Appstudio update test-component-pac-jtvt

Pipelines as Code configuration proposal
To start the PipelineRun, add a new comment with content /ok-to-test
For more detailed information about running a PipelineRun, please refer to Pipelines as Code documentation Running the PipelineRun
To customize the proposed PipelineRuns after merge, please refer to Build Pipeline customization

Pipelines as Code CI/test-component-pac-jtvt-on-pull-request has successfully validated your commit.

StatusDurationName

✅ Succeeded
7 seconds
init

✅ Succeeded
21 seconds
clone-repository

✅ Succeeded
57 seconds
build-container

✅ Succeeded
45 seconds
inspect-image

✅ Succeeded
30 seconds
deprecated-base-image-check

✅ Succeeded
4 minutes
clair-scan

✅ Succeeded
1 minute
clamav-scan

✅ Succeeded
29 seconds
sbom-json-check

✅ Succeeded
10 seconds
label-check

✅ Succeeded
8 seconds
show-summary

✅ Succeeded
7 seconds
show-sbom

Pipelines as Code CI/test-component-pac-jtvt-on-pull-request has successfully validated your commit.

StatusDurationName

✅ Succeeded
7 seconds
init

✅ Succeeded
13 seconds
clone-repository

✅ Succeeded
47 seconds
build-container

✅ Succeeded
47 seconds
deprecated-base-image-check

✅ Succeeded
23 seconds
inspect-image

✅ Succeeded
19 seconds
clair-scan

✅ Succeeded
1 minute
clamav-scan

✅ Succeeded
11 seconds
sbom-json-check

✅ Succeeded
8 seconds
label-check

✅ Succeeded
8 seconds
show-sbom

✅ Succeeded
10 seconds
show-summary

Pipelines as Code CI/test-component-pac-jtvt-on-pull-request has successfully validated your commit.

StatusDurationName

✅ Succeeded
7 seconds
init

✅ Succeeded
13 seconds
clone-repository

✅ Succeeded
47 seconds
build-container

✅ Succeeded
23 seconds
inspect-image

✅ Succeeded
47 seconds
deprecated-base-image-check

✅ Succeeded
19 seconds
clair-scan

✅ Succeeded
1 minute
clamav-scan

✅ Succeeded
11 seconds
sbom-json-check

✅ Succeeded
8 seconds
label-check

✅ Succeeded
8 seconds
show-sbom

✅ Succeeded
10 seconds
show-summary


Add e2e tests for event sources

This has 2 dependencies:

A software framework for executing e2e tests, ideally BDD-based to be able to clearly express complex scenarios (Kubernetes uses Ginkgo)
The infrastructure to support running those tests, including a registry for storing temporary artifacts and a target environment for deploying them (to be defined)

Assigning myself. I'll write a demo test suite that uses Kubernetes's e2e testing framework:

Writing good e2e tests for Kubernetes
Kubernetes End-to-end Testing for Everyone

Closing this. The tests are written and only need to be executed in our infra.


(1216) Allow a workflow manager to reallocate an assessment

This follows on from #552 and adds service and client methods to allocate an assessment, as well as adding a controller method to call the allocation method and show a flash message to the user.
Screenshot

 Allow a workflow manager to reallocate an assessment


GitHub actions workflow for continuous integration

I have add continuous integration workflows using GitHub Actions for running R CMD check and tests and sending the results to Codecov. In particular, I used the usethis package functions to add the two github workflows to this R project. I was able to successfully run both check and tests and obtained badges and displayed in the README.md.


Make AnsatzSampling TransformUnoder compatible with array-valued oper…

…ators

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

0 of 1 (0.0%)  changed or added relevant line in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 67.377%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

src/AnsatzSampling.jl
0
1
0.0%

Totals

Change from base Build<PHONE_NUMBER>:
0.0%

Covered Lines:
316

Relevant Lines:
469

💛  - Coveralls


Area 51: Escape MissingNo. Style Graphical Glitch Happens in Level

So if you go back into the gas room after leaving it to the rest of the level with the clean air, the gas room causes the whole screen to have a MissingNo. style graphical glitch for 1 frame.

Should be fixed now. Wait for the autobuild to complete before trying, as usual.


Fix reference leak in ComparableTimSort

At the moment ComparableTimSort use a static temp array for performing the sort. The array is not clean up after sorting, therefore maintaining static references to the sorted objects.
This pull request simply mimics what is being done in TimSort which correctly cleanup these references after sorting.

What is the purpose of the tmpCount?

tmpCount holds the size of the array that is effectively used (it grows non linearly see ensureCapacity) to only set to null what is needed.
Note that the proposed change is just to sync with the fix that was added to TimSort for the same problem

Which one is the static temp array?

tmp is not static but ComparableTimSort is used statically by Sort. Sort is used internally inside LibGdx for example to implement Array.sort. Therefore, as soon of at least one call to sort is made, a static reference is created and persisted.
The tmp array is resized by jumping to next power of 2. It may jump to fairly igger than needed size (ot avoid frequent reallocation). The tmpCount avoids nulling out an oversized array ; it just null out the used part of the array.

Can you include a link to the source you based it on?

TimSort in com.badlogic.gdx.utils here. In particular, this commit from Nathan Sweet

Thanks!


Consider not using the term blacklist

https://inclusivenaming.org/word-lists/tier-1/whitelist/

Sorry for late response - just now saw this (apparently I don't get notifications for issues/PRs).
This has been adjusted already a while back. Thanks for bringing to my attention 👍


Option -stoponwatchdog not recognising docker proxy failure

Describe the bug
I am using ubuntu 22.04 with docker v27.0.3 [build 7d4bcd8] and latest docker-proxy v1.3.4. When we update docker, it might happen, that the socket vanishes for some time. I am using the -stoponwatchdog feature, but it will not detect that situation for days.
Here is a log example of it:
docker-proxy  | 2024/07/24 22:32:54 cron: panic running job: runtime error: invalid memory address or nil pointer dereference
docker-proxy  | goroutine 233 [running]:
docker-proxy  | github.com/robfig/cron.(*Cron).runWithRecovery.func1()
docker-proxy  | 	/home/runner/go/pkg/mod/github.com/robfig/cron@v1.2.0/cron.go:161 +0x69
docker-proxy  | panic({0xaad020, 0x10b18e0})
docker-proxy  | 	/opt/hostedtoolcache/go/1.18.10/x64/src/runtime/panic.go:838 +0x207
docker-proxy  | github.com/containrrr/watchtower/pkg/metrics.NewMetric({0x0, 0x0})
docker-proxy  | 	/home/runner/work/watchtower/watchtower/pkg/metrics/metrics.go:31 +0x22
docker-proxy  | github.com/containrrr/watchtower/cmd.runUpdatesWithNotifications(0xc00039f4e0)
docker-proxy  | 	/home/runner/work/watchtower/watchtower/cmd/root.go:377 +0x171
docker-proxy  | github.com/containrrr/watchtower/cmd.runUpgradesOnSchedule.func1()
docker-proxy  | 	/home/runner/work/watchtower/watchtower/cmd/root.go:325 +0xd2
docker-proxy  | github.com/robfig/cron.FuncJob.Run(0xc000355fd0?)
docker-proxy  | 	/home/runner/go/pkg/mod/github.com/robfig/cron@v1.2.0/cron.go:92 +0x1a
docker-proxy  | github.com/robfig/cron.(*Cron).runWithRecovery(0x5692f6?, {0xc7e060?, 0xc0001b61e0?})
docker-proxy  | 	/home/runner/go/pkg/mod/github.com/robfig/cron@v1.2.0/cron.go:165 +0x62
docker-proxy  | created by github.com/robfig/cron.(*Cron).run
docker-proxy  | 	/home/runner/go/pkg/mod/github.com/robfig/cron@v1.2.0/cron.go:199 +0x79f

To Reproduce
Set the following compose settings:
    image: wollomatic/socket-proxy:1
    restart: unless-stopped
    user: "65534:998"
    read_only: true
    cap_drop:
      - ALL
    security_opt:
      - no-new-privileges
    command:
      - '-loglevel=info'
      - '-allowhealthcheck'
      - '-allowfrom=<IP_ADDRESS>/0'
      - '-listenip=<IP_ADDRESS>'
      - '-allowGET=/v[0-9.]+/(containers|images)/.*'
      - '-allowPOST=/v[0-9.]+/(containers|images|networks)/.*'
      - '-allowDELETE=/v[0-9.]+/(containers|images|networks)/.*'
      - '-allowHEAD=.*'
      - '-watchdoginterval=30' # check for socket availability
      - '-stoponwatchdog' # halt program on error and let compose restart it
      - '-shutdowngracetime=5' # wait 5 seconds before shutting down
    healthcheck:
      test: ["CMD", "./healthcheck"]
      interval: 10s
      timeout: 5s
      retries: 2

and update docker. When another docker container is using this proxy, the error message appears.
Expected behavior
I would expect that the socker-proxy detects the problem with the docker socket, kills the process and let docker restart the container again.

Thanks for reaching out. Updating docker was indeed the reason I added the watchdog. I use a similar configuration and it works.
Could You please set the loglevel to debug? Then every watchdog action should be logged.
I'll try to reproduce the issue later. There's a docker update waiting on my test server anyway.

How's your docker daemon configured? Do you have live-restore enbled?

yes, live restore is active:
    "live-restore": true,

Here it works like it should:
dockerproxy-1  | time=2024-07-25T11:32:24.859Z level=DEBUG msg="checking socket availability" origin=checkSocketAvailability
dockerproxy-1  | time=2024-07-25T11:32:52.106Z level=INFO msg="httputil: ReverseProxy read error during body copy: unexpected EOF"
dockerproxy-1  | time=2024-07-25T11:32:54.860Z level=DEBUG msg="checking socket availability" origin=checkSocketAvailability
dockerproxy-1  | time=2024-07-25T11:32:54.860Z level=ERROR msg="socket is unavailable" origin=watchdog error="dial unix /var/run/docker.sock: connect: connection refused"
dockerproxy-1  | time=2024-07-25T11:32:54.860Z level=WARN msg="stopping socket-proxy because of unavailable socket" origin=watchdog
dockerproxy-1  | time=2024-07-25T11:33:00.079Z level=INFO msg="starting socket-proxy" version=1.3.4 os=linux arch=amd64 runtime=go1.22.5 URL=github.com/wollomatic/socket-proxy

Line 1 - successful check
Line 2 - problem occured due to Docker update
Line 3 - watchdog check
Line 4 - watchdog detects connectivity error
Line 5 - socket-proxy exits due to unsuccessful watchdog check
Line 6 - socket-proxy is restarted by Docker
That's my configuration:
  dockerproxy:
    image: wollomatic/socket-proxy:1.3.4
    restart: unless-stopped
    user: "65534:998"
    mem_limit: 64M
    read_only: true
    cap_drop:
      - ALL
    security_opt:
      - no-new-privileges
    command:
#      - '-loglevel=info'
      - '-loglevel=debug'
      - '-listenip=<IP_ADDRESS>'
      - '-allowfrom=traefik'
      - '-allowGET=/v1\..{1,2}/(version|containers/.*|events.*)'
#      - '-watchdoginterval=300'
      - '-watchdoginterval=30'
      - '-stoponwatchdog'
      - '-shutdowngracetime=5'
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock:ro
    networks:
      - docker-proxynet

I'm not really sure where your log excerpt in the first post comes from - I guess that's the output of Watchtower and not socker-proxy?

It is the log output of docker-proxy, but yes watchtower was using it.

This is weird, because socket-proxy does not use any external dependency like robfig/cron.
Also, any panic would terminate socket-proxy and lead to be restarted be Docker.
Could you please give me a bit more context of the log, or the complete compose file?
If you don't want to share it in public, feel free to send it to me via email<EMAIL_ADDRESS>

This is our compose file for the docker-proxy itself:
---
services:
  docker-proxy-watchtower:
    container_name: ${COMPOSE_PROJECT_NAME}-watchtower
    image: wollomatic/socket-proxy:1
    restart: unless-stopped
    user: "65534:998"
    read_only: true
    cap_drop:
      - ALL
    security_opt:
      - no-new-privileges
    command:
      - '-loglevel=debug'
      - '-allowhealthcheck'
      - '-allowfrom=<IP_ADDRESS>/0'
      - '-listenip=<IP_ADDRESS>'
      - '-allowGET=/v[0-9.]+/(containers|images)/.*'
      - '-allowPOST=/v[0-9.]+/(containers|images|networks)/.*'
      - '-allowDELETE=/v[0-9.]+/(containers|images|networks)/.*'
      - '-allowHEAD=.*'
      - '-watchdoginterval=30' # check for socket availability
      - '-stoponwatchdog' # halt program on error and let compose restart it
      - '-shutdowngracetime=5' # wait 5 seconds before shutting down
    healthcheck:
      test: ["CMD", "./healthcheck"]
      interval: 10s
      timeout: 5s
      retries: 2

    labels:
      # watchtower
      - "com.centurylinklabs.watchtower.enable=true"
      - "com.centurylinklabs.watchtower.scope=${COMPOSE_PROJECT_NAME}"

    networks:
      - docker-proxy_global

    volumes:
      - /var/run/docker.sock:/var/run/docker.sock

    deploy:
      resources:
          limits:
              memory: 64M

  watchtower:
    container_name: ${COMPOSE_PROJECT_NAME}-watchtower-app
    image: containrrr/watchtower:latest
    restart: unless-stopped

    depends_on:
      - docker-proxy-watchtower

    environment:
      TZ: Europe/Berlin
      DOCKER_HOST: tcp://docker-proxy-watchtower:2375
      WATCHTOWER_NO_STARTUP_MESSAGE: "true"
      WATCHTOWER_SCOPE: "${COMPOSE_PROJECT_NAME}"
      WATCHTOWER_LABEL_ENABLE: "true"
      WATCHTOWER_CLEANUP: "true"
      WATCHTOWER_TIMEOUT: 30s

    labels:
      # Watchtower
      - "com.centurylinklabs.watchtower.enable=true"
      - "com.centurylinklabs.watchtower.scope=${COMPOSE_PROJECT_NAME}"

    networks:
      - docker-proxy_global

    volumes:
      - /etc/localtime:/etc/localtime:ro
      - /etc/timezone:/etc/timezone:ro

    deploy:
      resources:
        limits:
          memory: 64M

networks:
  docker-proxy_global:
    external: true

# vim: syntax=yaml ts=2 sw=2 et sr softtabstop=2 autoindent

and this is another compose file in part, which is using this proxy for watchtower:
---

services:
  app:
    image: lukevella/rallly
    restart: unless-stopped
    depends_on:
      - postgres

    env_file:
      - .env

    networks:
      - default
      - traefik_global

    labels:
      - "traefik.enable=true"
      - "traefik.http.routers.${COMPOSE_PROJECT_NAME}.rule=Host(`some.app.com`)"
      - "traefik.http.routers.${COMPOSE_PROJECT_NAME}.entrypoints=websecure"
      - "traefik.http.routers.${COMPOSE_PROJECT_NAME}.tls.certresolver=letsencrypt_prod"
      - "traefik.http.routers.${COMPOSE_PROJECT_NAME}.middlewares=hsts-header@file"
      - "traefik.http.routers.${COMPOSE_PROJECT_NAME}.service=app-${COMPOSE_PROJECT_NAME}"
      - "traefik.http.services.app-${COMPOSE_PROJECT_NAME}.loadbalancer.server.port=3000"

      # watchtower
      - "com.centurylinklabs.watchtower.enable=true"
      - "com.centurylinklabs.watchtower.scope=${COMPOSE_PROJECT_NAME}"

    deploy:
      resources:
        limits:
          memory: 512M

  postgres:
    image: postgres:16
    restart: always
    volumes:
      - ./data/postgres:/var/lib/postgresql/data

    environment:
      POSTGRES_DB: ${PG_DATABASE}
      POSTGRES_USER: ${PG_USER}
      POSTGRES_PASSWORD: ${PG_PASSWORD}

    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U ${PG_USER}"]
      interval: 5s
      timeout: 5s
      retries: 5

    labels:
      # watchtower
      - "com.centurylinklabs.watchtower.enable=true"
      - "com.centurylinklabs.watchtower.scope=${COMPOSE_PROJECT_NAME}"

    deploy:
      resources:
        limits:
          memory: 256M

  watchtower:
    container_name: ${COMPOSE_PROJECT_NAME}-watchtower
    image: containrrr/watchtower:latest
    restart: unless-stopped

    environment:
      TZ: Europe/Berlin
      DOCKER_HOST: tcp://docker-proxy-watchtower:2375
      WATCHTOWER_NO_STARTUP_MESSAGE: "true"
      WATCHTOWER_SCOPE: "${COMPOSE_PROJECT_NAME}"
      WATCHTOWER_LABEL_ENABLE: "true"
      WATCHTOWER_CLEANUP: "true"
      WATCHTOWER_TIMEOUT: 30s

    labels:
      # watchtower
      - "com.centurylinklabs.watchtower.enable=true"
      - "com.centurylinklabs.watchtower.scope=${COMPOSE_PROJECT_NAME}"

    networks:
      - docker-proxy_global

    volumes:
      - /etc/localtime:/etc/localtime:ro
      - /etc/timezone:/etc/timezone:ro

    deploy:
      resources:
        limits:
          memory: 48M

networks:
  docker-proxy_global:
    external: true
  traefik_global:
    external: true

# vim: syntax=yaml ts=2 sw=2 et sr softtabstop=2 autoindent

Thank you. I've noticed one issue with the config. Please set the label "com.centurylinklabs.watchtower.enable"to false for the socket-proxy service. When Watchtower updates socket-proxy, Watchtower will loose its connection to the docker socket and fails to finish the update. Maybe this caused Watchtower to crash.
See https://github.com/wollomatic/socket-proxy/blob/b19b3d2658263d77b57b3a9bbea42c8ea418dcf2/examples/docker-compose/watchtower/compose.yaml#L27

I just did a docker update and could not see a problem. I also disabled the auto-update and changed to monitor-only. Maybe that does the trick.
      - "com.centurylinklabs.watchtower.enable=false"
      - "com.centurylinklabs.watchtower.monitor-only=true"

Sounds good :-)


As a developer I want Hydrate to scaffold a manifests directory

As a developer I want a place to put my namespace yams files. The Hydrate tool should create a manifests directory in the component.yaml output to support this. The tool should also tell me what I should guide me about what I should put inside of this directory.
Example:

name: "cloud-native"
generator: "static"
path: "./manifests"
subcomponents:
  - name: "elasticsearch-fluentd-kibana"
    source: "../fabrikate-elasticsearch-fluentd-kibana"
  - name: "prometheus-grafana"
    source: "../fabrikate-prometheus-grafana"
  - name: "istio"
    source: "../fabrikate-istio"
  - name: "kured"
    source: "../fabrikate-kured"

An example is here

To clarify, this issue involves the following steps (correct me if I'm wrong)

[ ] Add the path: "./manifests" attribute to the component.yaml file

[ ] Add comments guiding the user to create namespace.yaml files in the ./manifests directory


Oauth endpoints not created

Description
I followed the documentation here, and I cannot seem to get the oauth module working as is specified. In the docs, it says it sets up the following endpoints:

slack/oauth_redirect
slack/install

However, it appears neither is actually configured. I followed the default config (subbing in my own configs, of course), and have yet to see it return anything other than a cannot GET... message. Am I perhaps doing something wrong? Are the docs out of date or perhaps showing for a future release? I would love some guidance here.
What type of issue is this? (place an x in one of the [ ])

[x] bug?
[ ] enhancement (feature request)
[x] question
[x] documentation related
[ ] testing related
[ ] discussion

Requirements (place an x in each of the [ ])

[x] I've read and understood the Contributing guidelines and have done my best effort to follow them.
[x] I've read and agree to the Code of Conduct.
[x] I've searched for any related issues and avoided creating a duplicate issue.

Bug Report
Filling out the following details about bugs will help us solve your issue sooner.
Reproducible in:
package version: 2.2.3
node version: 14.4
OS version(s): Linux pop-os 5.4.0-7634-generic #38~1592497129~20.04~9a1ea2e-Ubuntu SMP Fri Jun 19 22:43:37 UTC  x86_64 x86_64 x86_64 GNU/Linux
Steps to reproduce:

Follow the docs
Attempt to set up redirect
Try to use oauth to authenticate
Cry :cry:

Expected result:
Authentication to work
Actual result:
Great sadness
Attachments:
Logs, screenshots, screencast, sample project, funny gif, etc.

 If so, the OAuth options (clientId, clientSecret, stateSecrect, etc) need to be passed to ExpressReceiver instead.
const receiver = new ExpressReceiver({
  signingSecret: process.env.SLACK_SIGNING_SECRET
  clientId: process.env.SLACK_CLIENT_ID,
  clientSecret: process.env.SLACK_CLIENT_SECRET
  stateSecret: 'my-state-secret',
  scopes: ['channels:read', 'groups:read', 'channels:manage', 'chat:write', 'incoming-webhook'],
  installationStore: {
    storeInstallation: async (installation) => {
      // change the line below so it saves to your database
      return await database.set(installation.team.id, installation);
    },
    fetchInstallation: async (InstallQuery) => {
      // change the line below so it fetches from your database
      return await database.get(InstallQuery.teamId);
    },
  },
});

const app = new App({
  receiver: receiver,
});

I am not. I just followed the instructions exactly. Is it required to define a custom receiver? I didn't need to do this to use the events endpoint.

@jparr721 it isn't required. It is just a common reason for people to run into issues.
I need a bit more info to help you debug. Can you share your code initializing App?
Once you start your bolt app in terminal, if you go to https://localhost:3000/slack/install in your browser, does it fail?

Yes, I get the cannot GET /slack/install message. Here is my code for initializing:
async function startSlackBot(): Promise<void> {
  const slackPort = dotenvValue(DotenvVariable.SlackPort, '8080');
  const slackClientId = dotenvValue(DotenvVariable.SlackClientId, '');
  const slackSigningSecret = dotenvValue(DotenvVariable.SlackSigningSecret, '');
  const slackbotUserSigningToken = dotenvValue(
    DotenvVariable.SlackbotUserSigningToken,
    '',
  );
  const organizationPrivateKey = dotenvValue(
    DotenvVariable.OrganizationPrivateKey,
    '',
  );

  const bot = new App({
    token: slackbotUserSigningToken,
    signingSecret: slackSigningSecret,
    clientId: slackClientId,
    stateSecret: organizationPrivateKey,
    scopes: ['channels:history', 'reactions:read', 'bot'],
    installationStore: {
      storeInstallation,
      fetchInstallation,
    },
  });

  await bot.start(slackPort);
}

@jparr721 you are missing clientSecret.  Try adding that and let me know if it works

@stevengill That seems to have worked flawlessly, to anyone copying my config, I also had to remove the token field. Very sorry about this mistake, thanks so much for taking the time to review my error.


Move maintainers to repo description?

"An opinionated guide to setting up STScI-owned GitHub repositories maintained by @spacetelescope/style-gurus "
Inspired by https://github.com/astropy/package-template/
p.s. I am talking about possibly removing CODEOWNERS file.

Move maintainers to repo description?

Can we not have it duplicated? The CODEOWNERS file can help identify reviewers/owners of specific style guides (see GitHub docs): https://help.github.com/articles/about-codeowners/

Oh I did not know about this feature. Thanks!

Duplicate is fine. Or feel free to close if this does not make sense.

I think about this more and agree that CODEOWNERS is more useful.


Run on a different dataset

Hello,
I want to integrate your approach into my project, so how can I use it on a different dataset?
is there a certain format for the dataset?

Hello @MayarOssama -- sorry for the very late reply. You can see through the generate_df function the three datasets that we use in the study represented as a pandas df with one row per sentence. You can simply modify this function to import your dataset with each sentence as a line in the table. Hope this helps!


Implement hoster vm migrate for simplified, manual VM fail-over

HA offers an easy and a fully automated way to fail-over the VMs from an offline node to a working one, but migrating these VMs back to the original node is a pain.
hoster vm migrate will automate that process:

it will pause the scheduler, so there are no snapshot/replication conflicts
it will replicate the latest changes using OpenZFS replication
it will stop the VM
it will perform one more replication to ensure the changed data is copied (since the VM was live, there could be still some changes in the queue)
it will use the REST API call to the remote host to change the VM's parent and start it, when the migration is finished
it will unpause the scheduler, so it can continue working as normal

Closing this issue as "would not implement". Automated VM and Jail migration will be provided by the WebUI (where you can more easily click around and perform few actions at once).
You can still migrate the VM/Jail over to another system within a CLI, but the process is a bit more involved:

Replicate the VM/Jail to another host
Stop the VM/Jail, and remove the automatic replication job for it
Execute hoster vm cireset or hoster jail cireset on the new host, in order to change the IP address and add the new SSH keys
Alternatively (if the "external" network is used), execute hoster vm set parent to switch the VM/Jail from being a backup to a regular VM/Jail mode
Start the VM/Jail on a new host
Apply the firewall rules, change loadbalancer IPs, etc
Done


ci: add updater

Same as https://github.com/deco-cx/deco/pull/618

Please take a look at the following pull request for a demo: https://github.com/boywithkeyboard/deco-apps/pull/1


Contribute to MrKrishnaAgarwal/Wordle Clone

Hey,
Thanks for being here
I want suggestions on:

How to add more words
How to make it accurate
How to make it better

Asmi You can close this issue,
This was just a To-Do List,
If you are an viewer, let me tell you, I transferred this repo to a random person :)


Improve performance

After I changed pooling layer from RoI Pooling to RoI Align, training time take longer abount 2x.

Could you improve the computing time?

Hi,
I checked forward/backward computation time by this script. (not strict one)
times are roughly same.
https://github.com/katotetsuro/roi_align/blob/master/test_performance.py
At practical case, RoIAlign is about 10% slower than RoIPooling in training of my implementation of MaskRCNN
https://github.com/katotetsuro/chainer-maskrcnn
Caffe2 implementation might be better than mine. It starts from for each RoI loop.
https://github.com/caffe2/caffe2/blob/master/caffe2/operators/roi_align_gradient_op.cu

Thank you for you reply.
I think if you want to measure gpu time of roi align, you should synchronize gpus.
I usually measure gpu time like below.
https://github.com/yukitsuji/Yolo_v2_chainer/blob/master/utils/timer.py

Thanks! I'll check later.


Error when I open integrated terminal on macOS

VSCode Version: 1.16.1
OS Version: 10.12.6 (Sierra)

Error: The terminal process command /bin/false -l failed to launch (exit code: 1)
Steps to Reproduce:

Open integrated terminal
Verify that error pops up at top of the screen.

Workaround:
Seems that /bin/false wasn't a file on my computer. There was /usr/bin/false, but using that path in settings still gave the same error.
In the end I overwrote the default settings for the integrated terminal to be "terminal.integrated.shell.osx": "bash" and then it launched as normal.

Reproduces without extensions: Yes
Related Issues?:
https://github.com/Microsoft/vscode/issues/14528
https://github.com/Microsoft/vscode/issues/14768

This happens in some enterprise environments when they change $SHELL to /bin/false to try to prevent usage. You can try adding this to your settings:
"terminal.integrated.shell.osx": "/bin/bash"

If that doesn't work I suggest contacting your sysadmin.


Multiple code improvements - squid:S1192, squid:S1213, squid:S1488, squid:S2293, squid:UselessParenthesesCheck

This pull request is focused on resolving occurrences of Sonar rules
squid:S1192 - String literals should not be duplicated.
squid:S1213 - The members of an interface declaration or class should appear in a pre-defined order.
squid:S1488 - Local Variables should not be declared and then immediately returned or thrown.
squid:S2293 - The diamond operator ("<>") should be used.
squid:UselessParenthesesCheck - Useless parentheses around expressions should be removed to prevent any misunderstanding.
You can find more information about the issue here:
https://dev.eclipse.org/sonar/rules/show/squid:S1192
https://dev.eclipse.org/sonar/rules/show/squid:S1213
https://dev.eclipse.org/sonar/rules/show/squid:S1488
https://dev.eclipse.org/sonar/rules/show/squid:S2293
https://dev.eclipse.org/sonar/rules/show/squid:UselessParenthesesCheck
Please let me know if you have any questions.
George Kankava

@georgekankava
I agree with most of the change, except the logging message.

no response for a long time. close it.


[NEW]: Bittrex winds down operations in the US

Date
2023-03-31
Description
Bittrex winds down operations in the US due to "continued regulatory uncertainty".
Links
https://bittrex.zendesk.com/hc/en-us/articles/10080271948701
https://www.coindesk.com/policy/2023/03/31/crypto-exchange-bittrex-to-wind-down-us-operations-next-month/
https://www.businesswire.com/news/home/20230331005339/en/Bittrex-Statement-on-U.S.-Operations
Agreement

[X] I irrevocably agree to release my contribution under the CC-BY 3.0 License

Attribution name
YabosMcGee
Personal link
No response

https://web3isgoinggreat.com/?id=bittrex-crypto-exchange-to-close-us-operations


Copy ByteBufPair buffers when using with SSL (#2401)

The netty SSL handler uses a coalescing buffer queue, which modifies
the buffers used to queue the writes so that SSL_write can be given
larger chunks, thereby increasing the 'goodput'.
If we pass in a retained duplicate as we have been doing until now,
then later clients will be passed junk, as SSL will have modified cached
entry buffers.
This patch introduces a copying ByteBufPair encoder, which is only
used with SSL connections.

Issues reported to Netty:

https://github.com/netty/netty/issues/14069
https://github.com/netty/netty/issues/14068


PSI Library: Implement Sum (Statistic) (Rust)

depends on #14

gRPC Definition

[x] Write definition
[ ] Write comments/docs

Rust Runtime

[x] Write runtime
[ ] Implement tests
[ ] Write comments/docs

Rust Validator

[ ] Write validator
[ ] Implement tests
[ ] Write comments/docs

Python bindings

[ ] Create bindings
[ ] Implement tests
[ ] Write docs

R bindings

[ ] Create bindings
[ ] Implement tests
[ ] Write docs

first attempt in commit e8a066d8c9b6a0ede651549e3db07ef2faf61eeb

need to add Traits

docs/tests moved to #62, #63


Video freeze UI until video is loaded on IOS, scroll is stuck

Bug
Happy new year to all !
I am the creator of SoSkills app which is available on Apple and Android
SoSkills is a video sharing community application in the gaming ecosystem.
More info here https://soskills.io
Keep in mind user can swipe through videos on the Home page with FlatList as Instagram short, TikTok etc
When user swipe to the bottom, app is going to load new videos by doing a request to the server for having videos object from BDD with uri property which is the path of the video on Amazon, so the file is not get by my server but directly with react-native-video (uri is with https)
So when user swipe, new item in the Flatlist are rendered and Video component start to init video with new uri from Amazon.
Request take some time when there's an average connexion or bad connexion, UI will freeze, app will be stuck and user can't do anything on the app until video is loaded by react-native-video.
No hidden process or work is doing during the scroll, just react-native-video is blocking the JS thread and UI freeze
Platform

Android with Redmi Note 10S phone
IOS with Iphone 12 pro

Environment info

React native: 0.67.3
Library version: [v6.0.0-alpha.4]
Steps To Reproduce
Use average connexion or bad connexion which is the best scenario.
Create a FlatList with with 3 item where item is taking all the viewport so one item by viewport.
Get new data when item + 1 === item.length and get new data, ui will freeze.
Expected behaviour
UI with no freeze, scroll still possible even if Video component is loading the video as Android with their video player.
On Android, if video is not loaded, user has just to wait but if he wants to scroll he can, without being stopped.
Reproducible sample code
SoSkills is a private company, code is not open source so can't do that but i shared screenshot and video
Video sample
This example is done with my Iphone 12 pro on 4g which is average so if you don't have good connexion, it's really not good !
https://user-images.githubusercontent.com/3983160/210596138-0d291326-06ba-4cae-bfcc-85e260be4add.mp4

Hi !
Did you find a solution about this problem ? I got the same issue, tried many thing that not working.
Thanks! :)

For me I downgraded to 5.2.1 from 6.0.0-alpha.4 and every thing works well, till they release update to fix this problem

Hi
I have also facing the same issue with 6.0.0-alpha.4 and Did you find a solution about this problem ?

My solution was just to downgrade react-native-video to version 5.2.1 and everything works fine the freezing didn't happen again, it looks like the problem is coming from the new version of react-native-video

Same with version 6.0.0-alpha.1

any other solution? I can't downgrade because 6.0.0-alpha.5 fixed another problem for me

This solution, is working for me
https://github.com/react-native-video/react-native-video/issues/2744#issuecomment-1237459473

@zuluHumand be careful, it is not thread safe, that is why it has been reverted

facing this issue in (v6.0.0, v6.1.2) versions. In v6.0.0-alpha.7 it is working fine but there are other issues in this version and it is not stable.

I'm having the issue in (v6.0.0, v6.1.2) versions. In v6.0.0-alpha.7 it is working fine cannot go back since there are another issues in this version and I would like to use the stable one. I think this issue has to be re-opened since is happening on the latest stable releases

I'm having the issue in (v6.0.0, v6.1.2) versions. In v6.0.0-alpha.7 it is working fine cannot go back since there are another issues in this version and I would like to use the stable one. I think this issue has to be re-opened since is happening on the latest stable releases

Is it working fine with Android also???


add watson middleware for more efficient search index updates

During (re-)import findings are updated multiple times, triggering multiple updates of the watson search index (via post_save) signals.
Turns out django-watson provides a middleware to help with this. All updates to model instances are grouped / deduplicated and executed at the end of the request.
This saves 3 database queries per (created/updated) finding in an import.

seems awesome; have you been able to measure the gain or see any difference by tracking the sql requests issued?

Yes, using django-debug-toolbar. If only the auditlog had the same feature 😩


config => toml

Change current poorly made config system to toml
ref: https://github.com/ToruNiina/toml11 or https://marzer.github.io/tomlplusplus/index.html

https://github.com/AnimeIdiots/twrs-dpp/commit/9a2b1908f15ef447f25b6c246976e18af2cc0ae2


Fix/map in dashboards

After many updates to the new map it had broken the map in the dashboards. As we aren't certain exactly how we are going to integrate the two and what feature we want on the dashboards with the new map I have rolled the dashboards map back (now map-old inside the react components. This means we can build the new as we like and not have to worry about version v3 affecting production when we release the demo.

Add map-old
Integrate new Geostore provider back into old map
Fix some small bugs in the widget settings menu

This also allows us to put the new map on staging without any risk off affecting external pages.

@01painadam I think it's better if you review this one. We don't have to re-review the code just test the application.


[turborepo] @turbo/codemod migrate sets output for persistent/non-cacheable task

What version of Turborepo are you using?
1.8.2
What package manager are you using / does the bug impact?
pnpm
What operating system are you using?
Mac
Describe the Bug
When running pnpx @turbo/codemod migrate new outputs are added to a persistent and on-cached step, which seems antithetical to the purpose of those configs.

Expected Behavior
No outputs should be added to a persistent/non-cacheable task
To Reproduce
pnpx @turbo/codemod migrate
on a turbo.json that has
"dev": {
       "cache": false,
       "persistent": true,
}

Reproduction Repo
No response

Good catch @maschwenk - will fix. Thanks!

tl;dr, yes, you're exactly right.
For some more background - previously, if you left out outputs, we would add in defaults ("build/**/*", "dist/**/*") for you (https://github.com/vercel/turbo/pull/2712 | specific line).
Because of that, no outputs, and empty outputs weren't equivalent. We modified this in 1.7 (details) to make this more explicit, and as part of this changed, provided a codemod for users who were (likely unintentionally) relying on the default outputs we were setting under the hood.

@tknickman but just to clarify. Now that there is no default for outputs, outputs not set and outputs set to [] are now functionally the same? I mean maybe you save one method call or something, but the functional outcome is identical?


Openstack .novalocal hardcoded

Hello, this hardcode
https://github.com/CiscoCloud/microservices-infrastructure/blob/master/plugins/inventory/terraform.py#L252
https://github.com/CiscoCloud/microservices-infrastructure/blob/master/plugins/inventory/terraform.py#L253

negates custom config in /roles/common/defaults/main.yml
Spend 2 hours today trying to figure out why my cluster isn't working right

The value in defaults can be overridden with playbook vars.  Identified that the issue relies on dnsmasq role and is caused because of NetworkManager restart and the .novalocal setting in /etc/hostname. Setting the /etc/hostname to the proper hostname seems to resolve the issue.

any updates on this?


Possible minor bug

<input class="form-control" [cpPosition]="'bottom'" [(colorPicker)]="value" [value]="value"/>
Given the above and a default value in the text field, If I, before opening the color picker once,  select all text in the input field with the mouse and hit backspace (deleting it), I get an error:
error_handler.js:56 TypeError: Cannot read property 'setColorFromString' of undefined
at ColorPickerDirective.changeInput (color-picker.directive.js:91)
at Wrapper_ColorPickerDirective.handleEvent (/ColorPickerModule/ColorPickerDirective/wrapper.ngfactory.js:246)
at CompiledTemplate.proxyViewClass.View_ColorFieldComponent0.handleEvent_8 (/FormModule/ColorFieldComponent/component.ngfactory.js:144)
at CompiledTemplate.proxyViewClass. (view.js:664)
at HTMLInputElement. (dom_renderer.js:486)
at ZoneDelegate.webpackJsonp.1509.ZoneDelegate.invokeTask (zone.js:275)
at Object.onInvokeTask (ng_zone.js:260)
at ZoneDelegate.webpackJsonp.1509.ZoneDelegate.invokeTask (zone.js:274)
at Zone.webpackJsonp.1509.Zone.runTask (zone.js:151)
at HTMLInputElement.ZoneTask.invoke (zone.js:345)
If someone first clicked in the field, and then tries the same, you don't get the error. If you delete the characters one by one (same deal, initalizes a color picker view) you dont get the error.
The error only occurs when deleting all text of the text box without ever having seen the color picker dialog.

Same issue here.
The changeInput method is causing this, it is at line 104 in color-picker.directive.ts
I wanted to add a guard for the method but I can't make it compile with my changes.
changeInput(value: string) {
        if (this.dialog) this.dialog.setColorFromString(value, true);
}


Use both RealmSwift and Objective-C Realm in same project

I'm trying to use both RealmSwift and Objective-C Realm in same project
I'm working on a project written in Objective-C, and I'm migrating it to Swift part by part
objective-c models are based on Realm Objective-C, I want to make new models written in swift to use RealmSwift, I know I can use swift with Objective-C Realm but I don't want to
my plan is by the end of the migrating from objective-c to swift I will delete Realm Objective-C and use  RealmSwift only
any ideas on how I can achieve that ?

What you're asking for is not supported. To quote from the first paragraph of the [Realm Swift documentation]:

If you’re looking to use Realm from Objective‑C, or from mixed Objective‑C & Swift apps, please see Realm Objective‑C instead. The Realm Objective‑C and Realm Swift APIs are not interoperable and using them together is not supported.

I'd suggest using Realm Objective-C from Swift as you migrate your codebase to Swift, and then switching over to Realm Swift once your model classes are no longer accessed from Objective-C.


Missing manifest file from MISP feed

Hi David
Im trying to get your MISP feed, from within my own MISP installation, but it seems it requires a manifest.json file, which are not present.
Thanks in advance.

Sorry, my fault.
Fixed. Please, retry. Services has been restored.

Hi David.
Its up and running again. Thank you :) Closing the issue


setTextColor inconsistency

setTextColor accepts only gray or RGB values which is inconsistent with the other two color functions: setFillColor and setDrawColor.
A solution could be to remove setTextColor entirely and use setFillColor to set the text color as well (most drawing APIs work in that fashion) or to enable CMYK for text too.
See also: #754
A bonus would be to add support for spot colors: a single channel with a name (string, for example a Pantone name) and a RGB or CMYK equivalent for preview purposes.

#1397
@MrRio Is this merge-worthy?

I wrote a solution:
#1397
@MrRio Is this merge-worthy?

CMYK functionality not tested because i dont know how it should look correct...

@MrRio
I checked the reference and I think that the code is correct. Maybe it would be smarter to write a parser-method for the colors which unites the color parsing functionality from the three methods into one method. Probably if you want to use color-profiles (like requested  in #1393 ) the color parsing functionality should have the opportunity to see which color profile is used and convert e.g. RGB to CMYK on the fly even if the programmer uses RGB values and vice versa.
@ertdfgcvb
Can you check if this the solution works for you?

@arasabbasi
Thank you for the quick response and for your commits.
Probably a general parser for the color arguments is a good idea (for the sake of DRY)…
I'm not so sure about the implicit conversion: does the PDF spec allow mixed color spaces?
I think it should be up to the user to convert the colors "by hand" instead of some behind-the-scenes feature doing this… it could cause more issues than benefits.
Also: how do you explicitly specify the color space for a document in jsPDF? Is this even possible and / or necessary?

Well... tbh I would say, that specifying the color space at the beginning makes more sense than what is done now. Now it assumes that it is CMYK because all 4 parameters are used. But what if you want to implement transparency (PDF 1.4). You need an 4th parameter for the transparency. so in the long run you need some more control.

DRYed it up into a centeral colorString Function.
Added functionality to use css colornames.

When dealing with inks the "overprint" notion becomes quite important.
iText (a java PDF lib) handles this separately for stroke and fill (while drawing, not related directly to color)…
Also: API wise, this same library handles colors as objects: the user defines a color (CMYK / RGB / spot and gradients) with all the attributes and then uses it in the drawing calls… just some food for thought for v2 :)

You seem to know more about colors...
Can you probably check if this is working? I dont know how to see if the ICC is used #1417

I'd check it but I'm not able to build the library via npm.
I get this error:
npm WARN<EMAIL_ADDRESS>requires a peer of<EMAIL_ADDRESS><2 || ^2.1.0-beta || ^2.2.0 but none was installed. options.entry is deprecated, use options.input jspdf.js (2172:84) The 'this' keyword is equivalent to 'undefined' at the top level of an ES module, and has been rewritten
plus a few more lines like the above.

Solved by PR #1397
Merged on 11 January 2018
Will be part of next version.


PGP signatures

Could you please resign your latest release using GPG?
This is now a requirement for Arch Linux: https://www.archlinux.org/todo/use-gpg-signatures-and-https-sources/
Thanks in advance!

Releases are getting signed now, starting from v0.16.0


nndet prep_train fails using local Dockerfile

Hello,
When trying to run your Docker version of the nnDetection network:
cd src/picai_baseline/nndetection/training_docker/
docker build . --tag joeranbosma/picai_nndetection:latest

The preprocessing steps worked well but when running the Docker command of nndet prep_train:
docker run --cpus=6 --gpus='"device=0"' -it --rm \
        -v /workdir:/workdir \
        joeranbosma/picai_nndetection:latest nndet prep_train \
        Task2203_picai_baseline /workdir/ \
        --custom_split /workdir/nnUNet_raw_data/Task2203_picai_baseline/splits.json \
        --fold 0

I have the following error message:
=============
== PyTorch ==
=============

NVIDIA Release 20.12 (build 17950526)
PyTorch Version 1.8.0a0+1606899

Container image Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.

Copyright (c) 2014-2020 Facebook Inc.
Copyright (c) 2011-2014 Idiap Research Institute (Ronan Collobert)
Copyright (c) 2012-2014 Deepmind Technologies    (Koray Kavukcuoglu)
Copyright (c) 2011-2012 NEC Laboratories America (Koray Kavukcuoglu)
Copyright (c) 2011-2013 NYU                      (Clement Farabet)
Copyright (c) 2006-2010 NEC Laboratories America (Ronan Collobert, Leon Bottou, Iain Melvin, Jason Weston)
Copyright (c) 2006      Idiap Research Institute (Samy Bengio)
Copyright (c) 2001-2004 Idiap Research Institute (Ronan Collobert, Samy Bengio, Johnny Mariethoz)
Copyright (c) 2015      Google Inc.
Copyright (c) 2015      Yangqing Jia
Copyright (c) 2013-2016 The Caffe contributors
All rights reserved.

NVIDIA Deep Learning Profiler (dlprof) Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.

Various files include modifications (c) NVIDIA CORPORATION.  All rights reserved.
NVIDIA modifications are covered by the license terms that apply to the underlying project or file.

NOTE: MOFED driver for multi-node communication was not detected.
      Multi-node communication performance may be reduced.

NOTE: The SHMEM allocation limit is set to the default of 64MB.  This may be
   insufficient for PyTorch.  NVIDIA recommends the use of the following flags:
   nvidia-docker run --ipc=host ...

[#] Creating plans and preprocessing data
Traceback (most recent call last):
  File "/opt/conda/lib/python3.8/site-packages/pkg_resources/__init__.py", line 567, in _build_master
    ws.require(__requires__)
  File "/opt/conda/lib/python3.8/site-packages/pkg_resources/__init__.py", line 884, in require
    needed = self.resolve(parse_requirements(requirements))
  File "/opt/conda/lib/python3.8/site-packages/pkg_resources/__init__.py", line 775, in resolve
    raise VersionConflict(dist, req).with_context(dependent_req)
pkg_resources.ContextualVersionConflict: (packaging 20.4 (/opt/conda/lib/python3.8/site-packages), Requirement.parse('packaging>20.9'), {'shap'})

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/opt/conda/bin/nndet_prep", line 33, in <module>
    sys.exit(load_entry_point('nndet', 'console_scripts', 'nndet_prep')())
  File "/opt/conda/bin/nndet_prep", line 25, in importlib_load_entry_point
    return next(matches).load()
  File "/opt/conda/lib/python3.8/importlib/metadata.py", line 77, in load
    module = import_module(match.group('module'))
  File "/opt/conda/lib/python3.8/importlib/__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1014, in _gcd_import
  File "<frozen importlib._bootstrap>", line 991, in _find_and_load
  File "<frozen importlib._bootstrap>", line 975, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 671, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 783, in exec_module
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "/opt/code/nnDetection/scripts/preprocess.py", line 36, in <module>
    from nndet.planning import DatasetAnalyzer
  File "/opt/code/nnDetection/nndet/planning/__init__.py", line 2, in <module>
    from nndet.planning.experiment import PLANNER_REGISTRY
  File "/opt/code/nnDetection/nndet/planning/experiment/__init__.py", line 6, in <module>
    from nndet.planning.experiment.v001 import D3V001
  File "/opt/code/nnDetection/nndet/planning/experiment/v001.py", line 6, in <module>
    from nndet.ptmodule import MODULE_REGISTRY
  File "/opt/code/nnDetection/nndet/ptmodule/__init__.py", line 3, in <module>
    from nndet.ptmodule.base_module import LightningBaseModule
  File "/opt/code/nnDetection/nndet/ptmodule/base_module.py", line 24, in <module>
    import pytorch_lightning as pl
  File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/__init__.py", line 20, in <module>
    from pytorch_lightning import metrics  # noqa: E402
  File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/metrics/__init__.py", line 15, in <module>
    from pytorch_lightning.metrics.classification import (  # noqa: F401
  File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/metrics/classification/__init__.py", line 14, in <module>
    from pytorch_lightning.metrics.classification.accuracy import Accuracy  # noqa: F401
  File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/metrics/classification/accuracy.py", line 16, in <module>
    from torchmetrics import Accuracy as _Accuracy
  File "/opt/conda/lib/python3.8/site-packages/torchmetrics/__init__.py", line 14, in <module>
    from torchmetrics import functional  # noqa: E402
  File "/opt/conda/lib/python3.8/site-packages/torchmetrics/functional/__init__.py", line 14, in <module>
    from torchmetrics.functional.audio.pit import permutation_invariant_training, pit, pit_permutate
  File "/opt/conda/lib/python3.8/site-packages/torchmetrics/functional/audio/__init__.py", line 14, in <module>
    from torchmetrics.functional.audio.pit import permutation_invariant_training, pit, pit_permutate  # noqa: F401
  File "/opt/conda/lib/python3.8/site-packages/torchmetrics/functional/audio/pit.py", line 24, in <module>
    from torchmetrics.utilities.imports import _SCIPY_AVAILABLE
  File "/opt/conda/lib/python3.8/site-packages/torchmetrics/utilities/imports.py", line 22, in <module>
    from pkg_resources import DistributionNotFound, get_distribution
  File "/opt/conda/lib/python3.8/site-packages/pkg_resources/__init__.py", line 3239, in <module>
    def _initialize_master_working_set():
  File "/opt/conda/lib/python3.8/site-packages/pkg_resources/__init__.py", line 3222, in _call_aside
    f(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/pkg_resources/__init__.py", line 3251, in _initialize_master_working_set
    working_set = WorkingSet._build_master()
  File "/opt/conda/lib/python3.8/site-packages/pkg_resources/__init__.py", line 569, in _build_master
    return cls._build_from_requirements(__requires__)
  File "/opt/conda/lib/python3.8/site-packages/pkg_resources/__init__.py", line 582, in _build_from_requirements
    dists = ws.resolve(reqs, Environment())
  File "/opt/conda/lib/python3.8/site-packages/pkg_resources/__init__.py", line 775, in resolve
    raise VersionConflict(dist, req).with_context(dependent_req)
pkg_resources.ContextualVersionConflict: (packaging 20.4 (/opt/conda/lib/python3.8/site-packages), Requirement.parse('packaging>20.9'), {'shap'})
Traceback (most recent call last):
  File "/usr/local/bin/nndet", line 369, in <module>
    action(sys.argv[2:])
  File "/usr/local/bin/nndet", line 148, in nndet_prep_train
    subprocess.check_call(cmd)
  File "/opt/conda/lib/python3.8/subprocess.py", line 364, in check_call
    raise CalledProcessError(retcode, cmd)
subprocess.CalledProcessError: Command '['nndet_prep', '2203']' returned non-zero exit status 1.

However, if I use the version from Docker Hub:
docker pull joeranbosma/picai_nndetection:latest

docker run ... nndet prep_train will run without issue. I believe there might be an issue when installing the dependencies in the Dockerfile but I was not able to find what was causing the issue.
Best,
Alexandre

Hello Alexandre,
Thanks for pointing out this issue! You are indeed correct, the build throws the following error:
ERROR: After October 2020 you may experience errors when installing or updating packages. This is because pip will change the way that it resolves dependency conflicts.

We recommend you use --use-feature=2020-resolver to test your packages with the new resolver before it becomes the default.

tensorboard 2.12.0 requires protobuf>=3.19.6, but you'll have protobuf 3.14.0 which is incompatible.
requests 2.24.0 requires urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1, but you'll have urllib3 1.26.14 which is incompatible.
torchmetrics 0.11.1 requires torch>=1.8.1, but you'll have torch 1.8.0a0+1606899 which is incompatible.
shap 0.41.0 requires packaging>20.9, but you'll have packaging 20.4 which is incompatible.
docker 6.0.1 requires requests>=2.26.0, but you'll have requests 2.24.0 which is incompatible.
mlxtend 0.21.0 requires scikit-learn>=1.0.2, but you'll have scikit-learn 0.23.2 which is incompatible.

I've seen this error before, it's caused by the update of dependencies (e.g., mlxtend to version 0.21.0), where different dependencies have conflicts. I've been able to fix this error by fixing a bunch of dependencies to the exact version used in joeranbosma/picai_nndetection:latest:
mlxtend==0.19.0
tensorboard==2.11.0
requests==2.28.1
torchmetrics==0.7.3
docker==6.0.1
packaging==20.4
mlflow==1.30.0

I've updated the repository such that the latest version builds successfully: https://github.com/DIAGNijmegen/picai_baseline/tree/main/src/picai_baseline/nndetection/training_docker
Could you try again with the updated requirements.txt?

This indeed did the trick! This fix will be integrated in https://github.com/DIAGNijmegen/picai_baseline/pull/48.


PySide6 QTimer.timeout.connect does not work within QMainWidget, but in QApplication

Hi,
I've made a PySide6 GUI application with several QTimer objects within widgets.
If I execute the application with python, everything is fine. Also deployed with cx_freeze.
Now I've tried nuitka with following command:
python.exe -m nuitka --mingw64 --standalone test.py --plugin-enable=pyside6 --plugin-enable=pylint-warnings --follow-imports
The result does not work, since the methods connected to the timers are not executed. I've made 2 small examples you can find at the end.

Nuitka version, full Python version and Platform (Windows, OSX, Linux ...)

python -m nuitka --version

<IP_ADDRESS>
Python: 3.9.4 (tags/v3.9.4:1f2e308, Apr  6 2021, 13:40:21) [MSC v.1928 64 bit (AMD64)]
Executable: C:\Users\Bad\AppData\Local\Programs\Python\Python39\python.exe
OS: Windows
Arch: x86_64

How did you install Nuitka and Python

installed via pip. No venv

The specific PyPI names and versions

python -m pip freeze

PySide6==6.1.3

Also supply a Short, Self Contained, Correct, Example
Not Working Example QTimer within Widget:

#%%
import sys
from PySide6.QtWidgets import QApplication, QMainWindow
from PySide6.QtCore import QTimer

class MainWidget(QMainWindow):
    def __init__(self, parent=None):
        super(MainWidget, self).__init__(parent)
        self.timer = QTimer(self) #self
        self.timer.timeout.connect(self.update)
        self.timer.start(1000)
        self.count = 0

    def update(self):
        self.count += 1
        print ("update ",self.count)
        if self.count >5:
            self.timer.stop()
            self.close()

if __name__ == "__main__":
    app = QApplication(sys.argv)
    mymain = MainWidget()
    mymain.show()
    sys.exit(app.exec())

Expected output:
>test.exe
update 1
update 2
update 3
update 4
update 5
update 6

Working Example - QTimer within QApplication:
#%%
import sys
from PySide6.QtWidgets import QApplication
from PySide6.QtCore import QTimer

class MainApp(QApplication):
    def __init__(self, parent=None):
        super(MainApp, self).__init__(parent)
        self.timer = QTimer(self) #self
        self.timer.timeout.connect(self.update)
        self.timer.start(1000)
        self.count = 0

    def update(self):
        self.count += 1
        print ("update",self.count)
        if self.count >5:
            self.timer.stop()
            self.exit()

if __name__ == "__main__":
    app = MainApp(sys.argv)
    sys.exit(app.exec())

Any idea?
Best regards
Bastian

I would have not provided this request if both examples would work as they should. I've stripped everything down. Could there be any inference with other installed python modules?

The first example is not working for me under windows and - just tested - linux (ubuntu)

I spend the time, because I can see you are a diligent reporter, but if this wouldn't work, I think I should know. I was also using 3.9 like you are. Maybe you are having a hello world issue of some sorts, maybe you can use a git clone and run this:
python3.9 bin/compare_with_cpython Mini.py
and provide the output? That is my script used for testing, and it makes sure to compare outputs and use the same Python, etc.

of course, I can do it.
Mini.py is my example?

OK, here is the result for following example, fresh pyside6 install an different Windows10:
PS D:\Projekte\Nuitka> & C:/Users/xxx/AppData/Local/Programs/Python/Python39/python.exe bin/compare_with_cpython ../test1.py
Comparing output of '../test1.py' using 'C:\Users\xxx\AppData\Local\Programs\Python\Python39\python.exe' with flags  ...
********************************************************************************
CPython:
********************************************************************************
update  1
update  2
update  3
update  4
update  5
update  6
 ********************************************************************************
Nuitka:
********************************************************************************

Now the QWidget Window is open and it does nothing... Nothing is counted.
After closing the window, the diff is mentioned:
Nuitka-Options:INFO: Used command line options: --python-flag=no_warnings --full-compat --verbose-output=../test1.py.optimization.log --show-modules-output=../test1.py.inclusion.log --run ../test1.py
Nuitka:INFO: Starting Python compilation with Nuitka '0.6.17rc8' on Python '3.9' commercial None.
Nuitka:INFO: Completed Python level compilation and optimization.
Nuitka:INFO: Generating source code for C backend compiler.
Nuitka:INFO: Running data composer tool for optimal constant value handling.
Nuitka:INFO: Running C level backend compilation via Scons.
Nuitka-Scons:INFO: Backend C compiler: C:\Users\xxx\AppData\Local\Nuitka\Nuitka\gcc\x86_64\10.2.0-11.0.0-8.0.0-r5\mingw64\bin\gcc.exe (gcc.exe).
Nuitka-Scons:INFO: Compiled 10 C files using ccache.
Nuitka-Scons:INFO: Cached C files (using ccache) with result 'cache miss': 10
Nuitka:INFO: Keeping build directory 'test1.build'.
Nuitka:INFO: Successfully created 'test1.exe'.
Nuitka:INFO: Launching 'test1.cmd'.
 --- C:\Users\xxx\AppData\Local\Programs\Python\Python39\python.exe (stdout)
+++ nuitka (stdout)

@@ -1,7 +1 @@

-update  1
-update  2
-update  3
-update  4
-update  5
-update  6

Error, results differed (stdout).
PS D:\Projekte\Nuitka>

Instead the Cpython variant opens the window and close is after 6 seconds, counter is shown in the console afterwards.
The failing example is still the same:
#%%
import sys
from PySide6.QtWidgets import QApplication, QMainWindow
from PySide6.QtCore import QTimer

class MainWidget(QMainWindow):
    def __init__(self, parent=None):
        super(MainWidget, self).__init__(parent)
        self.timer = QTimer(self) #self
        self.timer.timeout.connect(self.update)
        self.timer.start(1000)
        self.count = 0

    def update(self):
        self.count += 1
        print ("update ",self.count)
        if self.count >5:
            self.timer.stop()
            self.close()

if __name__ == "__main__":
    app = QApplication(sys.argv)
    mymain = MainWidget()
    mymain.show()
    sys.exit(app.exec())

I've updated the testcode using an QLabel instead QMainWindow to have visual feedback.
The counter ticks with 500ms, so its faster ;)
The Qlabel window shows the counter.
#%%
import sys
from PySide6.QtWidgets import QApplication, QLabel, QMainWindow
from PySide6.QtCore import QTimer

class MainWidget(QLabel):
    def __init__(self, parent=None):
        super(MainWidget, self).__init__(parent)
        self.timer = QTimer(self) #self
        self.timer.timeout.connect(self.update)
        self.timer.start(500)
        self.count = 0

    def update(self):
        self.count += 1
        self.setText("update %s"% (self.count))
        print ("update ",self.count)
        if self.count >5:
            self.timer.stop()
            self.close()

if __name__ == "__main__":
    app = QApplication(sys.argv)
    mymain = MainWidget()
    mymain.show()
    sys.exit(app.exec())

This does it for me, thank you, but I am totally confused as to what the difference could be. But once I know the bug, maybe I can tell why it was working for me with the other example.

Thank you,
I've just double checked within a fresh installed linux VM (CinnamonMint) if the issue persists.
I'm somehow glad that the issue now shows up at your system. :)

I checked, and it seems that the update function is never called, while __init__ runs normally. As a QApplication, there is no issue for me, but you say there was for you, this might prove useful to explain why it happens.

A search and replace of update to update2 works around the issue. It seems QLabel has a update method, and that one is picked over the overload. Question becomes, if this a determistic thing or not. I was using python -m nuitka --run so I am having hashes determistic, that's a leftover from Nuitka process. it sets PYTHONHASHSEED=0 if not already option -R is used.
However, the QApplication doesn't have an update and sometimes I have executed the failing programs with bash afterwards, so this might be a false lead, although it would have explained different results. It might be a PySide6 issue of resolving the method. The self.update apparently is a compiled method object, even when it fails.
I will get in touch with Qt company and it probably needs to be debugged there. Can you confirm or deny that changing the name of the callback works for you?

I checked, and it seems that the update function is never called, while __init__ runs normally. As a QApplication, there is no issue for me, but you say there was for you, this might prove useful to explain why it happens.

No, with "QApplication", there is no issue for me, too. Sorry if my first post was misleading. I'm not an english native speaker.
I've made one "Not Working Example QTimer within Widget:" showing the bug and one working example with QAPplication, which is fine.

I've renamed the method called by timer timeout from def update(self): to def tmr_timeout(self):.
Now everything is working fine. Thanks! Sorry for your circumstances! That is my first python GUI project, and I've a lot to learn.
Now I need to doublecheck all my files :)

Well, that's of course not right. I am not sure it's a bug of yours, I am pretty sure it's one of ours, Nuitka and/or PySide6 here, but at least you now have a workaround. I cannot work on this right away, but it seems important, and so this will be dealt with eventually.
However, thanks for the good report, and sticking with me on this. :)

We now have a workaround for reference losses in connecting the slots with methods, that's another bug in PySide6 there.
And just doing this, workarounds this bug.
                  if func.im_func.__name__ == "update":
                      func.im_func.__name__ = "update_tmr"

I wish there was a way to know if a function name causes the issue. But for now, your example works when I add that out of the box.
I also can do this I guess
                  if not func.im_func.__name__.startswith("_pyside6_workaround_"):
                      func.im_func.__name__ = "_nuitka_" + func.im_func.__name__

That will affect tracebacks, but it will make PySide6 definitely not consider the signature of a base method.

So I put this on develop only, will be in 1.8 release. If any issue is caused by it, I would to catch it before putting it on stable, and it will potentially change behavior of programs.

So this issue is still open, and I find no trace of this being in the release, I am confused now.

Ah, I remember, first of all, the code was not good, doing it multiple times potentially:
                  if not receiver.im_func.__name__.startswith("_pyside6_workaround_"):
                      receiver.im_func.__name__ = "_nuitka_" + receiver.im_func.__name__

And then Qt was crashing, if you did this to some of their things, but there also never was a reason to do it for non-compiled functions, which it did, so I guess, this can come back in enhanced form for 2.0 then.

Thanks for your report, this is fixed on the factory branch, which is a development version under rapid development. You can try it out by going here: https://nuitka.net/doc/factory.html
Feedback if this is working is very welcome, just please do not share plans of doing it, but rather confirmations or denials of it working.

This is now on the develop and the commercial staging branch and part of the latest pre-release, will be part of the 2.0 release that will eventually follow.

This is part of the stable release 2.0 that I just made.


VMSS: confirmation on specify NOT latest as image version of specific Markplace image

az feedback auto-generates most of the information requested below, as of CLI version 2.0.62

VMSS
Pinning VMSS to a specific Marketplace image version may cause service outage in future. We have seen several support cases and sev2s because of this. Customers should pick "latest" as the image version whenever possible. This allows VMSS to auto upgrade when a newer version is available.
IaaS Portal automatically puts "latest" as the image version for any VMSS deployment from Marketplace. However, in Powershell and CLI, customers still have the option to specify version. We need to warn customers when they are deploying VMSS pinned to a specific image version from Azure Marketplace, and ask them to consider using "latest" as the image version.
Ask [Powershell and CLI]
Warn customers when they are deploying VMSS pinned to a specific image version from Azure Marketplace, and ask them to consider using "latest" as the image version.
https://docs.microsoft.com/en-us/powershell/scripting/developer/cmdlet/requesting-confirmation-from-cmdlets?view=powershell-7
https://msazure.visualstudio.com/One/_workitems/edit/5730841/

Reasonable ask

I have to warn that this request is a breaking change.
Azure CLI is not an interactive client. Most users use Azure CLI for automation. If we ask “Do you still want to proceed?” and wait for a response from user, it is a breaking change.
We must be careful.

hi @qwordy thanks for raising the good point! per communication with service team, they're ok to a warning message. Could you pls take care of this in this sprint? thanks.

But PLease, what is the Powershell/CLI command line to specify it musst use the "latest" image ??? please what is it ?

New-AzVmss   -ResourceGroupName "TEstScaleSet"
-VMScaleSetName "TestScaleSet"   -Location "southafricanorth"
-VirtualNetworkName "TestVnet"   -SubnetName "TestSubnet"
-version "latest"   -PublicIpAddressName "TestPubIP"
-LoadBalancerName "TestLB" `
-Credential $cred

Ive tried -imageversion "latest" ? and a few other, nothing seems to be valid ?

@DailyTech Hi, the command you give is PowerShell command. If it is a problem related to Azure PowerShell, please submit it to https://github.com/Azure/azure-powershell/issues
In addition, may I ask does CLI also have this issue? If so, please add --debug after the executed CLI command, and then send the printed information to me. My email address is<EMAIL_ADDRESS>


更新算法包

详见 https://github.com/weijianwen/SJTUThesis/issues/145

https://github.com/weijianwen/SJTUThesis/pull/150 @gaocegege


Password Reset

We have a means to Reset a Password

We send a request for a password reset with an Email address
If we have an user with that Email, we send an email with the token for resetting
2.1 The token is kept in a sql table and a BackgroundService is set to delete it in 15 minutes
The user opens the link in the email
The user changes their password (within the 15 minutes limit)

Pretty positive the token has to be hashed in the DB to make it more secure, but this will do for now
Closes #40

Know Issue: Bad Reset Email
Opening Issue #50


Added fix for non-working ellipses

Modified pagination to work with json object
Added display attribute for dynamic link creation text
Modified navigation to work with set id
Checked for ellipses and type to properly navigate
Fixed introduced previous button cycle behaviour

Issue created with js file - not sure what happened


Clarify daily measurements

Hi,
This looks good to me, please merge.
It would be nice to also add after your intro sentence: "Although participants are encouraged visually to supply all of the measures every day (see figure 2), participants can choose to skip specific measurements anytime or even choose to provide multiple instances of the same measure within a single day."
(where figure 2 is the screenshot you send earlier)
Additionally, at the end of the "Daily repeated measurement" section we should add:
"Measures are, as much as possible, based on existing and validated scales, see [x][x]." With [x] linking to

https://aacnjournals.org/ajcconline/article-abstract/7/3/200/6298/Validity-of-the-numeric-rating-scale-as-a-measure
https://www.sciencedirect.com/science/article/pii/S0012369215396793

I think then we are good to go!


remove GSAP from UMD version + webpack dev

[ ] Remove GSAP from the UMD version
[ ] Webpack dev

Close as solved with v2.0.0


Azure ML R Managed Endpoint Deployment fails: Deployment template language expression evaluation failed: 'Unable to evaluate language function 'concat'

Describe the bug
Command Name
az ml online-deployment create
Extension Name: ml. Version: 2.0.3.
Errors:
Code: InvalidTemplate
Message: Deployment template language expression evaluation failed: 'Unable to evaluate language function 'concat': all function arguments must be string literals, integer values, boolean values or arrays. Please see https://aka.ms/arm-template-expressions/#concat for usage details.'. Please see https://aka.ms/arm-template-expressions for usage details.

To Reproduce:
Steps to reproduce the behavior. Note that argument values have been redacted, as they may contain sensitive information.

Build custom Dockerfile and push it to the Workspace Container Registry
Prepare R inference script, endpoint.yml and deployment.yml
Deploy Managed Online Endpoint using az ml online-endpoint create
az ml online-deployment create -n {} --endpoint {} -f {} -w {} -g {}

Expected Behavior
The deployment should succeed and the endpoint should be reachable
Environment Summary
Linux-5.11.0-41-generic-x86_64-with-debian-bullseye-sid, Ubuntu 21.04
Python 3.6.13
Installer: PIP

azure-cli 2.30.0 *

Extensions:
azure-devops 0.22.0
application-insights 0.1.14
account 0.2.1
ml 2.0.3

Additional Context
Dockerfile:
FROM rocker/tidyverse:3.6.3-ubuntu18.04

ENV R_LIBS_USER=/home/dockeruser/lib/r

# Install python (this is still required by AzureML, but this requirement will soon be removed )
RUN apt-get update -qq && \
    apt-get install -y python3-pip
RUN ln -f /usr/bin/python3 /usr/bin/python
RUN ln -f /usr/bin/pip3 /usr/bin/pip
RUN pip install -U pip

# Install azureml-base and libfuse (this is required for data access in local execution -- this requirement will also be removed soon)
RUN sudo apt-get install -y libfuse-dev
RUN pip install azureml-dataprep azureml-core

# User account
RUN useradd --create-home dockeruser
WORKDIR /home/dockeruser
USER dockeruser:dockeruser

# Install Miniconda
ENV CONDA_PATH=/home/dockeruser/miniconda
ENV PATH="${PATH}:${CONDA_PATH}/bin/"
RUN wget -qO /home/dockeruser/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-4.7.12-Linux-x86_64.sh && \
    bash /home/dockeruser/miniconda.sh -b -p $CONDA_PATH && \
    rm /home/dockeruser/miniconda.sh
RUN conda init bash

# Install additional R packages
RUN mkdir --parents $R_LIBS_USER
RUN R -e "install.packages('xtable', lib = '$R_LIBS_USER' )"

inference.R:
#* Liveness check
#* @get /live
function() {
  "alive"
}

#* Readiness check
#* @get /ready
function() {
  "ready"
}

#* Test function
#* @param data_folder, Data folder
#* @post /score
function(data_folder) {
    print("Data folder parameter is set to:\n")
    print(data_folder)
    return(data_folder)
}

endpoint.yml:
$schema: https://azuremlsdk2.blob.core.windows.net/latest/managedOnlineEndpoint.schema.json
name: my-test-ep01
description: Test endpoint.
auth_mode: key

deployment.yml:
$schema: https://azuremlschemas.azureedge.net/latest/managedOnlineDeployment.schema.json
name: my-test-dpl01
endpoint_name: my-test-01
model:
  local_path: inference.R
code_configuration:
  code:
    local_path: .
  scoring_script: inference.R
environment:
  name: my-test-01
  image: mycontainerreg.azurecr.io/testing/my-test-01
instance_type: Standard_DS2_v2
instance_count: 1

I got more information about the error by deploying the endpoint locally. The deployment seems to fail because the dockeruser is not an elevated account, thus is missing write permission to the /var/app directory.
If changed the Dockerfile so that all operations are executed as root. This fixed the previous problem, but now it ran into a new error: AttributeError: 'NoneType' object has no attribute 'keys'. Probably the deployment.yml file is missing the keys property, but which property is that?
Error report:
Step 6/7 : RUN conda env create -n inf-conda-env --file conda.yml
 ---> Running in 9192442d7bc8

# >>>>>>>>>>>>>>>>>>>>>> ERROR REPORT <<<<<<<<<<<<<<<<<<<<<<

    Traceback (most recent call last):
      File "/root/miniconda/lib/python3.7/site-packages/conda/exceptions.py", line 1074, in __call__
        return func(*args, **kwargs)
      File "/root/miniconda/lib/python3.7/site-packages/conda_env/cli/main.py", line 78, in do_call
        exit_code = getattr(module, func_name)(args, parser)
      File "/root/miniconda/lib/python3.7/site-packages/conda_env/cli/main_create.py", line 77, in execute
        directory=os.getcwd())
      File "/root/miniconda/lib/python3.7/site-packages/conda_env/specs/__init__.py", line 40, in detect
        if spec.can_handle():
      File "/root/miniconda/lib/python3.7/site-packages/conda_env/specs/yaml_file.py", line 18, in can_handle
        self._environment = env.from_file(self.filename)
      File "/root/miniconda/lib/python3.7/site-packages/conda_env/env.py", line 151, in from_file
        return from_yaml(yamlstr, filename=filename)
      File "/root/miniconda/lib/python3.7/site-packages/conda_env/env.py", line 137, in from_yaml
        data = validate_keys(data, kwargs)
      File "/root/miniconda/lib/python3.7/site-packages/conda_env/env.py", line 36, in validate_keys
        for key in data.keys():
    AttributeError: 'NoneType' object has no attribute 'keys'

`$ /root/miniconda/bin/conda-env create -n inf-conda-env --file conda.yml`

  environment variables:
                 CIO_TEST=<not set>
  CONDA_AUTO_UPDATE_CONDA=false
               CONDA_PATH=/root/miniconda
               CONDA_ROOT=/root/miniconda
                     PATH=/usr/lib/rstudio-server/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/
                          usr/bin:/sbin:/bin:/root/miniconda/bin/
       REQUESTS_CA_BUNDLE=<not set>
            SSL_CERT_FILE=<not set>

     active environment : None
       user config file : /root/.condarc
 populated config files :
          conda version : 4.7.12
    conda-build version : not installed
         python version : 3.7.4.final.0
       virtual packages :
       base environment : /root/miniconda  (writable)
           channel URLs : https://repo.anaconda.com/pkgs/main/linux-64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/r/linux-64
                          https://repo.anaconda.com/pkgs/r/noarch
          package cache : /root/miniconda/pkgs
                          /root/.conda/pkgs
       envs directories : /root/miniconda/envs
                          /root/.conda/envs
               platform : linux-64
             user-agent : conda/4.7.12 requests/2.22.0 CPython/3.7.4 Linux/5.11.0-41-generic ubuntu/18.04.4 glibc/2.27
                UID:GID : 0:0
             netrc file : None
           offline mode : False

An unexpected error has occurred. Conda has prepared the above report.

It seems that the error message in the title of this issue is given whenever the deployment YAML file contains errors. I was able to fix the previous error by adding a conda environment file (which doesn't make any sense, since I'm using a custom image...)
Now I got the same error about 'concat' again. Deploying locally with the --debug flag, the following error is revealed:
Updating local deployment (my-test-ep01 / my-test-dpl01) .docker.api.build: Looking for auth config
docker.api.build: Sending auth config ('myco.azurecr.io', 'https://index.docker.io/v1/', 'mltemp01cr.azurecr.io')
urllib3.connectionpool: http://localhost:None "POST /v1.41/build?t=my-test-ep01%3Amy-test-dpl01&q=False&nocache=False&rm=False&forcerm=False&pull=False&dockerfile=Dockerfile HTTP/1.1" 200 None
urllib3.connectionpool: http://localhost:None "GET /v1.41/images/e6cf7d30c1c2/json HTTP/1.1" 200 None
urllib3.connectionpool: http://localhost:None "GET /v1.41/containers/json?limit=-1&all=1&size=0&trunc_cmd=0&filters=%7B%22label%22%3A+%5B%22azureml-local-endpoint%22%2C+%22endpoint%3Dmy-test-ep01%22%5D%7D HTTP/1.1" 200 None
urllib3.connectionpool: http://localhost:None "GET /v1.41/containers/88f5dd76ac00d6d364894c32965acf0a46a7246d8d589cfb7e9ee1688b4da468/json HTTP/1.1" 200 None
urllib3.connectionpool: http://localhost:None "POST /v1.41/containers/88f5dd76ac00d6d364894c32965acf0a46a7246d8d589cfb7e9ee1688b4da468/stop HTTP/1.1" 304 0
urllib3.connectionpool: http://localhost:None "DELETE /v1.41/containers/88f5dd76ac00d6d364894c32965acf0a46a7246d8d589cfb7e9ee1688b4da468?v=False&link=False&force=False HTTP/1.1" 204 0
urllib3.connectionpool: http://localhost:None "POST /v1.41/containers/create?name=my-test-ep01.my-test-dpl01 HTTP/1.1" 201 88
urllib3.connectionpool: http://localhost:None "GET /v1.41/containers/8af509f017f9f2be39a31e67f2eb2defe149deb2f043a490ec32ec2b6687a018/json HTTP/1.1" 200 None
urllib3.connectionpool: http://localhost:None "POST /v1.41/containers/8af509f017f9f2be39a31e67f2eb2defe149deb2f043a490ec32ec2b6687a018/start HTTP/1.1" 204 0
...urllib3.connectionpool: http://localhost:None "GET /v1.41/containers/8af509f017f9f2be39a31e67f2eb2defe149deb2f043a490ec32ec2b6687a018/json HTTP/1.1" 200 None
Done (0m 20s)
Traceback (most recent call last):
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/custom/online_deployment.py", line 42, in ml_online_deployment_create
    ml_client.begin_create_or_update(deployment, local=local, vscode_debug=vscode_debug, no_wait=no_wait)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_ml_client.py", line 491, in begin_create_or_update
    return _begin_create_or_update(entity, self._operation_container.all_operations, **kwargs)
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/functools.py", line 807, in wrapper
    return dispatch(args[0].__class__)(*args, **kw)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_ml_client.py", line 579, in _
    return operations[AzureMLResourceType.ONLINE_DEPLOYMENT].begin_create_or_update(entity, **kwargs)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_operations/online_deployment_operations.py", line 71, in begin_create_or_update
    deployment=deployment, local_endpoint_mode=self._get_local_endpoint_mode(vscode_debug)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_operations/_local_deployment_helper.py", line 92, in create_or_update
    deployment_metadata=deployment_metadata,
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_utils/_endpoint_utils.py", line 70, in local_endpoint_polling_wrapper
    return event.result()
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/concurrent/futures/_base.py", line 425, in result
    return self.__get_result()
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/concurrent/futures/_base.py", line 384, in __get_result
    raise self._exception
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/concurrent/futures/thread.py", line 56, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_operations/_local_deployment_helper.py", line 248, in _create_deployment
    local_endpoint_mode=local_endpoint_mode,
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_local_endpoints/docker_client.py", line 182, in create_deployment
    endpoint_name=endpoint_name, deployment_name=deployment_name, container=container
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_local_endpoints/docker_client.py", line 425, in _validate_container_state
    raise LocalEndpointInFailedStateError(endpoint_name=endpoint_name, deployment_name=deployment_name)
azext_mlv2.manual.vendored_curated_sdk.azure.ml._local_endpoints.errors.LocalEndpointInFailedStateError: Local deployment (my-test-ep01 / my-test-dpl01) is in failed state. Try getting logs to debug scoring script.
cli: None
cli: Traceback (most recent call last):
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/custom/online_deployment.py", line 42, in ml_online_deployment_create
    ml_client.begin_create_or_update(deployment, local=local, vscode_debug=vscode_debug, no_wait=no_wait)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_ml_client.py", line 491, in begin_create_or_update
    return _begin_create_or_update(entity, self._operation_container.all_operations, **kwargs)
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/functools.py", line 807, in wrapper
    return dispatch(args[0].__class__)(*args, **kw)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_ml_client.py", line 579, in _
    return operations[AzureMLResourceType.ONLINE_DEPLOYMENT].begin_create_or_update(entity, **kwargs)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_operations/online_deployment_operations.py", line 71, in begin_create_or_update
    deployment=deployment, local_endpoint_mode=self._get_local_endpoint_mode(vscode_debug)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_operations/_local_deployment_helper.py", line 92, in create_or_update
    deployment_metadata=deployment_metadata,
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_utils/_endpoint_utils.py", line 70, in local_endpoint_polling_wrapper
    return event.result()
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/concurrent/futures/_base.py", line 425, in result
    return self.__get_result()
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/concurrent/futures/_base.py", line 384, in __get_result
    raise self._exception
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/concurrent/futures/thread.py", line 56, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_operations/_local_deployment_helper.py", line 248, in _create_deployment
    local_endpoint_mode=local_endpoint_mode,
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_local_endpoints/docker_client.py", line 182, in create_deployment
    endpoint_name=endpoint_name, deployment_name=deployment_name, container=container
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_local_endpoints/docker_client.py", line 425, in _validate_container_state
    raise LocalEndpointInFailedStateError(endpoint_name=endpoint_name, deployment_name=deployment_name)
azext_mlv2.manual.vendored_curated_sdk.azure.ml._local_endpoints.errors.LocalEndpointInFailedStateError: Local deployment (my-test-ep01 / my-test-dpl01) is in failed state. Try getting logs to debug scoring script.

cli.azure.cli.core.util: azure.cli.core.util.handle_exception is called with an exception:
cli.azure.cli.core.util: Traceback (most recent call last):
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/custom/online_deployment.py", line 42, in ml_online_deployment_create
    ml_client.begin_create_or_update(deployment, local=local, vscode_debug=vscode_debug, no_wait=no_wait)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_ml_client.py", line 491, in begin_create_or_update
    return _begin_create_or_update(entity, self._operation_container.all_operations, **kwargs)
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/functools.py", line 807, in wrapper
    return dispatch(args[0].__class__)(*args, **kw)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_ml_client.py", line 579, in _
    return operations[AzureMLResourceType.ONLINE_DEPLOYMENT].begin_create_or_update(entity, **kwargs)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_operations/online_deployment_operations.py", line 71, in begin_create_or_update
    deployment=deployment, local_endpoint_mode=self._get_local_endpoint_mode(vscode_debug)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_operations/_local_deployment_helper.py", line 92, in create_or_update
    deployment_metadata=deployment_metadata,
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_utils/_endpoint_utils.py", line 70, in local_endpoint_polling_wrapper
    return event.result()
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/concurrent/futures/_base.py", line 425, in result
    return self.__get_result()
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/concurrent/futures/_base.py", line 384, in __get_result
    raise self._exception
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/concurrent/futures/thread.py", line 56, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_operations/_local_deployment_helper.py", line 248, in _create_deployment
    local_endpoint_mode=local_endpoint_mode,
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_local_endpoints/docker_client.py", line 182, in create_deployment
    endpoint_name=endpoint_name, deployment_name=deployment_name, container=container
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/vendored_curated_sdk/azure/ml/_local_endpoints/docker_client.py", line 425, in _validate_container_state
    raise LocalEndpointInFailedStateError(endpoint_name=endpoint_name, deployment_name=deployment_name)
azext_mlv2.manual.vendored_curated_sdk.azure.ml._local_endpoints.errors.LocalEndpointInFailedStateError: Local deployment (my-test-ep01 / my-test-dpl01) is in failed state. Try getting logs to debug scoring script.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/site-packages/knack/cli.py", line 231, in invoke
    cmd_result = self.invocation.execute(args)
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/site-packages/azure/cli/core/commands/__init__.py", line 657, in execute
    raise ex
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/site-packages/azure/cli/core/commands/__init__.py", line 720, in _run_jobs_serially
    results.append(self._run_job(expanded_arg, cmd_copy))
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/site-packages/azure/cli/core/commands/__init__.py", line 691, in _run_job
    result = cmd_copy(params)
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/site-packages/azure/cli/core/commands/__init__.py", line 328, in __call__
    return self.handler(*args, **kwargs)
  File "/home/myusername/anaconda3/envs/azurecli/lib/python3.6/site-packages/azure/cli/core/commands/command_operation.py", line 121, in handler
    return op(**command_args)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/custom/online_deployment.py", line 50, in ml_online_deployment_create
    log_and_raise_error(err, debug)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/custom/raise_error.py", line 89, in log_and_raise_error
    _raise_cli_error(error)
  File "/home/myusername/.azure/cliextensions/ml/azext_mlv2/manual/custom/raise_error.py", line 68, in _raise_cli_error
    raise CLIError(message)
knack.util.CLIError: Local deployment (my-test-ep01 / my-test-dpl01) is in failed state. Try getting logs to debug scoring script.

cli.azure.cli.core.azclierror: Local deployment (my-test-ep01 / my-test-dpl01) is in failed state. Try getting logs to debug scoring script.
az_command_data_logger: Local deployment (my-test-ep01 / my-test-dpl01) is in failed state. Try getting logs to debug scoring script.
cli.knack.cli: Event: Cli.PostExecute [<function AzCliLogging.deinit_cmd_metadata_logging at 0x7fe85951af28>]
az_command_data_logger: exit code: 1
cli.__main__: Command ran in 21.206 seconds (init: 0.106, invoke: 21.100)
telemetry.save: Save telemetry record of length 3269 in cache
telemetry.check: Negative: The /home/myusername/.azure/telemetry.txt was modified at 2021-12-17 18:41:18.218818, which in less than 600.000000 s

Route to service team.

Hey @lehmus , thanks for reporting this issue. The engineering team will help to investigate this issue. In the meantime, you can use az ml online-deployment get-logs --name my-deployment --endpoint-name my-endpoint --lines 100 --resource-group my-resource-group --workspace-name my-workspace to get the logs for your online deployment to help diagnose the current issues.
If you had a hard time finding the online deployment schema, you can find it here

I made a few changes to the deployment definition (model & environment). Again, deploying locally reveals the actual error message:
Creating or updating online_deployments
Creating local deployment (my-test-ep01 / my-test-dpl01) .Done (0m 5s)
400 Client Error for http+docker://localhost/v1.41/containers/e6a7f3af39092c518eaebb41ef7c9fceed72e5bc1a2edbe065b15b6f32044694/start: Bad Request ("failed to create shim: OCI runtime create failed: container_linux.go:380: starting container process caused: exec: "runsvdir": executable file not found in $PATH: unknown")

I also tried to deploy to Azure and fetch the logs as @Mossaka commented. But this command also runs into an error:
Code: BadRequest
Message: The request is invalid.
Exception Details:      (DeploymentLogsUnavailable) Logs for deployment are not available because it failed in provisioning. This may be caused by the environment failing to build. Following error was found on the deployment: {"code":"InferencingClientCallFailed","statusCode":404,"message":"{{\"title\":\"Not Found\"}}"}
        Code: DeploymentLogsUnavailable
        Message: Logs for deployment are not available because it failed in provisioning. This may be caused by the environment failing to build. Following error was found on the deployment: {"code":"InferencingClientCallFailed","statusCode":404,"message":"{{\"title\":\"Not Found\"}}"}

This is the refined deployment.yml:
$schema: https://azuremlschemas.azureedge.net/latest/managedOnlineDeployment.schema.json
name: my-test-dpl01
endpoint_name: my-test-01
model:
  name: my-test-01
  local_path: inference.R
code_configuration:
  code:
    local_path: .
  scoring_script: inference.R
environment: azureml:my-test-01:1 # custom environment exists in AML Workspace
instance_type: Standard_DS2_v2
instance_count: 1

As a side note, deployment seems to require the model schema, although it should be optional when deploying a custom image.

I have managed to deploy the endpoint now. The error messages and the documentation have improved recently, so it is easier to debug issues.


Documentation missing of how to implement debounce in searchbox widget

The documentation for the searchBox widget says:

But how exactly must it be implemented? Does queryHook expect a (debounced) return? If so, what? object, function, bool?
Calling a debounce/deferr function inside queryHook seems not to work.
	queryHook:function(query, search) {
		$.debounce(search(query), 1000);
		return false; // ?
	}

You would do something like that:
    queryHook: $.debounce(function(query, search) {
      search(query);
    }, 1000);

Thanks for all the feedbacks and issues, much appreciated, really. We have a tutorial section #849 planned that would go deeper into cases like that.

This works! Thank you, @vvo !
...
queryHook: $.throttle(function(query, search) {
    query = query.replace(/\./, "");
    search(query);
}, 1000),
...

awesome ;)


visualize BLIP attention

Is there a way to visualize what/where blip focuses in an image when given an input text? similar to grad cam for visualizing weights

Hi, you can use this code to visualize the gradcam on cross-attention maps for BLIP:
https://github.com/salesforce/ALBEF/blob/main/visualization.ipynb

Thank you. I'll take a look.

I have the same question about visualizations.


Problem to separate docker-gen and nginx

Hello,
I tried your nginx-proxy and it works fine! Thanks for this great image!
I try to separate the nginx and the docker-gen as described at your readme file.  Problem is the command part, which can't be executet ad CMD / ENTRY
-notify-sighup nginx -watch -only-exposed /etc/docker-gen/templates/nginx.tmpl /etc/nginx/conf.d/default.conf

How should I create / start my container?
A prepared docker-gen image to use with nginx would also be great? Any plans to add such a image?

Try removing the "-only-exposed" flag.
When you separate the nginx-gen, it no longer appears in the container list.
Due to the way the nginx.tmpl is setup, it will cause de detection of the CurrentContainer to fail.

You also need to tweak the template as in https://github.com/jwilder/nginx-proxy/pull/750 to detect the proxy container.


Warn when output shape not specified for Lambda on Theano

I have a feeling that having DeprecationWarning and Exception later would be better, but that's up to you.

Thanks!