --reset the old branch to the new branch and just update the existing pull request.


Creating About page

creating the About page which gives the user an infomation about feature that the website provide and also the future insight.
Mission: A brief description of what our website aims to achieve.
Key Features: A summary of the main functionalities we offer.
User Benefits: How our platform helps and supports users.
Technologies: Highlighting the technology stack we use.
Security & Privacy: Information on how we ensure user data is safe.
Future Insights: A glimpse of upcoming features and plans for the platform.

@Hh440 This section is great.. from where did you got this design ?

@muruga21 please assign so that i can start working on it

@Hh440 yeah


Fix: subprocess excution error

Removed some test as scrapping is testing in another test.

Fix build issues before requesting review

vale is not complaining, so i will initiate the release.


Fix the website link to the GitHub Repo

reactjstraining organization does not exist, updated link to reference repository in reactjs org.

Actually, we just got moved to ReactTraining. Can you switch it to that?

Looks like the Readme has been rejiggered anyways. Thanks for the PR nonetheless!

Just out of curiosity, why did you transfer the project from @reactjs to @reacttraining? :smiley:

@mjackson and @ryanflorence use the React Training business to support the development of React Router (and other projects), so it makes sense to have it contained in the related org. It gives some more visibility to their business which in turn feeds back into their ability to work on the project.

Oh, it's ok :) Thanks for the answer :)

No worries, thanks!


Flat map array

This PR adds the possibility to skip the invalid elements in array and just keep those, that were valid.

Codecov Report

Merging #17 into master will increase coverage by 0.03%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master      #17      +/-   ##
==========================================
+ Coverage   99.62%   99.65%   +0.03%
==========================================
  Files          10       10
  Lines         266      294      +28
==========================================
+ Hits          265      293      +28
  Misses          1        1

Impacted Files
Coverage Δ

SwiftyJSONModelTests/JSONObjectTests.swift
100% <100%> (ø)
:white_check_mark:

SwiftyJSONModel/JSONObject.swift
98.61% <100%> (+0.33%)
:white_check_mark:

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DB import cmd seems to be missing from cli

What happened:
Attempted to run xeol db import
What you expected to happen:
It to be imported based on the readme https://github.com/xeol-io/xeol#:~:text=xeol db import — provide xeol with a database archive to explicitly use (useful for offline DB updates)
How to reproduce it (as minimally and precisely as possible):
xeol db import
Anything else we need to know?:
Environment:

Output of xeol version:  0.5.0
OS (e.g: cat /etc/os-release or similar): macos/alpine

Hi, thanks for reporting this! I just added a db import command in #99.
Going to release a new minor version shortly.

Well that was amazingly fast! Much appreciated 🎉

No problem! Happy to please!
This will be available in v0.6.0, should be available in about 30 mins once CI tasks finish.


[BZ#1272363] added more tests for this bug fix

@Rikkola Could you please take a look at this.

+1
Just as a note. The ProjectScreenPresenter is getting bloated, it is over 1000 lines long. This change actually reduces the amount of lines. The next change on this area (who ever does the work, this is not targeted at @jomarko ) should take the build functionality from ProjectScreenPresenter and make a new class for it.

Thanks, @jomarko!
msater: eb8586bf5140cfae0d671249a77c34c610da51c8


Support for NestJS v10

Updated the packages to NestJS v10.
All tests passed.
Sample app still works.
There are deprecation warnings for all methods from the MetadataScanner used in your TaskExplorerService but I did not find any instructions with what it should be replaced.

@madeindjs Merge would be appretiated 🙏🏼

Fixed it. Thank you for checking

@NikoHadouken , I published it on NPM (here). Thanks for your contribution


Pivot missing

Pivot tables

Housekeeping: I was looking around to see which issues to fix before the next release and exploring how to tag them, when I noticed the milestones and this bug here. Would you be ok with renaming the milestone to something more reasonable, like 8.0 ?

Would it be easier to at least implement that pivot tables are supported via the reader and writer (without creating/altering pivots via ABAP)? E.g. if I have an Excel with a pivot table and I use the reader to read an Excel file and immediatly want to write it back via the writer to another file (and the pivot table "survives" the read and write back via abap2xlx)?
Maybe this sounds weird, but via Excel I can create a pivot table based on an empty cell range and can set the option to update a pivot table everytime when the excel file is opened. If at least the pivot table wouldn't "break" by reading and writing (via abap2xlx) I could use an empty template excel file which contains the pivot table (based on a specific cell range) and could fill this cell ranges (the basis for the pivot table) via abap2xlsx (so reading an empty template excel file, adding data to a cell range and produce an excel file which has a pivot table based on data of an internal table which was added by abap2xlsx)

For now, pivot tables are not implemented at all. We need volunteers to code the feature, could you propose a pull request, e.g. a preview of the solution you propose, to support a discussion?


Fixup ecw5410

This fixes ath10k-ct driver/firmware issues on ECW5410-L EU variant.  Root cause was setting regdom to US on this platform causes the radios/firmware to hang hard.  This update no longer sets regdom to anything in fwcfg, leaving system at platform defaults.  Users can override using fwcfg as needed on their platforms of choice.  Tx-buffers are increased from 2200 to 2400 since some extra RAM was available in the firmware.  This should improve throughput with many (100+) stations associated because the firmware can build bigger AMPDUs for the various peers.  This update brings in latest ath10k-ct firmware too.

hmkay, lets try and work on those git rebase skills the tree/PR is pretty dirty/tainted :-) manually pulled the 2 commits.
merged into pending, Thanks !


Added a comment explaining a failing condition

Incorrect base for the feature branch

Used an incorrect base to the feature branch. Closing and creating another PR


Consistent tag format?

It's a super-minor point but could you be consistent with your tags and decide on V or v as a prefix?

Hi Alan,
Are you referring to consistency between buildah commands?
Can you give a specific example?

@Ace-Tang yes please to a specific example and thanks for raising the issue!

Sorry, yes. I was referring to the fact that version 1.0 has the tag V1.0 (upper-case) but all the previous tags were v0.8 (lower-case) but it really isn't that important.
It's a really, really, really minor point - and I'm just curious - but it tripped-up some automation code I'd written that checks out releases based on the number and it assumed you'd continue using lower-case "v". It's my fault - I shouldn't make assumptions. From now on I'll track using the entire tag string but just wondered (in my own sad little world) why it was inconsistent.
Loving buildah BTW.

@alanbchristie, sorry still not quite on the same page. Are you talking about a container tag? The output of buildah version looks unchanged.
Can you provide the code block that broke? might give me the insight I need 😄

@alanbchristie Sorry about that, I will see about changing it to lower case.


Keep track of the current descriptor set, index buffer, and vertex buffers in the sync layer

With Vulkan you can do for example: vkCmdBeginRenderPass, vkCmdBindIndexBuffer, vkCmdEndRenderPass, vkCmdFillBuffer, vkCmdBeginRenderPass, vkCmdDrawIndexed, vkCmdEndRenderPass.
Assuming that the buffer of vkCmdFillBuffer is the same as the one of vkCmdBindIndexBuffer, vulkano isn't able to understand that the index buffer is going to be used by vkCmdDrawIndexed and will not insert a pipeline barrier. Instead it will add a barrier between vkCmdBindIndexBuffer and vkCmdFillBuffer, which is useless.

Done in #685 #581 #687
Will merge when #687 is tested.

https://github.com/vulkano-rs/vulkano/pull/687 was merged.


report_destination before sleeping

Make sure you are using the latest version: run youtube-dl --version and ensure your version is 2018.08.22. If it's not, read this FAQ entry and update. Issues with outdated version will be rejected.

[x] I've verified and I assure that I'm running youtube-dl 2018.08.22

Before submitting an issue make sure you have:

[x] At least skimmed through the README, most notably the FAQ and BUGS sections
[x] Searched the bugtracker for similar issues including closed ones
[x] Checked that provided video/audio/playlist URLs (if any) are alive and playable in a browser

What is the purpose of your issue?

[ ] Bug report (encountered problems with youtube-dl)
[ ] Site support request (request for adding support for a new site)
[x] Feature request (request for a new functionality)
[ ] Question
[ ] Other

Description of your issue, suggested solution and other information
This is minor enhancement request when downloading playlist videos with sleep between 2 downloads, using --sleep-interval / --max-sleep-interval
youtube-dl first sleeps and then prints the name of the file (which is more or less title of the video)
[download] Sleeping 11.85 seconds...
[download] Destination: some_title.webm
Sometimes sleeps are more than 30-45 seconds and I have to wait to find out which video its going to download next.
I request to rearrange this a bit ... first print the filename and then sleep.
[download] Destination: some_title.webm
[download] Sleeping 11.85 seconds...
This can be achieved by calling self.report_destination(filename) inside download() function of common.py.. i.e. just before sleep call which happens just before real_download() function call.
This will also eliminate report_destination(filename) lines located inside many "downloaders". And instead bring it to one single place. (common.py)
I can create a PR if developer wants.

No such change will be accepted since downloaders may output arbitrary messages (like [hlsnative] Downloading m3u8 manifest) before actual writing to file (that is [download] Destination: stands for) so that this will break logical flow.

Ok how about adding this line:

Ok how about changing output slightly from
[download] Sleeping 11.85 seconds...
to
[download] Sleeping 11.85 seconds for  ...

 If you want to get title before downloading then you have to separate info extraction and actual downloading or even handle downloading on your own.

But info_dict and filename are already available at that stage. There is no need to change anything. I am just requesting to be more verbose. In any case, thank you for your prompt replies.

Then use it. I've already pointed out how you should do that. And again: I'm not going to do any verbosity changes just to fit your concrete case. You want "sleeping X seconds for filename", someone may want to have "sleeping Y seconds for filesize video", someone may already rely on current wording. This output is not supposed to be used as source of metadata. For metadata you have info dict that you must use.


Polish translation

Hi guys, I've previously translated the Ergo website to Polish, now I'd be happy to translate the SigmaUSD one. I'm a professional translator with ~20 years of experience (specialisations: IT, gaming, marketing, crypto).

https://drive.google.com/drive/folders/1N4px3ja45tF0q38W0Lh5kkT4SyCIcgVl?usp=sharing

The text in the question mark bubble of SigUSD and SigRSV Aktualna cena is outside the text box. Also missing purchaseButton text on both StableCoin and ReserveCoin pages. Finally needs text for viewSigmaUSDV1Text on all three pages.

Thanks for letting me know. Updated the translation.json file on the google drive.


Add CONTRIBUTING.md

https://github.com/jwplayer/buildpipe-buildkite-plugin/pull/66#pullrequestreview-479726648
https://github.com/jwplayer/buildpipe-buildkite-plugin/commit/531dff0702893b93adb76d30ddc42f8323d26983
https://github.com/jwplayer/buildpipe-buildkite-plugin/pull/66.patch

add-contributing


App launch delay on drag and drop to app/dock icon

The app launches slower than usual when opened by drag and drop to the app/dock icon.

Lastest version (updated 9/27) fixes this issue for me. Droplet launches are as fast as normal launches.
I used the date of the Github update as the version and build number do not appear to have been updated.

I spoke too soon. Initially, it was very fast to launch. After a few tests, droplet drag and drop has a noticeable delay again.
I can't find anything obvious. I've tried different folders, but the delay on launch remains.
Quit the app and restarted. Droplet delay remains.
Subsequent folder drags to the icon with app open are instantaneous.

Does to be solved in version 2.5.


Deleted commented code and unused files

Codecov Report

Merging #88 (556902a) into main (c5e4d7b) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##             main      #88   +/-   ##
=======================================
  Coverage   85.36%   85.36%
=======================================
  Files           8        8
  Lines         123      123
  Branches        5        5
=======================================
  Hits          105      105
  Misses         18       18

Impacted Files
Coverage Δ

backend/app.js
86.95% <ø> (ø)

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Operations to_candid and from_candid as surface syntax.

Provide to_candid and from_candid operations in Motoko, for converting to and from Candid encoded Blobs.
Related to https://github.com/dfinity/motoko/pull/1754, which focuses on the IR and backend parts of this feature.
Redoes parts of https://github.com/dfinity/motoko/pull/1652, which did something very similar.
However there are a couple of subtle differences from the existing and past attempts:

to_candid uses the type inference to infer the types of its literal tuple arguments.  So, it often requires no explicit type annotations (unlike current serialization prim).
from_candid also using bidirectional typing to avoid annotations.  But it only works in type checking contexts (not type synthesizing ones), and always produces a tuple that matches the expected type of the context around the Blob to be deserialized.  It's an error to provide a non-shared, (or non-?) context for checking from_candid.
from_candid should produce null for any errors, and otherwise produce an optional result on success.  The current prim traps (not recoverable), and does not wrap with an optional ? constructor.

Steps to do

[x] typing.  See @nomeata's PR that did this.
[x] use existing codegen for SerializePrim to codegen for to_candid.
[x] use existing codegen for DeserializePrim to codegen for from_candid, wrapping with an option, but still trapping on failure.
Future PR: adapt existing codegen Serialization.deserialize_from_blob, so that it produces an option, and does not trap on failure.

Hmm.  While it seems like the literal tuple syntax is fine for to_candid (since it is new syntax that we are defining), I still cannot seem to get the existing parsing and typing rules for serialize to work now, since they had expected to take a single value in terms of their typing and syntax.  Trying to adjust them is more challenging than I originally thought.
One problem is that we parse tuples and them forget them as tuples if they have a single member.  That's one headache, and I think that there are more too.

@matthewhammer we should get together and nail this next week - I was distracted by my own PR and reviewing some code for @ggreif. Sorry for the lack of attention.

@crusso @ggreif I'm back from PTO as of today.  Looking at this PR again now.  Happy to meet soon.

@crusso @matthewhammer  I know the team has a million different priorities, but I just wanted to follow up regarding a conservative estimate of this feature so that I can plan my own project roadmap around its expect delivery.
I'm dynamically spinning up canisters, and would love to have this feature so that I can use a record for a constructor some of my auto-scaling canister actors. Here's what one of those canisters looks like.
shared ({ caller = owner }) actor class UserCanister({
  pk: Text;
  owners: ?[Principal];
}) {

The issue is that I would like to dynamically upgrade my canisters through my indexing canister meaning that I need the record -> Blob or [Nat8]conversion for theargparameter of theinstall_code` method.
install_code : shared {
      mode : { #install; #reinstall; #upgrade};
      canister_id : Principal;
      wasm_module : [Nat8];
      arg : [Nat8];
    } -> async ();

Since there does not yet exist a record -> Blob or [Nat8]` conversion to do so, I am either forced to do my canister upgrades purely through the frontend with JavaScript targeting the individual canisters directly, or to simplify my existing canister constructors to take just a single argument which can be converted to Blob.

@crusso @matthewhammer I know the team has a million different priorities, but I just wanted to follow up regarding a conservative estimate of this feature so that I can plan my own project roadmap around its expect delivery.

We are hoping to release this within the next or maybe subsequent release (so weeks, not months). Maybe by the end of the week if you care comfortable installing the compiler yourself (rather than waiting for dfx to include it in a release).

I'm dynamically spinning up canisters, and would love to have this feature so that I can use a record for a constructor some of my auto-scaling canister actors. Here's what one of those canisters looks like.
shared ({ caller = owner }) actor class UserCanister({
  pk: Text;
  owners: ?[Principal];
}) {

The issue is that I would like to dynamically upgrade my canisters through my indexing canister meaning that I need the record -> Blob/[Nat8] conversion for the arg parameter of the install_code method.
install_code : shared {
      mode : { #install; #reinstall; #upgrade};
      canister_id : Principal;
      wasm_module : [Nat8];
      arg : [Nat8];
    } -> async ();

Since there does not yet exist a record -> Blob or [Nat8]` conversion to do so, I am either forced to do my canister upgrades purely through the frontend with JavaScript targeting the individual canisters directly, or to simplify my existing canister constructors to take just a single argument which can be converted to Blob.

You don't actually need to wait for this surface syntax to land and could access some of it already by jumping through some undocumented hoops (or work around it more safely by abusing ExperimentalInternetComputer at some expense). I'd be happy to share instructions privately by email (or you can actually figure it out from the revised tests in this PR).
Note that there is a restriction that you need to know the (non-generic) static type of the thing that you want to serialize, but it sounds like that may be the case in your application. Is the record type fixed at compile time?
BTW, I'd use Blob. not [Nat8] for the wasm blob and argument blob. A Blob is much more compact (every Nat8 takes 4 bytes in our current representation).

@crusso @matthewhammer I know the team has a million different priorities, but I just wanted to follow up regarding a conservative estimate of this feature so that I can plan my own project roadmap around its expect delivery.
I'm dynamically spinning up canisters, and would love to have this feature so that I can use a record for a constructor some of my auto-scaling canister actors. Here's what one of those canisters looks like.
shared ({ caller = owner }) actor class UserCanister({
  pk: Text;
  owners: ?[Principal];
}) {

The issue is that I would like to dynamically upgrade my canisters through my indexing canister meaning that I need the record -> Blob/[Nat8] conversion for the arg parameter of the install_code method.
install_code : shared {
      mode : { #install; #reinstall; #upgrade};
      canister_id : Principal;
      wasm_module : [Nat8];
      arg : [Nat8];
    } -> async ();

Since there does not yet exist a record -> Blob or [Nat8]` conversion to do so, I am either forced to do my canister upgrades purely through the frontend with JavaScript targeting the individual canisters directly, or to simplify my existing canister constructors to take just a single argument which can be converted to Blob.

@crusso Thanks for offering the experimental featureset & "undocumented" approach, but I'm building a developer tool so I'm looking to expose this functionality to end users. Therefore, it's probably best that I wait until this feature is released.

We are hoping to release this within the next or maybe subsequent release (so weeks, not months).

Ideally I'd like to push this out during the hackathon (early June), but the clarity is nice so I can plan between building a demo and additional features myself vs. actually releasing a pre-alpha version for developers to play with during the hackathon. Regardless, happy that this is on the order of a month away from being released 👍

Note that there is a restriction that you need to know the (non-generic) static type of the thing that you want to serialize, but it sounds like that may be the case in your application. Is the record type fixed at compile time?

Yes, the use case is for the developer to define a static record type as the parameters passed to the constructor of a canister actor. This type could be modified through upgrades over time, but is fixed at compile time.

A Blob is much more compact (every Nat8 takes 4 bytes in our current representation).
Thanks for the tip - will make these changes!

@matthewhammer feel free to merge #3232 into this branch if it helps you make more progress.

@Matthew, I addressed my own comment by restoring idl.mo and adding idl-ops.mo. Let's merge.


Cannot connect to Bigtable API with service account -SSLHandshakeException

I am trying to run the java/hello-world sample as a standalone application into a local environement.
I created a Service Account, saved the key file and passed it as an GOOGLE_APPLICATION_CREDENTIALS environment variable, as described here: https://cloud.google.com/docs/authentication/production#providing_credentials_to_your_application.
However, my SSL handshake fails and the sample cannot connect to the Bigtable instance in my project.
The stacktrace bellow.
I am  stuck. The sample works well when deployed in the Google node itself.
Thank you!
oct. 12, 2017 4:33:03 PM com.google.api.client.http.HttpRequest execute
AVERTISSEMENT: exception thrown while executing request
javax.net.ssl.SSLHandshakeException: Received fatal alert: access_denied
at sun.security.ssl.Alerts.getSSLException(Alerts.java:192)
at sun.security.ssl.Alerts.getSSLException(Alerts.java:154)
at sun.security.ssl.SSLSocketImpl.recvAlert(SSLSocketImpl.java:2023)
at sun.security.ssl.SSLSocketImpl.readRecord(SSLSocketImpl.java:1125)
at sun.security.ssl.SSLSocketImpl.performInitialHandshake(SSLSocketImpl.java:1375)
at sun.security.ssl.SSLSocketImpl.startHandshake(SSLSocketImpl.java:1403)
at sun.security.ssl.SSLSocketImpl.startHandshake(SSLSocketImpl.java:1387)
at sun.net.www.protocol.https.HttpsClient.afterConnect(HttpsClient.java:559)
at sun.net.www.protocol.https.AbstractDelegateHttpsURLConnection.connect(AbstractDelegateHttpsURLConnection.java:185)
at sun.net.www.protocol.http.HttpURLConnection.getOutputStream0(HttpURLConnection.java:1316)
at sun.net.www.protocol.http.HttpURLConnection.getOutputStream(HttpURLConnection.java:1291)
at sun.net.www.protocol.https.HttpsURLConnectionImpl.getOutputStream(HttpsURLConnectionImpl.java:250)
at com.google.api.client.http.javanet.NetHttpRequest.execute(NetHttpRequest.java:77)
at com.google.api.client.http.HttpRequest.execute(HttpRequest.java:981)
at com.google.auth.oauth2.ServiceAccountCredentials.refreshAccessToken(ServiceAccountCredentials.java:365)
at com.google.cloud.bigtable.grpc.io.RefreshingOAuth2CredentialsInterceptor.refreshCredentials(RefreshingOAuth2CredentialsInterceptor.java:379)
at com.google.cloud.bigtable.grpc.io.RefreshingOAuth2CredentialsInterceptor.access$100(RefreshingOAuth2CredentialsInterceptor.java:60)
at com.google.cloud.bigtable.grpc.io.RefreshingOAuth2CredentialsInterceptor$2.call(RefreshingOAuth2CredentialsInterceptor.java:328)
at com.google.cloud.bigtable.grpc.io.RefreshingOAuth2CredentialsInterceptor$2.call(RefreshingOAuth2CredentialsInterceptor.java:325)

This was a proxy/firewall problem.
If behind a proxy/firewall, try to go through another network to test the functioning.


Implement RemoveSecurities for Coarse and Fine Universes

Current Behaviour
Currently Lean only allows to remove securities from a User-Defined Universe
Requested Behavior
Allow to use RemoveSecurities also for Coarse and Fine Universes.
A Few Use Cases

At the moment, simple Long/Short strategies that use Coarse/Fine Universe can only be built in two ways:

Performing all the needed calculations within the Universe module to select securities to go Long and securities to go Short. Then, once this Universe is created, the same calculations need to be performed again within the Alpha module in order to know which securities were Longs and which ones were Shorts. This process is not elegant and slow. However, it allows for a much more thorough screening of securities than scenario 2 below as you could perform the calculations in Universe across hundreds of securities and then repeat them in Alpha for just the few securities you have already decided to trade.

A potential solution to this scenario would be the ability to tag the securities as Long/Short (or any other tags) in Universe in order for the Alpha to know what to do with them.

Performing a basic preliminary selection in Universe based on price, volume and fundamentals and keep a few hundred of assets. This Universe will then be sent to Alpha for calculations to select the few Longs and Shorts. This process looks more elegant as the calculations are only performed once, however the algorithm would be really slow and inefficient since most of the securities in the Universe won't be traded and therefore useless to stay in the Universe. Actually, with normal capacity, the maximum number of assets that could be in Universe with minute data would be around 100 and that with risk of crashing already.

I believe the second scenario makes a more general case, and that simply being able to get rid of the useless securities from the Universe (once the decision of trading has been made) would fix the issue.

Any strategies that need intraday data to make the trading decision. For example, selecting securities based on price, volume and fundamentals within Universe that could be interesting for the day. Then, waiting for the market open to make the final decision on which of those securities to trade based on behavior during the trading session. This is a similar issue to the second scenario mentioned above, in which only a few assets are traded and the remaining stay in Universe slowing down the algorithm and potentially causing a crash.

The solution would be again to remove those remaining securities from Universe.
Checklist

[x] I have completely filled out this template
[x] I have confirmed that this issue exists on the current master branch
[x] I have confirmed that this is not a duplicate issue by searching [issues]

We're planning on a way to add any generic data to the security object; e.g. an indicator; or pair trading data; and then allowing access to that anywhere in QCA. This would solve many use cases.

Second issue of performance; agreed - ideally we will address this by pushing new selection criteria on demand: universe.ProcessSelection( symbol[] ).

In addition; adjust RemoveSecurity() to remove from all universes


[Suggestion]To supporting WE_CUI Forge edition

Hi~This is not a bug, may I suggest to making GP support WE-CUI ForgeEdition? liteLoader edition was quite stable until the VanilliaFix mod has to added to the client side. there is a conflict between two mod, then I could found CUI ForgeEdition was not supported by GP.
I means if there were similar interface, Will GP support that in the future?

No, there will be no support for the forge edition as it is the "unofficial" version and a complete hack. If you have an issue with the liteloader version then create a ticket as that is how you get issues resolved.
https://github.com/Mumfrey/WorldEditCUI/issues


[tor] if run with "tor.v3" option, then "lnd must only be listening on localhost when running with Tor inbound support enabled"

Background
I got the following error when starting LND with tor service activated for the first time :
Attempting automatic RPC configuration to bitcoind
Automatically obtained bitcoind's RPC credentials
2018-10-11 15:55:13.562 [INF] LTND: Shutdown complete
lnd must *only* be listening on localhost when running with Tor inbound support enabled

I have already been running bitcoind with tor for some times without issues.
I think I'm getting something wrong with either LND or tor configuration, but can't tell what.
Your environment

lnd version 0.5.0-beta commit=25145acc46cc5d18e4e348eed097300b1391d2a7
Linux Celeri 4.15.0-36-generic #39-Ubuntu SMP Mon Sep 24 16:19:09 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux
Bitcoin Core Daemon version v0.16.3
Tor version : <IP_ADDRESS> (git-0edaa32732ec8930).
lnd.conf content :

debuglevel=trace
bitcoin.active=1
bitcoin.mainnet=1
bitcoin.node=bitcoind
alias=88325dc3ad81fd9caf2249ea74dcff62ad8542b0ab35d1a1e25d5d2f7ac29f34

tor.active=1
tor.v3=1

Steps to reproduce
I started a new LND node from scratch, created a wallet, and let it synchronize. Tor was NOT activated then.
When synch was over, I turned it off, and created the lnd.conf file with content as seen upside.
When running lnd again, I get the error message already provided.
I turned off tor.v3=1 inside the conf file, and then lnd can start normally.
Here is the relevant piece of code I could find.
https://github.com/lightningnetwork/lnd/blob/8dfcbc160d056cba039c7e1d7931d4867bc385de/config.go#L937-L947
Expected behaviour
LND should start up with listening on tor v3 enabled.
Actual behaviour
LND would only start if listening on the P2P interface is disabled

This is intended to prevent unintentionally leaking any identifying information. You must run lnd with listen=localhost if you intend to use Tor.

It works, but then I suggest to add it to the configuring_tor. I can make the PR.

Sure 👍

#2053


Allow overriding the debug type.

Debugging cross platform might need other debug type than Full. This PR makes that possible (by overriding in build scripts.

@mterwoord is this still needed? I think the project layout has changed so much that it's no longer going to be easy to merge. Also this change should really be in a .props file.
I'm going to close this for now, lets discuss in gitter if you still need it.


multiple camera support

an example of using multiple kinects can be found in the cinder block http://forum.libcinder.org/topic/new-kinect-support#23286000000454019

This is working nicely so far and the branch has been merged into the develop branch.


Mysql 21.0.2 incompatible with poem-openapi 1.0.31

Hey there,
I would like to use Poem with Mysql, but they seem to be using incompatible bitvec / funty versions. On build I get a  error[E0034]: multiple applicable items in scope    --> C:\Users\local\.cargo\registry\src\github.com-1ecc6299db9ec823\bitvec-0.19.4\src\field.rs:307:25.
This problem seems to be known in funty and can apparently be solved by updating all dependencies to funty 2.0.0 (or at least the same version.) Unfortunately it is nested quite deeply in the dependencies.
Example Toml, full build output, and cargo tree output uploaded here: https://gist.github.com/Christoph-AK/366e6c39c24976d5bf48064e658b6670
Can this be solved from this crate?
MySQL Issue: https://github.com/blackbeam/rust-mysql-simple/issues/300

Have you enabled the staticfiles or template feature?

Not explicitly, as per the cargo.toml in the gist.
Are they included in default?
Is either likely to impact this problem?

Please upgrade to v1.0.33, it removes akasma from dependencies.

Wow, thanks for looking into it so quickly! My projects now build successfully, thank you! And sorry for the inconvenience and having to rip the templating out.


Add ER/Tables for WHN

🚀 Deployed on https://6504be17ca3291270af41fbd--cozy-fox-0defec.netlify.app


⚠ Samsung has degraded performance

In a7614ae, Samsung (https://samsung.com) experienced degraded performance:

HTTP code: 200
Response time: 2569 ms

Resolved: Samsung performance has improved in 189df3c.


Feature request > Keyboard shortcut(s)

Hi @logon84,
If you would consider adding keyboard shortcut support to this app (volume up/down is all I would personally need) then I would be able to pass those command(s) to my media center box from Home Assistant on all of my devices. And that would be sweet.
🙏

I am outside of my city this week, so I cannot test. But doesn't TAB key switch from one element to others in the app? Once with focus on volume, if I remember right, using arrows will increase/decrease the value.

Thank you for the response.
Unfortunately, that isn't a beneficial solution.
To illustrate: I use a app called Voice Meeter (it allows me to use two sound cards independently). It accepts keyboard shortcuts for volume control.
While I'm watching a full screen movie on my media PC I can send those keyboard shortcuts to the PC through Unified Remote, Home Assistant, etc.
Thus I can increase or decrease the volume without pausing the movie (or resizing its window).
Using the TAB key (as you describe) assumes that pySVS is running in the foreground and that one is either physically controlling the PC, or is remotely controlling it. Either way the movie experience would be interrupted.
Let's say I'm watching Game of Thrones and there's a battle scene. It would be nice to be able to turn up the bass from my phone.
At this point, one might ask, why not just use the SVS app?
 Every time you open it, it crashes. So then you reopen it and then you have to wait 10 another seconds or so for it to reestablish its Bluetooth connection with the sub.
I assume pySVS would maintain a persistent connection with the sub.
If pySVS accepted keyboard shortcuts it could run continuously on the media PC and process commands on-the-fly. And I could control it through the same interface I already use to control media volume, balance, toggle subtitles on/ off, control the lighting in my house, the thermostat, yadda yadda yadda.

Even if SVS eventually get around to fixing their app... who needs it?!
Sorry for the verbose explanation / thanks for reading.

This scenario is too specific for me to commit changes in pysvs just for this. But if I correctly understood what you want to achieve, probably is way easier for you to just use the command line mode, this way you can send commands to the sub in the background:
python3 pysvs.py -o -30
Run this and it will set volume on the sub to -30dB.
If you want to increase or decrease by relative units, first ask the sub for the current volume:
python3 pysvs.py -o A
And then with basic output filtering you can achieve relative volume change.

I found the MAC address by using a third-party Bluetooth scanner.
I'm running W11 / Ubuntu (via Windows Subsystem for Linux)
stevland@Loves5:/mnt/c/pySVS-main$ ./pySVS.py -i
Traceback (most recent call last):
  File "/mnt/c/pySVS-main/./pySVS.py", line 145, in TX_thread
    async with BleakClient(address,adapter=dev) as client:
  File "/home/stevland/.local/lib/python3.10/site-packages/bleak/__init__.py", line 565, in __aenter__
    await self.connect()
  File "/home/stevland/.local/lib/python3.10/site-packages/bleak/__init__.py", line 605, in connect
    return await self._backend.connect(**kwargs)
  File "/home/stevland/.local/lib/python3.10/site-packages/bleak/backends/bluezdbus/client.py", line 129, in connect
    device = await BleakScanner.find_device_by_address(
  File "/home/stevland/.local/lib/python3.10/site-packages/bleak/__init__.py", line 385, in find_device_by_address
    return await cls.find_device_by_filter(
  File "/home/stevland/.local/lib/python3.10/site-packages/bleak/__init__.py", line 441, in find_device_by_filter
    async with cls(**kwargs) as scanner:
  File "/home/stevland/.local/lib/python3.10/site-packages/bleak/__init__.py", line 158, in __aenter__
    await self._backend.start()
  File "/home/stevland/.local/lib/python3.10/site-packages/bleak/backends/bluezdbus/scanner.py", line 168, in start
    manager = await get_global_bluez_manager()
  File "/home/stevland/.local/lib/python3.10/site-packages/bleak/backends/bluezdbus/manager.py", line 1046, in get_global_bluez_manager
    await instance.async_init()
  File "/home/stevland/.local/lib/python3.10/site-packages/bleak/backends/bluezdbus/manager.py", line 278, in async_init
    assert_reply(reply)
  File "/home/stevland/.local/lib/python3.10/site-packages/bleak/backends/bluezdbus/utils.py", line 22, in assert_reply
    raise BleakDBusError(reply.error_name, reply.body)
bleak.exc.BleakDBusError: [org.freedesktop.DBus.Error.TimedOut] Failed to activate service 'org.bluez': timed out (service_start_timeout=25000ms)

Yes, total newbie.
I subseqently realized that by "Windows" you probably mean installing Python in Windows.
So I've done that and installed bleak, pillow and requests.
When I try to run pySVS from Windows Command Prompt:
Traceback (most recent call last):
  File "C:\pySVS-main\pySVS.py", line 145, in TX_thread
    async with BleakClient(address,adapter=dev) as client:
  File "C:\Users\stevland\AppData\Local\Programs\Python\Python312\Lib\site-packages\bleak\__init__.py", line 565, in __aenter__
    await self.connect()
  File "C:\Users\stevland\AppData\Local\Programs\Python\Python312\Lib\site-packages\bleak\__init__.py", line 605, in connect
    return await self._backend.connect(**kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\stevland\AppData\Local\Programs\Python\Python312\Lib\site-packages\bleak\backends\winrt\client.py", line 287, in connect
    raise BleakDeviceNotFoundError(
bleak.exc.BleakDeviceNotFoundError: Device with address 08:EB:ED:62:DD:02 was not found.

OS Name	Microsoft Windows 11 Pro
Version	10.0.22621 Build 22621
Python 3.12.0 (tags/v3.12.0:0fb18b0, Oct  2 2023, 13:03:39) [MSC v.1935 64 bit (AMD64)] on win32
Package                                                 Version
------------------------------------------------------- ---------
bleak                                                   0.21.1
certifi                                                 2023.7.22
charset-normalizer                                      3.3.0
idna                                                    3.4
Pillow                                                  10.1.0
pip                                                     23.3
requests                                                2.31.0
urllib3                                                 2.0.7
winrt-runtime                                           2.0.0b1
winrt-Windows.Devices.Bluetooth                         2.0.0b1
winrt-Windows.Devices.Bluetooth.Advertisement           2.0.0b1
winrt-Windows.Devices.Bluetooth.GenericAttributeProfile 2.0.0b1
winrt-Windows.Devices.Enumeration                       2.0.0b1
winrt-Windows.Foundation                                2.0.0b1
winrt-Windows.Foundation.Collections                    2.0.0b1
winrt-Windows.Storage.Streams                           2.0.0b1


Add support to parse picklist values

When generating documentation for custom objects, include pick list values in documentation
TODO:

[x] Ensure documentation generator to include pick list values

@cesarParra  not sure if you have an integration test to verify but believe the changes are completed. Let me know

@cesarParra not sure if you have an integration test to verify but believe the changes are completed. Let me know

@RaviVaranasi Yeah, the CI tests will run once I approve.

@cesarParra Unsure of the last commit but should be ready for review again


Add better handling for options and errors

Improve test for existance xlsx2csv. The old way would print a message if the command failed for any reason.  Now it tests explicitly for its existance before printing the pip install message.
parameterize output file and csv column parsing of MSA code and name
Add a -h help option

looks good, thanks mike!


Update mastermind semver

Initial start of PR for #562 . Integration tests failing. Looking in to them

All checks green, though I am not confident on the resolution. Changed an error deep equals check to a check on the string equivalence of the error. Also modified test data. Unclear what the mode in the test hardness cases is derived from.

Ahh, ok, yes - I now remember why this is happening the way it is. The old version of semver we were on had only halfway converted the below-1.0.0 handling of carets - the parser was still doing the old thing, but the stringifier had the new logic. As a result, ^0.8.0 would be parsed as "greater than or equal to 0.8.0 and less than 1.0.0" - but in the new model, that stringifies to >=0.8.0, < 1.0.0.
This all happens in the test output as it does because we prepend the caret.


[feature-request] Improve Extract Variable by including without final and/or without type annotations

Thank you for taking the time to file an issue!
In order to route, prioritize, and act on this, please include:

Dart SDK Version: 2.2.0

I would like the IntelliJ Dart plugin to improve the extraction of a variable. Since the analysis server needs to support it first, then that means I'm asking the Dart team to help improve the tooling for Dart developers.

@vsmenon, I don't think area-intellij is the right label here. 'Extract variable' refactoring is implemented on the Analysis Server end, so changes should be done on the server end as well.

Duplicate of https://github.com/dart-lang/sdk/issues/31701


hassUrl breaks the links

thank you for the answer.
There seems to be a problem with the links of the cameras and other things.
in the log i get:
`
SvelteKitError: Not found: /api/camera_proxy_stream/camera.warehouse
at resolve2 (file:///rootfs/build/server/index.js:4027:18)
at resolve (file:///rootfs/build/server/index.js:3859:34)
at Object.handle (file:///rootfs/build/server/chunks/hooks.server-hoE62lsD.js:2:26)
at respond (file:///rootfs/build/server/index.js:3857:43)
at process.processTicksAndRejections (node:internal/process/task_queues:95:5) {
status: 404,
text: 'Not Found'
}
SvelteKitError: Not found: /local/liran.jpg
at resolve2 (file:///rootfs/build/server/index.js:4027:18)
at resolve (file:///rootfs/build/server/index.js:3859:34)
at Object.handle (file:///rootfs/build/server/chunks/hooks.server-hoE62lsD.js:2:26)
at respond (file:///rootfs/build/server/index.js:3857:43)
at process.processTicksAndRejections (node:internal/process/task_queues:95:5) {
status: 404,
text: 'Not Found'
}
SvelteKitError: Not found: /local/plex_recently_added/plex/Plex_Recently_Added/f612.jpg
at resolve2 (file:///rootfs/build/server/index.js:4027:18)
at resolve (file:///rootfs/build/server/index.js:3859:34)
at Object.handle (file:///rootfs/build/server/chunks/hooks.server-hoE62lsD.js:2:26)
at respond (file:///rootfs/build/server/index.js:3857:43)
at process.processTicksAndRejections (node:internal/process/task_queues:95:5) {
status: 404,
text: 'Not Found'
}
SvelteKitError: Not found: /local/plex_recently_added/plex/Plex_Recently_Added/p612.jpg
at resolve2 (file:///rootfs/build/server/index.js:4027:18)
at resolve (file:///rootfs/build/server/index.js:3859:34)
at Object.handle (file:///rootfs/build/server/chunks/hooks.server-hoE62lsD.js:2:26)
at respond (file:///rootfs/build/server/index.js:3857:43)
at process.processTicksAndRejections (node:internal/process/task_queues:95:5) {
status: 404,
text: 'Not Found'
}
SvelteKitError: Not found: /api/hass_agent/media_player.avipc_win11/thumbnail.png
at resolve2 (file:///rootfs/build/server/index.js:4027:18)
at resolve (file:///rootfs/build/server/index.js:3859:34)
at Object.handle (file:///rootfs/build/server/chunks/hooks.server-hoE62lsD.js:2:26)
at respond (file:///rootfs/build/server/index.js:3857:43)
at process.processTicksAndRejections (node:internal/process/task_queues:95:5) {
status: 404,
text: 'Not Found'
}
`

Originally posted by @abeksis in https://github.com/matt8707/ha-fusion/discussions/222#discussioncomment-8190326

The links point to the right URL but on the wrong port, i.e. 8099 (fusion) instead of 8123 (ha)


checkboxgroup with multiple options

extend the select headless hook to accept multiple strings
value type string[]
possible UI example of checkbox group or multi select

There is no multiselect for chakra nor flowbite, so resorting to checkboxgroup


Configuration

ASP.NET 5->Runtime->Configuration

Get, set,
Providers: JSON, XML, INI, env vars
Custom providers

@danroth27
Does it make sense to cover Microsoft.Framework.ConfigurationModel.UserSecrets in this article as well?

Nah, we are going to have a specific topic covering handling app secrets. See #93.


Add Chainguard Enforce configuration

Chainguard Enforce is a GitHub app that verifies container signatures.
It's able to verify signatures using Sigstore's keyless signing as well
as GPG keys. This is already set up and working in the audit event
library.
The provided configuration will verify that folks are using sigstore's
keyless signatures on their commits, and will also accept GitHub API's
GPG keys to have apps like renovate have valid signatures.
To set up keyless signatures, use gitsign [1]. If on mac, you may
install it as follows:
brew install sigstore/tap/gitsign

And set it up in this repository only:
cd /path/to/this/repository
git config --local commit.gpgsign true  # Sign all commits
git config --local tag.gpgsign true  # Sign all tags
git config --local gpg.x509.program gitsign  # Use gitsign for signing
git config --local gpg.format x509  # gitsign expects x509 args

This shouldn't be set for all repositories as it will add references to
the repositories and branches o a public transparency log, which you
don't want in a private or internal GitHub repository.
[1] https://github.com/sigstore/gitsign
Signed-off-by: Juan Antonio Osorio<EMAIL_ADDRESS>

Codecov Report

Merging #49 (5f84579) into main (82aa63d) will not change coverage.
The diff coverage is n/a.

:exclamation: Current head 5f84579 differs from pull request most recent head 005cf72. Consider uploading reports for the commit 005cf72 to get more accurate results

@@           Coverage Diff           @@
##             main      #49   +/-   ##
=======================================
  Coverage   73.81%   73.81%
=======================================
  Files          10       10
  Lines         550      550
=======================================
  Hits          406      406
  Misses        115      115
  Partials       29       29

Flag
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@JAORMX does that mean that by enabling this, we're restricting the repo to only signed commits from sigstore's keyless signatures ?

@matoszz kinda. This configuration will accept keyless signatures that are verified via the public sigstore instance AND GitHub API's GPG signature which makes bots like Renovate work. However, Enforce is currently not strictly enforcing. Meaning, folks will still be able to merge work even if it doesn't pass the code commit checks. This is on purpose to start rolling this out and get folks' feedback.

The 'unverified' UI element that shows up is not the most intuitive thing. Is there a way to get GitHub to trust the sigstore signatures?

@adammohammed not at the moment. This is a GitHub limitation that is actually being worked on by the GitHub team, but there is no estimate on when they'll get it sorted.


Jstd

1.3.3c was just released, please update this PR

so I worked with this PR and I have to agree that git submodules suck and don't help us in any way. I think that we should abandon this idea and just upgrade jasmine adapter and jstd just like we did in the past.
we can discuss this during standup, but I think that the benefit this gives us is tiny compared to the new complexity it brings. Worst of all, I don't see this as a suitable solution for angular-seed, which is one of the goals I was hoping to achieve here.

for seed, i think we should stick with checking it in, but I would go for
npm for the rest of us.
2011/10/13 Igor Minar <
<EMAIL_ADDRESS>
so I worked with this PR and I have to agree that git submodules suck and
don't help us in any way. I think that we should abandon this idea and just
upgrade jasmine adapter and jstd just like we did in the past.
we can discuss this during standup, but I think that the benefit this gives
us is tiny compared to the new complexity it brings. Worst of all, I don't
see this as a suitable solution for angular-seed, which is one of the goals
I was hoping to achieve here.
--
Reply to this email directly or view it on GitHub:
https://github.com/angular/angular.js/pull/579#issuecomment-2398229

maybe.. or we'll just wait a bit more for node based runner...


As a developer, I want my database to run on SQL Server database so it is suitable for production and scaling up

Rather than SQLite, we should use SQL server, so it can also be deployed to Azure.
Description from lecture:
Refactor your Chirp! application so that it uses an SQL Server database when executed locally. Such a database can be instantiated via docker for example as in the following:

docker run -e "ACCEPT_EULA=Y" -e "MSSQL_SA_PASSWORD=yourStrong(!)Password" -p 1433:1433  --name sqlpreview --hostname sqlpreview -d mcr.microsoft.com/mssql/server:2022-latest
Ensure your tests are still running - using SQLite in-memory and/or test containers.
Run your production code with Azure SQL.
Ensure you apply your migrations when deploying to App Services.
Extend your CheepRepository to support create (test and implement).
Using FluentValidation to ensure all inputs are valid.
Add a Chirp! form to your app which is only visible when a user is signed in.
Ensure a user can only post to the form if she is signed in.

Acceptance criteria:

a user can only post to the form if she is signed in.
Production code can be run with Azure SQL.
Chirp! form to your app is only visible when a user is signed in.

all criteria are fulfilled


Gradle 4.10: Illegal reflective access to method java.lang.Object.finalize()

I'm running gradle -version and receive the following warning. Browsing the issues here it seems that the current assumption is that with bundled groovy-version this should no happen any longer
Expected Behavior
Gradle should not spill out warnings the user cannot provide
Current Behavior
 $ gradle --version -s
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.codehaus.groovy.reflection.CachedClass (file:/srv/private/Development/gradle-4.10/lib/groovy-all-2.4.15.jar) to method java.lang.Object.finalize()
WARNING: Please consider reporting this to the maintainers of org.codehaus.groovy.reflection.CachedClass
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release

------------------------------------------------------------
Gradle 4.10
------------------------------------------------------------

Build time:   2018-08-27 18:35:06 UTC
Revision:     ee3751ed9f2034effc1f0072c2b2ee74b5dce67d

Kotlin DSL:   1.0-rc-3
Kotlin:       1.2.60
Groovy:       2.4.15
Ant:          Apache Ant(TM) version 1.9.11 compiled on March 23 2018
JVM:          10.0.2 (Oracle Corporation 10.0.2+13-Ubuntu-1ubuntu<IP_ADDRESS>)
OS:           Linux 4.15.0-33-generic amd64

Steps to Reproduce (for bugs)
Start gradle --version in the aforementioned environemnt

As stated in the other issue, this is a Groovy problem that we can't fix. What I'm probably gonna do is filter out the warning, as neither we nor our users can do anything about it.

Unfortunately these warnings never go through our logging infrastructure, because the IllegalAccessLogger is set up during the early boot phase of the JVM and uses System.err before we can replace it. We can't fix that without causing an illegal access warning ourselves.
We can avoid the warning when running gradle -version by not using GroovySystem. For the daemon we could open up certain JVM modules to ALL_UNNAMED to allow Groovy (and everyone else) to access them. But then we will also miss out on other, valid warnings.

@marcphilipp Given the explanation above I'm tempted to close this, as we have fixed the one instance where we could prevent the warning (which was also the one that most users complained about). Suppressing the warnings for other usages of Groovy (e.g. compiling Groovy code in your own project) seems like a bad idea to me, as it could hide other issues.

FYI : it was trivial to avoid the warning for gradle -v, just by switching to calling a static method on ReleaseInfo rather than GroovySystem.

I don't think we should underestimate how annoying this message is to users, and how bad it makes Gradle look. I'd be tempted to use the nuclear option to suppress all warnings and then prioritize helping get this fixed in Groovy before we remove that option.

To follow up on this. The warning is displayed whenever we compile groovy sources (because that's always done in a separate JVM) and whenever we execute tests that use groovy. So for a project generated with gradle init --dsl groovy --type java-library --test-framework spock will generate the warning twice for gradle build: https://e.grdev.net/s/qg3hxalyeke7i/console-log
I don't think the argument about hiding other issues holds water, since my understanding is that the JVM will only report the first illegal access warning, and hide the rest. Assuming that user code is doing this after Groovy, then the warnings will be hidden anyway. If this is the case, then we are just scaring users with a nasty warning with no benefit.
I can see a few options:

When launching compiler and test processes, supply the relevant --allow-opens so that this warning doesn't show up. (See below)
Do some sort of hackery when launching the compiler and test processes, as described here: https://stackoverflow.com/questions/46454995/how-to-hide-warning-illegal-reflective-access-in-java-9-without-jvm-argument
Print a big disclaimer before the JVM reported message, informing users that it's really not our fault and to please ignore the warning. We'd need to intentionally load GroovySystem or similar to ensure that our disclaimer came right before the warning.
I tried adding --illegal-access=deny to the jvmargs for the groovy compile and test processes: this actually suppressed the warnings. I'll admit that I have no idea what Groovy is doing in these cases, however. If this "just works" then we could make it the default, providing a mechanism to permit illegal access if they really need to.

Of these, the first seems safest and least likely to cause other, unexpected issues.
For option 1 this is sufficient for the Test task that uses Spock:
test {
    jvmArgs('--add-opens', 'java.base/java.lang=ALL-UNNAMED')
    jvmArgs('--add-opens', 'java.base/java.lang.invoke=ALL-UNNAMED')
}

However, for GroovyCompile, it's not possible due to #7045.

I don't think the argument about hiding other issues holds water, since my understanding is that the JVM will only report the first illegal access warning, and hide the rest.

The JVM de-duplicates them like our deprecation logger does, i.e. it won't report the same access twice. But there can be many different illegal accesses, all of which will be reported.
The problem is that you can't just give access to Groovy. You have to give access to all ALL-UNNAMED, which in the unmodularized case is everything. So any problems in the user's own code will be hidden.

The JVM de-duplicates them like our deprecation logger does, i.e. it won't report the same access twice. But there can be many different illegal accesses, all of which will be reported.

You sound confident of that, but it hasn't been my experience. Without any --illegal-access parameter, I only see a single illegal access reported per-jvm. I've tried various combinations of loading Groovy and code that performs illegal access, and I've been unable to see multiple issues reported.
If I use --illegal-access=warn, then I see all illegal reflective access, de-duplicated.

Ah right, I had warn in my jvm args from some earlier experiment. The default is oneshot, as you said.
In that case I wonder what the value of that singular warning is if everything else is hidden from the user. We might as well pass --illegal-access=permit until Groovy is fixed then, since Groovy will always be the first warning. As long as we allow the user to overwrite that default, it should be fine.

I think --illegal-access=permit is the default, and will result in the current behaviour. This is why I recommend using --allow-open to avoid these warnings.

Right, I had assumed that "permit" and "oneshot" were different, but they're actually different names for the same mode. So --add-opens it is.

We opened up the two commonly accessed packages for the daemon and the GroovyCompile task.
We didn't do it for Test, because depending on what code you run, the list of illegal accesses is almost endless. Users can try for themselves by passing --illegal-access=deny and then adding the relevant --add-opens till their tests pass. For some it may only require 1 or 2, for others it may be 20. For instance, CodeNarc uses so many JVM internals that I gave up at some point.

If you want to go with the add-open option, here's a command to find which module provides which package ->
java --list-modules | tr @ " " | awk '{ print $1 }' | xargs -n1 java -d
the name of the module will be shown with the @ while the name of the packages without it
NOTE: tested with JDK 11
IMPORTANT: obviously is better not to do the illegal access in the first place, but until the transition is done, it is an alternative.


RuntimeError: Mask tensor can take 0 and 1 values only

Hello, the author, I encountered some problems in reproducing your project:
When I run the pre training command "bash run/retrain. bash", an error occurs after several steps. The situation is as follows：
(hop) wuyifei@dell-Precision-7920-Tower:~/code/HOP-VLN$ bash run/pretrain.bash
You are using 0 GPUs to train!!
Loading image features from img_features/ResNet-152-imagenet.tsv
read_num 0
feature_store: True
Loading image features from img_features/ResNet-152-imagenet.tsv
read_num 0
feature_store: True
you have loaded 1069620  time steps
Loading image features from img_features/ResNet-152-imagenet.tsv
read_num 0
feature_store: True
Loading image features from img_features/ResNet-152-imagenet.tsv
read_num 0
feature_store: True
you have loaded 17420  time steps
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
Iteration:   0%|| 0/8357 [00:00<?, ?it/s]/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:142: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
labels[~masked_indices] = -1  # We only compute loss on masked tokens
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:142: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
labels[~masked_indices] = -1  # We only compute loss on masked tokens
Iteration:   0%|| 0/8357 [00:00<?, ?it/s]
Traceback (most recent call last):
File "./tasks/pretrain/main.py", line 762, in
main()
File "./tasks/pretrain/main.py", line 727, in main
global_step, tr_loss = trainval(params, train_dataset, eval_dataset, model, tokenizer)
File "./tasks/pretrain/main.py", line 179, in trainval
for step, batch in epoch_iterator:
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/tqdm/std.py", line 1185, in iter
for obj in iterable:
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 628, in next
data = self._next_data()
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1333, in _next_data
return self._process_data(data)
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1359, in _process_data
data.reraise()
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/_utils.py", line 543, in reraise
raise exception
RuntimeError: Caught RuntimeError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 302, in _worker_loop
data = fetcher.fetch(index)
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 58, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 58, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py", line 212, in getitem
output = self.getQuery(query, self.nag_trajs, self.nag_trajs_seq, self.nag_trajs_bnb)
File "/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py", line 460, in getQuery
masked_text_seq, masked_text_label, attention_mask = mask_tokens(text_seq, self.tok, self.args)
File "/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py", line 142, in mask_tokens
labels[~masked_indices] = -1  # We only compute loss on masked tokens
RuntimeError: Mask tensor can take 0 and 1 values only
Can you help me solve this problem? I would be grateful！

I originally installed the torch according to the required version, but reported the same error as that in #3.According to your comments below, I installed the torch version matching my CUDA, and then reported the above error.Now,my CUDA is 11.7.

You are using 0 GPUs to train!!

Hello, thanks for your interest. Firstly, "You are using 0 GPUs to train!!" may show that your cuda is unavailable. Secondly, I do not encounter this RuntimeError problem, I guess it may also be due to the torch version.

Hello, the author, I encountered some problems in reproducing your project:
When I run the pre training command "bash run/retrain. bash", an error occurs after several steps. The situation is as follows：
(hop) wuyifei@dell-Precision-7920-Tower:~/code/HOP-VLN$ bash run/pretrain.bash
You are using 0 GPUs to train!!
Loading image features from img_features/ResNet-152-imagenet.tsv
read_num 0
feature_store: True
Loading image features from img_features/ResNet-152-imagenet.tsv
read_num 0
feature_store: True
you have loaded 1069620 time steps
Loading image features from img_features/ResNet-152-imagenet.tsv
read_num 0
feature_store: True
Loading image features from img_features/ResNet-152-imagenet.tsv
read_num 0
feature_store: True
you have loaded 17420 time steps
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
Iteration: 0%|| 0/8357 [00:00<?, ?it/s]/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:137: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
probability_matrix.masked_fill_(torch.tensor(special_tokens_mask, dtype=torch.uint8), value=0.0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:141: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:142: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
labels[~masked_indices] = -1 # We only compute loss on masked tokens
/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py:142: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525496686/work/aten/src/ATen/native/TensorAdvancedIndexing.cpp:1646.)
labels[~masked_indices] = -1 # We only compute loss on masked tokens
Iteration: 0%|| 0/8357 [00:00<?, ?it/s]
Traceback (most recent call last):
File "./tasks/pretrain/main.py", line 762, in
main()
File "./tasks/pretrain/main.py", line 727, in main
global_step, tr_loss = trainval(params, train_dataset, eval_dataset, model, tokenizer)
File "./tasks/pretrain/main.py", line 179, in trainval
for step, batch in epoch_iterator:
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/tqdm/std.py", line 1185, in iter
for obj in iterable:
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 628, in next
data = self._next_data()
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1333, in _next_data
return self._process_data(data)
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1359, in _process_data
data.reraise()
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/_utils.py", line 543, in reraise
raise exception
RuntimeError: Caught RuntimeError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 302, in _worker_loop
data = fetcher.fetch(index)
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 58, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/wuyifei/anaconda3/envs/hop/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 58, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py", line 212, in getitem
output = self.getQuery(query, self.nag_trajs, self.nag_trajs_seq, self.nag_trajs_bnb)
File "/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py", line 460, in getQuery
masked_text_seq, masked_text_label, attention_mask = mask_tokens(text_seq, self.tok, self.args)
File "/home/wuyifei/code/HOP-VLN/tasks/pretrain/batch_loader.py", line 142, in mask_tokens
labels[~masked_indices] = -1 # We only compute loss on masked tokens
RuntimeError: Mask tensor can take 0 and 1 values only
Can you help me solve this problem? I would be grateful！

Hello, thanks for your interest. Firstly, "You are using 0 GPUs to train!!" may show that your cuda is unavailable. Secondly, I do not encounter this RuntimeError problem, I guess it may also be due to the torch version.

Yes, at the beginning, I configured the environment according to your requirements. I could use 3 GPU for training, but the error in #3  would be reported. According to the answer in that question, I upgraded my pytorch version to adapt to my CUDA version（11.7）, and then ran it again, it would display 0 GPU for training


Cant generate epub from downloaded file

After i download a novel from boxnovel i cant generate the epub file.
I read epub file with external epub reader moonreader. I already try to reinstall quicknovel after update yet still the same issue

And also it could not read chapter from boxnovel and freewebnovel

what is the link of the novel that returns "error loading novel"

https://boxnovel.com/novel/demon-sect-cultivation-i-can-disable-debuffs/

Unable to replicate, have you checked that quicknovel has storage permission?

Can it be because i restore data from backup with different version ? Cause after i tried random novel from the same site it works the same also for same novel in different site

i have the same problem, and yes my quicknovel already has permission. when i choose android/data/... it's fine. but when i create and choose a folder "Download/epub", it cannot and show that error


Investigate improper order for bookending logic

James says if the random track is at the end of the album, it will play something from the beginning of the album.

This shouldn't be an issue now that we are using track numbers to order the files.


Add user.yml config sample

I'm not entirely sure of the purpose of this. Could we get a bit more explanation for this please? Ideally a bit more on the 'why' in the commit message as well.
See https://github.com/alphagov/styleguides/blob/master/git.md#commit-messages and https://github.com/alphagov/styleguides/blob/master/pull-requests.md for the GOV.UK guidance on commits and pull requests which is pretty good.


python310Packages.icnsutil: 1.0.1 -> 1.1.0

Automatic update generated by nixpkgs-update tools. This update was made based on information from passthru.updateScript.
meta.description for python310Packages.icnsutil is: Create and extract .icns files.
meta.homepage for python310Packages.icnsutil is: https://github.com/relikd/icnsutil
Updates performed

Ran passthru.UpdateScript

To inspect upstream changes
Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
found 1.1.0 with grep in /nix/store/8fv2z4g4z39b4p3vqhf0z910cy611zq3-python3.10-icnsutil-1.1.0
found 1.1.0 in filename of file in /nix/store/8fv2z4g4z39b4p3vqhf0z910cy611zq3-python3.10-icnsutil-1.1.0

Rebuild report (if merged into master) (click to expand)

3 total rebuild path(s)

3 package rebuild(s)

First fifty rebuilds by attrpath
desktopToDarwinBundle
python310Packages.icnsutil
python311Packages.icnsutil

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/8fv2z4g4z39b4p3vqhf0z910cy611zq3-python3.10-icnsutil-1.1.0 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A python310Packages.icnsutil https://github.com/r-ryantm/nixpkgs/archive/abf376b749af92c9e9b6924bc6913c01914f2e8e.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/8fv2z4g4z39b4p3vqhf0z910cy611zq3-python3.10-icnsutil-1.1.0
ls -la /nix/store/8fv2z4g4z39b4p3vqhf0z910cy611zq3-python3.10-icnsutil-1.1.0/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review run on x86_64-linux 1

3 packages built:

desktopToDarwinBundle
python310Packages.icnsutil
python311Packages.icnsutil

Maintainer pings
cc @reckenrode for testing.

Result of nixpkgs-review pr 231417 run on x86_64-linux 1

5 packages built:

desktopToDarwinBundle
python310Packages.icnsutil
python310Packages.icnsutil.dist
python311Packages.icnsutil
python311Packages.icnsutil.dist

Thanks for the cleanup. LGTM


Added an overloaded function to create engine with a custom version

There is a requirement to include the EY-Tim integration tests in the raicode deployment workflow. For that we need to test against the currently built engine version. The compute service supports passing a custom engine version header in the create engine request.  Added a new function to create the engine with the provided version.

thanks @miazamrai
can you also bump up the current sdk version ?

@NRHelmi Done


Update RssReader

Turns out you need to do a bit more work to get the correct text content from the feed.

thanks - mm this may have conflicts with the existing RssReader + notebook that I merged into main, could you repull?

Updated


Knife bootstrap can't be aborted and locks shell for 30 seconds.

Description
executing knife bootstrap against an invalid address locks shell for 30 seconds. CTRL+C does not work
Chef Version
$ chef -v
Chef Development Kit Version: 0.14.25
chef-client version: 12.10.24
berks version: 4.3.3
kitchen version: 1.8.0

Platform Version
osx 10.11.4
Replication Case
run the below bootstrap command, count to 3, and start pressing CTRL+C repeatedly.
$ time knife bootstrap foo_bar -VV
Connecting to foo_bar
DEBUG: Looking for bootstrap template in /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/chef-12.10.24/lib/chef/knife/bootstrap/templates
DEBUG: Found bootstrap template in /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/chef-12.10.24/lib/chef/knife/bootstrap/templates
DEBUG: Adding foo_bar
DEBUG: establishing connection to foo_bar:22
^C^C^C
0.83s user 0.17s system 3% cpu 31.070 total

There's likely not much we can do about it, as this is probaly down in the net-ssh implementation, but we'd be open to a PR to help with it.


Handle host master key changing

We only grab the master key once on portal load. If it changes we don't update it.

addressed in https://github.com/projectkudu/AzureFunctionsPortal/pull/652