Pods timing out mounting volumes.

BUG REPORT
What happened:
Pods unable to mount volumes.
What you expected to happen:
Pods to mount volumes.
How to reproduce it (as minimally and precisely as possible):
Have a pod try and mount a volume.
Anything else we need to know?:
# kubectl describe pod percona-6687f7cf88-tfdxs
Name:               percona-6687f7cf88-tfdxs
Namespace:          default
Priority:           0
PriorityClassName:  <none>
Node:               st13p01if-ztds02221001/<IP_ADDRESS>
Start Time:         Tue, 30 Oct 2018 11:56:11 -0700
Labels:             name=percona
                    pod-template-hash=2243937944
Annotations:        <none>
Status:             Pending
IP:
Controlled By:      ReplicaSet/percona-6687f7cf88
Containers:
  percona:
    Container ID:
    Image:         percona
    Image ID:
    Port:          3306/TCP
    Host Port:     0/TCP
    Args:
      --ignore-db-dir
      lost+found
    State:          Waiting
      Reason:       ContainerCreating
    Ready:          False
    Restart Count:  0
    Limits:
      cpu:  500m
    Requests:
      cpu:  500m
    Environment:
      MYSQL_ROOT_PASSWORD:  k8sDem0
    Mounts:
      /var/lib/mysql from openebs-percona-test (rw)
      /var/run/secrets/kubernetes.io/serviceaccount from default-token-qdbwz (ro)
Conditions:
  Type              Status
  Initialized       True
  Ready             False
  ContainersReady   False
  PodScheduled      True
Volumes:
  openebs-percona-test:
    Type:       PersistentVolumeClaim (a reference to a PersistentVolumeClaim in the same namespace)
    ClaimName:  openebs-percona-test-pvc
    ReadOnly:   false
  default-token-qdbwz:
    Type:        Secret (a volume populated by a Secret)
    SecretName:  default-token-qdbwz
    Optional:    false
QoS Class:       Burstable
Node-Selectors:  <none>
Tolerations:     ak=av:NoSchedule
                 node.kubernetes.io/not-ready:NoExecute for 300s
                 node.kubernetes.io/unreachable:NoExecute for 300s
Events:
  Type     Reason                  Age                 From                             Message
  ----     ------                  ----                ----                             -------
  Warning  FailedScheduling        15m (x14 over 15m)  default-scheduler                pod has unbound PersistentVolumeClaims (repeated 12 times)
  Normal   Scheduled               15m                 default-scheduler                Successfully assigned default/percona-6687f7cf88-tfdxs to st13p01if-ztds02221001
  Normal   SuccessfulAttachVolume  15m                 attachdetach-controller          AttachVolume.Attach succeeded for volume "pvc-73d29257-dc75-11e8-9707-008cface4910"
  Warning  FailedMount             2m (x6 over 13m)    kubelet, st13p01if-ztds02221001  Unable to mount volumes for pod "percona-6687f7cf88-tfdxs_default(73eafea7-dc75-11e8-9707-008cface4910)": timeout expired waiting for volumes to attach or mount for pod "default"/"percona-6687f7cf88-tfdxs". list of unmounted volumes=[openebs-percona-test]. list of unattached volumes=[openebs-percona-test default-token-qdbwz]

Environment:
# kubectl get nodes
NAME                     STATUS    ROLES               AGE       VERSION
st11p01if-ztds01204301   Ready     controlplane        5d        v1.11.3
st11p01if-ztds01224701   Ready     worker              5d        v1.11.3
st11p01if-ztds03201601   Ready     etcd                5d        v1.11.3
st11p01if-ztds07071101   Ready     worker              5d        v1.11.3
st11p01if-ztds09065001   Ready     worker              5d        v1.11.3
st11p01if-ztds10054201   Ready     worker              5d        v1.11.3
st11p01if-ztds16132001   Ready     worker              5d        v1.11.3
st11p01if-ztds25111801   Ready     worker              5d        v1.11.3
st13p01if-ztds01195101   Ready     worker              5d        v1.11.3
st13p01if-ztds01243201   Ready     controlplane,etcd   5d        v1.11.3
st13p01if-ztds02221001   Ready     worker              5d        v1.11.3
st13p01if-ztds02263701   Ready     worker              5d        v1.11.3
st13p01if-ztds04192201   Ready     worker              5d        v1.11.3
st14p01if-ztds09354301   Ready     etcd                5d        v1.11.3
st14p01if-ztds11303101   Ready     worker              5d        v1.11.3
st14p01if-ztds14013801   Ready     worker              5d        v1.11.3

# kubectl get pods --all-namespaces
NAMESPACE                  NAME                                                             READY     STATUS              RESTARTS   AGE
cattle-logging             fluentd-4x4t6                                                    2/2       Running             0          5d
cattle-logging             fluentd-8fqvt                                                    2/2       Running             0          5d
cattle-logging             fluentd-bzlnx                                                    2/2       Running             0          5d
cattle-logging             fluentd-ft58r                                                    2/2       Running             0          5d
cattle-logging             fluentd-g64zq                                                    2/2       Running             0          5d
cattle-logging             fluentd-gvfrz                                                    2/2       Running             0          5d
cattle-logging             fluentd-nfrkf                                                    2/2       Running             0          5d
cattle-logging             fluentd-nknb2                                                    2/2       Running             0          5d
cattle-logging             fluentd-q9dmg                                                    2/2       Running             0          5d
cattle-logging             fluentd-qgl25                                                    2/2       Running             0          5d
cattle-logging             fluentd-qk5bs                                                    2/2       Running             0          5d
cattle-logging             fluentd-sb7cq                                                    2/2       Running             2          5d
cattle-logging             fluentd-t5hbs                                                    2/2       Running             0          5d
cattle-logging             fluentd-ts2w9                                                    2/2       Running             0          5d
cattle-logging             fluentd-w2h6r                                                    2/2       Running             0          5d
cattle-logging             fluentd-zmnfd                                                    2/2       Running             0          5d
cattle-logging             log-aggregator-45jxr                                             1/1       Running             0          5d
cattle-logging             log-aggregator-4q7zw                                             1/1       Running             0          5d
cattle-logging             log-aggregator-6ww5q                                             1/1       Running             0          5d
cattle-logging             log-aggregator-7crbc                                             1/1       Running             0          5d
cattle-logging             log-aggregator-8bcr2                                             1/1       Running             0          5d
cattle-logging             log-aggregator-8mz7x                                             1/1       Running             0          5d
cattle-logging             log-aggregator-8qxkn                                             1/1       Running             0          5d
cattle-logging             log-aggregator-95j84                                             1/1       Running             0          5d
cattle-logging             log-aggregator-gvgfw                                             1/1       Running             0          5d
cattle-logging             log-aggregator-jvmtf                                             1/1       Running             0          5d
cattle-logging             log-aggregator-krbhr                                             1/1       Running             0          5d
cattle-logging             log-aggregator-lggxp                                             1/1       Running             1          5d
cattle-logging             log-aggregator-mr45z                                             1/1       Running             0          5d
cattle-logging             log-aggregator-mzz4j                                             1/1       Running             0          5d
cattle-logging             log-aggregator-pm5fd                                             1/1       Running             0          5d
cattle-logging             log-aggregator-xcw57                                             1/1       Running             0          5d
cattle-system              cattle-cluster-agent-7cc799bbc8-6cx7c                            1/1       Running             2          5d
cattle-system              cattle-node-agent-228fq                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-4jh8x                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-6hksh                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-6n8cm                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-7pdsp                                          1/1       Running             1          5d
cattle-system              cattle-node-agent-8bghh                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-94mhx                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-ddh99                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-pgqw2                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-qllf8                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-qx8mz                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-sqp29                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-tzmnd                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-z4lfq                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-zbjbx                                          1/1       Running             0          5d
cattle-system              cattle-node-agent-zfwch                                          1/1       Running             0          5d
default                    percona-6687f7cf88-tfdxs                                         0/1       ContainerCreating   0          11m
default                    pvc-73d29257-dc75-11e8-9707-008cface4910-ctrl-5f46b99c96-5sjww   2/2       Running             0          11m
default                    pvc-73d29257-dc75-11e8-9707-008cface4910-rep-5586687449-bxvlj    1/1       Running             0          11m
default                    pvc-73d29257-dc75-11e8-9707-008cface4910-rep-5586687449-f65tt    1/1       Running             0          11m
default                    pvc-73d29257-dc75-11e8-9707-008cface4910-rep-5586687449-qphz8    1/1       Running             0          11m
ingress-nginx              default-http-backend-d88bc9f8c-j2lq2                             1/1       Running             0          5d
ingress-nginx              nginx-ingress-controller-4kxdt                                   1/1       Running             0          5d
ingress-nginx              nginx-ingress-controller-8chf6                                   1/1       Running             0          5d
ingress-nginx              nginx-ingress-controller-bshnw                                   1/1       Running             0          5d
ingress-nginx              nginx-ingress-controller-cxs67                                   1/1       Running             0          5d
ingress-nginx              nginx-ingress-controller-k2g62                                   1/1       Running             0          5d
ingress-nginx              nginx-ingress-controller-n476q                                   1/1       Running             0          5d
ingress-nginx              nginx-ingress-controller-rsbj8                                   1/1       Running             0          5d
ingress-nginx              nginx-ingress-controller-rzkr9                                   1/1       Running             0          5d
ingress-nginx              nginx-ingress-controller-skmsf                                   1/1       Running             0          5d
ingress-nginx              nginx-ingress-controller-svw68                                   1/1       Running             0          5d
ingress-nginx              nginx-ingress-controller-vjwml                                   1/1       Running             1          5d
ingress-nginx              nginx-ingress-controller-z2ctp                                   1/1       Running             0          5d
kube-state-metrics-cnrdw   kube-state-metrics-cnrdw-7f89c969c6-9gj7b                        1/1       Running             0          39m
kube-system                canal-5vgcm                                                      3/3       Running             0          5d
kube-system                canal-8jv26                                                      3/3       Running             0          5d
kube-system                canal-8qh5q                                                      3/3       Running             0          5d
kube-system                canal-8zdsv                                                      3/3       Running             0          5d
kube-system                canal-gxdd2                                                      3/3       Running             0          5d
kube-system                canal-khk5r                                                      3/3       Running             0          5d
kube-system                canal-m7nz6                                                      3/3       Running             3          5d
kube-system                canal-mstb7                                                      3/3       Running             0          5d
kube-system                canal-n67t2                                                      3/3       Running             0          5d
kube-system                canal-nrmcv                                                      3/3       Running             0          5d
kube-system                canal-p4sxn                                                      3/3       Running             0          5d
kube-system                canal-qst4b                                                      3/3       Running             0          5d
kube-system                canal-r57q8                                                      3/3       Running             0          5d
kube-system                canal-sb4ws                                                      3/3       Running             0          5d
kube-system                canal-vh6s2                                                      3/3       Running             0          5d
kube-system                canal-vnlm7                                                      3/3       Running             0          5d
kube-system                kube-dns-66d9fddc75-fj584                                        3/3       Running             0          22h
kube-system                kube-dns-66d9fddc75-mxmjq                                        3/3       Running             3          5d
kube-system                kube-dns-66d9fddc75-vvrj7                                        3/3       Running             0          22h
kube-system                kube-dns-66d9fddc75-z26n9                                        3/3       Running             0          5d
kube-system                kube-dns-autoscaler-7d686797f4-8rt92                             1/1       Running             0          5d
kube-system                kubernetes-dashboard-845689f6b8-mdptl                            1/1       Running             0          22h
kube-system                metrics-server-7db77d889-pv2zv                                   1/1       Running             0          5d
kube-system                rke-ingress-controller-deploy-job-dcmpn                          0/1       Completed           0          5d
kube-system                rke-kubedns-addon-deploy-job-sz9nw                               0/1       Completed           0          5d
kube-system                rke-metrics-addon-deploy-job-clq7f                               0/1       Completed           0          5d
kube-system                rke-network-plugin-deploy-job-psksk                              0/1       Completed           0          5d
openebs                    cstor-sparse-pool-44lm-84d4d886d7-487j8                          2/2       Running             0          26m
openebs                    cstor-sparse-pool-4rry-6bb65864b6-726cq                          2/2       Running             0          26m
openebs                    cstor-sparse-pool-yfo1-7bf5f7bd47-xcsjp                          2/2       Running             0          26m
openebs                    openebs-apiserver-7b6fcb7bdf-k4qk8                               1/1       Running             0          26m
openebs                    openebs-ndm-2j2fp                                                1/1       Running             0          26m
openebs                    openebs-ndm-4qwdg                                                1/1       Running             0          26m
openebs                    openebs-ndm-6crbp                                                1/1       Running             0          26m
openebs                    openebs-ndm-c9j24                                                1/1       Running             0          26m
openebs                    openebs-ndm-fsz5m                                                1/1       Running             0          26m
openebs                    openebs-ndm-jz82c                                                1/1       Running             0          26m
openebs                    openebs-ndm-lt847                                                1/1       Running             0          26m
openebs                    openebs-ndm-qvbnt                                                1/1       Running             0          26m
openebs                    openebs-ndm-rv8c2                                                1/1       Running             0          26m
openebs                    openebs-ndm-wfsqp                                                1/1       Running             0          26m
openebs                    openebs-ndm-x9dz2                                                1/1       Running             0          26m
openebs                    openebs-ndm-zw5s9                                                1/1       Running             0          26m
openebs                    openebs-provisioner-5cf45d689c-tt6d7                             1/1       Running             0          26m
openebs                    openebs-snapshot-operator-5f69fbcb74-cdl9f                       2/2       Running             0          26m

# kubectl get svc
NAME                                                TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)             AGE
kubernetes                                          ClusterIP   <IP_ADDRESS>       <none>        443/TCP             5d
percona-mysql                                       ClusterIP   <IP_ADDRESS>    <none>        3306/TCP            11m
pvc-73d29257-dc75-11e8-9707-008cface4910-ctrl-svc   ClusterIP   <IP_ADDRESS>   <none>        3260/TCP,9501/TCP   11m

# kubectl get sc
NAME                        PROVISIONER                                                AGE
openebs-cstor-sparse        openebs.io/provisioner-iscsi                               27m
openebs-jiva-default        openebs.io/provisioner-iscsi                               1h
openebs-snapshot-promoter   volumesnapshot.external-storage.k8s.io/snapshot-promoter   1h

# kubectl get pv
NAME                                            CAPACITY   ACCESS MODES   RECLAIM POLICY   STATUS        CLAIM                                STORAGECLASS           REASON    AGE
pvc-73d29257-dc75-11e8-9707-008cface4910        5G         RWO            Delete           Bound         default/openebs-percona-test-pvc     openebs-jiva-default             13m

# kubectl get pvc
NAME                       STATUS    VOLUME                                     CAPACITY   ACCESS MODES   STORAGECLASS           AGE
openebs-percona-test-pvc   Bound     pvc-73d29257-dc75-11e8-9707-008cface4910   5G         RWO            openebs-jiva-default   13m

OS (e.g. from /etc/os-release):

# cat /etc/os-release
NAME="Oracle Linux Server"
VERSION="7.5"
ID="ol"
VERSION_ID="7.5"
PRETTY_NAME="Oracle Linux Server 7.5"
ANSI_COLOR="0;31"
CPE_NAME="cpe:/o:oracle:linux:7:5:server"
HOME_URL="https://linux.oracle.com/"
BUG_REPORT_URL="https://bugzilla.oracle.com/"
ORACLE_BUGZILLA_PRODUCT="Oracle Linux 7"
ORACLE_BUGZILLA_PRODUCT_VERSION=7.5
ORACLE_SUPPORT_PRODUCT="Oracle Linux"
ORACLE_SUPPORT_PRODUCT_VERSION=7.5

Kernel:

# uname -a
Linux st11p01if-ztds01204301.example.com 4.14.35-1818.2.1.el7uek.x86_64 #2 SMP Mon Aug 27 21:16:31 PDT 2018 x86_64 x86_64 x86_64 GNU/Linux

When working with Rancher, iSCSI needs to be enabled. More details on this are available at:

https://docs.openebs.io/docs/next/prerequisites.html
https://rancher.com/docs/rancher/v2.x/en/cluster-admin/volumes-and-storage/#iscsi-volumes-with-rancher-launched-kubernetes-clusters


Return rgb when rgba is loaded

Sometimes, cv2.imread returns (H, W, 4) array (e.g., the image below).
It seems that this behavior is dependent on the build of cv2.
The bug occurred with the cv2 installed using anaconda, but the same problem did not occur for cv2 installed with apt.

EDIT:
Alpha channel extracted by img = cv2.imread(path)[:, :, 3]

RGB extracted by img = cv2.imread(path)[:, :, :3][:. :. ::-1]

PIL
f = Image.open(path); img = f.convert('RGB');

@Hakuyume
Please review this again.


ValueError: Invalid time.

Hello, I am getting this exception:
Could not parse date string -1
Traceback (most recent call last):
  File "/home/mikula/.virtualenvs/crawler/lib/python3.6/site-packages/reppy/ttl.py", line 60, in ttl
    return max(self.minimum, parse_date(expires) - date)
  File "/home/mikula/.virtualenvs/crawler/lib/python3.6/site-packages/reppy/util.py", line 11, in parse_date
    raise ValueError("Invalid time.")
ValueError: Invalid time.

Can you please include the input and steps to reproduce this exception?

I am calling this lib from celery tasks in my worker, its really hard to reproduce it probably :/ I will try.

One more thing, is reppy thread/fork save? Because I am using reppy in Celery. I have global file with reppy and multiprocess locks like this: https://github.com/UPOLSearch/UPOL-Crawler/blob/development/crawler/urls/robots.py

Hello,
I have the same problem. It occurs with only a few robots.txt:
exception :
Could not parse date string -1
Traceback (most recent call last):
  File "/usr/local/lib/python3.5/dist-packages/reppy/ttl.py", line 60, in ttl
    return max(self.minimum, parse_date(expires) - date)
  File "/usr/local/lib/python3.5/dist-packages/reppy/util.py", line 11, in parse_date
    raise ValueError("Invalid time.")
ValueError: Invalid time.

or :
Could not parse date string 0
Traceback (most recent call last):
  File "/usr/local/lib/python3.5/dist-packages/reppy/ttl.py", line 60, in ttl
    return max(self.minimum, parse_date(expires) - date)
  File "/usr/local/lib/python3.5/dist-packages/reppy/util.py", line 11, in parse_date
    raise ValueError("Invalid time.")
ValueError: Invalid time.

examples :
from reppy.robots import Robots

r = Robots.fetch('http://www.tripadvisor.fr/robots.txt')
r = Robots.fetch('https://www.udemy.com/robots.txt')
r = Robots.fetch('https://www.jamendo.com/robots.txt')
r = Robots.fetch('https://musopen.org/robots.txt')

I don't know if it's related but the response headers for all those files contains :
Cache-Control : "no-cache, no-store, max-age=0, must-revalidate "

Thanks for the reproducing case. This appears to be a very simple typo bug. PR coming.

v0.4.4 has been pushed to pypi with a fix for this issue.


[tests] Cleanup deprecation warnings

Coverage remained the same at 71.435% when pulling c8b4f1c83bbfd818540173cb42144dac4c1f3110 on Djailla:warnings into d747e09885e90d4c5f702f0bb4f0ea42e63f4eb0 on django-extensions:master.

Thanks !


OAuthPrompt does not respond to invoke activity with 200

Version
Microsoft.Bot.Builder.Dialogs v4.4.3
Describe the bug
After completing the auth flow in Teams, the bot receives an invoke activity with the verification code. I route this activity to the currently active OAuthPrompt dialog, which gets the token and ends itself as expected. But my bot responds to the request with 501 Not Implemented instead of 200. Teams repeatedly sends the invoke activity (I assume because it didn't get a 200) and my bot repeatedly responds with 501. While this is happening, the "Sign In" button in Teams shows a spinning indicator.
This does not happen with the JS SDK. In JS, my bot responds to the request with 200, Teams does not send multiple invoke activities, and the spinning indicator goes away after the auth flow is completed. I noticed that the JS OAuthPrompt explicitly sends an invokeResponse:
else if (this.isTeamsVerificationInvoke(context)) {
    const code: any = context.activity.value.state;
    await context.sendActivity({ type: 'invokeResponse', value: { status: 200 }});
    token = await this.getUserToken(context, code);
}

To Reproduce
Steps to reproduce the behavior:

Start with the C# bot authentication sample and register your bot, set up authentication, etc.
The sample does not handle the invoke activity for Teams, so add code to make sure those activities get to the OAuthPrompt. I did this somewhat crudely by just running the dialog on unrecognized activity types:

// DialogBot.cs
protected override async Task OnUnrecognizedActivityTypeAsync(ITurnContext turnContext, CancellationToken cancellationToken)
{
    await Dialog.Run(turnContext, ConversationState.CreateProperty<DialogState>(nameof(DialogState)), cancellationToken);
}

Add the bot to Teams and chat with it to go through the auth flow. Observe the outbound 501 responses.

[bug]

I have raised a PR #1963 which could potentially resolve this plus a related issue, #1893, regarding Teams signin. Some comments regarding the PR are on the other issue.

There are two issues here:

in the SDK code we need to fix the OAuth prompt and sensitive http marshaling #1979 and #2005
in the samples we should forward the Invoke activity to the Dialog if using Teams.

At some point is would be good to have (2) in the core SDK but we deferred on that because we were not sure of the set of possible Invokes Teams could send.

The JavaScript code should also not send a 200 if it didn't find the magic code.

fixed


normalizer configuration

Without looking at the implemenation details, it would be much preferred to put the normalizer definition with the reduxForm definition rather than at the middleware creation level.
On a project with 20+ forms throughout it can get a bit hairy to have the normalization definition so divorced from the form definition.

I agree that it's awkward, but the reducer and component are really separate concerns. https://github.com/erikras/redux-form/issues/134#issuecomment-148644828

Excellent point about the dichotomy, but it really is necessary, as there are two parts to redux-form, the component and the reducer, and they are each in charge of validation and normalization respectively. I suppose that the component could normalize in the onChange function, but it really is a superior design for the reducer to be in full control over its data, just receiving actions and modifying state.

Could the normalization be integrated a bit tighter in the same way that errors are. E.g. from the component I declare normalized fields?
Sharing phone or email normalization is likely common and would still likely trim down many real-world implementations of the normalize call to be data types rather than form types.

I'm not sure I follow you. Normalizing functions that are even a little bit complex can, and should, be kept as reusable and testable modules, like they are in the example.

code probably can explain it better. Rather than formReducer.normalize() using form names for keys, it uses possible field names or types as keys:
import {reducer as formReducer} from 'redux-form';

export const formReducer.normalize({
  email: emailFieldNormalizer,
  phone: emailFieldNormalizer,
});

import {reduxForm} from 'redux-form';

export default reduxForm({
  name: 'example',
  fields: ['name', 'email', 'phone'],
  // match field key to normalize key
  normalize: ['email', 'phone'],

  // match object key === field key to object value === normalize key
  normalize: { email: 'email', primaryPhone: 'phone'},
})(MyForm);

export const formReducer.normalize({
  email: emailFieldNormalizer,
  phone: emailFieldNormalizer,
});

I'm still confused. What is primaryPhone? Why is phone using emailFieldNormalizer? Why are there two normalize keys in the config passed to reduxForm()?

erp. Writing code in the github issue editor makes me extra sloppy. I updated the code example. The two normalize keys in the reduxForm were to demonstrate two different APIs. One more restrictive and the other more flexible.

Okay, your message has successfully been communicated.
The problem with this is that, as I said in my first comment, it's the reducer that needs to know what rule to apply to what value. Putting that mapping on the component doesn't help at all.

Does that not communicate to the reducer what it needs to know in the same way that the fields key communicates to the reducer what properties an instance should have? I suppose I don’t understand why doing this at the form name level accomplished the reducer knowing everything it needs versus at the field level.

The reducer doesn't know about the fields.

I'd like to chime in here and say that I agree with iamdustan on this one. As far as implementation details go, I don't really care where the normalize routines get fired, but as far as code organization and sanity go, forcing users to put all normalizing code with the store configuration is really awkward. I've been working with redux-form for only a few days now (still learning the ropes), and I'm 99% sure that when I'm reviewing my code, if the normalizing code is not organized with the rest of the form code, I will forget that it's there (or even worse, if I'm reviewing somebody else's code, I'll have even less of a chance of remembering to look there).
iamdustan's suggestion of grouping that normalizing code with the rest of the form code seems like exactly the right thing--if the right thing as far as when it fires is for it to happen at the reducer, then that makes complete sense.  I have no idea, however, if it's technically feasible to have the normalize code grouped with the form code, yet have it fire at the reducer.

I agree. There is much to be gained by the proposition.

I'm new to redux-form and so far I'm loving the flexibility it provides, but I also agree that it would be so much more developer friendly to have the form configuration in a single place.

So, I guess the question is: taking it for granted that the reducer shouldn't know about the fields or anything else from the calling domain... should it know about normalizers, either? Does it make sense to perform data transformation in a reducer? (While it's technically not a 'side-effect', it does seem to cross the streams, separation-of-concerns-wise...)
Or, would both the reducer itself and the API signature for redux-form be cleaner and clearer if normalization happened in a pipeline prior to dispatch()?

I second that suggestion. Pre-dispatch is preferred, as it's raw input. As such it does not need to be part of redux, and one can choose from the many plugins out there

On 10 apr. 2016, at 10:38, Christian Lilley<EMAIL_ADDRESS>wrote:
So, I guess the question is: taking it for granted that the reducer shouldn't know about the fields or anything else from the calling domain... should it know about normalizers, either? Does it make sense to perform data transformation in a reducer? (While it's technically not a 'side-effect', it does seem to cross the streams, separation-of-concerns-wise...)
Or, would both the reducer itself and the API signature for redux-form be cleaner and clearer if normalization happened in a pipeline prior to dispatch()?
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I can see it from many different sides.

Normalize in reducer - If you had two different form components that were editing the same data, would you really want to put the normalizing code in both components? No, it's the reducer's job to accept change events and store the data canonically.

Normalize in middleware - Similar to normalizing in the reducer, but more abstract...and potentially reusable?

Normalize in form component - Closer to where you are thinking about the presentation and editing of the data. The reducer just stores, it doesn't think or do anything intelligently with the data dispatched.

Like most engineering problems, there are tradeoffs with each option. Due to the decoupling of fields from the form component in the major rewrite next version (v6), I think the library will be moving from Option 1 to 3, giving the normalizing responsibility to the field itself.

Sounds great!
On Apr 11, 2016, at 8:30 AM, Erik Rasmussen <notifications<EMAIL_ADDRESS>wrote:
I can see it from many different sides.

Normalize in reducer - If you had two different form components that were editing the same data, would you really want to put the normalizing code in both components? No, it's the reducer's job to accept change events and store the data canonically.

Normalize in middleware - Similar to normalizing in the reducer, but more abstract...and potentially reusable?

Normalize in form component - Closer to where you are thinking about the presentation and editing of the data. The reducer just stores, it doesn't think or do anything intelligently with the data dispatched.

Like most engineering problems, there are tradeoffs with each option. Due to the decoupling of fields from the form component in the major rewrite next version (v6), I think the library will be moving from Option 1 to 3, giving the normalizing responsibility to the field itself.
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Option 3 sounds great and more intuitive!

Is there any way to use the normalizers without requiring the exact field name be in the reducer?


Hotfix/add on change callback

I wasn't sure how to get access to the file, so I added a call to onChange that would be passed via props. It's currently blacklisted on the file input's props. With this you get access to the event, file, and dataURI.

Calls a this.props.onChange(e, newFileState)

Looks good to me @cameronjroe, thanks!


ASP.NET + Redis + ProtocolBuffer: Invalid deserialization of repeated fields

Expected Behavior
When reading from Redis stream data like this:
"subscription":{
  "msisdn":"D5B53751-E9F3-44C1-84B6-797AB98D0C13",
  "sessions":[
    {
      "ipAddress":"<IP_ADDRESS>",
      "ipAddress":"<IP_ADDRESS>"
    }
  ],
  "results":[
     {
       "category": 12,
       "category": 10
     }
  ]
},

This message should be de-serialized into C# generated ProtocolBuffer message with repeated fields populated.
Actual Behavior
Instead, repeated fields are just empty as if the message were:
"subscription":{
  "msisdn":"D5B53751-E9F3-44C1-84B6-797AB98D0C13",
  "sessions":[  ],
  "results":[  ]
},

Steps to Reproduce the Problem

setup the client as suggested at Use the Dapr .NET SDK

In our case it is:
  public class SaveController: ControllerBase
  {
    [Topic( Constants.PubsubName, Constants.PubsubTopic )]
    [HttpPost("saveEvent")]
    public async Task<IActionResult> SaveEvent( onWebAccess event, [FromServices] DaprtClient _daprClient )
    {
      // event does not contain any of the repeated fields, so they are set to default (empty)
    }
  }

use configuration for Redis containing:

spec:
  type: pubsub.redis
  version: v1
  metadata:
    name: RedistHost
    value: <address:port to your redis>

We tried different ProtocolBuffer messages and all of them have the same issue
We tried to manually insert JSON-serialized message into Redis stream - the same issue
We tried to let Dapr to publish message into Redis stream - message is properly serialized and repeated fields have content. So the bug must be on reading side.
Similar issues were reported already:

https://github.com/dapr/dotnet-sdk/issues/268#issuecomment-605427567
https://github.com/dapr/dotnet-sdk/issues/268#issuecomment-665545891

even an issue was created https://github.com/PlanBGmbH/dapr-vote/issues/2

despite marked as fixed, the bug still appears

We have not tried Any fields, but the discussion above suggest it should be buggy too.

Hi @git-torrent the Dapr .NET SDK does not provide any serialization facilities directly, it calls through to either System.Text.Json or the protobuf serializer.

This message should be de-serialized into C# generated ProtocolBuffer message with repeated fields populated.

What's not super clear to me from your example is what code is attempting to deserialize the message? Are you relying on MVC model binding (System.Text.Json) for this? I'm confused because your example talks about protobuf but shows MVC model binding.
If I understand the issue you're describing - this is a pubsub message in JSON format, and part of it contains a repeated JSON property:
// snip
{
  "ipAddress":"<IP_ADDRESS>",
  "ipAddress":"<IP_ADDRESS>"
}

Is this a format you control or is this something externally specified?
I mention this because the semantics of a repeated property in JSON is ambiguous in the spec. Different JSON serializers will behave differently for this case. It can also be used as an attack vector: https://labs.bishopfox.com/tech-blog/an-exploration-of-json-interoperability-vulnerabilities

It's possible that the cloud events middleware is sanitizing the duplicate properties. https://github.com/dapr/dotnet-sdk/blob/master/src/Dapr.AspNetCore/CloudEventsMiddleware.cs#L56
I'll test this out and try to see if that's the case.

I tested this out and the cloud-events middleware is passing through the duplicate properties for the case I tested.
[Fact]
        public async Task InvokeAsync_ReplacesBodyJson_DuplicatePropertyNames()
        {
            var encoding = Encoding.UTF8;
            var app = new ApplicationBuilder(null);
            app.UseCloudEvents();

            // Do verification in the scope of the middleware
            app.Run(httpContext =>
            {
                httpContext.Request.ContentType.Should().Be("application/json");
                ReadBody(httpContext.Request.Body).Should().Be("{\"name\":\"jimmy\",\"name\":\"billy\"}");
                return Task.CompletedTask;
            });

            var pipeline = app.Build();

            var context = new DefaultHttpContext();
            context.Request.ContentType = "application/cloudevents+json";
            context.Request.Body = MakeBody("{ \"datacontenttype\": \"application/json\", \"data\": {\"name\":\"jimmy\", \"name\":\"billy\"} }", encoding);

            await pipeline.Invoke(context);
        }


Landoop docker image for a dev environment

According to the doc, the docker image is supposed to be created with 6GB memory. I have a dev machine which consists of only 8GB memory. Can we create a landoop docker image with just around 1.5GB? Or, do we have separate mini version of the landoop image for dev environment?

We have made improvements in the last couple months and now you can run fast-data-dev with less memory, but you can't go as low as 1.5GB.
Why is that? Because fast-data-dev runs 5 heavy (by an 8GB laptop standards), JVM-based programs: zookeeper, kafka broker, schema registry, kafka connect worker and kafka rest proxy.
In the current state, you can try with 4 or 4.5GB of RAM. Please remember that on macOS you run docker inside a virtual machine, so some of this memory goes to the VM operating system (linux) itself.
You can go even lower if you disable most connectors you don't need and adjust the connect heap. That way it may work with 2.5GB or even 2GB:
docker run --rm -it -p 3030:3030 \
           -e DISABLE=azure-documentdb,blockchain,bloomberg,cassandra,coap,druid,elastic,elastic5,ftp,hazelcast,hbase,influxdb,jms,kudu,mongodb,mqtt,redis,rethink,voltdb,yahoo,hdfs,jdbc,elasticsearch,s3,twitter \
           -e CONNECT_HEAP=512m landoop/fast-data-dev

But if you see some of the components (broker, schema registry, etc) to keep restarting, it means you have too little RAM.
If you have a spare Linux machine, you can set fast-data-dev to run there (but please use --net=host -e ADV_HOST=[IP_ADDRESS]) and all your developers access that instead of running it on their own laptops.

@andmarios Thanks a lot! This answers my question perfectly.

@andmarios Can we stop rest proxy? Do we really need the same?

No you can't unless you fork the repository and disable it.
But without REST Proxy, Kafka Topics UI will not work.


vuex-router-sync not work correctly in asyncData function

The vuex-router-sync plugin:
import { sync } from 'vuex-router-sync'
export default ({app: {router, store}}) => {
  sync(store, router)
}

The nuxt.config.js
  plugins: [
    // '~plugins/axios',
    '~plugins/vuex-router-sync'
  ],

And then in some of my components:
asyncData({store}){
   console.log(store.state.route.params.id);//not the current url params
}

In the above code, like a router /test/:id, I want to get data in server side, but if the browser location changes like this:
from / to /test/:id，in the asyncData, the route is still /, if I try to get store.route.params.id, it is undefine.
Then if I refresh browser in the path /test/:id, like: /test/1, in the asyncData function, server side will excute, client side will not. And the store.state.route.params.id is 1, this is OK.
Then if click the browser back, and return. In server side AsyncData not excute, it excutes in client side, but this time store.state.route.params.id is undefined. However, the context.route is correct, and when the component is mounted, the store.state.route is right.
There is two questions for me:
1.Why the route from / to /test/:id, in server side, the asyncData does not excute?And when fresh browser in /test/:id, asyncData excute in server side?
2.Why when asyncData excute in client side, store.state.route is not the some with context.route?

I tried as you described, It works fine. Blow is the repo, if I missed anything, pls feel free to point out.
https://github.com/clarkdo/nuxt-issues/tree/issue_2090

Thank you for reply! I cloned your repo, It is the same with my described.Below is the capture:
1.location: http://localhost:3000/test/1, refresh brower, the asyncData excute in cmd, this is ok:

2.Then I clicked the "Home" link, back to home, and then click "Test Id". This time the asyncData excute in client side, it is print below:

This time the store.route is /, you can see it in above picture.
What I know is that the vuex-router-sync  commits route in the hook afterEach. When  the asyncData function excute in client side, the store.state.route is not changed, and it is before route, after a lot of
time, the  store.state.route is changed, when you can console it in mounted hook.
Like below:

Then I try to change the vuex-router-sync:

just change afterEach to beforeEach

// sync store on router navigation
  const afterEachUnHook = router.beforeEach((to, from) => {
  	console.log(to, from, 'router.afterEach');
    if (isTimeTraveling) {
      isTimeTraveling = false
      return
    }
    currentPath = to.fullPath
    store.commit(moduleName + '/ROUTE_CHANGED', { to, from })
  })

Vue console the error:

I think there is a bug, though, I can get route from the context, but in client side asyncData function, store.state.route is not the same with context.route.
I'am try to tranform a vue-server-renderer project to nuxt.js. In vue-server-renderer project , the fetch hook can work well with router.

Sorry about my mistake, you are right. asyncData is in beforeEach and vuex-sync watching is in afterEach.
I suggest that you may move the afterEach inside vuex-router-sync into a middleware.

I updated the codes, you may have a look at https://github.com/clarkdo/nuxt-issues/tree/issue_2090

There is an error : Cannot read property 'registerModule' of undefined.
It has an error in your repo:
plugins/sync.js
export default ({app: {router, store}}) => {
    store.registerModule(moduleName, {
    ...
}

Is there some changed with Nuxt.js?

No, can you describe in brief your steps?

I changed my middleware with your code in my project. This time it is worked well.
There is a question I don't understand that is why in server side the middleware and plugins excute just once when router changed. Exactly, it is just excuting when fresh a browser, or init app.
How does the hook work in server side or client side? The official docs is not explicit. So can some thing more detail?

With your repo, I just do:
1.npm install
2.npm run dev
3.browser to http://localhost:3000/
4.browser display:

plugins execution is under createApp which only executes once as you said, it's designed for running before instantiating the root vue.js application.
middleware in server side is called in ssr server entry just like plugins, and in client is called in client.js->render which is a route beforeEach hook.

I got it. Thanks!

1.Why the route from / to /test/:id, in server side, the asyncData does not excute?And when fresh browser in /test/:id, asyncData excute in server side?
How to solve this question ?


allow configuration of the context root

Atlassian cloud uses confluence in it's URI for search.
With this pull request I have:

Made the "context root" (part of the URI just after the domain/port) configurable
Allowed for there to be an empty context root
Updated the README on how to use this

Coverage decreased (-17.5%) to 73.626% when pulling 681aa7121bbdad938127e413020daf9693d56bca on aaronblythe:config_context_root into 8e701482606ee94e6d3ce88e819f34a84fc4ea6a on amwelch-oss:master.

Coverage decreased (-0.8%) to 90.323% when pulling 0655ff7db5bda2b9132a8cabe813b5018d894117 on aaronblythe:config_context_root into 8e701482606ee94e6d3ce88e819f34a84fc4ea6a on amwelch-oss:master.

Coverage decreased (-18.0%) to 73.118% when pulling babcca2c8c74299a7077823dff2a2e3829de2cbb on aaronblythe:config_context_root into 8e701482606ee94e6d3ce88e819f34a84fc4ea6a on amwelch-oss:master.

Coverage decreased (-18.0%) to 73.118% when pulling 772df4431a03e202b0af32aeef89f10f6cce431c on aaronblythe:config_context_root into 8e701482606ee94e6d3ce88e819f34a84fc4ea6a on amwelch-oss:master.

Sorry about the delayed response. This looks great though, thanks!


Add node taints to Flatcar on AWS

Adds the ability to specify node taints on Flatcar worker pools, along with the corresponding DaemonSet tolerations on bootstrap.

Add node_taints variable to Flatcar worker module on AWS.
Add daemonset_tolerations to Flatcar kubernetes module on AWS and propagate to bootstrap module.

Testing

Created a new cluster and a tainted worker pool.
Ensured worker nodes had the specified taints.
Ensured system daemonsets (e.g. Calico) were still scheduled on the tainted nodes.

Closed by #968


The -main compiler switch accepts a fully qualified class name as a parameter

This PR adds a little explanation regarding the class parameter of the -main C# compiler switch
Fixes #5691

Thanks, @sputier, for adding this important detail. We'll merge your PR as soon as an internal build completes.


Improve quality of opening book

Right now the engine parses 3 files in chessengine.openings at the start of each game to find good opening moves. The file chessengine/openings/ViswanathanAnand.pgn contains very few games, and we could probably replace it with a much larger file. Also, we should look for PGN files that contain a more diverse set of opening moves if possible.

Hi Hrushikeshrv, can you please elaborate further on this issue?
I searched on the web and found some pretty large PGN files of games.

Sure, right now the 3 PGN files in chessengine.openings are minimal, and cover mostly Queen's pawn and King's pawn openings. We should include diverse PGN files that include more openings, but at the same time, we should keep the total size of the files to less than, say, 100,000 games to keep the startup time reasonable.
I have found that http://www.pgnmentor.com/files.html#openings is a good place for PGN files. They have organized the files according to different openings, so you can choose a few files from there that contain a good number of moves and include them in the distribution.

May I work on this

Hey, I'm new to open source. May I work on this issue?

Sorry @Tatwansh , I'll have to assign this to @prasoonmhwr since he commented first

@hrushikeshrv Thanks for assigning the issue, I know that we need to replace the existing pgn file with a file having more games, justs wanted to confirm how many pgn file do you need in this folder 3 or more.


Solution in Layer's Of Lasagna [Swift]

The solution for Test #4 is expecting "25" as it's answers, however the correct answer should be 39. Could be a error with the way the test code was written.

Because if you send remainingMinutesInOven a value for elapsedMinutes of 13, the output of remainingMinutesInOven is 27: expectedMinutesInOven starts at 40; 40 - 13 (elapsed time) = 27 ; 12 + 27 = 39.

The test case for expectedMinutesInOven even explicitly expects "27" as the correct return value. The expected return value for totalTimeInMinutes can't be 25 for the values given, which are the same as the values given to test the other two functions, and those tests pass with those values while the final test does not, even with the same values.

I think this is actually a bit of confusion, however. The third function seems to imply asking for the sum of the output of the first two functions, and that seems logical; however, what it is actually asking for is a sum of the output of the second function and the argument for "elapsedMinutes". I think at least part of this confusion is that the second parameter for totalTimeInMinutes is identical to the parameter for remainingMinutesInOven, implying that it is the output of the function remainingMinutesInOven that should be used, when in fact elapsedMinutes in the function totalTimeInMinutes is supposed to be a constant Int value instead.
IMO the right solution here is to change "elapsedMinutes" in the third function to be some other name. It invites confusion to use identical labels for two different concepts.


refactor: message & notice-bar

Coverage remained the same at 63.715% when pulling 30c4a6a88224afaefd3db6e6e1eef54826013bca on fanpaa:dev into 3838575e06c36938bf1cd59f18b2743f429a0c88 on ZhonganTechENG:dev.

ok,我检查下


Allow CTRL+ENTER to map to new result tab

Hi,
I often remote into my work desktop and lose functionality of the '' key.  This keeps me from being able to use Ctrl+\ to create a new tab.
Would it be possible to have the option of using Ctrl+Enter to create new results tabs?
Thanks,
Ryan

You can redefine any shortcuts (well, almost any) in preferences->General->Keys. Command "Execute SQL in new tab".

Excellent.  Thanks.


Don't Merge! PR real time test for target branch full build

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[Never mind, there are two ways to do this, the documented way also works] Step 24 correction

Step 24 "In Solution Explorer, in the Phoneword.Android project, double-click Properties and select the Android Manifest tab:"
It should be:
In Solution Explorer, right-click Phoneword.Android project, click Properties and select the Android Manifest tab:

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

ID: 2de3e72c-8948-4dd5-e37f-9cf81e62c127
Version Independent ID: 7b7c5c7f-4102-8e91-fbe6-7d21fcc8f5be
Content: Xamarin.Forms Quickstart - Xamarin
Content Source: docs/xamarin-forms/get-started/hello-xamarin-forms/quickstart.md
Product: xamarin
GitHub Login: @davidbritch
Microsoft Alias: dabritch

My mistake, there are two ways to do this. The documented way also works.


Front is not running (Dev mode)

When i run the project with the docker-compose.debug.yml, the front is not working

Resolved, merged in master

Sorry, still not working for me

Could you please add more details for it ? What error you are getting ? What Os you are using ?

I' using windows as OS, so i deleted the sudo before chmod ... and i used the terminal as administrator,
i have this error message :
=> [express internal] load build context                                                                           0.0s
=> => transferring context: 2.00kB                                                                                0.0s
=> [express  1/18] FROM docker.io/library/node:20@sha256:5f21943fe97b24ae1740da6d7b9c56ac43fe3495acb47c1b232b0a35  0.0s
=> CACHED [express  2/18] WORKDIR /api                                                                             0.0s
=> CACHED [express  3/18] RUN  chown -R node:node /api                                                             0.0s
=> CACHED [express  4/18] COPY --chown=node:node package*.json .                                                   0.0s
=> ERROR [express  5/18] RUN npm ci                                                                                1.5s

[express  5/18] RUN npm ci:
1.414 npm ERR! code EUSAGE
1.422 npm ERR!
1.422 npm ERR! npm ci can only install packages when your package.json and package-lock.json or npm-shrinkwrap.json are in sync. Please update your lock file with npm install before continuing.
1.422 npm ERR!
1.423 npm ERR! Missing<EMAIL_ADDRESS>from lock file
1.423 npm ERR!
1.423 npm ERR! Clean install a project
1.424 npm ERR!
1.424 npm ERR! Usage:
1.424 npm ERR! npm ci
1.424 npm ERR!
1.424 npm ERR! Options:
1.424 npm ERR! [--install-strategy <hoisted|nested|shallow|linked>] [--legacy-bundling]
1.424 npm ERR! [--global-style] [--omit <dev|optional|peer> [--omit <dev|optional|peer> ...]]
1.424 npm ERR! [--strict-peer-deps] [--foreground-scripts] [--ignore-scripts] [--no-audit]
1.424 npm ERR! [--no-bin-links] [--no-fund] [--dry-run]
1.424 npm ERR! [-w|--workspace  [-w|--workspace  ...]]
1.424 npm ERR! [-ws|--workspaces] [--include-workspace-root] [--install-links]
1.424 npm ERR!
1.425 npm ERR! aliases: clean-install, ic, install-clean, isntall-clean
1.425 npm ERR!
1.425 npm ERR! Run "npm help ci" for more info
1.435
1.435 npm ERR! A complete log of this run can be found in: /root/.npm/_logs/2023-11-17T07_17_04_792Z-debug-0.log

failed to solve: process "/bin/sh -c npm ci" did not complete successfully: exit code: 1

Please check now.

Hello,
now the front is running but the back is crashed.
Also the host of back called is locahost:4200/api (normaly it should be localhost:3000/api)

this is the error when i try to connect in the front
Error occurred while trying to proxy: localhost:4200/api/user/authenticate
this is the error displayed on ther terminal
mean_express  | [nodemon] app crashed - waiting for file changes before starting...
mean_angular  |
mean_angular  | Warning: This is a simple server for use in testing or debugging Angular applications
mean_angular  | locally. It hasn't been reviewed for security issues.
mean_angular  |
mean_angular  | Binding this server to an open connection can result in compromising your application or
mean_angular  | computer. Using a different host than the one passed to the "--host" flag might result in
mean_angular  | websocket connection issues. You might need to use "--disable-host-check" if that's the
mean_angular  | case.
mean_angular  |
mean_angular  | One or more browsers which are configured in the project's Browserslist configuration will be ignored as ES5 output
is not supported by the Angular CLI.
mean_angular  | Ignored browsers: kaios 2.5, op_mini all
mean_angular  | - Generating browser application bundles (phase: setup)...

It is using proxy for all api calls, please check package.json, 'ng serve --proxy-config proxy.conf.json' , it use proxy.conf.json file for configuration.
Could you please build with no cache
'Docker compose build --no-cache'

In the package.json (front) i have :
"scripts": {
"ng": "ng",
"start": "ng serve --proxy-config proxy.conf.json --host <IP_ADDRESS> --watch --poll 2000",
"serve": "ng serve --proxy-config proxy.conf.json",
"build": "ng build --configuration production",
"test": "ng test",
"lint": "ng lint",
"e2e": "ng e2e",
"dev:ssr": "ng run frontend:serve-ssr",
"serve:ssr": "node dist/frontend/server/main.js",
"build:prod": "ng build --configuration production --output-path=dist",
"build:ssr": "ng build --configuration production && ng run frontend:server:production",
"build:output": "npm run build:ssr --output-path=dist",
"prerender": "ng run frontend:prerender",
"dev-server": "concurrently "nodemon ../api/server.js --watch api" "npm run serve""
},
and in the docker-compose.debug.yml i added args:  - "--no-cache" to the express
express: #name of the second service
build: # specify the directory of the Dockerfile
context: ./api
dockerfile: debug.dockerfile
args:
- "--no-cache"
container_name: mean_express
volumes:
- ./api:/api
ports:
- "3000:3000" #specify ports forewarding
environment:
- SECRET=Thisismysecret
- NODE_ENV=development
- MONGO_DB_USERNAME=admin-user
- MONGO_DB_PASSWORD=admin-password
- MONGO_DB_HOST=database
- MONGO_DB_PORT=
- MONGO_DB_PARAMETERS=?authSource=admin
- MONGO_DB_DATABASE=mean-contacts
links:
- database
but i have the same problem

Hi @bmlaghui ,
I just recloned, and build the project docker compose -f 'docker-compose.debug.yml' build --no-cache
After that I ran docker compose -f 'docker-compose.debug.yml up' and it is working as expected.
Could you please make sure that You have all latest and then run above ?

hi!,
it's working for me , i've replaced the express specification the the docker-compose.debug.yml same as docker-compose.nginx.yml


Read-only CodeEditor prevents opening Find box

URL (minimal example if possible)
E.g.: https://openui5nightly.hana.ondemand.com/entity/sap.f.DynamicPage/sample/sap.f.sample.DynamicPageFreeStyle/code
Steps to reproduce the problem:

Open the above sample code editor which is read-only.
Switch to the view/DynamicPageFreeStyle.view.xml tab.
Press Ctrl + f (Windows, Linux, and Chrome OS) or ⌘ + f (Mac)
Type e.g. "onMessageButtonPress" or any text that is outside of the viewport but still in the code.

What is the expected result?
The finding feature works even if the code editor is in read-only mode.
What happens instead?
In the 2nd step, browser opens its native Find field. Even though the text "onMessageButtonPress" is definitely in the code, browser fails to find it in the code editor.
Any other information? (attach screenshot if possible)

This happens only if the code editor is in read-only mode. If the code editor is writable, finding the text works with the find feature from ace.
Currently, the UI5 control sap.ui.codeeditor.CodeEditor uses ace 1.4.4. But even with 1.4.4, ace allows showing its search field even if the editor is in read-only (so it's not an issue of ace):

Go to https://rawgit.com/ajaxorg/ace/v1.4.4/kitchen-sink.html
Click on "Read-Only" in control panel.
Press the key combination mentioned in the 2nd step above. Ace shows its search field wich finds texts that are also out of the viewport.

Hello @boghyon ,
Thank you for sharing this finding. I've created an internal incident<PHONE_NUMBER>. The status of the issue will be updated here in GitHub.
Thanks and Best Regards,
Tsanislav


Paraformer: different dimension of tensors

Describe the bug
I am testing Paraformer architecture and got this traceback during model testing:
Traceback (most recent call last):
  File "/root/wenet-2.2.1/examples/csv/paraformer/wenet/bin/recognize.py", line 385, in <module>
    main()
  File "/root/wenet-2.2.1/examples/csv/paraformer/wenet/bin/recognize.py", line 366, in main
    hyps = model.paraformer_greedy_search(
  File "/root/wenet-2.2.1/wenet/paraformer/paraformer.py", line 210, in paraformer_greedy_search
    predictor_outs = self.calc_predictor(encoder_out, encoder_mask)
  File "/root/wenet-2.2.1/wenet/paraformer/paraformer.py", line 156, in calc_predictor
    self.predictor(
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1190, in _call_impl
    return forward_call(*input, **kwargs)
  File "/root/wenet-2.2.1/wenet/cif/predictor.py", line 75, in forward
    hidden, alphas, token_num = self.tail_process_fn(hidden, alphas,
  File "/root/wenet-2.2.1/wenet/cif/predictor.py", line 96, in tail_process_fn
    mask_1 = torch.cat([mask, zeros_t], dim=1)
RuntimeError: Tensors must have same number of dimensions: got 5 and 2

To Reproduce
Steps to reproduce the behavior:

Train a Paraformer model
Star evaluation

Additional context
wenet - 2.2.1
pytorch - 1.13.1
python - 3.10

Thanks for your feedback. I would like to ask what dataset you are using?

Hello! Any update on the issue?

i meet the same problem.
test dataset is aishell1-test

There are some mistakes of the naming of two variables in here, i.e., 'encoder_mask' and 'encoder_out_lens'. We coud fix it by referring to the original implementation funasr.
`
In wenet/paraformer/paraformer.py, you need following change:
false:
predictor_outs = self.calc_predictor(encoder_out, encoder_mask)
true:
predictor_outs = self.calc_predictor(encoder_out, encoder_out_lens)
false:
def calc_predictor(self, encoder_out, encoder_out_lens):
    encoder_mask = (~make_pad_mask(
        encoder_out_lens, max_len=encoder_out.size(1))[:, None, :]).to(
            encoder_out.device)

true:
def calc_predictor(self, encoder_out, encoder_mask):
    encoder_mask = (~make_pad_mask(
        encoder_mask, max_len=encoder_out.size(1))[:, None, :]).to(
            encoder_out.device)

false:
decoder_outs = self.cal_decoder_with_predictor(encoder_out,
encoder_out_lens,
pre_acoustic_embeds,
pre_token_length)
true:
decoder_outs = self.cal_decoder_with_predictor(encoder_out,
encoder_mask,
pre_acoustic_embeds,
pre_token_length)
false:
def cal_decoder_with_predictor(self, encoder_out, encoder_out_lens,
sematic_embeds, ys_pad_lens):
true:
def cal_decoder_with_predictor(self, encoder_out, encoder_mask,
sematic_embeds, ys_pad_lens):
`
By doing this, it's work for me to do the paraformer_greedy_search decoding on aishell-1 testset.

@lxp3 I have patched my fork and got one exception only during inference:
2023-06-27 16:31:02,536 INFO Checkpoint: loading from checkpoint exp/conformer/avg_6.pt for GPU
2023-06-27 16:31:02,536 INFO Checkpoint: loading from checkpoint exp/conformer/avg_6.pt for GPU
2023-06-27 16:31:12,168 INFO 1122 ▁▁▁▁▁
Traceback (most recent call last):
  File "/root/wenet-2.2.1/examples/csv/paraformer/wenet/bin/recognize.py", line 385, in <module>
    main()
  File "/root/wenet-2.2.1/examples/csv/paraformer/wenet/bin/recognize.py", line 358, in main
    hyps = model.paraformer_beam_search(
  File "/root/wenet-2.2.1/wenet/paraformer/paraformer.py", line 292, in paraformer_beam_search
    predictor_outs = self.calc_predictor(encoder_out, encoder_mask)
  File "/root/wenet-2.2.1/wenet/paraformer/paraformer.py", line 156, in calc_predictor
    self.predictor(
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1190, in _call_impl
    return forward_call(*input, **kwargs)
  File "/root/wenet-2.2.1/wenet/cif/predictor.py", line 75, in forward
    hidden, alphas, token_num = self.tail_process_fn(hidden, alphas,
  File "/root/wenet-2.2.1/wenet/cif/predictor.py", line 96, in tail_process_fn
    mask_1 = torch.cat([mask, zeros_t], dim=1)
RuntimeError: Tensors must have same number of dimensions: got 5 and 2

@egorsmkv  It's supposed to use the 'encoder_out_lens' as input  instead of 'encoder_mask' when calling the self.calc_predictor().
predictor_outs = self.calc_predictor(encoder_out, encoder_out_lens)

@lxp3 now I am getting another exception:
Traceback (most recent call last):
  File "/root/wenet-2.2.1/examples/csv/paraformer/wenet/bin/recognize.py", line 385, in <module>
    main()
  File "/root/wenet-2.2.1/examples/csv/paraformer/wenet/bin/recognize.py", line 358, in main
    hyps = model.paraformer_beam_search(
  File "/root/wenet-2.2.1/wenet/paraformer/paraformer.py", line 300, in paraformer_beam_search
    decoder_outs = self.cal_decoder_with_predictor(encoder_out,
  File "/root/wenet-2.2.1/wenet/paraformer/paraformer.py", line 165, in cal_decoder_with_predictor
    decoder_out, _, _ = self.decoder(encoder_out, encoder_mask,
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1190, in _call_impl
    return forward_call(*input, **kwargs)
  File "/root/wenet-2.2.1/wenet/transformer/decoder.py", line 136, in forward
    x, tgt_mask, memory, memory_mask = layer(x, tgt_mask, memory,
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1190, in _call_impl
    return forward_call(*input, **kwargs)
  File "/root/wenet-2.2.1/wenet/transformer/decoder_layer.py", line 118, in forward
    self.src_attn(x, memory, memory, memory_mask)[0])
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1190, in _call_impl
    return forward_call(*input, **kwargs)
  File "/root/wenet-2.2.1/wenet/transformer/attention.py", line 186, in forward
    return self.forward_attention(v, scores, mask), new_cache
  File "/root/wenet-2.2.1/wenet/transformer/attention.py", line 101, in forward_attention
    if mask.size(2) > 0 :  # time2 > 0
IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 2)

@lxp3 thanks! Now it works.


[mbedtls] remove GSDK mbedtls config template from includes

This fixes a build failure that occurs when -DOT_COAPS=ON.
Including this directory was causing the 'mbedtls_config.h' from that directory to be loaded instead of the one
in src/src
This PR also adds a copy of psa_crypto_config.h to src/src

@jwhui - Unrelated to this PR, could you set the default merge strategy in this repo to use squashed merges?

LGTM

@jwhui can you merge this PR please?


Profile version error for "latest"

I get these errors with string value "latest" and for a specific version e.g 1.1.0 for profile version arg of the attachment module
2024/11/28 17:47:25 Terraform apply | Error: Invalid index
 2024/11/28 17:47:25 Terraform apply |
 2024/11/28 17:47:25 Terraform apply |   on .terraform/modules/scc_profile/modules/attachment/main.tf line 39, in locals:
 2024/11/28 17:47:25 Terraform apply |   39:   latest_profile = local.sorted_list[length(local.sorted_list) - 1]
 2024/11/28 17:47:25 Terraform apply |     ├────────────────
 2024/11/28 17:47:25 Terraform apply |     │ local.sorted_list is empty tuple
 2024/11/28 17:47:25 Terraform apply |
 2024/11/28 17:47:25 Terraform apply | The given key does not identify an element in this collection value: a
 2024/11/28 17:47:25 Terraform apply | negative number is not a valid index for a sequence.

Code
module "scc_profile" {
  for_each                       = { for entry in local.security_center_profiles : entry.id => entry }
  source                         = "terraform-ibm-modules/scc/ibm//modules/attachment"
  profile_name                   = each.value.profile_name
  profile_version                = "latest"
  use_profile_default_parameters = true
  scc_instance_id                = module.security_center[each.value.resource_instance].guid
  attachment_name                = each.value.attachment_name
  attachment_description         = each.value.attachment_description
  attachment_schedule            = each.value.attachment_schedule
  scope = [{
    environment = "ibm-cloud"
    properties = [{
        name  = "scope_type"
        value = "account"
      }]
  }]
}
...

@65156 what value did you use for profile name? Please be aware that the SCC team included a version number in some of the profile names.
For example, you need to use this full string for the CIS profile name: CIS IBM Cloud Foundations Benchmark v1.1.0. They said that actually the version of the benchmark, and it just also hgappens that the profile version is 1.1.0 too. But technically there could be a profile named CIS IBM Cloud Foundations Benchmark v1.1.0 on version 1.2.0 (not confusing at all :/ )


2024-04-19, Python으로 웹 스크래퍼 만들기: From 4.0 to 4.4

<EMAIL_ADDRESS>


feat(shared): Add a tsl.so C-shared library

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


fix(CI): remove target path of binary locations in .releaserc.yml

Closes #67

:tada: This PR is included in version 1.0.2 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Migrate Firehose Doc to Gitbook

Move firehose.streamingfast.io to GitBooks, following a similar pattern we have done for Substreams

The docs are all ported at this point and have been. There is a new structure to the docs and content as well.

I'm going to close this per the Zoom conversation with Julien on 09/06/22. The overall work for this is done and smaller, more granular tasks have been identified and will be input into Planning.


Unpin numpy as a host dep

Continuation of #85
cc @h-vetinari @ngam @mkitti

Damn, still broken: https://github.com/MilesCranmer/PySR/actions/runs/5192076497

What is the load error to begin with? Set LD_DEBUG=libs for Linux.

Not sure. I think if I fix the libdstdcxx-ng to an earlier version the error goes away (IIRC).
Here's a run with LD_DEBUG=libs (just started)

Damn, still broken: https://github.com/MilesCranmer/PySR/actions/runs/5192076497

You have a completely separate issue there; it looks like it's scipy, but it's not. I've tested it. It might however be influenced if something similar to the numpy situation is happening for scipy (e.g. reinstalling it through julia).

Rather than a two-step setup, why not include python -m pysr.test main (with whatever preparations are necessary) here?

If I want to constrain libstdcxx-ng'<13', I guess I should add that to host:?

You would have to add it under run_constrained:. But it shouldn't be necessary, so I'd be interested how it fails without that pin.

I also thought this post was quite interesting about how the whole gig works: https://discourse.julialang.org/t/the-present-and-the-future-of-package-registration/99890

What does that have to do with this?
It's basically analgous to a conda channel. We can create our own registry:
https://github.com/GunnarFarneback/LocalRegistry.jl
I just don't want to run it.

Superseded by https://github.com/conda-forge/pysr-feedstock/pull/90


#1103 Refactor Multi.toFlow() to avoid blocking - Mutiny1

Switching from channelFlow to callbackFlow brings simplification
Blocking issue (https://github.com/smallrye/smallrye-mutiny/issues/1103) was caused by buffering of the channel that underlies the Flow, solved by explicit switching to an unlimited channel that doesn't buffer.

Let's see progress on #1105

@heubeck You can sync from #1105 👍

really sure?
Every use of the toFlow needs to be re-compiled, I'm afraid there might be transient usages in libraries that get the bytecode-incompatible version by downstream dependency management and break at runtime.
I'll do it, if you say so, just mentioning.

Hum you have a point.

So the fix for 1.x could be to keep the method, and perform unlimited buffering, and update the docs.
WDYT?

So the fix for 1.x could be to keep the method, and perform unlimited buffering, and update the docs.
WDYT?

convinced 😊
Will also add a statement for that thing to the mutiny 2 docs as it's not obvious.


macros: Drop anyhow dependency

Since #1688 was merged, it is used in a single place and it is easy to remove, so it doesn't seem worth it to keep depending on it.

Thanks a lot!


After selecting a dataset, approving a new statement (or a source of a suggested one) makes all (other) suggested sources disappear

To reproduce, switch to the "freebase" dataset in the gadget, go to a random freebase item, approve a new statement, but none of the sources. The page reloads, the new statement appears, none of the sources (that weren't approved, but neither were they rejected) is suggested again.
Alternatively, approve or reject one of the sources. The page reloads, the new statement with the approved source is there. If there were other suggested sources, they're not suggested again
Using the "all sources" dataset works as expected.

In this case it is a data model issue. Approval or rejection currently is at the statement level, not at the source level. So if a single statement has multiple sources, then the statement is accepted with all its sources. If we want to keep sources separate, it would be necessary to import the statements differently into the backend, i.e. repeat the statement for each source.
Not sure if this is really a bug. We should have a more thorough discussion on this.

Is the data model after selecting a dataset different from the "all sources" datamodel? Because that one allows approving statements without approving any of the sources.

No, the problem is in the way statements with multiple sources are represented when they are imported. There are two ways:
Q123 P456 "abc" source S1 source S2

is represented internally as a single statement with a single approval, whereas
Q123 P456 "abc" source S1
Q123 P456 "abc" source S2

is represented internally as two statements with each a separate approval. In the initial dataset we had decided to duplicate statements with multiple sources so each statement in the backend only has a single source. Apparently, some of the newer datasets use the single-statement-multiple-sources model.
While it is possible to fix the problem in the backend, this change would have major consequences for the backend and might even have performance problems. I would prefer fixing the problem on the data level instead.

This is related to #34 .

If we want to keep sources separate, it would be necessary to import the statements differently into the backend, i.e. repeat the statement for each source.

I believe that it's what is done currently.

Apparently, some of the newer datasets use the single-statement-multiple-sources model.

I don't think so. The dataset uploaded a few weeks ago (result-06-10) use one statement per source with single snak sources and the one with Freebase ids use also one statement per source but the sources contains two snaks.

To reproduce, switch to the "freebase" dataset in the gadget, go to a random freebase item, approve a new statement, but none of the sources.

I believe that what happens here is that the main snak + qualifiers get saved but the statements with the same main snak + qualifiers get approved in the backend. To fix this issue we should maybe not mark as approved a statement with source when only the main snak + qualifiers get approved.

Alternatively, approve or reject one of the sources. The page reloads, the new statement with the approved source is there. If there were other suggested sources, they're not suggested again

Does it happen only with Freebase ids? If yes, I believe that it is because the frontend does not support yet sources that have two snaks. It is the topic of issue #34

Does it happen only with Freebase ids? If yes, I believe that it is because the frontend does not support yet sources that have two snaks. It is the topic of issue #34

After managing to find an item with suggestions other than Freebase ids, it looks like it does not affect all suggestions - I approved the voice actor occupation on https://www.wikidata.org/wiki/Q2468138 by approving http://www.imdb.com/title/tt2809036/.

If I do a request
curl -i "https://tools.wmflabs.org/wikidata-primary-sources/entities/Q7430618?state=any"

I get a result with two sources:
Q7430618\tP646\t\"/m/0bfvws\"\tS248\tQ20635329\tS577\t+00000002015-02-13T00:00:00Z/11

The second source seems to be a timestamp, and I couldn't find documentation on the property S577 that is used here.
Regarding the "accepting statement including source" issue: I would say this is the correct behaviour. You should not be able to accept a statement without its source. You might be able to accept the statement a second time with a second source, though. Maybe the UI should ensure this is handled this way?

Regarding the "accepting statement including source" issue: I would say this is the correct behaviour. You should not be able to accept a statement without its source. You might be able to accept the statement a second time with a second source, though. Maybe the UI should ensure this is handled this way?

If it should only be possible to accept a statement with at least one source, the UI needs to be changed - having an "approve" button next to the statement itself certainly suggests that a statement can be approved without a source. Though I agree - with dataset support, there should be at least one valid source for each statement, which is the dataset.

Maybe the UI should ensure this is handled this way?

I agree with you. I'll work on it today

It should be fixed now. Feel free to reopen the bug if it is not the case.


Fix: read token component (ST-691)

@ericHgorski this branch currently fails to compile.

@ericHgorski this branch currently fails to compile.

I think its a cloudlfare problem. It builds/runs fine locally. Are you having an issue?


RO-2960 Update RE-1082 dependencies

This change is the result of running gating/update_dependencies/*
See update_dependencies in https://rpc-openstack.atlassian.net/wiki/spaces/RE/pages/19005457/RE+for+Projects for more details.
Issue: RO-2960

Testing changes to the dependency update script


Gamepad support

I really like windy's support of keyboard/mouse, but for making a game-engine I want to support gamepads, primarily.
I made a light wrapper for libstem_gamepad, which is made in C, and works on Windows, Linux, and OSX. I could make it feel a bit more like windy's state-helpers (like buttonPressed / buttonDown / buttonReleased / buttonToggle) and make a PR to include this, if there is interest. Is there a more nim-ish way to do this? Is this outside the scope of what windy is trying to do?
Usage currently looks like this:
let windowSize = ivec2(320, 240)
let window = newWindow("null0", windowSize)
makeContextCurrent(window)
loadExtensions()

proc onGamepadAttached(device: ptr Gamepad_device; context: pointer) =
  var js = device[]
  echo "attached: " & $js.deviceID

proc onGamepadRemoved(device: ptr Gamepad_device; context: pointer) =
  var js = device[]
  echo "removed: " & $js.deviceID

proc onButtonDown (device: ptr Gamepad_device; buttonID: cuint; timestamp: cdouble; context: pointer) =
  var js = device[]
  echo "buttonDown(" & $js.deviceID & "): " & $buttonID

proc onButtonUp (device: ptr Gamepad_device; buttonID: cuint; timestamp: cdouble; context: pointer) =
  var js = device[]
  echo "buttonUp(" & $js.deviceID & "): " & $buttonID

proc onAxisMoved (device: ptr Gamepad_device; axisID: cuint; value: cfloat; lastValue: cfloat; timestamp: cdouble; context: pointer) =
  var js = device[]
  echo "axis(" & $js.deviceID & "): " & $axisID & " : " & $value

const GAMEPAD_POLL_ITERATION_INTERVAL=30
gamepad.deviceAttachFunc(onGamepadAttached)
gamepad.deviceRemoveFunc(onGamepadRemoved)
gamepad.buttonDownFunc(onButtonDown)
gamepad.buttonUpFunc(onButtonUp)
gamepad.axisMoveFunc(onAxisMoved)
gamepad.init()

var iterationsToNextPoll = GAMEPAD_POLL_ITERATION_INTERVAL
while not window.closeRequested:
  pollEvents()
  dec iterationsToNextPoll
  if iterationsToNextPoll == 0:
    gamepad.detectDevices()
    iterationsToNextPoll = GAMEPAD_POLL_ITERATION_INTERVAL
  gamepad.processEvents()

Running in Github actions, I realized the windows build-flags probably need some work, so I could use some help testing/tuning:
when defined(windows):
  {.compile: "vendor/gamepad/source/gamepad/Gamepad_windows_dinput.c".}
  {.compile: "vendor/gamepad/source/gamepad/Gamepad_windows_mm.c".}
  {.passC: "-DFREEGLUT_STATIC -I C:/MinGW/dx9/include".}
  {.passL: "C://MinGW//dx9//lib//x64//Xinput.lib C://MinGW//dx9//lib//x64//dinput8.lib C://MinGW//dx9//lib//x64//dxguid.lib C://MinGW//WinSDK//Lib//x64//WbemUuid.Lib C://MinGW//WinSDK//Lib//x64//Ole32.Lib C://MinGW//WinSDK//Lib//x64//OleAut32.Lib".}

This seems to work on fresh OSX, though:
when defined(macosx):
  {.compile: "vendor/gamepad/source/gamepad/Gamepad_macosx.c".}
  {.passL: "-framework IOKit".}

I ended up making a separate library. It still doesn't build right for windows, but I will try to set aside some to get it working this weekend. I have published it for nimble, but am happy to modify to make it fit better with windy, if there is interest.

Wow this is pretty cool! I like that you are makin the game pad support. We don't need it the moment, but I can see us needing this in the future!

I could use some help publishing it, I am very new to nim. It builds fine, but if I try to install it in my test project from nimble, it says the C files are missing. I am probably missing some small thing in the nimble file. @treeform you have published a ton of packages, any hints?


import error

Describe the question

A clear and concise description of what the question is.
TypeError: Descriptors cannot not be created directly.
If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0.
If you cannot immediately regenerate your protos, some other possible workarounds are:

Downgrade the protobuf package to 3.20.x or lower.
Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).

More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates
Environment (please complete the following information):

OS: mac
Python 3.8

Screenshots

If applicable, add screenshots to help explain your problem.

Additional context

Add any other context about the problem here.

Thanks for your issue and we will fix this problem soon !

You can first downgrade protobuf to 3.20.1 for further use.

We will try to fix the version bug soon.

Hello, the dependent packages used in DeepKE have been updated. You can reinstall DeepKE now.


feat: add short name for Mode Mainnet

What it solves
Adds short name for Mode Mainnet:
https://github.com/ethereum-lists/chains/blob/master/_data/chains/eip155-34443.json
Contracts we merged into safe-deployment at https://github.com/safe-global/safe-deployments/pull/356
Thanks in advance!

Will be solved in https://github.com/safe-global/safe-core-sdk/pull/675


ERROR thread 'tokio-runtime-worker' panicked at 'called Result::unwrap() on an Err value: O blablabla

$ proxy-rs find --types HTTP HTTPS -l 10 --levels High --countries ID
thread 'tokio-runtime-worker' panicked at 'called Result::unwrap() on an Err value: Os { code: 17, kind: CrossesDevices, message: "The system cannot move the file to a different disk drive." }', C:\Users\Ikhsani Hidayat.cargo\registry\src\index.crates.io-6f17d22bba15001f\proxy-rs-0.2.72\src\utils\geolite_database.rs:130:44
stack backtrace:
0:     0x7ff77bd981cc -
1:     0x7ff77bdb5feb -
2:     0x7ff77bd93949 -
3:     0x7ff77bd97f7b -
4:     0x7ff77bd9a789 -
5:     0x7ff77bd9a43f -
6:     0x7ff77bd9ac8e -
7:     0x7ff77bd9ab7d -
8:     0x7ff77bd98b49 -
9:     0x7ff77bd9a880 -
10:     0x7ff77be4aab5 -
11:     0x7ff77be4afc3 -
12:     0x7ff77bb0b520 -
13:     0x7ff77bb2230e -
14:     0x7ff77ba23c31 -
15:     0x7ff77ba31a3a -
16:     0x7ff77baff2bf -
17:     0x7ff77b8d7a44 -
18:     0x7ff77bc3926d -
19:     0x7ff77bc360e3 -
20:     0x7ff77bc60d76 -
21:     0x7ff77bc39007 -
22:     0x7ff77bc2fe84 -
23:     0x7ff77bc4e4d0 -
24:     0x7ff77bc4199b -
25:     0x7ff77bc33c9e -
26:     0x7ff77bc4a418 -
27:     0x7ff77bd9fefc -
28:     0x7ffd50f626ad - BaseThreadInitThunk
29:     0x7ffd5118aa68 - RtlUserThreadStart
ERROR [proxy_rs::judge] <Judge [HTTP] httpbin.org>: Timeout error
ERROR [proxy_rs::judge] <Judge [HTTPS] httpbin.org>: Timeout error
I have been tried to run export RUST_BACKTRACE=1 and export RUST_BACKTRACE=full
but still getting error. how to solve this problem?
I'm using windows 11

Try reinstalling using git
cargo install --git https://github.com/zevtyardt/proxy.rs

Let me know if this patch works

Try reinstalling using git
cargo install --git https://github.com/zevtyardt/proxy.rs

Let me know if this patch works

THANKS. IT WORKS


The amount units drop down is not styled like other dropdowns

Issue description
The amount units drop down is not styled like other dropdowns
Wallet version
Which version of wallet are you using?
0.3.0
System specification
Windows
Is it a repeatable issue?
Y/N

Fixed with next version


replace the word hang with something more appropriate

Depending on the usage, had to choose different ways of expressing it.  Didn't change use of hanging for formatting as that term is specific.
Fix https://github.com/PowerShell/PowerShell/issues/5147

did you look for hung as well?

@TravisEz13 fixed 3 instances of hung


Preserve explicitly assigned header ids

Fixes #613.
Also fixes one test which relied on the buggy behaviour.

Looks all good to me. Many thanks for finding and fixing this issue!


Adds options to generate immutable types.

The purpose of this PR is to add options for generating immutable Java types.  Please let me know if you think something like this would be useful to add to jsonschem2pojo.  (We're using these modifications internally at Sift Science.)
For the address.json example, the generated code with immutable=true and generateBuilderClasses=true looks roughly like:
@JsonDeserialize(builder = Address.Builder.class)
public class Address {
    @JsonProperty("post-office-box")
    private final String postOfficeBox;
    ...
    @JsonIgnore
    private final Map<String, Object> additionalProperties;

    private Address(Address.Builder builder) {
        this.postOfficeBox = builder.postOfficeBox;
        ...
        this.additionalProperties = ImmutableMap.copyOf(builder.additionalProperties);
    }

    // no setter methods

    public static Address.Builder newBuilder() {
        return new Address.Builder();
    }

    @JsonProperty("post-office-box")
    public String getPostOfficeBox() {
        return postOfficeBox;
    }
    ...
    @JsonAnyGetter
    public Map<String, Object> getAdditionalProperties() {
        return this.additionalProperties;
    }

    public final static class Builder {
        private String postOfficeBox;
        ...
        private Map<String, Object> additionalProperties = new HashMap<String, Object>();

        private Builder() { }

        public Address build() {
            return new Address(this);
        }

        @JsonProperty("post-office-box")
        public Address.Builder withPostOfficeBox(String postOfficeBox) {
            this.postOfficeBox = postOfficeBox;
            return this;
        }

        public Address.Builder withAdditionalProperties(Map<String, Object> additionalProperties) {
            this.additionalProperties = additionalProperties;
            return this;
        }

        @JsonAnySetter
        public Address.Builder withAdditionalProperty(String name, Object value) {
            this.additionalProperties.put(name, value);
            return this;
        }
    }
}

And generated code with immutable=true, generateBuilderClasses=true, and usePublicFields=true looks roughly like:
@JsonDeserialize(builder = Address.Builder.class)
public class Address {
    @JsonProperty("post-office-box")
    public final String postOfficeBox;
    ...
    @JsonIgnore
    public final Map<String, Object> additionalProperties;

    private Address(Address.Builder builder) {
        this.postOfficeBox = builder.postOfficeBox;
        ...
        this.additionalProperties = ImmutableMap.copyOf(builder.additionalProperties);
    }

    // no setter or getter methods

    public static Address.Builder newBuilder() {
        return new Address.Builder();
    }

    public final static class Builder {
        // Builder is identical to above
        ...
    }
}

At the moment, the options immutable=true and generateBuilderClasses=false don't work together.  (For these options, it is necessary to generate a constructor that takes one argument per property and initializes all property fields, but I haven't written code to do this.)  I can merge these options into one or maybe take a stab at generating constructors for immutable Java types.

@joelittlejohn What would be the next steps to have this feature merged?

+1 I'd really like to use this :-)

So what is blocking this?

@diversit I take your point, but the complexity and cost of your solution in Java is very large. Java doesn't have a notion of structural sharing, so doing a full, deep clone when one property changes is hugely expensive. Your short example is neat, however as the number of properties grows there's an explosion of code required to achieve the model you're proposing. I completely agree that it's a better model, but it's just impractical in Java [hint: use Clojure for a sane approach to immutability and effortless JSON].
It's time to get this in. I see a bunch of further changes have happened on this branch that aren't associated with the original PR - I'll pick through what's here and see how easy it is to merge only the builder parts.

+1 for immutability

Another +1


Improvement pytest

So this PR adds unit tests, and code coverage checks.  I think we should start maturing our test writing chops sooner than later.  As the team grows the tests will give new members some confidence that they aren't committing system breaking changes.  Also, chasing a 100% code-coverage can be a new pastime.
A bigger change is that I moved example into a src directory.
I was convinced of this for a few reasons, one of which was this blog post:
https://blog.ionelmc.ro/2014/05/25/python-packaging/#the-structure
Let me know what you think.

Check out this new thang:

Check out this new thang:

Yes, I saw that thang!


CLI Tool

The Current System doesn't allow the graphql schema to be rebuilt in runtime after it has been changed/edited

Why do you want to rebuild the schema? I thought we were building
entity and service types

Issue Description Update
A CLI-tool to help generate types for the graphql model which reruns after every change to the graphql schema


GPU memory consumption increases over the Epoch a lot

Hi,
thanks for the great work. I successful trained the 4-scale-swin-L model on a smaller Dataset with a few 1000 images which are 1024x1024 each. When training now with 100k images (same size as before) per epoch the GPU memory seems to slowly increase until the GPU goes out of memory. Is that the normal behavior? I train with batchsize 1 per GPU on TITAN RTX 24GB GPUs.
Thinking it might be the bigger serialized dataset which takes 435.86 MiB - I went from a Swin -L to a Swin-B backbone with the same result just after more iterations. Starting with around 12GB being allocated at the start - it goes up until it doesn't fit the 24GB in ~20k iterations. I attached the log of that training with 1 GPU and batch size 1.
Support would be highly appreciated :)
example_log.LOG

Thanks for providing the issue.
1. Common phenomenon if there is a mild mem increase in early epochs.
We observed the increasing memory usage during training in both the original DINO and the detrex version,  but only in the early epochs and most mild.
Some reasons might contribute to the phenomenon: 1) DINO random resizes images as augmentation. Early training samples might have small sizes. The max image size will be (1333, 800) if bs=1. If you want to know the max GPU mem needed, you might run a test script, where all training images are resized to the max sizes. 2) The GPU mem needed is related to the ground truth boxes annotated in your training images. Some training images might have more annotated boxes, which results in a mem peak after training for a while.
In summary, it is common to have a mild memory increase in the early steps.
2. For you case
I looked at your log and found the GPU utilization increased significantly, even after 10 epochs, which is strange to me. We checked our training logs on COCO. The GPU mem usage increases from about 32G (~1k steps) to 38G (~60k steps), and the usage become stable then. I speculate it to the uncenterty mentioned above. For example, a image with many annotations have the max random sizes at a training point, which will cause a mem peak.

Thanks for the answer:
I checked the amount of annotation per image: They vary a lot and can go up to 6.5k annotated objects in one patch. So that's probably the cause of the memory peaks. We hopefully soon get new GPUs - so I can test DINO with the data.
Or do you see any ideas of avoiding the peaks?

There are two ways to reduce GPU mems. The first is to use smaller models or input resolution. Another is to introduce some engineering techniques. Two commonly used ways are mixed precision training and gradient checkpointing.

Thanks for the advice - I will try it out :) .


Add conversion functions to Size and Vector

This PR adds conversion functions to Size and Vector for convenience.

Thanks for the review, I applied the requested changes.


Added fingerprints for  Heatit Z-TRM2 and Z-TRM3 (fingerprints.yml)

Added fingerprints for Heatit Z-TRM2 and Z-TRM3

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

@fredrile can you please click these buttons

@fredrile can you please click these buttons

You mean the CLA? If so, It´s signed.

@greens please review

Hello - We are closing this PR. If you would like to pursue WWST Certification please reach out to<EMAIL_ADDRESS>


Enable Airflow installation directly in the UI

Migrated from GitLab: https://gitlab.com/meltano/meltano/-/issues/664
Originally created by @dmor on 2019-05-29 21:15:04

Currently, the user must install Airflow from the command line in order to activate the "Orchestration" step in the UI.
Proposed Solution: enable the user to click "install Airflow" from the UI and handle all configuration and setup steps in the UI itself, without needing the command line at all.

View 3 previous comments from the original issue on GitLab


MaxInactivityTimeDeviceLock Documentation incorrectly specifies seconds instead of minutes

Hi Trying to use
./Device/Vendor/MSFT/Policy/Config/DeviceLock/MaxInactivityTimeDeviceLock
The documentation says time in seconds but I think it should be minutes.

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

ID: 28a3dde0-fe8d-25d3-3a7e-83acf9c394c6
Version Independent ID: 2c654710-0be1-1d50-9972-6ccf9d072bf1
Content: Policy CSP - DeviceLock - Windows Client Management
Content Source: windows/client-management/mdm/policy-csp-devicelock.md
Product: w10
Technology: windows
GitHub Login: @ManikaDhiman
Microsoft Alias: dansimp

Just now i verified in group poicy editor, and i  conformed  time is in seconds only.
Policy setting: Interactive logon: Machine inactivity limit
Location in the Local Security Policy snap-in:
Computer Configuration/Windows Settings/Security Settings/Local Policies/Security Options/

@toggenation - Can you please share any screenshot showing that this input is required in Mins instead of seconds.

From here => https://docs.microsoft.com/en-us/windows/client-management/mdm/devicelock-csp it specifies minutes

But here => https://docs.microsoft.com/en-us/windows/client-management/mdm/policy-csp-devicelock#devicelock-maxinactivitytimedevicelock it specifies seconds.

But in testing when I set it to seconds ( 15*16 =900) it took I think 900 minutes to lock but setting it to 15 minutes I got the expected behaviour.
This is a screenshot of a working intune policy works with it specified in minutes

And the original link to where I found the mention of minutes instead of seconds:
https://social.technet.microsoft.com/Forums/en-US/a427d387-8a64-439b-9a7f-66115dfa7c07/intune-screen-timeout-for-windows-10-desktop?forum=microsoftintuneprod#9fb63275-771c-4337-a1d5-b49f67ffbfc2