Training time and number of GPUS

Hi, thanks for sharing the implementation. I wonder how many gpus (and what kind of gpu) you have used and how long to train the stage 1 and stage 2. Since I don't have much gpus, I want to see if I can afford the training or fine tuning.

Hi @JialeTao, depend on the config, training can be fast or slow. For the config in this repo which is ViT-VGAN base, it takes about 1.45s per iteration with a batch size of 4 on a A100, this is quite demanding. So if you dont have much gpus,  I recommend training a much smaller config than the config I have in this repo. Also, there are plans to train smaller models so you can wait if you want but it will be a long time later since I'm too busy these days 😭

Thanks for the reply. Then for the vit-vqgan base, what how many iterations you have trained? And the 1.45s means stage 1 training or stage 2 training? And the last, A100 with 40G menmory or 80G?

Hi @JialeTao, 1,45s per iteration is for stage 1 training and the GPU is A100 40GB. I have trained vit-vqgan base for 1000000 iterations with 32 A100s and each gpu has batch size of 4

Hi @JialeTao, the training vit-vqgan small is faster than I expected and it is just released. The speed is 1.05s per iteration for a batch size of 8 and it can even go up to 16 but 8 is good enough, again this is for A100 40GB. Also if you dont have any further question, I will close this issue. Feel free to reopen

Hi @JialeTao, the training vit-vqgan small is faster than I expected and it is just released. The speed is 1.05s per iteration for a batch size of 8 and it can even go up to 16 but 8 is good enough, again this is for A100 40GB. Also if you dont have any further question, I will close this issue. Feel free to reopen

Hi @thuanz123 , thanks for sharing the checkpoint of vit-vqgan small. Then for this small-small model, how many GPUs and how many iterations you have trained?

Hi @JialeTao, the training vit-vqgan small is faster than I expected and it is just released. The speed is 1.05s per iteration for a batch size of 8 and it can even go up to 16 but 8 is good enough, again this is for A100 40GB. Also if you dont have any further question, I will close this issue. Feel free to reopen

Hi @thuanz123 , thanks for sharing the checkpoint of vit-vqgan small. Then for this small-small model, how many GPUs and how many iterations you have trained?

For quick training, I use 32 gpus A100 40GB and train for 500000 iterations on ImageNet. But I think a decent GPU with 8GB VRAM is enough, just lower the batch size and train longer


big-endian arch not supported producing R-IFF/WAVE

yep

Well there is endian support but its untested.
😶


Add preconditioning to Kriging system

The Kriging system is quite ill-conditioned when data locations are too close from each other. At some point, I have to fix this by adding regularization or any other preconditioning approach.
References:

https://arxiv.org/pdf/1602.00853.pdf
https://link.springer.com/article/10.1007/BF02065878

Solved with nugget regularization.


[NSQ] Fix check for NSQ 1.x.x

Response from the /stats route has been modified for NSQ 1.x.x. This PR removes the deprecated data key.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.


(Wizard2.0-Bug)MintedCappedCrowdsale: whitelisted investors can not buy

Steps for reproduce:

Open wizard https://5ae0d38fc9659230d752d6bc--architect-coin-64174.netlify.com/
Create crowdsale with parameters:
"name": "T1RyWy_0013.json",
"ticker": "t0013",
"decimals": 3,
"reservedTokens":[
{
"address" :"0x27F2f56e6Ee35E4995A965337ba2A7b4ec492FcC",
"dimension": "percentage",
"value": 60
},
{
"address" :"0x41B4073E966c169dB22185805A951A0f1b805320",
"dimension": "tokens",
"value": 2000
}
],
"walletAddress":"0x0e036E74F31aDDb9e0ADcB80dEA9Ed1E187DFe50",
"gasprice": 40,
"mincap": 1,
"whitelisting":true,
"tiers":[
{
"name":"###1",
"allowModify": true,
"startDate": "",
"startTime": "",
"endDate":"",
"endTime":"",
"rate":1000,
"supply": 100,
"whitelist":[
{
"address":"0x27F2f56e6Ee35E4995A965337ba2A7b4ec492FcC",
"min":6,
"max":100
},
{
"address":"0x41B4073E966c169dB22185805A951A0f1b805320",
"min":8,
"max":55
}]
}]

}

Buy tokens as a whitelisted investor

Expected result:

every whitelisted investors should be able to buy allowed amount

Actual result:

both whitelisted investor aren't able to buy

If you are reporting a problem with Token Wizard, please include the following information:
Which network did you use? (Mainnet, Kovan, Rinkeby, etc.)
Ropsten
If you were able to create it, what is the URL of your crowdsale?

Exec ID: 0x4a1e10046c2ed90fa0d66d37620e8e2912711e6ef4219f4c89c9fed07f58e0de *

https://5ae0d38fc9659230d752d6bc--architect-coin-64174.netlify.com/invest?exec-id=0x4a1e10046c2ed90fa0d66d37620e8e2912711e6ef4219f4c89c9fed07f58e0de&networkID=3

Reverted TXs:
https://ropsten.etherscan.io/tx/0x9752a44f751c8807543b70d860b5a38cef5d8b6dc2d20b45055ab7f7901133c6
https://ropsten.etherscan.io/tx/0xc9a00a2681eb64ec9cf4b04d747fff3cfca16a750684d8111e9b77a99f6f9521
https://ropsten.etherscan.io/tx/0xf1b959a06cb8ef83e3c63acc08139cb94c4c931b3110d0d1932f23254a132ba4
https://ropsten.etherscan.io/tx/0x5cb26178296005d0531f1de710264a8860df854f7e847de89fadec5101d0b106
Do you have screenshots showing the problem?

Do you see errors in the dev console? If yes, please include a screenshot
To open the dev console in Google Chrome, press F12, or go to View -> Developer -> Developer Tools, and open the Console tab
If you see errors, please right click on them and "Save as..". Zip saved file and attach it to the Issue.
No

I can't reproduce it for test URL: https://5aec92f21f12b70339c64d4a--architect-coin-64174.netlify.com/


Add functionality to serialize a system without time series

There are three sets of changes here:

Add a to_dict method so that the IS system and components can be serialized to a JSON string without the time series data.
Remove serialization of a system’s validation descriptors. This is a breaking change in that any custom packages that were defining their own validation descriptors will need to pass them at deserialization time (there probably aren’t any). This actually fixes an issue where the descriptors were not upgraded by PSY during an upgrade across major versions.
Update the test code that compares objects recursively to exclude comparison of time series fields that will not be valid in this scenario.

If I follow the logic behind this case, then the objective is to not check for UUIDs in the validation step

In the case where we serialize/de-serialize the system to/from a JSON string, losing the time series, we need to be able to exclude comparison of time series fields while traversing the components. The new exclude parameter allows us to skip custom fields.


IS not a bug.In Formio material bulder option is there or we need to convert json to material in angular version

Environment
Please provide as many details as you can:

Hosting type

[x] Form.io
[ ] Local deployment

Version:

Formio.js version:
Frontend framework:
Browser:
Browser version:

Steps to Reproduce

Expected behavior
Observed behavior
Example
If possible, please provide a screenshot, live example (via JSFiddle or similar), and/or example code to help demonstrate the issue.
For code or form JSON, please enclose in a code block:
// your code here

Please use the standard template when submitting tickets for us to look at. It is hard for me to determine what you are asking about here.

I  mean ,if any key is there for visualize form as material view.


Master branch tests are failing in CI and locally

Describe the bug
You can see in the circleci CI that the tests are failing with the following error
Command failed with exit code 1: /root/project/bin/vite.js build
    [vite] Build errored out.
    [Error: ENOENT: no such file or directory, open '/root/project/temp/dist/root/project/temp/dist/index.html'] {
      errno: -2,
      code: 'PLUGIN_ERROR',
      syscall: 'open',
      path: '/root/project/temp/dist/root/project/temp/dist/index.html',
      pluginCode: 'ENOENT',
      plugin: 'vite:emit',
      hook: 'generateBundle'
    }

This also happens for me locally
For some reason that error makes the tests skip instead of failing, so it still shows the green check
To Reproduce
Expected behavior

Seems to be from this line:
https://github.com/vitejs/vite/blob/9c2d43530406c73d350efba804af8a8ea7718ae7/src/node/build/index.ts#L586
We need to call fs.mkdirp before writing, in case the dist folder is missing.


Error on app start or click on any image "h is an invalid start of value et..

I'm using the lates version of the app but getting error on application start or if i click on any image
see screenshot
windows 11
Describe the bug

A clear and concise description of what the bug is.
Version:
v1.2.1
To Reproduce
Steps to reproduce the behavior and description of what happens.
Expected behavior
A clear and concise description of what you expected to happen.
Source Image
all. images. Easy Diffusion v2.5.38
Source Image or Screenshots
If applicable, add screenshots to help explain your problem.
Additional context
Add any other context about the problem here.

Thanks for this, I am currently adding support for Easy Diffusion metadata.


[11.x] Improves PHP 8.4 compatibility

Notice this while adding PHP 8.4 support to laravel/pail

@crynobone Is it correct that we all need to update al these method properties? Otherwise I will create a script to update them in batches.

That's doesn't require any changes. Please read what's new on PHP 8.4 for further detail


[cleanup][broker]Cleanup Unused code in DispatchRateLimter

Motivation

Cleanup unused code in DispatchRateLimiter

Modifications

Removing DispatchRateLimiter#getPoliciesDispatchRate and the UT about it

Verifying this change

[x] Make sure that the change passes the CI checks.

Documentation
Check the box below or label this PR directly.
Need to update docs?

[ ] doc-required
(Your PR needs to update docs and you will update later)

[x] doc-not-needed
(Please explain why)

[ ] doc
(Your PR contains doc changes)

[ ] doc-complete
(Docs have been already added)

/pulsarbot run-failure-checks


Use new environment tag styles to fix A11y issues

Context
The qa tag is not deemed to have sufficient contrast for accessibility by Axe. Rather than just pick a different colour we've switched to new govuk-tag styles for all non-production environments.
Changes proposed in this pull request
Before:

After:

There are a couple of other places where tags appear for Sandbox specific features, e.g.

The production interface is unchanged:

Guidance to review

Does it look OK?
Is there any more CSS that we can remove?

Link to Trello card
https://trello.com/c/ALvwnGc6/1844-include-serious-accessibility-issues-in-axe-tests
Things to check

[x] This code does not rely on migrations in the same Pull Request
[x] If this code includes a migration adding or changing columns, it also backfills existing records for consistency
[x] API release notes have been updated if necessary
[x] New environment variables have been added to the Azure config

Are there screenshots of the other environments too?

Are there screenshots of the other environments too?

@fofr I've added 'after' screenshots for all the other environments.


Project resolution

Sorry for the dumb question, but my esp display in only 128x64. Will lowering the resolution in the menuconfig help or am i just screwed?

@Kl0ibi Forgot to add the display has four pins instead of 7


adds auto-scaling for MachineSet based on number of BareMetalHosts

In many clusters, it is desirable for the size of a MachineSet to always equal
the number of matching BareMetalHosts. In such a scenario, the cluster owner
wants all of their hardware to be provisioned and turned into Nodes, and they
want to remove excess Machines in case they remove hosts from their cluster.
This change adds a controller that scales MachineSets to the number of matching
BareMetalHosts. The behavior is opt-in, requiring an annotation on the
MachineSet.
fixes #188

@dhellmann this is ready for re-review.

I'm currently chasing a nil pointer dereference that seems unrelated to this PR, but we all know how that can turn out, so I want to get to the bottom of it before merging.

I fixed the nil pointer dereference, so this is safe to merge. It ended up being a result of this landmine leftover from the earliest days of scaffolding the actuator. It wasn't on any code path, until now. The "real" actuator gets created only in main.go. Because of how both kubebuilder and operator-sdk scaffold things, the abandoned code was reactivated when I added the machineset controller in the same package.

Moving this PR to the openshift repo: https://github.com/openshift/cluster-api-provider-baremetal/pull/52


feat: Fetch Node Executions directly if possible

lyft/flyte#438
This builds on the work from lyft/flyteadmin#111 to directly query NodeExecution children for NodeExecutions which use the new isParent flag. Most of the work was in the useChildNodeExecutions and useExecutionDataCache hooks to use the right logic for building a query for the node_executions endpoint.

Codecov Report

Merging #109 into master will increase coverage by 0.67%.
The diff coverage is 97.77%.

@@            Coverage Diff             @@
##           master     #109      +/-   ##
==========================================
+ Coverage   69.37%   70.04%   +0.67%
==========================================
  Files         383      383
  Lines        6299     6337      +38
  Branches      986      997      +11
==========================================
+ Hits         4370     4439      +69
+ Misses       1929     1898      -31

Impacted Files
Coverage Δ

.../components/Executions/Tables/NodeExecutionRow.tsx
97.77% <ø> (+6.66%)
:arrow_up:

src/components/Executions/types.ts
100.00% <ø> (ø)

src/models/AdminEntity/types.ts
100.00% <ø> (ø)

.../components/Executions/TaskExecutionsList/utils.ts
92.85% <87.50%> (-7.15%)
:arrow_down:

...onents/Executions/Tables/NodeExecutionChildren.tsx
100.00% <100.00%> (+60.00%)
:arrow_up:

src/components/Executions/Tables/RowExpander.tsx
100.00% <100.00%> (+28.57%)
:arrow_up:

src/components/Executions/Tables/constants.ts
100.00% <100.00%> (ø)

...rc/components/Executions/useChildNodeExecutions.ts
97.61% <100.00%> (+25.20%)
:arrow_up:

src/components/Executions/useExecutionDataCache.ts
87.91% <100.00%> (+9.86%)
:arrow_up:

src/components/Executions/utils.ts
78.18% <100.00%> (+1.48%)
:arrow_up:

... and 7 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update a5a9240...4ae688e. Read the comment docs.

:tada: This PR is included in version 0.14.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


(PUP-6702) Correctly manage paused Windows services

jenkins please test this on windows10ent-64a,windows10ent-32a,windows2008r2-64a,windows2012r2-64a,windows2012r2_ja-64a%7Blocale=ja%7D,windows2016-64a

CLA signed by all contributors.


Yii2 AssetBundle. Remover jquery v2.1.3 and replace jquery v1.11.0

Hello, i have create widget (editor widget). In my widget can run on jquery v1.11.0. But yii2 load jquery v2.1.3.
So i recive result "Uncaught TypeError: undefined is not a function". That problem will solve when i remover v2.1.3 in web/assets folder
But my app must run jquery v2.1.3 in another action so i can't remover it in config. So now i want remover   2.1.3 in my widget and replace by v1.11.0.
How can i do!
Thanks!

You need this: http://www.yiiframework.com/doc-2.0/guide-structure-assets.html#customizing-asset-bundles


Add support for Python 3.9

Summary
Python 3.9.0 was released on 10-05-2020, this commits marks the support
of Python 3.9 in qiskit-ignis. It adds the supported python version in
the package metadata and updates the CI configuration to run test jobs
on Python 3.9.
Details and comments
Missing support:

[x] qiskit-terra (https://github.com/Qiskit/qiskit-terra/pull/5189)
[x] numpy
[x]  scipy

Marking this on hold because we'll add this after the next release. Also need to wait for CI to comeback to see which dependencies need to be updated.

This should be good to go now. The only place we don't have coverage with this PR is windows on 3.9. This is because to run in CI we need to build aer from source (since it hasn't had a release with 3.9 support yet, but master has it). However, configuring ci to build aer from source on windows is more trouble than its worth so we can just wait to add that job until after aer releases.

This should be good to go now. The only place we don't have coverage with this PR is windows on 3.9. This is because to run in CI we need to build aer from source (since it hasn't had a release with 3.9 support yet, but master has it). However, configuring ci to build aer from source on windows is more trouble than its worth so we can just wait to add that job until after aer releases.


Wrong series returned from _curve

There is some bug in https://github.com/EthicalML/xai/blob/master/xai/init.py#L962
it was written as
r1s = r2s = []

but should be instead
r1s, r2s = [], []

The impact is that if the user would like to us r1s and r2s returned to construct the the curve (e.g. for storing the data for later analysis), they would find that r1s and r2s are referring to the same instance which stores all the curve data that should have been separately stored in r1s and r2s

Interesting - thank you for flagging, would you be interested on opening a PR @chen0040 ?


Inside Out File I/O f functionality is broken

The Inside Out File I/O functionality is broken.
This is shown by the Workload Tutorial Phase 3 File I/O, which used to work:
https://github.com/hyperledger/avalon/tree/master/docs/workload-tutorial
In Phase 3 after modifying the "hello world" program, it is supposed to create a file and return a key.
It returns a key, but the file is never created.
After typing:
The decrypted response is supposed to be:
Decrypted response:
[{'index': 0, 'dataHash':
'D040AFA0D78276BAFD1360A6170D7EB53446731F25E0F77343A07EEE3628731A',
'data': 'Hello jack [1]', 'encryptedDataEncryptionKey': '', 'iv': ''}]
Instead it is:
Decrypted response:
[{'index': 0, 'dataHash':
'D040AFA0D78276BAFD1360A6170D7EB53446731F25E0F77343A07EEE3628731A',
'data': 'Hello jack []', 'encryptedDataEncryptionKey': '', 'iv': ''}]
And NO file is created (that is, no file /tmp/tutorial/jack and no file in directory /tmp/tutorial/ ).
I was debugging the program and found iohandler_enclave.cpp TcfExecuteIoCommand() returns TCF_ERR_UNKOWN (-1), which is converted to 0xFFFFFFFF.  Looking at TcfExecuteIoCommand, that appers to occur when ocall_Process() throws a unknown exception.

Here is output from the command line. I modified the program to return an error string when WriteFile fails:
$ sudo docker exec -it avalon-shell bash
root@6b9bcdf039cc:/project/avalon# examples/apps/generic_client/generic_client.py -o \
>     --uri "http://avalon-listener:1947" \
>     --workload_id "hello-world" --in_data "jack"
[23:56:57 INFO    __main__] ******* Hyperledger Avalon Generic client *******
[23:56:57 INFO    __main__]
 Worker lookup response: {
    "result": {
        "totalCount": 1,
        "lookupTag": "e974449d8f929edaa5a93c1a473ae5124388d751ec5990f0c93e379a4bebe4a3",
        "ids": [
            "e974449d8f929edaa5a93c1a473ae5124388d751ec5990f0c93e379a4bebe4a3"
        ]
    },
    "id": 31,
    "jsonrpc": "2.0"
}

[23:56:57 INFO    __main__]
 Worker retrieve response: {
    "result": {
        "workerType": 1,
        "organizationId": "aabbcc1234ddeeff",
        "applicationTypeId": "11aa22bb33cc44dd",
        "details": {
            "workOrderSyncUri": "http://localhost:8080",
            "workOrderAsyncUri": "http://localhost:8080",
            "workOrderPullUri": "http://localhost:8080",
            "workOrderNotifyUri": "http://localhost:8080",
            "receiptInvocationUri": "http://localhost:8080",
            "workOrderInvocationAddress": "",
            "receiptInvocationAddress": "",
            "fromAddress": "",
            "hashingAlgorithm": "SHA-256",
            "signingAlgorithm": "SECP256K1",
            "keyEncryptionAlgorithm": "RSA-OAEP-3072",
            "dataEncryptionAlgorithm": "AES-GCM-256",
            "workOrderPayloadFormats": "JSON-RPC",
            "workerTypeData": {
                "verificationKey": "-----BEGIN PUBLIC KEY-----\nMFYwEAYHKoZIzj0CAQYFK4EEAAoDQgAEb3Dc5gkFMMTXvpppAPOZBZ2hLc6cfZvr\nMVW/WZVBMxZI31YYDI8E/yTHuiDl67S3jgym9SE1GHlj4jWXtPGs5Q==\n-----END PUBLIC KEY-----\n",
                "extendedMeasurements": [
                    "DEADBEEF00000000DEADBEEF0000000000000000000000000000000000000000",
                    "AFAE1D46D8967C39260B1B96E4194661EDF3C2F2031418906B44D7AD65D038A3"
                ],
                "proofDataType": "TEE-SGX-IAS",
                "proofData": "",
                "encryptionKey": "-----BEGIN RSA PUBLIC KEY-----\nMIIBCgKCAQEAyWcy2i+AK5S1I1rBYpGvSRW58xie7XK37BKUHLBmLcUei8HCvo9U\nR02HHagZrCUdevoJlI8oRB08jYtv2dDV4VIsi3wdJDtjNoeXAtONWTkDhauV1TiN\nRZkNPd6JOWyz7sb/euVN7leVhuWoToUfg64G4n7eDp2I3caRIDg2xrRzdu9GX0+k\nOA8irHQPTV8e+QxBnrIpCq+PJfqSb7XJzSXqPiTplg46UEM0ZHd1EA/uGLJ9S5X/\nsYV4MQZKRcKb+TXJNGg/0r9fkVB9txZ3ATgEwRSqMa1N4CmmuYUw24PsipaNqjZT\nblr9Cn4pjZ6wESGzV7VGvxhnhDKYiwFp9QIDAQAB\n-----END RSA PUBLIC KEY-----\n",
                "encryptionKeySignature": ""
            }
        },
        "status": 1
    },
    "id": 32,
    "jsonrpc": "2.0"
}

[23:56:57 INFO    avalon_sdk.worker.worker_details] *********Updating Worker Details*********
[23:56:57 INFO    avalon_sdk.worker.worker_details] Hashing Algorithm : SHA-256
[23:56:57 INFO    avalon_sdk.worker.worker_details] Signing Algorithm : SECP256K1
[23:56:57 INFO    __main__] **********Worker details Updated with Worker ID*********
e974449d8f929edaa5a93c1a473ae5124388d751ec5990f0c93e379a4bebe4a3

[23:56:57 INFO    __main__] Work order submit request : {
    "jsonrpc": "2.0",
    "method": "WorkOrderSubmit",
    "id": 32,
    "params": {
        "workOrderId": "fa1777a9c64dad0e55a1fedaf16d7a0edc92755298cb6240f331bdcc265a4709",
        "responseTimeoutMSecs": 6000,
        "payloadFormat": "JSON-RPC",
        "resultUri": " ",
        "notifyUri": " ",
        "workerId": "e974449d8f929edaa5a93c1a473ae5124388d751ec5990f0c93e379a4bebe4a3",
        "workloadId": "68656c6c6f2d776f726c64",
        "requesterId": "e1d361e77307fc9fc9228f0bdf39c11c7552d9b6aecc77860fee64d54a956481",
        "workerEncryptionKey": "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",
        "dataEncryptionAlgorithm": "AES-GCM-256",
        "encryptedSessionKey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
        "sessionKeyIv": "36FC81AB8DC4E7EB8E6FC6EF",
        "requesterNonce": "fe0332fec48ad1fce7884b0cb9205e9b",
        "encryptedRequestHash": "5F5DCE4E4B0529CE61942A69ADC7CE4FC120202D73A569943135BFCA7B484BF339A5934A218F5C38FA7C44EA01733D87",
        "requesterSignature": "",
        "inData": [
            {
                "index": 0,
                "data": "QLmGnmtT5aXacPIZncYJQ3BePY4="
            }
        ]
    }
},

[23:56:57 INFO    __main__] Work order submit response : {
    "error": {
        "code": 5,
        "message": "Work order is computing. Please query for WorkOrderGetResult                  to view the result"
    },
    "id": 33,
    "jsonrpc": "2.0"
}

[23:57:03 INFO    __main__] Work order get result : {
    "result": {
        "workOrderId": "fa1777a9c64dad0e55a1fedaf16d7a0edc92755298cb6240f331bdcc265a4709",
        "workloadId": "68656c6c6f2d776f726c64",
        "workerId": "e974449d8f929edaa5a93c1a473ae5124388d751ec5990f0c93e379a4bebe4a3",
        "requesterId": "e1d361e77307fc9fc9228f0bdf39c11c7552d9b6aecc77860fee64d54a956481",
        "workerNonce": "Z2STSST23dFfzweKC8wgaUlxtwPZTr2fW/qhHM/6z7Y=",
        "workerSignature": "MEQCIHAqRhFe+PmsREHV8X7CeDjZOppcYDD5oU8zUUj3AinUAiBGrz4lYNIJM2QKQEZWzhzoYVedgNRBircJuxSkOCrvIA==",
        "outData": [
            {
                "index": 0,
                "dataHash": "FD053FD3D186700121ADA65DC60C1F4E15585800656415FAD91B7D3DA1B6EDB3",
                "data": "Yr2JmWHdnBtjWOqVJZgAeaS60wAezmMgsXy1EjsCQSzo/7lgTkrE5pbu+gat0XyFZHK6DnGZywyo0A5KIpFuX7OqlkuVVo4DEHAZyA==",
                "encryptedDataEncryptionKey": "",
                "iv": ""
            }
        ]
    },
    "id": 34,
    "jsonrpc": "2.0"
}

[23:57:03 INFO    __main__] Signature verification Successful
[23:57:03 INFO    avalon_crypto_utils.crypto_utility] Decryption result at client - Hello jack [GetCountOrKey Error from WriteFile(1)4294967295]
[23:57:03 INFO    __main__]
Decrypted response:
 [{'index': 0, 'dataHash': 'FD053FD3D186700121ADA65DC60C1F4E15585800656415FAD91B7D3DA1B6EDB3', 'data': 'Hello jack [GetCountOrKey Error from WriteFile(1)4294967295]', 'encryptedDataEncryptionKey': '', 'iv': ''}]
root@6b9bcdf039cc:/project/avalon#

I get these error messages in the console:
avalon-enclave-manager    | File /tmp/tutorial/jack delete failed
avalon-enclave-manager    | File /tmp/tutorial/jack delete successful
avalon-enclave-manager    | Unable to open file /tmp/tutorial/jack
avalon-enclave-manager    |

I get these error messages in the console:
avalon-enclave-manager    | File /tmp/tutorial/jack delete failed
avalon-enclave-manager    | File /tmp/tutorial/jack delete successful
avalon-enclave-manager    | Unable to open file /tmp/tutorial/jack
avalon-enclave-manager    |

I tried reproducing the issue, but i didn't see "Unable to open file /tmp/tutorial/jack" error.
Also, i could see the file jack getting created in /tmp/tutorial path.
root@5fcb8f835da0:/project/avalon/scripts# ls -l /tmp/tutorial/
total 4
-rw-r--r-- 1 root root 40 Apr  8 08:11 jack
Did you create the folder /tmp/tutorial in enclave manager container before running the example workload?

Below are the outputs that were observed at client when the hello_world example was run.

First input request: examples/apps/generic_client/generic_client.py -o --uri "http://avalon-listener:1947" --workload_id "hello-world" --in_data "manju"

Response received:
Decryption result at client - Hello manju [E4F470D248527AA040236AF1643D12AC8E4822BB6403387A974BEFF185715BD0]
[08:39:01 INFO    main]
Decrypted response:
[{'index': 0, 'dataHash': '941FAACBD893AC87107BF302D86EE503E5BD9BC6B1EC84308C33ABFA6ADFB60F', 'data': 'Hello manju [E4F470D248527AA040236AF1643D12AC8E4822BB6403387A974BEFF185715BD0]', 'encryptedDataEncryptionKey': '', 'iv': ''}]

Subsequent request: examples/apps/generic_client/generic_client.py -o --uri "http://avalon-listener:1947" --workload_id "hello-world" --in_data "manju" "E4F470D248527AA040236AF1643D12AC8E4822BB6403387A974BEFF185715BD0"

Response received at the client:
[08:39:21 INFO    avalon_crypto_utils.crypto_utility] Decryption result at client - Hello manju [2]
[08:39:21 INFO    main]
Decrypted response:
[{'index': 0, 'dataHash': 'AC4BB43282C07CA1473DB0F2D25B5DE0409711B0CD37CB602668A3604DDF28D5', 'data': 'Hello manju [2]', 'encryptedDataEncryptionKey': '', 'iv': ''}]

The problem was the directory needed to be made from the Avalon Enclave Manager Docker Container.  That is:
sudo docker exec -it avalon-enclave-manager bash
mkdir /tmp/tutorial


Scala Common Enrich: BrowserLanguageEnrichment

This adds an enrichment to convert the browser language for an event into a human readable format. E.g. en-US becomes English, zh-cn becomes Chinese.

Hey @jramos! Thanks for this - exciting contribution.
A feedback point - although we make an exception for the IP anonymization enrichment, using configurable enrichments to mutate existing fields is not really The Snowplow Way. Instead, if this enrichment is enabled I would expect events to get a new context which includes maybe the general language family ("English") and the specific language variant ("Canadian English") - or whatever else is easily available...

Okay, I'll try to make the updates.

Thanks @jramos! We really appreciate the contribution :-)

closing as stale, feel free to reopen :+1:


[BUG] SUB CLUB BUGGY

🦄 Select your Profile

[ ] Streamer
[ ] User

⚙ Device

[ ] Phone
[ ] Computer

💾 System
None
🖥 Browser
None
📍 Where is the Bug?
None
🔗 Which page is it?
No response
ℹ Description
Varies of different reports from different sub club members.
majority of them do not see the sub club content, its all blurred out and when they click the content it brings them to subscription page even though they are.
some members sub club badges do not show up ( this also is happening to moderators, they are mods but the mod badge is gone along with there mod settings even though i checked on the dashboard and they are still an active mod)
sometimes new content shows up with just an error page.
🧨 How to reproduce
.
⚡ Expected Behavior
No response
😇 Anything else you could add?
Here some the usernames that have this issue that I can remember from the top of my head.
Sirz
MrKindaNiceGuy

Investigating

Hi @quincyentertainment, we fixed some errors we had with sub clubs last week, especially for the badges when the user is moderator + subscriber (they have to logout and login again for it to properly work).
I checked the 2 users you put in the comment and they are working fine. For them the issue seems to be solved.
If other users have the same issue, you can tell them to contact the Customer Support or send us their usernames if you prefer.

hello, the subclub member Sirz still has the same problem.

Going to take a look at it. Thanks for reporting it.

Hey! Hope all is well,
I'm sorry to that that they still have the same issue.

Hey! Hope all is well, I'm sorry to that that they still have the same issue.

Hi @quincyentertainment,
it seems our fix didn't work for those users.
We tested it with other users and it worked well for them.
Our customer support is going to reach out to them (Sirz and MrKindaNiceGuy) to try and solve the issue.
Thanks again for your time.

Hi @quincyentertainment We have reached out via email but have not received a response. We will email them again, but if you can let them know we are trying to reach them. So Sorry for the inconvenience!

Hello, So I have another member with the same issue
Quentin250
he sent me a video to show he cant access subclub content.
https://user-images.githubusercontent.com/125763737/227393604-b75353cf-9ab4-4105-a6ab-1406018b2f88.mp4


My Target to Support from 240

should i make                 double ratio = i / 300d;
as                 double ratio = i / 240d; to support from 240 or should i keep as is?
@elhanan-mishraky

Yes


[SPARK-42656][CONNECT] Adding SCALA REPL shell script for JVM client

What changes were proposed in this pull request?
Adding a simple script to start the Scala client in the Scala REPL. As well as a script to start the spark connect server for the client to connect to.
Why are the changes needed?
Make the JVM client more easy to be used.
Does this PR introduce any user-facing change?
No
How was this patch tested?
Manually tested.

Merging this.

Merged to master and branch-3.4.


feat: ui update for new flow

Description
ui change for new data flow:

removed all select models field
add magic button for generate

Fixes # (issue)
Type of change
Please delete options that are not relevant.

[x] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[x] This change requires a documentation update

we should add logic to check if model was existed on s3 bucket in hijacked generate function before calling the inference api

this logic is within the first api call:
            response = requests.post(f'{url}inference/v2', json=payload, headers={'x-api-key': api_key})


Add option to auto-disable if no .eslintrc

When I open a repo that doesn't use eslint, I get an obtrusive output error from this plugin, requiring me to manually disable it every single time.
It'd be really nice to have an option for this plugin to auto-disable itself if no .eslintrc is present in the repo (and/or if it's not in the dependencies)

This message is only shown once per new workspace. On the next open the output channel shouldn't come to front. You can alternatively disable eslint as a user setting and enable on the workspace you need to.

This message is only shown once per new workspace

Exactly. So when, for example, vscode restarts for an update, and I had 4 windows open, I'll get the error for each window, which gets annoying quick. This is especially noticeable because I use the vscode insiders build, which has daily updates.
The way vscode-standardjs handles this is a simple solution. Setting standard.usePackageJson (which is false by default) will tell the plugin to only enable itself if standard exists in your package.json.
I can make a PR if you're willing to accept that as a solution

@chrisdothtml in that example the message should be printed to the Output channel, but the channel shouldn't come to front. So it shouldn't be annoying.
Deciding if a valid eslint configuration file exists in a workspace is quite complicated since ESLint itself has many ways where such a configuration can be stored (e.g. .eslintrc.* file in any parent directory chain, a property in the package.json, ...).
This is why I stayed away from implementing this since it will put the ESLint extension into a catch-up game with the ESLint npm module (if they add a new method or a new lookup rule the extension has to provide this as well).
So what we could look at is adding a command to the output (e.g. via a command://... link) that when clicked disables the extension for this workspace.

in that example the message should be printed to the Output channel, but the channel shouldn't come to front

It does though; at least for me. Not sure if that's because we a different version of vscode or what.

Deciding if a valid eslint configuration file exists in a workspace is quite complicated

It doesn't check whether configuration is present, but rather the dependency. This is much more reliable because most projects won't work without it being in the dependencies. The only edge case is if eslint is globally installed, but in that case, the user can just leave this setting off

@chrisdothtml thanks for the clarification.
I tested it and on my machine using VS Code 1.23 and ESLint latest the Output channel comes only to front once. However the message is printed everytime.

@tell-y yes and no. In your setup the eslint server is still started. The feature request is to not start the server at all if there is no .eslintrc file.

What is the current status of this issue?

The problem is that ESLint has quite some locations where a eslint configuration can be stored. It is not only .eslintrc file in various directories but also package.json files. If we only want to check for .eslintrc.* files in the root directory then it is easy (see https://github.com/microsoft/vscode-eslint/blob/release/2.1.x/client/src/extension.ts#L838). But this will very likely not work for mono repos which became popular.

@dbaeumer Outside of checking for multiple locations, do you see any other cases that might block this?
I was also thinking maybe it's an optional toggle, and v1 could be just .eslintrc with the others to follow

The major problem is that this put the extension into a catchup with the ESLint library. If they add a new config location or a new way to define the config we need to honor this. This is why in general I stay away from this and such a feature can only go behind a flag and must be off by default.

Just saying, this would align with what prettier has:

I think I came here for this too.
I get an error message when I open a folder without node_modules directly under it, about a server not existing.
But I think it shouldn't have tried to start this server without a package.json in the first place. Typically, I'd use the eslint inside the repo for this.
For some reason, a global install of eslint does not seem to fix this.


Describe timer sample rate in metric_types docs. Fixes #435

Code does accept a sample rate for time metrics:
https://github.com/etsy/statsd/blob/bad366cd438cd59b2064dd03ff3d415fc7db0c4b/stats.js#L206-L225
At least one client sends these (Openstack Swift) and at least one
server implementation considers them malformed currently (collectd),
presumbaly due to the bad docs :)
Fixes #435

thanks for catching that!


Disable warnings

We should eventually turn this back off, of course, but for now: this adds the Rust directive that allows all warnings to the two crates that currently seem to be responsible for all the warnings. Dedicated to @Checkmate50!

Crap, I had to add some things and accidentally merged into the wrong branch (with my extra stuff).  Once #24 gets approved, then these won't be an issue, so I'll merge then (I can unroll the things and redo the changes, but it doesn't seem worth the effort).


Frontmatter plugins

Benefits of the new approach

It will allow me to upgrade the sharp library and fix #105. Currently blocked because no YAML transformer for gatsby will auto-transform paths in YAML files into images. By using markdown frontmatter instead I get this feature automatically.
Allows me to remove the custom transformer in the plugins directory. This is untested and hacky code which I can't maintain.
It's simpler to just have one file per plugin.

Drawbacks

Large frontmatter sections are unweildy from an editing perspective.

TODO

[x] Delete the plugin in the ./plugins directory.
[x] Get plugin logos working on the show page
[x] Check if the frontmatter of blog posts is polluted with irrelevant values. Might need to separate plugins out into a specialist query type ratner than the generl markdownRemark.
[x] Come up with a better way to set the to prop on the Link from the plugin index to show page. Currently works off name.
[x] Re-add back in all the plugins and migrate them to the new format.

Next up: https://github.com/gatsbyjs/gatsby/issues/6491


Cached linked wallets, using the entitlement cache to determine positive / negative ttl

Description
Cache linked wallets, busting the cache whenever an entitlement result for a principal comes back negative. This supports the UX where a user tries to join a channel / space, is denied, adds a linked wallet, and immediately tries again, but hopefully alleviates the high rpc call volume on base contracts for linked wallets during scrubbing.

https://github.com/river-build/river/pull/1635


Switch user to users group

story https://keboola.atlassian.net/browse/PS-24

You're very trusting :-).  I've chgrp'd the data folder just to be on the safe side.

not sure if that is a good idea - the Rserver might like to write something in there

It still can, it's all 7s

ok


A question about Dataset Update

Hi! When I read the paper, I have some questions about unlike NeRF, 3DGS does not use rays for training and we need to render full images, meaning we cannot have a mixed signal of edited images and un-edited images. Can you provide a detailed explanaion about it?

Sure! So in traditional NeRF training, individual rays are sampled from cameras in the training set, and then the NeRF is volumetrically rendered along the ray to get a color value for the pixel. Thus, for any given training iteration, a random batch of pixels_ can be sampled from all of the images in the training set, and the NeRF can be optimized on a per-pixel basis. Thus, this allows us to do a parallel "dataset update", where we update an individual image every so often, and then every NeRF optimization step, there will be a mixed set of pixels sampled from edited images and unedited images.
However, for GS, entire images must be rasterized at once, and the loss is computed on a per-image basis. Thus, it would not be possible to have a mixed set of edited signal and unedited signal in any given optimization step. Thus, we opt for an approach where a subset of images in the dataset are updated, and then the GS is optimized by randomly sampling entire images from the dataset, and over n iterations, some number of these iterations will optimize the GS using an edited image. Hopefully this answers your question

Thank you for your reply! I have understood what you mean, your answer is very helpful to me!


fix run constraint for cudatoolkit>=11.0

This attempts to fix #67  and #71.
According to https://docs.nvidia.com/deploy/cuda-compatibility/, cudatoolkit 11.X should run on all systems with __cuda 11.0-11.6. Similar to https://github.com/conda-forge/nvcc-feedstock/pull/71/files, the run_constraint is fixed.

Checklist

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

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

I tested the suggested changes and ran into problems. Apparently the PTX instructions were incompatible. That PTX incompatibility is  mentioned here: https://docs.nvidia.com/deploy/cuda-compatibility/#application-considerations.
As I understand, this is a requirement introduced by the nvcc part (and therefore not relevant here), but I am not a 100% sure.
In any case: once the compiled program contains PTX instructions, the run_constraint for that application MUST be as it was before __cuda => major.minor, even for versions >=11.X.
I am not sure the proposed change is safe

In any case: once the compiled program contains PTX instructions, the run_constraint for that application MUST be as it was before __cuda => major.minor, even for versions >=11.X.
I am not sure the proposed change is safe

In theory it's not safe, but I believe what the community previously landed on was that if a package is reliant on PTX it's that package's responsibility to pin the __cuda package appropriately to handle that. Otherwise, for packages without PTX there isn't really a path forward in allowing using older driver versions that should work fine. cc @jakirkham @leofang @isuruf to confirm

Would it be too much if the bot provided this information if compiler('cuda') is detected during linting?

What information?

That you should override the default run_exports if your project uses PTX.

That you should override the default run_exports if your project uses PTX.

Using compiler('cuda') doesn't necessarily mean you're using PTX. You can do a compilation without PTX.

That you should override the default run_exports if your project uses PTX.

Using compiler('cuda') doesn't necessarily mean you're using PTX. You can do a compilation without PTX.

True, but if I understand @jaimergp's point correctly we wanna give the PR reviewer a heads-up if potentially PTX could be generated/compiled in a feedstock. I think it's reasonable, though I wonder if it'd cause too much noise. We can move the discussion to conda-smithy, perhaps?

Yes, that was my question, thanks @leofang
It is about whether it would be too noisy to print this "hey pay attention if you are using PTX because this might bite you". I'll create an issue on conda-smithy for CUDA hints. I think we had more ideas around that too and we can brainstorm there.

I adjusted the PR with the requested changes. Also thanks for the clarification about the PTX instructions

Will let @jakirkham review before merging. Thanks @gabm!

Thanks @gabm for the PR and everyone for the reviews! 😄


"package humann-3.0.0 is excluded by strict repo priority"

Dear Nick,
Thank you so much for this tool. I tried the customized gtdb database (r202) in humann3 and It's improving my results by a lot.
Now, I'm trying to customize the last gtdb release (r207v2) using struo2. I managed to download everything and prepared the sample table and linked files. I also tested the snakemake dryrun mode and everything seems to be in order. However, when I run the pipeline using 5 genomes from the test data, I'm getting the following error:

CreateCondaEnvironmentException:
Your conda installation is not configured to use strict channel priorities. This is however crucial for having robust and correct environments (for details, see https://conda-forge.org/docs/user/tipsandtricks.html). Please configure strict priorities by executing 'conda config --set channel_priority strict'.

I changed it to strict priority and then, I'm getting this:

Creating conda environment bin/envs/humann3.yaml...
Downloading and installing remote packages.
CreateCondaEnvironmentException:
Could not create conda environment from /home/eortiz/Software/Struo2/bin/db_create/humann3/query/dmnd/../../../../envs/humann3.yaml:
Command:
mamba env create --quiet --file "/home/eortiz/Software/Struo2/.snakemake/conda/9ca7f54adf4ee41e2ed703f6dd2b2fc0.yaml" --prefix "/home/eortiz/Software/Struo2/.snakemake/conda/9ca7f54adf4ee41e2ed703f6dd2b2fc0"
Output:
Encountered problems while solving:
  - package humann-3.0.0-pyheec8a34_0 is excluded by strict repo priority
- --------------------------------------------
Any suggestions to fix this?
Thank you.

What is in your ~/.condarc? It should at least include:
channels:
  - conda-forge
  - bioconda


bump base version

@jacob-delgado: The following test failed, say /retest to rerun all failed tests:

Test name
Commit
Details
Rerun command

release-notes_istio_release-1.9
beb6d8669bc51340f6f524026fa8672d19c79f45
link
/test release-notes_istio_release-1.9

Instructions for interacting with me using PR comments are available here.  If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. I understand the commands that are listed here.

@jacob-delgado: The following test failed, say /retest to rerun all failed tests:

Test name
Commit
Details
Rerun command

release-notes_istio_release-1.9
beb6d8669bc51340f6f524026fa8672d19c79f45
link
/test release-notes_istio_release-1.9

Instructions for interacting with me using PR comments are available here.  If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. I understand the commands that are listed here.


Added free DSA course

What does this PR do?
Add Free DSA course
Why is this valuable (or not)?
This is 𝒇𝒓𝒆𝒆 𝒄𝒆𝒓𝒕𝒊𝒇𝒊𝒄𝒂𝒕𝒆 from 𝐆𝐨𝐨𝐠𝐥𝐞 by learning 𝐃𝐚𝐭𝐚 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐬 𝐚𝐧𝐝 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 with free practice material.
The course is available in four programming languages (Javascript, Java, C++ and Python)
How do we know it's really free?
Yes this course is by Google and free
For book lists, is it a book? For course lists, is it a course? etc.
Checklist:

[x] Read our contributing guidelines.
[x] Search for duplicates.
[x] Include author(s) and platform where appropriate.
[x] Put lists in alphabetical order, correct spacing.
[x] Add needed indications (PDF, access notes, under construction).
[x] Used an informative name for this pull request.

Follow-up

Check the status of GitHub Actions and resolve any reported warnings!

Hello @eshellman
Request you please review and merge the PR


Allow an easy way to create random PII/PHI data

In a project I'm working on, I'm working with AWS Comprehend to detect and redact PII data.
It would be nice if Datafaker could generate some explicit data including PII data, such as birth dates, full names, credit card data, medical records, etc.
Perhaps something like:
faker.pii().medical()
faker.pii().banking()
faker.pii().general()

or
faker.medical().phi()
faker.banking().pii()

Not sure yet, but the output should be something like:

Hello Zhang Wei, I am John. Your AnyCompany Financial Services, LLC credit card account 1111-0000-1111-0008 has a minimum payment of $24.53 that is due by July 31st. Based on your autopay settings, we will withdraw your payment on the due date from your bank account number XXXXXX1111 with the routing number XXXXX0000.
Customer feedback for Sunshine Spa, 123 Main St, Anywhere. Send comments to Alice at<EMAIL_ADDRESS>I enjoyed visiting the spa. It was very comfortable but it was also very expensive. The amenities were ok but the service made the spa a great experience.

(this is the AWS sample message).
I'll most likely build the above, but suggestions / feedback welcome.

how about the simplest way: put several suitable templates into yaml conf with expressions which during generation will be substituted with generated data?

Yes, I think something like that was going to be the approach. We have all the components to do generate the text already, just wasn't sure where to put it. And maybe it's not a good idea, maybe a custom faker is a much better solution anyway, since I think it's better if Datafaker provides the atomic elements, and tools around it focus on the composition of these fields, eg for the scenario I need it for. Thoughts?

yes, probably custom faker suits better here since the templates are a subject to be frequently changed. At the same time it might be useful to have something like that in doc examples


Numpad keys

https://developer.mozilla.org/en-US/docs/Web/API/KeyboardEvent/code/code_values
Missing Numpad* keys (NumpadEnter, NumpadMultiply, NumpadDecimal, NumpadEqual...)

Hi @GoGoris, thanks for opening an issue!
This enum is automatically generated by scraping this page: https://developer.mozilla.org/en-US/docs/Web/API/KeyboardEvent/key/Key_Values, so anything that doesn't appear on this page won't show up in the enum.
However, check out this section: https://developer.mozilla.org/en-US/docs/Web/API/KeyboardEvent/key/Key_Values#Numeric_keypad_keys.  Will these values work for your purpose?

Hi @nfriend,
Because of numerous reasons, people prefer to use the numpad for all numeric inputs in Belgium. For them there is no difference between Enter and NumpadEnter. They are not included in the link you sent. It looks like the documentation on MDN is not completely up to date?

Thanks @GoGoris, I took a little closer look at this.  Looks like NumpadEnter is a valid value for event.code.  However, this module is intended to be used with event.key.  From the README:

[This module] provides an enum with string values that correspond with the event.key values

It looks like the event.code value is Enter for both regular Enter and the Numpad Enter:

(Screenshot taken from https://keycode.info/ in Firefox.)
Based on this, I think it is correct that this module not include NumpadEnter.  Maybe the best way forward would be to create a new module that is intended to be used with event.code?
I'm going to close this for now, but I can reopen if you disagree 😄.  Thanks for opening an issue!

Thanks! I did not know that event.key also returns a string. This makes my code so much simpler :)

No problem, glad it simplified your code 😄


Wayland: segfault after dropping window

Repro:
extern crate winit;

fn main() {
    let mut events_loop = winit::EventsLoop::new();

    let mut window = winit::WindowBuilder::new()
        .build(&events_loop)
        .ok();

    events_loop.run_forever(|event| {
        match event {
            winit::Event::WindowEvent { event: winit::WindowEvent::Closed, .. } => {
                window.take();
            },
            _ => (),
        }
        winit::ControlFlow::Continue
    });
}

Valgrind:
==3984== Invalid read of size 8
==3984==    at 0x66058C0: wl_proxy_get_listener (in /usr/lib/libwayland-client.so.0.3.0)
==3984==    by 0x21FAD8: <wayland_client::generated::client::wl_surface::WlSurface as wayland_client::Proxy>::from_ptr_initialized (wayland_api.rs:3274)
==3984==    by 0x1CCB93: <wayland_client::generated::client::wl_keyboard::WlKeyboard as wayland_client::Implementable<ID>>::__dispatch_msg (wayland_api.rs:4708)
==3984==    by 0x1C6CB3: wayland_client::event_queue::dispatch_func::{{closure}} (event_queue.rs:343)
==3984==    by 0x1C29C4: std::panicking::try::do_call (panicking.rs:305)
==3984==    by 0x2A1F8E: __rust_maybe_catch_panic (lib.rs:102)
==3984==    by 0x1C26B5: std::panicking::try (panicking.rs:284)
==3984==    by 0x1CE021: std::panic::catch_unwind (panic.rs:361)
==3984==    by 0x1C4FA2: wayland_client::event_queue::dispatch_func (event_queue.rs:341)
==3984==    by 0x6605623: ??? (in /usr/lib/libwayland-client.so.0.3.0)
==3984==    by 0x66069B3: wl_display_dispatch_queue_pending (in /usr/lib/libwayland-client.so.0.3.0)
==3984==    by 0x2229E5: wayland_client::event_queue::EventQueue::dispatch (event_queue.rs:151)
==3984==  Address 0x8 is not stack'd, malloc'd or (recently) free'd

Running with WAYLAND_DEBUG=1 reveals the culprit:
[2853632.257] wl_keyboard@20.leave(4860, nil)

Okay, after discussions with the wayland devs on their IRC channels, while this case is deterministic here, it can actually not be distinguished from a specific kind of race in the protocol, which means I'll need to handle it in wayland-client. Not sure yet how I'll do that.
I'll integrate something to handle it in wayland-client 0.20, unless this specific issue needs a fix ASAP (looks like a pretty niche use, as a single-window app will likely just exit the event loop on Closed event), this will be fixed when I port winit to wayland-client 0.20.


Test upgrade with new upstream patch

This pull request is for testing an upstream commit and should not be merged.
This is to test the patch [1] does not break upgrades. This testing is in relation to issue https://github.com/rcbops/rpc-openstack/issues/1079.
[1] https://review.openstack.org/#/c/360385/

recheck_upgrade

Upgrade test passed.


ARTEMIS-1783 Remove need for guava in client

Refactor away from Guava memorize based on Guava Supplier to using java.util.Supplier and our own memorizer code.

@clebertsuconic @jbertram alternative to https://github.com/apache/activemq-artemis/pull/2081 so we don't have to increase client side dependencies.

@michaelandrepearce It looks fine to me: i haven't considered the client side deps on the past PR, sorry!

@franz1981 thanks for checking, will wait for @clebertsuconic and @jbertram to review also before we merge.

I like it better than my solution. +1

@michaelandrepearce We will have guava on artemis.commons... we would need to find a solution for those collections as well.

or just live with guava.

So guava was added client side only due to this change right. I think server side has had guava for a time. Concern I think is more about client dependencies not so much server side right?

@clebertsuconic removed guava entirely, and replaced either with Java Function equivalents (majority) or added a few extra bits in Artemis utils.

@michaelandrepearce nice one... we only need guava now for the CLI.. but that won't affect any runtime.. which is great!

@clebertsuconic where is it in the CLI, i must have not noticed, if you can point me to it,  ill try see what we can do there.

@michaelandrepearce io.airlift itself is using it.
I don't consider a big deal. this is not leaking to the server.


how to keep tab view on bottom while executing a card navigation transition?

I am using react-navigation with react-native-tab-view, since the tab view is in one React component, how do I navigate to another screen, keeping the tab view stationary at the bottom?

Wrap StackNavigator inside TabNavigator instead of TabNavigator inside StackNavigator

@satya164 I tried that in renderScene, but it says Failed prop type: Invalid prop childrensupplied toPagerScroll, expected a ReactNode

Here is the code for my renderScene, I pass this to the TabView prop renderScene
renderScene = ({ route }) => {     switch (route.key) {       case 'feed':         return createStackNavigator(           {             Feed: FeedScreen           },           {             initialRouteName: 'Feed',             headerMode: 'none'           }         );       case 'discover':         if (this.state.mounted.discover) {           return createStackNavigator(             {               Discover: DiscoverScreen             },             {               initialRouteName: 'Discover',               headerMode: 'none'             }           );         }         break; default:         return;

I got it, thanks!


Add bounds parameter to drop-files tray event

Would it be possible to pass the tray bounds data when files are dropped onto the tray?

Just to add, an alternative approach might be to add a tray.getBounds() method. I'm not sure of the difficulty in implementing either approach but tray.getBounds() might be a nicer approach because it can be used elsewhere (not just drop-files and click events).

It would be great if the drop-files event would default the tray window to be centered like it is with click and double-click. Looks related to gh-1543

Just to add, an alternative approach might be to add a tray.getBounds() method.

This was added in #6159 so I think this can be closed now since that API can be used from any tray event listener.


Add Wagtail Space NL 2022 banner to docs

Update of text and date to match the next upcoming event.
I also made the cookie name unique and moved it to a variable.
https://www.wagtail.space/2022/

👍


[QUESTION] Best practice or/and HOW-To do a HTTP Proxy

How to implement an HTTP PROXY with tsed?
I want all requests, unless we have a controller for it, to be redirected to a different server, but could not find any info on how to do that. I am planning to use http-proxy-middleware library with tsed. Thank you.

Hello @olegs-hl,
Here a simple example:

@Configuration({})
class Server {
   @Inject()
   app: PlatformApplication;

    $afterRoutesInit() {
       this.app.use('/api', createProxyMiddleware({ target: 'http://www.example.org', changeOrigin: true }));
    }
}

Then follow the documentation :) https://github.com/chimurai/http-proxy-middleware
See you
Romain

Hello @olegs-hl,
Here a simple example:

@Configuration({})
class Server {
   @Inject()
   app: PlatformApplication;

    $afterRoutesInit() {
       this.app.use('/api', createProxyMiddleware({ target: 'http://www.example.org', changeOrigin: true }));
    }
}

Then follow the documentation :) https://github.com/chimurai/http-proxy-middleware
See you
Romain


Datepicker callback function not called in Android

Using the example code, the success callback function never fires after selecting a time or date and pressing OK. When debugging the java file, I found that the onTimeSet and onDateSet functions in TimeSetListener and DateSetListener weren't being called.

+1
same thing here: Android 5.1.1

When I comment timeDialog.setButton() for BUTTON_POSITIVE on line 107 of DatePickerPlugin.java, the success callback is called as expected. Does the onTimeSet event need to be fired in that button's onClick event if it's being set manually?

I've got the same problem on Android 5.0.1

+1 on android 4.2.2 and up, using cordova 5.0.0 and Crosswalk 11

I'm working on that, thank you all.

Like ecthurlow said, I needed to call onDateSet and onTimeSet on click event of the buttons. I tested on devices Motorola 5.0.2 and Samsung 4.2.2, it worked fine. Tested on emulator 4.2.2 and 5.1.1 and it worked too.
These fixes are in Pull Request #96.


Tightened semantics of Dimension objects

This PR aims to address issue #843 and clean-up the definition of Dimension objects generally.
It is still work in progress and I've started this PR at the first commit just so that I can see the results of the notebook tests as I progress.
Edit: I have copied over the action items from the issue:

[x] Renaming the first argument from name to spec.
[x] Remove the deprecated 'initial' option from the values parameter.
[x] Declaring label as a parameter
[x] Allowing label to be passed as a kwarg and warning when ambiguous.
[x] Fixing the __call__ method, making it work with (name, label) tuples
[x] Aliased __call__ to clone.
[x] Implemented the spec property
[x] Update class docstring
[x] Updated equality semantics
[ ] Add more unit tests.

Looks good to me and I'm happy with the pprint.

Great!
I'm happy the tests have passed - I was worried there might be double specification of name somewhere. I'll now update the equality semantics and see if the tests still pass...
I am also considering making __str__ return only self.name so equality with strings makes sense. This means using pprint_label - which I would also consider aliasing to a nicer name, pretty, so it would be dim.pretty.

Rebasing against current master to get the push builds passing (pr builds are green).

The pr build has now passed for Python 3 and 3. I will now try to eliminate old uses of str(dim) and make sure pprint_label is used instead.

Rebasing again due to recent notebook test data updates.

Tests have passed and I think this PR is now ready to review.

@philippjfr  I've addressed your comments and the tests are passing. Any other suggestions for dimension improvements?

No, should I merge?

If you are happy with the changes, please do!


Bulk throttle

Issue #, if available:
a high failure rate in the bulk processing of PDF and PNG
Description of changes:
The bulk processor was feeding documents into DUS at a rate beyond its current capacity.  This was causing timeouts and also rate limit exceeded from services, especially ComprehendMedical which doesn't have currently a call "batching" feature.  At present, 2 calls per page need to be made to ComprehendMedical.  Rate limits are handled by retrying with an exponential backoff.
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

we can certainly give AWSRetry a go, in this commit I added it to the boto3 layer along with the other libraries,  then use in the comprehend helper.  Seems to be working in my preliminary tests so far,  but will give it more testing next.


fix(API): display of signature v in transaction

What this PR does / why we need it?
This PR adds chain_id to v in the return of eth_getTransactionByHash. It uses standard_v which is 0 or 1 previously, and now the v adds chain_id protection with the formula v = standard_v + chain_id * 2 + 35.
What is the impact of this PR?
No Breaking Change
PR relation:

Ref #1343

CI Settings

CI Usage
Tip: Check the CI you want to run below, and then comment /run-ci.
CI Switch

[x] E2E Tests
[x] Web3 Compatible Tests
[x] OCT 1-5 And 12-15
[x] OCT 6-10
[x] OCT 11
[x] OCT 16-19
[x] v3 Core Tests

CI Description

CI Name
Description

Chaos CI
Test the liveness and robustness of Axon under terrible network condition

Cargo Clippy
Run cargo clippy --all --all-targets --all-features

Coverage Test
Get the unit test coverage report

E2E Test
Run end-to-end test to check interfaces

Code Format
Run cargo +nightly fmt --all -- --check and cargo sort -gwc

Web3 Compatible Test
Test the Web3 compatibility of Axon

v3 Core Test
Run the compatibility tests provided by Uniswap V3

OCT 1-5 | 6-10 | 11 | 12-15 | 16-19
Run the compatibility tests provided by OpenZeppelin

/run-ci


Invalid issue 💩 , testing that Ocramius can find invalid issue so fast

Hey!

P.S It's only for fun, I am sorry if it's annoying you
Thanks

@ovr haha :D


Bug in Application->handleError

 /**
     * Handles exceptions and errors thrown by the request handler
     *
     * @param \Throwable|\Exception $exception
     * @return ResponseInterface
     */
    private function handleError(\Throwable $exception) : ResponseInterface
    {
        $response = $this->getErrorHandler()->handleException($exception);

        $this->trigger(self::EVENT_AFTER_REQUEST);
        $this->state = self::STATE_END;

        return $response->getPsr7Response();
    }

$this->getErrorHandler()->handleException() this is void method. it is not returned response

Thanks for the note. I'll take a look at this once I am able and provide a fix and update here.


Unable to download the BBC News dataset

Hi, I'm trying to train the model for classification on the BBC News dataset.
When I' visiting this link, getting the below error.
UserProjectAccountProblemUser project billing account not in good standing.The billing account for the owning project is disabled in state delinquent

Is there a plan to reinstate the dataset?
Also, can the weights of the model trained on this dataset be released?

The link should be working now.
I don't think we have the trained weights saved somewhere. We will post the links in this thread if available


I got error in PHPStorm

I use Doki theme v14.3.0.
PhpStorm 2020.3.3
Build #PS-203.7717.64, built on March 16, 2021
Runtime version: 11.0.10+8-b1145.96 amd64
VM: OpenJDK 64-Bit Server VM by JetBrains s.r.o.
Windows 10 10.0
Memory: 988M
Cores: 4
I got this IDE Fatal Error:
java.net.UnknownHostException: doki.assets.unthrottled.io 	at java.base/java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:220) 	at java.base/java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392) 	at java.base/java.net.Socket.connect(Socket.java:609) 	at java.base/sun.security.ssl.SSLSocketImpl.connect(SSLSocketImpl.java:289) 	at java.base/sun.net.NetworkClient.doConnect(NetworkClient.java:177) 	at java.base/sun.net.www.http.HttpClient.openServer(HttpClient.java:474) 	at java.base/sun.net.www.http.HttpClient.openServer(HttpClient.java:569) 	at java.base/sun.net.www.protocol.https.HttpsClient.<init>(HttpsClient.java:265) 	at java.base/sun.net.www.protocol.https.HttpsClient.New(HttpsClient.java:372) 	at java.base/sun.net.www.protocol.https.AbstractDelegateHttpsURLConnection.getNewHttpClient(AbstractDelegateHttpsURLConnection.java:203) 	at java.base/sun.net.www.protocol.http.HttpURLConnection.plainConnect0(HttpURLConnection.java:1232) 	at java.base/sun.net.www.protocol.http.HttpURLConnection.plainConnect(HttpURLConnection.java:1081) 	at java.base/sun.net.www.protocol.https.AbstractDelegateHttpsURLConnection.connect(AbstractDelegateHttpsURLConnection.java:189) 	at java.base/sun.net.www.protocol.http.HttpURLConnection.getInputStream0(HttpURLConnection.java:1592) 	at java.base/sun.net.www.protocol.http.HttpURLConnection.getInputStream(HttpURLConnection.java:1520) 	at java.base/java.net.HttpURLConnection.getResponseCode(HttpURLConnection.java:527) 	at java.base/sun.net.www.protocol.https.HttpsURLConnectionImpl.getResponseCode(HttpsURLConnectionImpl.java:334) 	at com.intellij.util.io.HttpRequests.openConnection(HttpRequests.java:630) 	at com.intellij.util.io.HttpRequests$RequestImpl.getConnection(HttpRequests.java:381) 	at com.intellij.util.io.HttpRequests$RequestImpl.getInputStream(HttpRequests.java:390) 	at io.unthrottled.doki.integrations.RestTools$performRequest$1.process(RestClient.kt:36) 	at io.unthrottled.doki.integrations.RestTools$performRequest$1.process(RestClient.kt:25) 	at com.intellij.util.io.HttpRequests.doProcess(HttpRequests.java:541) 	at com.intellij.util.io.HttpRequests.process(HttpRequests.java:523) 	at com.intellij.util.io.HttpRequests$RequestBuilderImpl.connect(HttpRequests.java:355) 	at io.unthrottled.doki.integrations.RestTools.performRequest(RestClient.kt:34) 	at io.unthrottled.doki.integrations.RestClient$performGet$1.call(RestClient.kt:18) 	at io.unthrottled.doki.integrations.RestClient$performGet$1.call(RestClient.kt:13) 	at com.intellij.openapi.application.impl.ApplicationImpl$1.call(ApplicationImpl.java:270) 	at java.base/java.util.concurrent.FutureTask.run(FutureTask.java:264) 	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128) 	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628) 	at java.base/java.util.concurrent.Executors$PrivilegedThreadFactory$1$1.run(Executors.java:668) 	at java.base/java.util.concurrent.Executors$PrivilegedThreadFactory$1$1.run(Executors.java:665) 	at java.base/java.security.AccessController.doPrivileged(Native Method) 	at java.base/java.util.concurrent.Executors$PrivilegedThreadFactory$1.run(Executors.java:665) 	at java.base/java.lang.Thread.run(Thread.java:834)
I don't know what was that.

:thinking: Hmm, does this link: https://doki.assets.unthrottled.io/backgrounds/wallpapers/yukino_dark.png not resolve for you?
I'll look into not having this exception bubble up.

I can open it. Maybe, somewhere in plugin I need VPN, so it's showing message like: Network refused, I need VPN.

:thinking: Hmm, well I have something set up in the code already if the asset cannot be resolved from https://doki.assets.unthrottled.io it tries to get the asset from https://github.com/doki-theme/doki-theme-assets
I assume that if you are using the sticker(s) and/or wallpaper(s) those are showing up, right?

Yes. I don't know, what is happened. Even now, the error is showed.

Everything works fine. Even now, the error is showed.

Okay, that's good. I'll have a fix out for the error that you reported shorty. Thanks for your understanding!


More interpolatable checks

Description
Relates to issue #4388. Note that this also bumps the expected fontTools revision to include recent changes in the interpolatable problem checker.
Checklist

[X] update CHANGELOG.md
[ ] wait for the tests to pass
[x] request a review

thanks, @simoncozens


Teleportation and controller selection are now webxr features features

Closing #7290
Teleportation and selection are now features that are a part of the default xr experience. to use it outside of the default experience (with typescript types):
const input = /* init babylon's xrInput class */
const pointerSelection = <WebXRControllerPointerSelection>featuresManager.enableFeature(WebXRControllerPointerSelection.Name, "latest", {
    xrInput: input
});

const teleportation = <WebXRMotionControllerTeleportation>featuresManager.enableFeature(WebXRMotionControllerTeleportation.Name, "latest", {
    floorMeshes: floorMeshes,
    xrInput: input
});
// connect both so that the selection will not be shown when teleportation is shown
result.teleportation.setSelectionFeature(result.pointerSelection);

To enable or disable, use the attach and detach functions:
const teleportation = <WebXRMotionControllerTeleportation>featuresManager.enableFeature(WebXRMotionControllerTeleportation.Name, "latest", {
    floorMeshes: floorMeshes,
    xrInput: input
}, false /* optionally do not auto-attach */);

// enabling it:
teleportation.detach();

//disabling it:
teleportation.attach()

Fantastic! can you fix the conflict and update the webxr doc? Thanks a ton!

I love resolving conflicts that I personally created :-)
I am planning on re-writing the doc at the end of this month, with everything done so far.


Feature/bulkimport

Form label "Select a file" needs to be updated.

Trying to upload two csv files on a new text classification project results in only one being imported. Second one fails with:
backend_1   | [14/Dec/2020 13:24:20] "POST /v1/projects/3/docs/upload HTTP/1.1" 201 0
backend_1   | Internal Server Error: /v1/projects/3/docs/upload
backend_1   | Traceback (most recent call last):
backend_1   |   File "/src/venv/lib/python3.6/site-packages/django/db/backends/utils.py", line 84, in _execute
backend_1   |     return self.cursor.execute(sql, params)
backend_1   | psycopg2.errors.UniqueViolation: duplicate key value violates unique constraint "api_label_project_id_text_8507ce37_uniq"
backend_1   | DETAIL:  Key (project_id, text)=(3, negative) already exists.

I think this is a race condition because both upload requests are send simultaneously. Uploading one after another works fine.

Test csv files for race condition. Project should not contain any labels before import.
text,label
"Terrible customer service.","negative"
"Really great transaction.","positive"
"Great price.","positive"

text,label
"bad day","negative"
"nice weather","positive"
"have fun","positive"

Test csv files for race condition. Project should not contain any labels before import.
text,label
"Terrible customer service.","negative"
"Really great transaction.","positive"
"Great price.","positive"

text,label
"bad day","negative"
"nice weather","positive"
"have fun","positive"

race condition is fixed now. please rebase on master and squash the commits.

race condition is fixed now. please rebase on master and squash the commits.


UX suggestion: click .livemd files to open them.

I've walked several new developers through setting up livebook and have experienced a consistent UX issue.
Developers open up their livebook.

Then they click the file they want to open.

Now they are stuck and don't know what to do. It's not entirely clear that the Open button relates to the selected file.
It's a consistent UX issue that I encounter while walking new developers through livebook. I think it's a stumbling block to adoption.
I suggest we open the .livemd file on the first click. However, that's just one approach to solve the core issue. There may be better solutions. This also means we need another method to fork files. (perhaps in the right-click dropdown?)
If there's any interest I'd be happy to open up a PR.

Hey @BrooklinJazz! We discussed it some time ago in #353. Also, while navigating the Open button is grayed out and when you select a file it becomes clickable, so it should be a fairly good indication.
Sidenote: we have plans to redesign the homepage and we will move the file selection to a modal, in which case the open button will be the only primary action, which should further clarify this.

That's awesome to hear! Thank you @jonatanklosko.
I agree that it should be, and once you know it it's a perfectly good UI. But, in practice, I see new folks get stuck.
Thank you!
Closing this issue then. 🙏


kitchen test Missing value for required option(s): ''client_name''

Is this a known error?
-----> Starting Kitchen (v1.8.0)
-----> Creating <cluster-master>...
       Bringing machine 'default' up with 'virtualbox' provider...
       ==> default: Importing base box 'ubuntu/wily64'...
==> default: Matching MAC address for NAT networking...
       ==> default: Checking if box 'ubuntu/wily64' is up to date...
       ==> default: Setting the name of the VM: kitchen-kubernetes-install-cluster-master_default_1466193966385_63533
       ==> default: Clearing any previously set forwarded ports...
       ==> default: Clearing any previously set network interfaces...
       ==> default: Preparing network interfaces based on configuration...
           default: Adapter 1: nat
           default: Adapter 2: hostonly
       ==> default: Forwarding ports...
           default: 22 (guest) => 2222 (host) (adapter 1)
       ==> default: Booting VM...
       ==> default: Waiting for machine to boot. This may take a few minutes...
           default: SSH address: <IP_ADDRESS>:2222
           default: SSH username: vagrant
           default: SSH auth method: private key
           default: Warning: Remote connection disconnect. Retrying...
           default: Warning: Remote connection disconnect. Retrying...
           default: Warning: Remote connection disconnect. Retrying...
           default:
           default: Vagrant insecure key detected. Vagrant will automatically replace
           default: this with a newly generated keypair for better security.
           default:
           default: Inserting generated public key within guest...
           default: Removing insecure key from the guest if it's present...
           default: Key inserted! Disconnecting and reconnecting using new SSH key...
       ==> default: Machine booted and ready!
       ==> default: Checking for guest additions in VM...
       ==> default: Setting hostname...
       ==> default: Configuring and enabling network interfaces...
       ==> default: Machine not provisioned because `--no-provision` is specified.
       [SSH] Established
       Vagrant instance <cluster-master> created.
       Finished creating <cluster-master> (0m58.18s).
-----> Converging <cluster-master>...
       Preparing files for transfer
       Preparing dna.json
       Resolving cookbook dependencies with Berkshelf 4.3.3...
E, [2016-06-17T22:06:42.147163 #8381] ERROR -- : Actor crashed!
ArgumentError: Missing value for required option(s): ''client_name''
        /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/ridley-4.5.1/lib/ridley/client.rb:57:in `validate_options'
        /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/ridley-4.5.1/lib/ridley/client.rb:124:in `initialize'
        /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/celluloid-0.16.0/lib/celluloid/calls.rb:26:in `public_send'
        /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/celluloid-0.16.0/lib/celluloid/calls.rb:26:in `dispatch'
        /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/celluloid-0.16.0/lib/celluloid/calls.rb:63:in `dispatch'
        /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/celluloid-0.16.0/lib/celluloid/cell.rb:60:in `block in invoke'
        /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/celluloid-0.16.0/lib/celluloid/cell.rb:71:in `block in task'
        /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/celluloid-0.16.0/lib/celluloid/actor.rb:357:in `block in task'
        /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/celluloid-0.16.0/lib/celluloid/tasks.rb:57:in `block in initialize'
        /opt/chefdk/embedded/lib/ruby/gems/2.1.0/gems/celluloid-0.16.0/lib/celluloid/tasks/task_fiber.rb:15:in `block in create'
>>>>>> ------Exception-------
>>>>>> Class: Kitchen::ActionFailed
>>>>>> Message: Failed to complete #converge action: [Missing value for required option(s): ''client_name'']
>>>>>> ----------------------
>>>>>> Please see .kitchen/logs/kitchen.log for more details
>>>>>> Also try running `kitchen diagnose --all` for configuration

@runningman84 have a look at my pull request and try out that branch. Ive been waiting for a code review and merge for ages, and its not happening, so im contemplating hard forking this, and re-writing it.


Adding dummy coveralls call in JS to trigger webhook

what does triggering the webhook do?

I was hoping it would turn the brown dot above to a green check mark somehow. Turns out it didn't...


Adapt for Zeus App with build in Tor pairing

https://twitter.com/ZeusLN/status/1353465407185637377?s=20

The manual process is described here; https://github.com/openoms/bitcoin-tutorials/blob/master/Zeus_to_RaspiBlitz_through_Tor.md

The MOBILE dialog is now using for Zeus Android & iOS the Tor connect. Further refactoring on the dialogs will be done on issue #2090 that will reorganize MOBILE into a CONNECT submenu.

Tested and works fine - with v1.7 Zeus will be Tor only by default.


TF 2.0: Can't use tf.keras.layers.LSTM on GPU.

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): YES
OS Platform and Distribution: Google Colab
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): tf-nightly-gpu-2.0-preview==2.0.0.dev20190218
Python version: 3.6.7
CUDA/cuDNN version: CUDA 10.0 CuDNN 7.4.2
GPU model and memory: ?

Describe the current behavior
Getting the following error when trying to fit a model using tf.keras.layers.LSTM with tf.keras:
---------------------------------------------------------------------------
UnknownError                              Traceback (most recent call last)
<ipython-input-30-145a5e1acc45> in <module>()
     18 model.fit(x=dataset,
     19           epochs=1,
---> 20           verbose=1)

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
    762           workers=0,
    763           shuffle=shuffle,
--> 764           initial_epoch=initial_epoch)
    765
    766     # Case 3: Symbolic tensors or Numpy array-like.

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, validation_freq, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
   1482         shuffle=shuffle,
   1483         initial_epoch=initial_epoch,
-> 1484         steps_name='steps_per_epoch')
   1485
   1486   def evaluate_generator(self,

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training_generator.py in model_iteration(model, data, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, validation_freq, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch, mode, batch_size, steps_name, **kwargs)
    244
    245       is_deferred = not model._is_compiled
--> 246       batch_outs = batch_function(*batch_data)
    247       if not isinstance(batch_outs, list):
    248         batch_outs = [batch_outs]

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py in train_on_batch(self, x, y, sample_weight, class_weight, reset_metrics)
   1226       else:
   1227         self._make_fit_function()
-> 1228         outputs = self._fit_function(ins)  # pylint: disable=not-callable
   1229
   1230     if reset_metrics:

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/backend.py in __call__(self, inputs)
   3207         value = math_ops.cast(value, tensor.dtype)
   3208       converted_inputs.append(value)
-> 3209     outputs = self._graph_fn(*converted_inputs)
   3210     return nest.pack_sequence_as(self._outputs_structure,
   3211                                  [x.numpy() for x in outputs])

/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py in __call__(self, *args, **kwargs)
    438       raise TypeError("Keyword arguments {} unknown. Expected {}.".format(
    439           list(kwargs.keys()), list(self._arg_keywords)))
--> 440     return self._call_flat(args)
    441
    442   def _filtered_call(self, args, kwargs):

/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py in _call_flat(self, args)
    507     # Only need to override the gradient in graph mode and when we have outputs.
    508     if context.executing_eagerly() or not self.outputs:
--> 509       outputs = self._inference_function.call(ctx, args)
    510     else:
    511       self._register_gradient()

/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py in call(self, ctx, args)
    295             attrs=("executor_type", executor_type,
    296                    "config_proto", config),
--> 297             ctx=ctx)
    298       # Replace empty list with None
    299       outputs = outputs or None

/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
     64     else:
     65       message = e.message
---> 66     six.raise_from(core._status_to_exception(e.code, message), None)
     67   except TypeError as e:
     68     if any(ops._is_keras_symbolic_tensor(x) for x in inputs):

/usr/local/lib/python3.6/dist-packages/six.py in raise_from(value, from_value)

UnknownError: Fail to find the dnn implementation.
	 [[{{node unified_lstm_8/CudnnRNN}}]]
	 [[loss_8/dense_12_loss/binary_crossentropy/weighted_loss/broadcast_weights/assert_broadcastable/is_valid_shape/else/_1/has_valid_nonscalar_shape/then/_47/has_invalid_dims/ExpandDims/_62]] [Op:__inference_keras_scratch_graph_9512]

Describe the expected behavior
It should train the model correctly. It is running on CPU.
Code to reproduce the issue
def create_model(vocab_size=10):
    model = tf.keras.Sequential([
        tf.keras.layers.Embedding(vocab_size, 80),
        tf.keras.layers.LSTM(64),
        tf.keras.layers.Dense(1, activation='sigmoid')
    ])
    return model

model = create_model(vocab_size=vocab_size)
model.compile(loss='binary_crossentropy',
              optimizer='adam',
              metrics=['accuracy'])

dataset1 = tf.data.Dataset.from_tensor_slices([[1, 2, 3], [4, 5,6]])
dataset2 = tf.data.Dataset.from_tensor_slices([1, 2])
dataset = tf.data.Dataset.zip((dataset1, dataset2))
model.fit(x=dataset,
          epochs=1,
          verbose=1)

Do you know where can we find tf.keras.layers.CuDNNLSTM in TF 2.0 ?
I did a search for my question and find your issue(related) at here.

@huan I believe tf.keras.layers.CuDNNLSTM will be deprecated in 2.0 in favor of tf.keras.layers.UnifiedLSTM.

Yes, I'm using a UnifiedLSTM, but I still can see the following error message, which suggest me to use the CuDNNLSTM.
Should we get rid of those message about the CuDNNLSTM ?
W0219 03:21:45.296270<PHONE_NUMBER>56256 tf_logging.py:161] <tensorflow.python.keras.layers.recurrent.UnifiedLSTM object at 0x7fee9331e198>: Note that this layer is not optimized for performance. Please use tf.keras.layers.CuDNNLSTM for better performance on GPU.

BTW I'm using tf.keras.layers.LSTM on GPU with TF 2.0 without any problem in the following environment:

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No
OS Platform and Distribution: 4.15.0-45-generic
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): tf-nightly-gpu-2.0-preview==2.0.0.dev20190218
Python version: 3.6.7
CUDA/cuDNN version: CUDA 10.0 CuDNN 7.4.2
GPU model and memory: GTX 1080, 8GB

I can't reproduce this in Colab, TF version '2.0.0-dev20190221'

@Threynaud Could you check with recent version of tf-nightly-gpu-2.0-preview-2.0.0.dev20190226? Please let us know how it progresses. Thanks!

I had the same issue. It turned out that I did not have cuDNN.
After installing cuDNN v<IP_ADDRESS> I no longer get this error.
TensorFlow version 2.0.0-dev20190310.

I think it was resolved. Closing due to lack of recent activity. Please open new ticket if you see similar issue. Thanks!

I had the same issue with Tensorflow 2.0.0-gpu-alpha version. After I reinstalled TF 2.0.0-nightly-gpu-dev040404 version it is resolved.

Came across this and want to give my opinion that somebody may find it helpful. According to TF2.0 documentation: https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/keras/layers/LSTM,
TF automatically selects which layer implementation to use, based on the available environment. If there are GPUs available and you want to use cuDNN implementation (aka "CuDNNLSTM" in v1), just make sure your LSTM layers meet the following arguments:
1. activation == 'tanh'
2. recurrent_activation == 'sigmoid'
3. recurrent_dropout == 0
4. unroll is False
5. use_bias is True
6. No use of masking.

This worked in my case. I've been using tf.keras.layers.LSTM from TF2.0 and it was very slow while I was using activation='relu', once I removed the activation (by default it uses tanh) the training improved a lot (from speed perspective, although in my case there wasn't any difference in performance/accuracy if using relu or tanh) .

@ljakupi Thanks for you tip. I changed to tf.keras.layers.LSTM and it indeed utilizes the GPU. But it seems the inner structure is different from CuDNNLSTM as my model performs worse when changed to tf.keras.layers.LSTM. Changed back to CuDNNLSTM (meanwhile back to tensorflow 1.13.1), it performs as before.
Or it might be related tensorflow 2.0 alpha? Not only LSTM thing?

@pennz I don't believe there is such change in the core that it impacts your end results this much! What is "performs worse" in your case, slower in training or worse in quality (accuracy or whatever metric you are using)?
Quick try: If your model in TF 1.13 performs better and you are using relu, try switching the activation to tanh and see if it has an impact in the performance in your TF 1.13 model. Since TF 2.0 LSTM uses tanh, it could be the case! I'm not sure about this since there can be many reasons, but try it, if you already didn't.

@pennz I don't believe there is such change in the core that it impacts your end results this much! What is "performs worse" in your case, slower in training or worse in quality (accuracy or whatever metric you are using)?
Quick try: If your model in TF 1.13 performs better and you are using relu, try switching the activation to tanh and see if it has an impact in the performance in your TF 1.13 model. Since TF 2.0 LSTM uses tanh by default, it could be the case! I'm not sure about this since there can be many reasons, but try it, if you already didn't.

@ljakupi Thanks for your remind, I will check with the tanh and relu thing, to make sure what makes the difference. The "performs worse" meant that the accuracy is worse. I will do more experiment for this.

@huan I believe tf.keras.layers.CuDNNLSTM will be deprecated in 2.0 in favor of tf.keras.layers.UnifiedLSTM.

Is this still the plan?

I know this is closed, but are there any good options right now to create a custom LSTM Cell that will use the GPU?  i.e. keras.layers.RNN(MyLSTMCell(units))  For example, what if I want to pass some custom states (calculated on the output of the cell) from an attention mechanism in time?
If I subclass LSTMCell I can do what I want, but I am forced onto the CPU.


Error: Unable to Extract uploader id

Checklist

[x] I'm asking a question
[x] I've looked through the README and FAQ for similar questions
[x] I've searched the bugtracker for similar questions including closed ones

Question

WRITE QUESTION HERE
I got this error code from a Discord Music Bot. I already did all the things it says i should do and so i thougt im gonna ask here if someone could help me:
ERROR: Unable to extract uploader id; please report this issue on https://yt-dl.org/bug . Make sure you are using the latest version; see  https://yt-dl.org/update  on how to update. Be sure to call youtube-dl with the --verbose flag and include its complete output.
Traceback (most recent call last):
File "C:\Python39\lib\site-packages\youtube_dl\YoutubeDL.py", line 815, in wrapper
return func(self, *args, **kwargs)
File "C:\Python39\lib\site-packages\youtube_dl\YoutubeDL.py", line 836, in __extract_info
ie_result = ie.extract(url)
File "C:\Python39\lib\site-packages\youtube_dl\extractor\common.py", line 534, in extract
ie_result = self._real_extract(url)
File "C:\Python39\lib\site-packages\youtube_dl\extractor\youtube.py", line 1794, in _real_extract
'uploader_id': self._search_regex(r'/(?:channel|user)/([^/?&#]+)', owner_profile_url, 'uploader id') if owner_profile_url else None,
File "C:\Python39\lib\site-packages\youtube_dl\extractor\common.py", line 1012, in _search_regex
raise RegexNotFoundError('Unable to extract %s' % _name)
youtube_dl.utils.RegexNotFoundError: Unable to extract uploader id; please report this issue on https://yt-dl.org/bug . Make sure you are using the latest version; see  https://yt-dl.org/update  on how to update. Be sure to call youtube-dl with the --verbose flag and include its complete output.
ERROR: Unable to extract uploader id; please report this issue on https://yt-dl.org/bug . Make sure you are using the latest version; see  https://yt-dl.org/update  on how to update. Be sure to call youtube-dl with the --verbose flag and include its complete output.
The Code is here:
`import discord
import os
import asyncio
import youtube_dl
Discord_Token = "X"
intents = discord.Intents.default()
intents.message_content = True
intents.members = True
client = discord.Client(intents=intents)
voice_clients = {}
yt_dl_opts = {'format': 'bestaudio/best', 'verbose': True}
ytdl = youtube_dl.YoutubeDL(yt_dl_opts)
ffmpeg_options = {'options': "-vn"}
@client.event
async def on_ready():
print(f"Bot logged in as {client.user}")
@client.event
async def on_message(msg):
if msg.author != client.user:
if msg.content.lower().startswith("!hi"):
await msg.channel.send(f"Hi, {msg.author.display_name}")
if msg.content.startswith("-play"):
    try:
        url = msg.content.split()[1]

        voice_client = await msg.author.voice.channel.connect()
        voice_clients[voice_client.guild.id] = voice_client

        loop = asyncio.get_event_loop()
        data = await loop.run_in_executor(None, lambda: ytdl.extract_info(url, download=False))

        song = data['url']
        voice_client.play(discord.FFmpegPCMAudio(song, **ffmpeg_options))
    except Exception as err:
        print(err)

if msg.content.startswith("-pause"):
    try:
        voice_client = voice_clients[msg.guild.id]
        if voice_client.is_playing():
            voice_client.pause()
    except Exception as err:
        print(err)

if msg.content.startswith("-stop"):
    try:
        voice_client = voice_clients[msg.guild.id]
        if voice_client.is_playing():
            voice_client.stop()
            del voice_clients[msg.guild.id]
            await voice_client.disconnect()
    except Exception as err:
        print(err)

if msg.content.startswith("-queue"):
    try:
        # Implement queue functionality here
        pass

    except Exception as err:
        print(err)

if msg.content.startswith("-np"):
    try:
        voice_client = voice_clients[msg.guild.id]
        if voice_client.is_playing():
            current_song = voice_client.source.title
            await msg.channel.send(f"Currently playing: {current_song}")
    except Exception as err:
        print(err)

client.run(Discord_Token)
`

Same issue here
youtube-dl --no-continue -f bestvideo[height<=720][fps=30]+bestaudio/best[height<=720] -o ./public/videos/1.mp4 --merge-output-format mp4 https://www.youtube.com/watch?v=4pQPtOJn38k
Video links:
https://www.youtube.com/watch?v=4pQPtOJn38k
https://www.youtube.com/watch?v=vZ6I13Hjv30

Same here:
> youtube-dl --verbose https://www.youtube.com/watch?v=YPrs3DqraWM

[debug] System config: []
[debug] User config: []
[debug] Custom config: []
[debug] Command-line args: ['--verbose', 'https://www.youtube.com/watch?v=YPrs3DqraWM']
[debug] Encodings: locale cp1252, fs utf-8, out utf-8, pref cp1252
[debug] youtube-dl version 2021.12.17
[debug] Python version 3.11.0 (CPython) - Windows-10-10.0.22621-SP0
[debug] exe versions: none
[debug] Proxy map: {}
[youtube] YPrs3DqraWM: Downloading webpage
ERROR: Unable to extract uploader id; please report this issue on https://yt-dl.org/bug . Make sure you are using the latest version; see  https://yt-dl.org/update  on how to update. Be sure to call youtube-dl with the --verbose flag and include its complete output.
Traceback (most recent call last):
  File "C:\Users\hunte\AppData\Roaming\Python\Python311\site-packages\youtube_dl\YoutubeDL.py", line 815, in wrapper
    return func(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\hunte\AppData\Roaming\Python\Python311\site-packages\youtube_dl\YoutubeDL.py", line 836, in __extract_info
    ie_result = ie.extract(url)
                ^^^^^^^^^^^^^^^
  File "C:\Users\hunte\AppData\Roaming\Python\Python311\site-packages\youtube_dl\extractor\common.py", line 534, in extract
    ie_result = self._real_extract(url)
                ^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\hunte\AppData\Roaming\Python\Python311\site-packages\youtube_dl\extractor\youtube.py", line 1794, in _real_extract
    'uploader_id': self._search_regex(r'/(?:channel|user)/([^/?&#]+)', owner_profile_url, 'uploader id') if owner_profile_url else None,
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\hunte\AppData\Roaming\Python\Python311\site-packages\youtube_dl\extractor\common.py", line 1012, in _search_regex
    raise RegexNotFoundError('Unable to extract %s' % _name)
youtube_dl.utils.RegexNotFoundError: Unable to extract uploader id; please report this issue on https://yt-dl.org/bug . Make sure you are using the latest version; see  https://yt-dl.org/update  on how to update. Be sure to call youtube-dl with the --verbose flag and include its complete output.

... I already did all the things it says i should do ....

Try again, try better: #30839.


start the Spyder with errors-AttributeError: module 'dateutil.tz' has no attribute 'UTC'

Description
What steps will reproduce the problem?

What is the expected output? What do you see instead?
Please provide any additional information below
AttributeError: module 'dateutil.tz' has no attribute 'UTC'
AttributeError: module 'dateutil.tz' has no attribute 'UTC'
Version and main components

Spyder Version: 3.2.3
Python Version: 3.6.2
Qt Versions: 5.6.2, PyQt5 5.6 on Windows

Dependencies
pyflakes >=0.6.0 :  1.6.0 (OK)
pycodestyle >=2.3:  2.3.1 (OK)
pygments >=2.0   :  2.2.0 (OK)
pandas >=0.13.1  :  1.0.1 (OK)
numpy >=1.7      :  1.18.1 (OK)
sphinx >=0.6.6   :  1.6.3 (OK)
rope >=0.9.4     :  0.9.4-1 (OK)
jedi >=0.9.0     :  0.10.2 (OK)
nbconvert >=4.0  :  5.2.1 (OK)
sympy >=0.7.3    :  None (NOK)
cython >=0.21    :  None (NOK)
qtconsole >=4.2.0:  4.3.1 (OK)
IPython >=4.0    :  6.1.0 (OK)
pylint >=0.25    :  1.7.2 (OK)

And Console shows “Kernel died, restarting”

And Console shows “Kernel died, restarting”

Duplicate of #11632

Please don't open several issues about the same problem for next time. It's a waste of time for us.