causally_upstream_of _or _within -o- part _of -> causally_upstream_of _or _within

With the decision to eliminate the 'involved in' terms and convert them to GO-CAM models we are losing information when we convert the GO-CAM to standard annotations. If the original annotation had a GP to term relation of causally_upstream_of_or_within 'blah involved in blac' and it is decomposed to an expression in which the GP is causally upstream of or within blah that is part of blac, only a single annotation is generated to blah. The information about the other process is lost in an annotation extension.
We need to generate annotations to both process as happens when the GP2term relation is part_of.
See http://noctua.geneontology.org/editor/graph/gomodel:64d5781900001000
and the annotation preview for an example.
ping @LiNiMGI

@ukemi are you proposing we add the property chain causally_upstream_of _or _within o part _of -> causally_upstream_of _or _within? I think that makes sense. Could you make an RO issue?

Yep. https://github.com/oborel/obo-relations/issues/746

Do you think we also need
acts_upstream_of_or_within o part_of -> acts_upstream_of_or_within?

Probably so.

@ukemi Is this part of a project, or something else?

Something else. Unless we consider annotation review due to obsoletion a project.

@balhoff knows better than I but I suspect once the property chains are added to RO, the reasoning that is in place will consider them and create the missing annotations.

@balhoff knows better than I but I suspect once the property chains are added to RO, the reasoning that is in place will consider them and create the missing annotations.

That's true, it should only require changes in RO.

If this only requires changes in RO, should we close this ticket?

I opened a pull request: https://github.com/oborel/obo-relations/pull/771

This has been merged in RO.


Revert "qtbase: fix intermittent rpi-qtauto gammaray build failures"

This issue has been fixed in the mainline meta-qt5@3820e2d1b2a8f961980.
This reverts commit dce88dd84a2efc38a60d48a48e6a22752591b8ff.

I have not looked at the upstream commit but might be a good idea to verify that the bitbake commands I wrote in the reverted commit's commit message does not give you any error.

Looking at the console output of the failed build, it looks like the same error is reintroduced. Do not know why. We were lucky that it just happened to fail.
Anyway, please make sure that the steps to reproduce are not failing before merging this (do not rely in Jenkins failing, because it's random).


incorrectly gives errors for XHTML

If I have an XHTML file (HTML stored as XML), specifically, HTML5, my file starts like this:
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE html>

Unfortunately HTMLHint thinks that < must be escaped, that a DOCTYPE must appear before it, etc. This will confuse my translators. Can HTMLHint accept valid XML intro information?

HTMLHint only support HTML code, xml is not supported.

Please, do you understand that XHTML is a type of HTML? I'm not talking about any old XML. I'm talking about XHTML, which is HTML that is extra-strict. Sure, the XHTML will have namespaces, but as far as HTMLHint is concerned those are just attributes.
See http://www.w3.org/TR/html5/introduction.html#html-vs-xhtml for more information.
So that only leaves us really with the XML declaration. Your tool simply needs to recognize that the first line may be an XML declaration. Why is that such a bad thing? Why must your tool prohibit an XML declaration for an XHTML file? If you would only allow a way for us not to consider the XML declaration an error. That is the main problem here.

Why add <?xml version="1.0" encoding="utf-8"?> at front?

@garretwilson I suggest using polyglot (x)html5. HtmlHint is able to deal with .xhtml files since #34; I have it set up at browserpad for instance (see the htmlhint.conf). It doesn't check all of xhtml's requirements, but it covers most of it, I believe. of course, additional rules for stricter validation would be great :)

@yaniswang , the XML declaration signals to a processor that they should maintain the strictness of XML. Everybody says their tools support strict HTML structure, but everybody lies (as Dr. House would say). I want one more indication so that the documents won't suddenly end up with
 or unescaped < in the middle of
 blocks (e.g. BlueGriffon editor).
I just want HTML5 that is valid XML. For the simple content I'm working with, this would also be valid HTML, so I don't see why this tool dies goes hysterical (hyperbole) when it sees an XML declaration.

I'm sorry, i have no idea how to check xml.
HTMLHint is a hint tool, only found some useful errors.
It is different from W3C checker.

@yaniswang , your tool seems very helpful except for this big stumbling block. It's just a simple XML declaration; see https://stackoverflow.com/a/16601746/421049 for example.
If I could get one of my company's developers to fix this (or do it myself) and submit a pull request, would you consider including it?


OpenVMS X86_64 platform port with rebase

This pull request contains the summary of the previous attempts after rebase.

Thanks, I think this looks good now


Failed to find any matching files for ./checkpoints/yolov3.tf

I get this error. Could you please help me to solve it?
2019-11-24 18:46:00.689586: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-11-24 18:46:00.746495: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fe63b527850 executing computations on platform Host. Devices:
2019-11-24 18:46:00.746532: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): Host, Default Version
Traceback (most recent call last):
File "detect.py", line 61, in
app.run(main)
File "/anaconda3/lib/python3.7/site-packages/absl/app.py", line 299, in run
_run_main(main, args)
File "/anaconda3/lib/python3.7/site-packages/absl/app.py", line 250, in _run_main
sys.exit(main(argv))
File "detect.py", line 33, in main
yolo.load_weights(FLAGS.weights)
File "/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training.py", line 181, in load_weights
return super(Model, self).load_weights(filepath, by_name)
File "/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/network.py", line 1143, in load_weights
pywrap_tensorflow.NewCheckpointReader(filepath)
File "/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/pywrap_tensorflow_internal.py", line 873, in NewCheckpointReader
return CheckpointReader(compat.as_bytes(filepattern))
File "/anaconda3/lib/python3.7/site-packages/tensorflow_core/python/pywrap_tensorflow_internal.py", line 885, in init
this = _pywrap_tensorflow_internal.new_CheckpointReader(filename)
tensorflow.python.framework.errors_impl.NotFoundError: Unsuccessful TensorSliceReader constructor: Failed to find any matching files for ./checkpoints/yolov3.tf

@jkiani64 You have to download the weights and run the convert script.
yolov3
wget https://pjreddie.com/media/files/yolov3.weights -O data/yolov3.weights
python convert.py
yolov3-tiny
wget https://pjreddie.com/media/files/yolov3-tiny.weights -O data/yolov3-tiny.weights
python convert.py --weights ./data/yolov3-tiny.weights --output ./checkpoints/yolov3-tiny.tf --tiny

right, you can also see the convert instruction in readme


Remove webrick dependency

As far as I can tell, this isn't actually used anywhere, so we avoid a CVE by dropping it. Upstream says it's not for use in production anyway.

@hayleycd if you're still around, it looks like you introduced this dependency as part of 2a38766. Is there something non-obvious I'm missing?

preview still seems to work. let's merge it and revert if something goes wrong.


How do I add this to Unity Package Manager via Git URL?

ref: Unity 2019.4.18f1
If I go to "Package Manager" within the Unity Development Environment, there is an option (+ ▼) in corner for "Add Package from GIT URL.."   I've tried every link from this repo that remotely makes sense, but all I get is "Error adding package..."
Note, there is also a choice with the Unity Package Manager to " Add package from tarball..."  but its clearly looking for a *.tgz file and not a tar.gz file...  which is what the release repo here provides.  So that's a fail, too..
Possible for you to address this at the intro README?  Many thanks for sharing your work, open source.

Hey, sorry but you can not use it via the GIT URL. In order to do so, the package has to be in the repository root, which is not true for this one.
But you still have 2 options on how to install it. You can do it by adding our scope registry or by using OpenUPM, both are described here:
https://github.com/StansAssets/com.stansassets.scene-management/blob/master/README.md
Do you have any difficulties with it? Let me know, would be happy to help!


Distance and Bearing creating bad results (ArcMap)

Tested with Build 19 Jan 2017 05:11

Open ArcMap
Add the topographic basemap
Open Distance and Direction tool
Line tab is enabled
For "From:" parameter, select "Distance and Bearing".
For "Starting Point" parameter, enter 45N 120W
[ ] ISSUE?: as you are typing in coordinate, the tool is creating the "temp" line; . I believe at this point in user interaction, that only the green dot is supposed to be drawn on the map to indicate the Starting Point location?
For "Distance/Length", enter 1000.
For "Units", select Kilometers.
For "Angle" enter 90. Keep units as degrees.
Enter return in the Angle parameter.
[ ] ISSUE: Angle and Starting and Ending Points are not cleared. (In Pro addin. all inputs are cleared after the line is drawn).
[ ] ISSUE: The line is now labeled with a length longer then user specified. The angle greater then the user specified. Should be 1000 Kilometers and 90 degrees.

With Line tab still active...

Re-enter 1000 for Distance and 90 for Angle. Enter return in Angle parameter.
[ ] ISSUE: the same line is not drawn. The line now has a longer line and greater angle then previous line.

The error in line length and angle keeps increasing each subsequent time you run the tool, i.e. each time I enter the same parameters (1000 Kilometers and 90 Degrees) the line is created with increasingly incorrect length and angle...

Re-enter 1000 for Distance and 90 for Angle. Enter return in Angle parameter.

ArcGIS Pro addin is working correctly.

@elinz fixed please test next build pull request https://github.com/Esri/distance-direction-addin-dotnet/pull/293

Verified on build 19 Jan 2017 13:18 Build Number 1155. Closing issue.


Scanning container images inside helm chart returns 0 vulnerabilities

terrascan version:  v1.15.2
Operating System: Windows (GitBash)

Description
I am trying to scan container images in my helm chart using terrascan.
What I Did
I installed terrascan using below steps:
$ git clone git@github.com:tenable/terrascan.git
$ cd terrascan
$ make build
$ ./bin/terrascan

I am using option --find-vuln of terrascan to scan container images in my helm chart. Below is the command:
terrascan scan -i helm --find-vuln
The scan results 0 vulnerabilities for all images I used to check. I tried this with dockerhub image and gcr image both but the result is same.

Hello Terrrascan Team,
please look into this issue. We are evaluating terrascan and need this feature if exist.

Hi @vistasunil
Could you please use option -l debug to set the log level to debug and share the logs?
Also, if possible, could you please share sample code where you're running terrascan.
Thanks

Hello @gaurav-gogia  Please find the output of below debug command attached here:
terrascan scan -i helm --find-vuln -l  debug
terrascan_debug_image_scan.txt

@vistasunil
I don't see any errors in container detection, I'll be able to deep dive and recreate the scenario if you could share a sample code file.

Hello @gaurav-gogia  I am trying to scan image that is part of kubernetes yaml or helm chart. Please find the same sample helm chart attached here:
test-chart.zip
.

@vistasunil
terrascan currently only supports finding vulnerabilities in container images. And as far as I understand helm charts, they are just package managers, container images aren't defined in them, so that's the reason you don't see any vulnerabilities.
Does this answer your question?

@gaurav-gogia Container images are defined in Kubernetes YAMLs and helm charts. Below is the snapshot:
      containers:         - name: test-chart           securityContext:             {}           **image: "nginx:1.16.0"**           imagePullPolicy: Always
I believe --find-vuln option is meant to find the vulnerabilties in YAMLs and Helm charts only. Please correct me if my understanding is wrong.

@vistasunil
Since terrascan is a static analyser, it doesn't execute helm charts/pull down images. You'll be able to get better results with terraform and k8s configuration.

@gaurav-gogia  as per your indication, I tried to run same command on k8s yaml too below and no image scanning happened again. Please find the attached file:
`
terrascan scan -i k8s -f tt.yaml --find-vuln -l debug
`
terrascan_k8s_scan_debug.txt

@gaurav-gogia  as per your indication, I tried to run same command on k8s yaml too below and no image scanning happened again. Please find the attached output and k8s yaml file in zip:
terrascan scan -i k8s -f tt.yaml --find-vuln -l debug
k8s.zip
terrascan_k8s_scan_debug.txt

@vistasunil
In this case it looks like there were no vulnerabilities found for the images described in the k8s configuration you've shared. Terrascan uses publicly available registry information from providers such as https://index.docker.io/ to figure out whether a certain container image has been reported to be vulnerable or not.

@gaurav-gogia  This is not true. This image has 239 vulnerabilities as below:
$ cat  nginx.yaml |grep "  severity:"|grep HIGH|wc -l
38
$ cat  nginx.yaml |grep "  severity:"|grep CRITICAL|wc -l
6
$ cat  nginx.yaml |grep "  severity:"|grep MEDIUM|wc -l
165
$ cat  nginx.yaml |grep "  severity:"|grep LOW|wc -l
24

Attaching the list of all CVEs for your reference. Please check why terrascan was unable to find them.
nginx_vulnerabilities.txt

@vistasunil
I think this discrepancy might be caused by the source terrascan uses to identify vulnerabilities.
It uses publicly available image registries like dockerhub to find if vulnerabilities are associated to an image.
Is it possible for you to share the source you're using to identify if a certain image is vulnerable?

@gaurav-gogia  I am using GCR scan to scan images and because of this only the above vulnerabilities were found. Also, I am not able to access https://index.docker.io/  as you shared. Please refer the screenshot for the error.

@vistasunil
Yes, I edited my comment earlier because of the same issue.
I'll have to look into it again. Will take some time to debug.

@gaurav-gogia  Sure. Please share your finding once you have something.

@vistasunil  Terrascan do fetch the vulnerabilities of images identified in your helm yaml files, but currently it only supports gcr,ecr and acr docker registry.
I can see in the chart you shared the value of repository is as below
repository: nginx #gcr.io/k8coe--poc/nginx
so for terrascan the image is part of the docker hub since you haven’t specified the registry, if you can use the complete GCR URL in the image name it will fetch the vulnerability from GCR and display that. If your registry is private do provide the creds as documented here

@Rchanger I did with gcr.io/k8coe--poc/nginx also but it did not work. Thats why I commented it and checked for dockerhub URL. So, its neither supporting gcr repo as well. It scans but returns nothing as I already shared. I did it again by changing to gcr.io as below but nothing returned. Please check the screenshots:
      containers:
        - name: test-chart
          securityContext:
            {}
          image: "gcr.io/k8coe--poc/nginx"
          imagePullPolicy: Always

@Rchanger I suggest you to please try the same yaml to scan with terrascan and see if you are able to find vulnerabilities.

@vistasunil
We don't do a vulnerability scan per se. Being a static analysis tool, we only fetch these vulnerabilities from the registries where container images are located. So if those registries have scanning enabled and if they report any vulnerabilities then terrascan will pick them up and report them.

@gaurav-gogia  Above statement stands true and it worked when I scanned same image using gcr scan and then Terrascan was able to fetch all vulnerabilities from there and report. Below is the snapshot:
Scan Summary -

        File/Folder         :   C:\WFC_Engg\project\test-chart\k8s.yaml
        IaC Type            :   k8s
        Scanned At          :   2022-08-29 06:14:30.0578832 +0000 UTC
        Policies Validated  :   43
        Violated Policies   :   25
        Low                 :   4
        Medium              :   17
        High                :   4
        Vulnerabilities     :   86

So, this concludes that Terrascan cant scan images on its own and depends on container registry scans for fetching the results? Please confirm.
Also, if this is the case then do you have plan to enable capability in Terrascan to scan images on its own like trivy or clair tools?

@vistasunil

So, this concludes that Terrascan cant scan images on its own and depends on container registry scans for fetching the results? Please confirm.

Yes, this is correct

Also, if this is the case then do you have plan to enable capability in Terrascan to scan images on its own like trivy or clair tools?

This feature is not currently in scope, because Terrascan is only meant to be a static analysis tool. Maybe @Rchanger or @cesar-rodriguez can answer this query better.

@Rchanger @cesar-rodriguez  Please share your comment on above query?


Don't queue ntp reload on newly created zones

When you create a new zone, no reason to ask all active servers to reload their ntp settings.
you see, when creating a zone, the old settings were blank, so it always thinks the settings have changed.
@Fryguy / @carbonin not sure if you feel safer always kicking it off.
In test, these queries get called for every zone created (which is a bunch)
In production, probably not so many.
(but this PR is because it was causing problems for me in tests)

LGTM


mset() returns +1 item in response

when executing an mset() with three key/value pairs, the response will be an array of 4 items with OK.
Using redis store, i'd expect to get 3 items

It's possible that this is actually an issue with cache-service-redis. I'll need to do more digging, but cache-service usually just passes through the data the children caches return. Also, redis is known to return OK whereas cache-service is not.

Actually, as currently written, .mset() simply passes the provided callback to the last cache module's .mset() implmentation.  Modules [0] through [n-2] aren't passed a callback at all; those responses/errors are completely lost.  Both .del() and .flush() are handled the same way.   Conversely, .set() passes the provided callback to the first cache module's .set() implementation, and the responses from modules [1] through [n-1] are lost.


Cannot cancel a dialog with a required field in an illegal state

What is affected?
Component
Description
Expect to be able to set up a form as so:
<md-dialog open>
        <form
            slot="content"
            id="email-dialog-form"
            method="dialog">
          <md-filled-text-field
              id="email-dialog-input"
              label="Email address"
              type="email"
              required>
          </md-filled-text-field>
        </form>
        <div slot="actions">
          <md-text-button
              value="cancel"
              form="email-dialog-form">
            Cancel
          </md-text-button>
          <md-text-button
              value="ok"
              form="email-dialog-form">
            OK
          </md-text-button>
        </div>
</md-dialog>

And that the user can cancel it without filling in the required field.
From the documentation and demos it's unclear how this could be arranged or whether it's possible.
Reproduction
https://lit.dev/playground/#project=W3sibmFtZSI6InNjcmlwdC5qcyIsImNvbnRlbnQiOiJpbXBvcnQgJ0BtYXRlcmlhbC93ZWIvZGlhbG9nL2RpYWxvZy5qcyc7XG5pbXBvcnQgJ0BtYXRlcmlhbC93ZWIvYnV0dG9uL3RleHQtYnV0dG9uLmpzJztcbmltcG9ydCAnQG1hdGVyaWFsL3dlYi90ZXh0ZmllbGQvZmlsbGVkLXRleHQtZmllbGQuanMnOyJ9LHsibmFtZSI6ImluZGV4Lmh0bWwiLCJjb250ZW50IjoiPCFET0NUWVBFIGh0bWw-XG48c2NyaXB0IHR5cGU9XCJtb2R1bGVcIiBzcmM9XCIuL3NjcmlwdC5qc1wiPjwvc2NyaXB0PlxuXG48bWQtZGlhbG9nIG9wZW4-XG4gICAgICAgICAgPHNwYW4gc2xvdD1cImhlYWRsaW5lXCI-RW50ZXIgeW91ciBlbWFpbDwvc3Bhbj5cbiAgICAgICAgPGZvcm1cbiAgICAgICAgICAgIHNsb3Q9XCJjb250ZW50XCJcbiAgICAgICAgICAgIGlkPVwiZW1haWwtZGlhbG9nLWZvcm1cIlxuICAgICAgICAgICAgbWV0aG9kPVwiZGlhbG9nXCI-XG4gICAgICAgICAgPG1kLWZpbGxlZC10ZXh0LWZpZWxkXG4gICAgICAgICAgICAgIGlkPVwiZW1haWwtZGlhbG9nLWlucHV0XCJcbiAgICAgICAgICAgICAgbGFiZWw9XCJFbWFpbCBhZGRyZXNzXCJcbiAgICAgICAgICAgICAgdHlwZT1cImVtYWlsXCJcbiAgICAgICAgICAgICAgcmVxdWlyZWQ-XG4gICAgICAgICAgPC9tZC1maWxsZWQtdGV4dC1maWVsZD5cbiAgICAgICAgPC9mb3JtPlxuICAgICAgICA8ZGl2IHNsb3Q9XCJhY3Rpb25zXCI-XG4gICAgICAgICAgPG1kLXRleHQtYnV0dG9uXG4gICAgICAgICAgICAgIHZhbHVlPVwiY2FuY2VsXCJcbiAgICAgICAgICAgICAgZm9ybT1cImVtYWlsLWRpYWxvZy1mb3JtXCI-XG4gICAgICAgICAgICBDYW5jZWxcbiAgICAgICAgICA8L21kLXRleHQtYnV0dG9uPlxuICAgICAgICAgIDxtZC10ZXh0LWJ1dHRvblxuICAgICAgICAgICAgICB2YWx1ZT1cIm9rXCJcbiAgICAgICAgICAgICAgZm9ybT1cImVtYWlsLWRpYWxvZy1mb3JtXCI-XG4gICAgICAgICAgICBPS1xuICAgICAgICAgIDwvbWQtdGV4dC1idXR0b24-XG4gICAgICAgIDwvZGl2PlxuPC9tZC1kaWFsb2c-In0seyJuYW1lIjoicGFja2FnZS5qc29uIiwiY29udGVudCI6IntcbiAgXCJkZXBlbmRlbmNpZXNcIjoge1xuICAgIFwibGl0XCI6IFwiXjIuMC4wXCIsXG4gICAgXCJAbGl0L3JlYWN0aXZlLWVsZW1lbnRcIjogXCJeMS4wLjBcIixcbiAgICBcImxpdC1lbGVtZW50XCI6IFwiXjMuMC4wXCIsXG4gICAgXCJsaXQtaHRtbFwiOiBcIl4yLjAuMFwiXG4gIH1cbn0iLCJoaWRkZW4iOnRydWV9XQ
Workaround
Need to manually invoke validation and prevent form closure on a submit action. Maybe there are other alternatives.
Is this a regression?
No or unsure. This never worked, or I haven't tried before.
Affected versions
1.0.1
Browser/OS/Node environment
Tested on Chrome 119.0.6045.159.

The use  of novalidate should answer your use case.
This should be added in the docs as the requirement is quite common while the approach is not completely trivial.

I think setting the attribute type="button" on the cancel button would be the solution here, so it still validates on the ok button.

@asyncLiz - can formnovalidate  be added as buttons properties:
in the example above, you might want to not  keep form validation (no novalidate attribute on the form element), and skip the validation on the cancel button (by adding a formnovalidate attribute)
@summersz - I don't think type="button" will close the dialog.

Yeah I reported this use case to MDN before: https://github.com/mdn/content/issues/10848 they should add that to the docs and indeed we need formnovalidate.

formnovalidate would be the right approach for this +1

It looks like formnovalidate doesn't work as expected when applied to the Cancel button. Initially I thought that the lack of propagation from md-text-button to button was the cause, but when I manually add the attribute to the inner button tag it also continues to fire the validation (why?). The only way I've found that prevents the validation is to add novalidate to the form, but that means no validation. Otherwise the current workaround looks like a JavaScript solution involving triggering manual validation and cancelling the dialog close.


Arducam:  -- a timeout occurred waiting for the next image buffer

Hello,
I have two Jetson systems, one an NVIDIA Jetson AGX Orin Developer Kit and another, a ConnectTech Hadron/Orin NX, which is headless.  I was able to successfully run the detectnet binary within Docker using the Arducam on the developer kit, but I have not been able to get the camera to work on the Hadron/Orin using the exact same setup.  I've tried recently to use video-viewer in headless mode with raw, reduced resolution, but the program stalls with the same error, no matter which test program I try: "waiting for the next image buffer".  Any suggestions for resolving this would be appreciated.
Thank you!
Craig
root@edge-mcm:/jetson-inference# video-viewer --headless --input-codec=raw --input-width=320 --input-height=240 /dev/video0 rtp://<IP_ADDRESS>:4815
[gstreamer] initialized gstreamer, version <IP_ADDRESS>
[gstreamer] gstCamera -- attempting to create device v4l2:///dev/video0
[gstreamer] gstCamera -- found v4l2 device: Arducam B0459 (USB3 12MP)
[gstreamer] v4l2-proplist, device.path=(string)/dev/video0, udev-probed=(boolean)false, device.api=(string)v4l2, v4l2.device.driver=(string)uvcvideo, v4l2.device.card=(string)"Arducam\ B0459\ \(USB3\ 12MP\)", v4l2.device.bus_info=(string)usb-3610000.xhci-2, v4l2.device.version=(uint)330344, v4l2.device.capabilities=(uint)2225078273, v4l2.device.device_caps=(uint)69206017;
[gstreamer] gstCamera -- found 5 caps for v4l2 device /dev/video0
[gstreamer] [0] video/x-raw, format=(string)YUY2, width=(int)4056, height=(int)3040, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 10/1, 5/1 };
[gstreamer] [1] video/x-raw, format=(string)YUY2, width=(int)3840, height=(int)2160, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [2] video/x-raw, format=(string)YUY2, width=(int)2016, height=(int)1520, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 50/1, 30/1, 15/1, 10/1, 5/1 };
[gstreamer] [3] video/x-raw, format=(string)YUY2, width=(int)1920, height=(int)1080, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 60/1, 30/1, 15/1, 10/1, 5/1 };
[gstreamer] [4] video/x-raw, format=(string)YUY2, width=(int)1280, height=(int)720, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 120/1, 60/1, 30/1, 15/1, 10/1, 5/1 };
[gstreamer] gstCamera -- selected device profile:  codec=raw format=yuyv width=1280 height=720
[gstreamer] gstCamera pipeline string:
[gstreamer] v4l2src device=/dev/video0 do-timestamp=true ! video/x-raw, format=(string)YUY2, width=(int)1280, height=(int)720 ! appsink name=mysink sync=false
[gstreamer] gstCamera successfully created device v4l2:///dev/video0
[video]  created gstCamera from v4l2:///dev/video0
------------------------------------------------
gstCamera video options:
------------------------------------------------
  -- URI: v4l2:///dev/video0
     - protocol:  v4l2
     - location:  /dev/video0
  -- deviceType: v4l2
  -- ioType:     input
  -- codec:      raw
  -- codecType:  cpu
  -- width:      1280
  -- height:     720
  -- frameRate:  120
  -- numBuffers: 4
  -- zeroCopy:   true
  -- flipMethod: none
------------------------------------------------
[gstreamer] gstEncoder -- codec not specified, defaulting to H.264
failed to find/open file /proc/device-tree/model
[gstreamer] gstEncoder -- detected board 'NVIDIA Orin NX'
[gstreamer] gstEncoder -- pipeline launch string:
[gstreamer] appsrc name=mysource is-live=true do-timestamp=true format=3 ! nvvidconv name=vidconv ! video/x-raw(memory:NVMM) ! nvv4l2h264enc name=encoder bitrate=4000000 insert-sps-pps=1 insert-vui=1 idrinterval=30 maxperf-enable=1 ! video/x-h264 ! rtph264pay config-interval=1 ! udpsink host=<IP_ADDRESS> port=4815 auto-multicast=true
No EGL Display
nvbufsurftransform: Could not get EGL display connection
[video]  created gstEncoder from rtp://<IP_ADDRESS>:4815
------------------------------------------------
gstEncoder video options:
------------------------------------------------
  -- URI: rtp://<IP_ADDRESS>:4815
     - protocol:  rtp
     - location:  <IP_ADDRESS>
     - port:      4815
  -- deviceType: ip
  -- ioType:     output
  -- codec:      H264
  -- codecType:  v4l2
  -- frameRate:  30
  -- bitRate:    4000000
  -- numBuffers: 4
  -- zeroCopy:   true
  -- latency     10
------------------------------------------------
[gstreamer] opening gstCamera for streaming, transitioning pipeline to GST_STATE_PLAYING
[gstreamer] gstreamer changed state from NULL to READY ==> mysink
[gstreamer] gstreamer changed state from NULL to READY ==> capsfilter0
[gstreamer] gstreamer changed state from NULL to READY ==> v4l2src0
[gstreamer] gstreamer changed state from NULL to READY ==> pipeline0
[gstreamer] gstreamer changed state from READY to PAUSED ==> capsfilter0
[gstreamer] gstreamer stream status CREATE ==> src
[gstreamer] gstreamer changed state from READY to PAUSED ==> v4l2src0
[gstreamer] gstreamer changed state from READY to PAUSED ==> pipeline0
[gstreamer] gstreamer stream status ENTER ==> src
[gstreamer] gstreamer message new-clock ==> pipeline0
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> capsfilter0
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> v4l2src0
[gstreamer] gstreamer message stream-start ==> pipeline0
[gstreamer] gstCamera -- onPreroll
[gstreamer] gstBufferManager recieve caps:  video/x-raw, format=(string)YUY2, width=(int)1280, height=(int)720, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction)120/1, interlace-mode=(string)progressive
[gstreamer] gstBufferManager -- recieved first frame, codec=raw format=yuyv width=1280 height=720 size=1843200
[cuda]   allocated 4 ring buffers (1843200 bytes each, 7372800 bytes total)
[cuda]   allocated 4 ring buffers (8 bytes each, 32 bytes total)
[gstreamer] gstreamer changed state from READY to PAUSED ==> mysink
[gstreamer] gstreamer message async-done ==> pipeline0
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> mysink
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> pipeline0
[cuda]   allocated 4 ring buffers (2764800 bytes each, 11059200 bytes total)
video-viewer:  captured 0 frames (1280x720)
[cuda]   allocated 2 ring buffers (1382400 bytes each, 2764800 bytes total)
[gstreamer] gstEncoder -- starting pipeline, transitioning to GST_STATE_PLAYING
[gstreamer] gstreamer message qos ==> v4l2src0
nvbuf_utils: Could not get EGL display connection
Opening in BLOCKING MODE
[gstreamer] gstreamer changed state from NULL to READY ==> udpsink0
[gstreamer] gstreamer changed state from NULL to READY ==> rtph264pay0
[gstreamer] gstreamer changed state from NULL to READY ==> capsfilter2
[gstreamer] gstreamer changed state from NULL to READY ==> encoder
[gstreamer] gstreamer changed state from NULL to READY ==> capsfilter1
[gstreamer] gstreamer changed state from NULL to READY ==> vidconv
[gstreamer] gstreamer changed state from NULL to READY ==> mysource
[gstreamer] gstreamer changed state from NULL to READY ==> pipeline1
[gstreamer] gstreamer changed state from READY to PAUSED ==> rtph264pay0
[gstreamer] gstreamer changed state from READY to PAUSED ==> capsfilter2
[gstreamer] gstreamer changed state from READY to PAUSED ==> encoder
[gstreamer] gstreamer changed state from READY to PAUSED ==> capsfilter1
[gstreamer] gstreamer changed state from READY to PAUSED ==> vidconv
[gstreamer] gstreamer stream status CREATE ==> src
[gstreamer] gstreamer changed state from READY to PAUSED ==> mysource
[gstreamer] gstreamer changed state from READY to PAUSED ==> pipeline1
[gstreamer] gstreamer message new-clock ==> pipeline1
[gstreamer] gstreamer stream status ENTER ==> src
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> rtph264pay0
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> capsfilter2
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> encoder
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> capsfilter1
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> vidconv
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> mysource
[gstreamer] gstEncoder -- new caps: video/x-raw, width=1280, height=720, format=(string)I420, framerate=30/1
video-viewer:  captured 1 frames (1280x720)
NvMMLiteOpen : Block : BlockType = 4
===== NVMEDIA: NVENC =====
NvMMLiteBlockCreate : Block : BlockType = 4
[gstreamer] gstreamer message stream-start ==> pipeline1
[gstreamer] gstreamer message latency ==> encoder
H264: Profile = 66, Level = 0
NVMEDIA: Need to set EMC bandwidth : 376000
NVMEDIA_ENC: bBlitMode is set to TRUE
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
^Creceived SIGINT
[gstreamer] gstCamera::Capture() -- a timeout occurred waiting for the next image buffer
video-viewer:  shutting down...
[gstreamer] gstCamera -- stopping pipeline, transitioning to GST_STATE_NULL
[gstreamer] gstCamera -- pipeline stopped
[gstreamer] gstEncoder -- shutting down pipeline, sending EOS
[gstreamer] gstEncoder -- transitioning pipeline to GST_STATE_NULL
[gstreamer] gstEncoder -- pipeline stopped
video-viewer:  shutdown complete

More info:  I'm beginning to suspect that it is a throughput issue.  When I try to sample video on the Hadron/Orin outside of the Docker container, the frame rate is abysmal:
mcadmin@edge-mcm:~$ ffmpeg -f v4l2 -framerate 1 -video_size 640x360 -input_format yuyv422 -i /dev/video0 -c copy out.mkv
ffmpeg version 4.2.7-0ubuntu0.1 Copyright (c) 2000-2022 the FFmpeg developers
built with gcc 9 (Ubuntu 9.4.0-1ubuntu1~20.04.1)
configuration: --prefix=/usr --extra-version=0ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/aarch64-linux-gnu --incdir=/usr/include/aarch64-linux-gnu --arch=arm64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared
libavutil      56. 31.100 / 56. 31.100
libavcodec     58. 54.100 / 58. 54.100
libavformat    58. 29.100 / 58. 29.100
libavdevice    58.  8.100 / 58.  8.100
libavfilter     7. 57.100 /  7. 57.100
libavresample   4.  0.  0 /  4.  0.  0
libswscale      5.  5.100 /  5.  5.100
libswresample   3.  5.100 /  3.  5.100
libpostproc    55.  5.100 / 55.  5.100
[video4linux2,v4l2 @ 0xaaab0e32c800] The V4L2 driver changed the video from 640x360 to 1280x720
[video4linux2,v4l2 @ 0xaaab0e32c800] The driver changed the time per frame from 1/1 to 1/5
Input #0, video4linux2,v4l2, from '/dev/video0':
Duration: N/A, start: 6935.544640, bitrate: 73728 kb/s
Stream #0:0: Video: rawvideo (YUY2 / 0x32595559), yuyv422, 1280x720, 73728 kb/s, 5 fps, 5 tbr, 1000k tbn, 1000k tbc
File 'out.mkv' already exists. Overwrite ? [y/N] y
Output #0, matroska, to 'out.mkv':
Metadata:
encoder         : Lavf58.29.100
Stream #0:0: Video: rawvideo (YUY2 / 0x32595559), yuyv422, 1280x720, q=2-31, 73728 kb/s, 5 fps, 5 tbr, 1k tbn, 1000k tbc
Stream mapping:
Stream #0:0 -> #0:0 (copy)
Press [q] to stop, [?] for help
frame=    9 fps=0.5 q=-1.0 Lsize=   16201kB time=00:00:01.60 bitrate=82897.2kbits/s speed=0.0863x
video:16200kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.005986%

OK I see, yes I was going to suggest trying your V4L2 USB camera with another utility to deduce if it's related to GStreamer (or my code), or moreso the connection / system configuration.   While I haven't used ffmpeg to capture V4L2 (cool trick btw), it would seem that's having issues too.  You could try cheese too if that works.
There are probably a bunch of potential reasons why USB camera behave differently between devkit and a customized carrier/system, such as perhaps is that USB3 connection working on the carrier for example?  What power mode is the Hadron running in?
If it does seem like the root of the issue is not jetson-inference, then folks more knowledgeable than I in those areas can probably help from a more general question relating to camera on the Jetson forums or ConnectTech support (probably try both)

I tried an old USB2.0 camera and had better luck, so this seems to be related to throughput over the hand-built cable to the carrier board jumper.  Indeed, at the full resolution/frame rate of the older camera, it still did not work.  However, it seems that by narrowing down the height and width of the frame, the stream is supported without errors:
detectnet --input-width=640 --input-height=480 --headless /dev/video0 file.mp4
Thank you for your help and especially for jetson-inference -- it is very impressive!!

Aha, okay - glad you figured out the culprit!  My pleasure to support jetson developers, good luck on your project!


Deployment results in UnsupportedApiVersionForRoleDefinitionHasDataActions

Deployment results in the following error:
{"code":"DeploymentFailed","message":"At least one resource deployment operation failed. Please list deployment operations for details. Please see https://aka.ms/arm-debug for usage details.","details":[{"code":"BadRequest","message":"{\r\n \"error\": {\r\n \"code\": \"UnsupportedApiVersionForRoleDefinitionHasDataActions\",\r\n \"message\": \"Assignments to roles with DataActions and NotDataActions are not supported on API version '2017-09-01'. The minimum required API version for this operations is '2018-01-01-preview'.\"\r\n }\r\n}"}]}

The workaround is to use either the owner GUID 8e3af657-a8ff-443c-a75c-2fe8c4bcb635, or deploy the raw template, https://github.com/Azure/Avere/blob/master/src/vfxt/azuredeploy-auto.json, and update the version for the "Microsoft.Authorization/roleAssignments" resources.


Adjust some more ux styles

Summary
More UX enhancements after zoom call with @michaelgamble.
Summary of changes:

Open accordion when clicking on chips
Adjust spacing in accordion cards content to be 24px from left, and from top-botton should be 32px.
Remove top margin from card content h5.
Chevron icon to be vertically aligned centered and has a size of 24px.
Change variable name
Accordion card item icon when is a warning should use the sys-away-indicator color.

Also as part of this PR, I added the logic to show the success texts description to the accordion card header.

Ticket Link
n/a
Related Pull Requests
n/a
Release Note
NONE

@cwarnermm There are some new translations going in with this PR, just pinging you in case you optionally want to review them.

Thanks, @mkraft! I'll review these new strings.

Thanks @cwarnermm that's really great.

@michelengelen as discussed during today's meeting, we need these changes in the main branch so QA and UX can test everything in a single branch. If you have anything else, I can address it in a different/new PR.
@mkraft @michaelgamble @furqanmlk ^^


fix(client): remove unnecessary return values

Checklist:

[x] I have read freeCodeCamp's contribution guidelines.
[x] My pull request has a descriptive title (not a vague title like Update index.md)
[x] My pull request targets the main branch of freeCodeCamp.
[x] I have tested these changes either locally on my machine, or GitPod.

Removed pointless return values inside a forEach loop. Also updated .some() conditions to use .includes().

Thank you, for your contribution to the page! 👍
We are happy to accept these changes, and look forward to future contributions. 🎉


Fix passing multiple ignores to pipenv check

Fix missing space in command line arguments to 'safety' when
multiple CVEs are ignored.

When multiple CVEs are ignored in pipenv check it results in error:
pipenv check -i 33073 -i 33074
Checking PEP 508 requirements...
Passed!
Checking installed package safety...
Notice: Ignoring CVE(s) 33073, 33074
An error occurred:
Usage: safety check [OPTIONS]

Error: Got unexpected extra argument (33074)

It is because the arguments passed to safety look like this: '--ignore 33073--ignore 33074'
This PR just adds the missing space.

Not sure if we want another testcase for pipenv check, but here is one I have used to reproduce this error and test the fix:
@pytest.mark.cli
@pytest.mark.needs_internet(reason='required by check')
@flaky
def test_pipenv_check_with_double_ignore(PipenvInstance):
    with PipenvInstance() as p:
        c = p.pipenv('check --ignore 666 --ignore 777')
        assert c.return_code == 0
        assert 'Ignoring CVE(s) 666, 777' in c.err

Would very much appreciate the additional test case, feel free to make a separate PR with that test.  Much appreciated and thanks for your contributions on this!


Sudden switch from File target to stdout

Hi,
We have recently begun to notice an issue where our production service suddenly switches from using the async wrapper around a file appender, to writing log data to standard out (or possibly standard error... can't tell with the current setup, unfortunately). When this happens, the file appender layouts are still applied to the messages - they end up in a different file, as directed by NLog, without the color sequence escapes, as seen in the configs below. This has thus far only happened in production, so reproducing and getting really good information has been extremely challenging.
This switch from the file to the standard out/error precedes a server crash by a few seconds when under production load. It's running in a docker container, inside of AWS infrastructure, and the docker container is recycled immediately when the application crashes, so our current attempts to capture the NLog internal logs have been unsuccessful.
We will certainly try to get more information on this, as soon as possible, but wanted to see if anyone else has encountered a situation like this and/or has any thoughts on possible causes? Couldn't find anything applicable on StackOverflow.
We are running on .NET Core 2.0.7 via the 2.0-runtime-jessie Dockerfile base on AWS's Docker AMI.
NLog version: 4.5.4, along with NLog.Web.AspNetCore 4.5.3 (these two don't appear to be in sync in general)
Platform: .NET Core 2.0.7
Current NLog config (xml or C#, if relevant)
<?xml version="1.0" encoding="utf-8" ?>
<nlog xmlns="http://www.nlog-project.org/schemas/NLog.xsd"
      xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
      autoReload="true"
      internalLogLevel="Warn"
      internalLogFile="/var/log/app/internal-nlog.txt">

  <extensions>
    <add assembly="Appy.Api" />
    <add assembly="Appy.Common" />
  </extensions>

  <variable name="correlationLayout" value=" Id=${mdlc:item=correlationId:whenEmpty=SYSTEM}," />
  <variable name="messageLayout" value="Message=${replace-newlines:inner=${message}}" />
  <variable name="exceptionLayout" value="${when:when=length('${exception}') > 0:inner= Type=${exception:Format=Type} Exception=${exception:format=ToString,StackTrace}${newline}}" />

  <targets>
    <target xsi:type="File" name="splunk-log" fileName="log\nlog-own.log"
             layout="${longdate}|${event-properties:item=EventId.Id}|${logger}|${uppercase:${level}}|  ${message} ${exception}" />

    <target name="splunkfileAsync" xsi:type="AsyncWrapper" queueLimit="20000" overflowAction="Discard">
      <target xsi:type="File" name="file"
              layout="${truncate:inner=[${date:universalTime=true:format=O}] Level=${level}, Category=${logger},${correlationLayout} ${messageLayout} ${exceptionLayout}}"
              fileName="/var/log/app/appy-${date:format=yyyyMMddHHmm}.log" maxArchiveFiles="60" />
    </target>

    <target xsi:type="ColoredConsole"
          name="console2"
          layout="${longdate} ${pad:padding=5:inner=-${level}-} Category=${logger}, ${message} ${exceptionLayout}"
          useDefaultRowHighlightingRules="True"
          errorStream="True">
      <highlight-word text="-Warn-"  foregroundColor="DarkYellow" />
      <highlight-word text="-Error-"  foregroundColor="DarkMagenta" />
      <highlight-word text="-Fatal-"  foregroundColor="DarkRed" backgroundColor="White"/>
    </target>
    <target xsi:type="Null" name="blackhole" />
  </targets>

  <rules>
    <logger name="Microsoft.*" minlevel="Trace" writeTo="blackhole" final="true" />

    <logger name="Enyim.*" levels="Trace,Debug" writeTo="blackhole" final="true" />

    <logger name="*" minlevel="Trace" writeTo="splunkfileAsync" />
  </rules>
</nlog>

What is the current result? random, unexpected switch from file appender to console appender
What is the expected result? keep using the file appender
Did you checked the Internal log? Working on it
Please post full exception details (message, stacktrace, inner exceptions) - no exceptions that we've found yet
Are there any workarounds? none that we've found
Is there a version in which it did work?  don't know
Can you help us by writing an unit test? Unable to reliably reproduce

Thank you very much for your help. Will append details as soon as I can but please let me know if there's any insight or other stuff that we need.

We will certainly try to get more information on this, as soon as possible,

any news on this?

but wanted to see if anyone else has encountered a situation like this and/or has any thoughts on possible causes

I think i have the same problem sometimes when using git or powershell on the powershell shell, it get struck in error mode and then all text keeps to be red.

Closing this due to inactivity. Please let us know if this still an issue and please provide the requested info -
thanks!


coder: use sri hash in updateScript

Description of changes

Things done

Built on platform(s)

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

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

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

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
24.05 Release Notes (or backporting 23.05 and 23.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

Why haven't you removed the previous hash variable?

@superherointj it's used to convert it to an SRI hash. I felt it was cleaner than nesting the commands.

@superherointj it's used to convert it to an SRI hash. I felt it was cleaner than nesting the commands.

Where is $NEW_HASH used now?

Sorry. I understood.


abort crashes in production app on device Lenovo TAB4 8504X

Our production app is crashing a lot in the Lenovo TAB4 8504X as reported by the play console. The crash is occurring on this device only and there are almost 90 crashes. The app is installed on over 200 of these same tablets. Please google the phone model for the device spec. We don't have this device for testing and also I am unable to reproduce it. I don't even understand the cause of the crash.
Below is the crash info.
backtrace:
  #00  pc<PHONE_NUMBER>01e5a8  /system/lib64/libc.so (abort+120)
  #00  pc<PHONE_NUMBER>0083e4  /system/lib64/liblog.so (__android_log_assert+296)
  #00  pc<PHONE_NUMBER>0706d8  /system/lib64/libhwui.so (android::uirenderer::renderthread::EglManager::createSurface(ANativeWindow*, bool)+336)
  #00  pc<PHONE_NUMBER>06e30c  /system/lib64/libhwui.so (android::uirenderer::renderthread::OpenGLPipeline::setSurface(android::Surface*, android::uirenderer::renderthread::SwapBehavior, android::uirenderer::renderthread::ColorMode)+76)
  #00  pc<PHONE_NUMBER>06ac90  /system/lib64/libhwui.so (android::uirenderer::renderthread::CanvasContext::setSurface(android::Surface*)+144)
  #00  pc<PHONE_NUMBER>073f08  /system/lib64/libhwui.so (android::uirenderer::renderthread::Bridge_initialize(android::uirenderer::renderthread::initializeArgs*)+16)
  #00  pc<PHONE_NUMBER>07627c  /system/lib64/libhwui.so (android::uirenderer::renderthread::MethodInvokeRenderTask::run()+24)
  #00  pc<PHONE_NUMBER>077560  /system/lib64/libhwui.so (android::uirenderer::renderthread::RenderThread::threadLoop()+336)
  #00  pc<PHONE_NUMBER>0115a4  /system/lib64/libutils.so (android::Thread::_threadLoop(void*)+276)
  #00  pc<PHONE_NUMBER>0a9b4c  /system/lib64/libandroid_runtime.so (android::AndroidRuntime::javaThreadShell(void*)+136)
  #00  pc<PHONE_NUMBER>077580  /system/lib64/libc.so (__pthread_start(void*)+36)
  #00  pc<PHONE_NUMBER>01f984  /system/lib64/libc.so (__start_thread+68)

@bnayagrawal
can you provide flutter doctor -v relative to the app build and the app's pubspec.yaml,
would be also useful the logs of flutter run --release on an android 8 device

Below is the contents of pubsec.yaml file
# The following defines the version and build number for your application.
# A version number is three numbers separated by dots, like 1.2.43
# followed by an optional build number separated by a +.
# Both the version and the builder number may be overridden in flutter
# build by specifying --build-name and --build-number, respectively.
# In Android, build-name is used as versionName while build-number used as versionCode.
# Read more about Android versioning at https://developer.android.com/studio/publish/versioning
# In iOS, build-name is used as CFBundleShortVersionString while build-number used as CFBundleVersion.
# Read more about iOS versioning at
# https://developer.apple.com/library/archive/documentation/General/Reference/InfoPlistKeyReference/Articles/CoreFoundationKeys.html
version: 1.0.0+1 # Not used in Android

environment:
  sdk: ">=2.8.0 <3.0.0"

dependencies:
  flutter:
    sdk: flutter
  flutter_localizations:
    sdk: flutter

  # The following adds the Cupertino Icons font to your application.
  # Use with the CupertinoIcons class for iOS style icons.
  cupertino_icons: ^0.1.3
  async: ^2.4.1
  json_annotation: ^3.0.1
  http: ^0.12.1
  geolocator: ^5.3.1
  file_picker: ^1.9.0+1
  flutter_sound: ^2.1.1
  intl: ^0.16.1
  camera: ^0.5.8+2
  path_provider: ^1.6.11
  video_player: ^0.10.11+2
  flick_video_player: ^0.1.1
  flutter_widgets: ^0.1.12
  barcode_scan: ^2.0.2
  validators: ^2.0.0+1
  fluttertoast: ^4.0.1
  app_settings: ^4.0.1+1
  font_awesome_flutter: ^8.8.1
  flutter_colorpicker: ^0.3.4
  painter: ^0.4.0
  flutter_spinkit: ^4.1.2+1
  permission_handler: ^5.0.1+1
  connectivity: ^0.4.8+6
  http_parser: ^3.1.4
  provider: ^4.1.2
  path: ^1.6.4
  package_info: ^0.4.0+18
  device_info: ^0.4.2+4
  badges: ^1.1.4
  like_button: ^1.0.1
  flutter_downloader: ^1.4.4
  event_bus: ^1.1.1
  open_file: ^3.0.1
  flutter_linkify: ^3.1.3
  url_launcher: ^5.5.0
  qr_flutter: ^3.2.0
  image_picker: ^0.6.7+2
  mobile_number: ^1.0.2
  dotted_border: ^1.0.6
  workmanager: ^0.2.3
  flutter_phoenix: ^0.1.0
  carousel_slider: ^2.2.1
  cached_network_image: ^2.3.1
  logging: ^0.11.4
  native_device_orientation: ^0.4.3
  share: ^0.6.5+3
  # Later: For single function plugins,
  # write platform code in SangrahApp
  battery_optimization: ^0.1.0
  qrscan:
    path: plugins/qrcode_scanner
  #State Management
  mobx: ^1.2.1
  flutter_mobx: ^1.1.0
  # database
  hive: ^1.4.4+1
  hive_flutter: ^0.3.1
  # FCM
  firebase_messaging: ^7.0.0
  flutter_local_notifications: ^1.4.4+4
  firebase_crashlytics: ^0.1.4+1
  # Expression evaluator
  dartxe:
    path: ../dartxe

dev_dependencies:
  build_runner: ^1.10.1
  mobx_codegen: ^1.1.0
  hive_generator: ^0.8.1
  json_serializable: ^3.3.0
  build_resolvers: ^1.3.10

dependency_overrides:
  analyzer: 0.39.14

# For information on the generic Dart part of this file, see the
# following page: https://dart.dev/tools/pub/pubspec

# The following section is specific to Flutter.
flutter:

  # The following line ensures that the Material Icons font is
  # included with your application, so that you can use the icons in
  # the material Icons class.
  uses-material-design: true

  # To add assets to your application, add an assets section, like this:
  # assets:
  #  - images/a_dot_burr.jpeg
  #  - images/a_dot_ham.jpeg
  assets:
    - assets/images/sangrah_white.png
    - assets/images/logo.png
    - assets/locales/

  # An image asset can refer to one or more resolution-specific "variants", see
  # https://flutter.dev/assets-and-images/#resolution-aware.

  # For details regarding adding assets from package dependencies, see
  # https://flutter.dev/assets-and-images/#from-packages

  # To add custom fonts to your application, add a fonts section here,
  # in this "flutter" section. Each entry in this list should have a
  # "family" key with the font family name, and a "fonts" key with a
  # list giving the asset and other descriptors for the font. For
  # example:
  # fonts:
  #   - family: Schyler
  #     fonts:
  #       - asset: fonts/Schyler-Regular.ttf
  #       - asset: fonts/Schyler-Italic.ttf
  #         style: italic
  #   - family: Trajan Pro
  #     fonts:
  #       - asset: fonts/TrajanPro.ttf
  #       - asset: fonts/TrajanPro_Bold.ttf
  #         weight: 700
  #
  # For details regarding fonts from package dependencies,
  # see https://flutter.dev/custom-fonts/#from-packages
  fonts:
    - family: NumberIcon
      fonts:
        - asset: assets/fonts/NumberIcon.ttf
    - family: DateTimeIcon
      fonts:
        - asset: assets/fonts/DateTimeIcon.ttf
    - family: FALightIcons
      fonts:
        - asset: assets/fonts/FALightIcons.ttf
    - family: FALightIcons2
      fonts:
        - asset: assets/fonts/FALightIcons2.ttf
    - family: Syncopate
      fonts:
        - asset: assets/fonts/Syncopate/Syncopate-Bold.ttf
          weight: 700
    - family: Nunito
      fonts:
        - asset: assets/fonts/Nunito/NunitoSans-SemiBold.ttf
          weight: 600
        - asset: assets/fonts/Nunito/NunitoSans-Black.ttf
          weight: 900
        - asset: assets/fonts/Nunito/NunitoSans-Regular.ttf
          weight: 400
        - asset: assets/fonts/Nunito/NunitoSans-Bold.ttf
          weight: 700

Below is the output of flutter doctor -v
[√] Flutter (Channel stable, 1.22.3, on Microsoft Windows [Version 10.0.19042.630], locale en-IN)
    • Flutter version 1.22.3 at C:\flutter
    • Framework revision 8874f21e79 (6 weeks ago), 2020-10-29 14:14:35 -0700
    • Engine revision a1440ca392
    • Dart version 2.10.3

[√] Android toolchain - develop for Android devices (Android SDK version 29.0.3)
    • Android SDK at C:\Users\BnayA\AppData\Local\Android\Sdk
    • Platform android-30, build-tools 29.0.3
    • ANDROID_SDK_ROOT = C:\Users\BnayA\AppData\Local\Android\Sdk
    • Java binary at: C:\Program Files\Android\Android Studio\jre\bin\java
    • Java version OpenJDK Runtime Environment (build 1.8.0_212-release-1586-b04)
    • All Android licenses accepted.

[√] Android Studio (version 3.6)
    • Android Studio at C:\Program Files\Android\Android Studio
    • Flutter plugin version 45.1.1
    • Dart plugin version 192.7761
    • Java version OpenJDK Runtime Environment (build 1.8.0_212-release-1586-b04)

[√] VS Code (version 1.51.1)
    • VS Code at C:\Users\BnayA\AppData\Local\Programs\Microsoft VS Code
    • Flutter extension version 3.16.0

[√] Connected device (1 available)
    • ONEPLUS A6010 (mobile) • <IP_ADDRESS>:5555 • android-arm64 • Android 10 (API 29)

• No issues found!

Looks very similar to https://github.com/flutter/flutter/issues/37376 and the issue reported in https://issuetracker.google.com/issues/70259031.
@bnayagrawal Can you provide flutter run --release as requested earlier ?

Heres the output of flutter run --release
C:\Users\BnayA\Work\Office\sangrahapp>flutter run --release
Launching lib\main.dart on ONEPLUS A6010 in release mode...
Running Gradle task 'assembleRelease'...

Running Gradle task 'assembleRelease'... Done                     187.9s (!)
√ Built build\app\outputs\flutter-apk\app-release.apk (11.9MB).
Installing build\app\outputs\flutter-apk\app.apk...                10.4s

Flutter run key commands.
h Repeat this help message.
c Clear the screen
q Quit (terminate the application on the device).
I/flutter (32343): token egjnoLfkQsuuWfgmv-P3qS:APA91bFIU8_Cce0H0iy3pCt3TWDH_4Lyuu8SDpmAXHdkeg_sB5mGhGKwIor2Urg357Vf1DIp3RWUbL9yBZkIn8viY7DfyaD5IUgqf8dkMsx3o-EHgss1nnDvspLnBPv74_mDXkjJRQCg

@bnayagrawal
Sorry, I meant, flutter run --release --verbose.

Without additional information, we are unfortunately not sure how to resolve this issue.
We are therefore reluctantly going to close this bug for now.
Please don't hesitate to comment on the bug if you have any more information for us; we will reopen it right away!
Thanks for your contribution.
Could everyone who still has this problem please file a new issue with the exact description of what happens, logs, and the output of flutter doctor -v.
All system setups can be slightly different, so it's always better to open new issues and reference related issues.

Without additional information, we are unfortunately not sure how to resolve this issue.
We are therefore reluctantly going to close this bug for now.
Please don't hesitate to comment on the bug if you have any more information for us; we will reopen it right away!
Thanks for your contribution.
Could everyone who still has this problem please file a new issue with the exact description of what happens, logs, and the output of flutter doctor -v.
All system setups can be slightly different, so it's always better to open new issues and reference related issues.


Segmentation Fault while running caffe2 example from docs

I'm trying to run the example code that you have on https://caffe2.ai/docs/tutorial-loading-pre-trained-models.html
But it gives Segmentation Fault 11 when I do p.run([img])
# where you installed caffe2. Probably '~/caffe2' or '~/src/caffe2'.
CAFFE2_ROOT = "/usr/local/caffe2"
# assumes being a subdirectory of caffe2
CAFFE_MODELS = "/usr/local/caffe2/python/models"
# if you have a mean file, place it in the same dir as the model

from caffe2.proto import caffe2_pb2
import numpy as np
import skimage.io
import skimage.transform
from matplotlib import pyplot
import os
from caffe2.python import core, workspace
import urllib2
print("Required modules imported.")

IMAGE_LOCATION =  "https://cdn.pixabay.com/photo/2015/02/10/21/28/flower-631765_1280.jpg"

# What model are we using? You should have already converted or downloaded one.
# format below is the model's:
# folder, INIT_NET, predict_net, mean, input image size
# you can switch the comments on MODEL to try out different model conversions
MODEL = 'squeezenet', 'init_net.pb', 'predict_net.pb', 'ilsvrc_2012_mean.npy', 227

# codes - these help decypher the output and source from a list from AlexNet's object codes to provide an result like "tabby cat" or "lemon" depending on what's in the picture you submit to the neural network.
# The list of output codes for the AlexNet models (also squeezenet)
codes =  "https://gist.githubusercontent.com/aaronmarkham/cd3a6b6ac071eca6f7b4a6e40e6038aa/raw/9edb4038a37da6b5a44c3b5bc52e448ff09bfe5b/alexnet_codes"
print "Config set!"

def crop_center(img,cropx,cropy):
    y,x,c = img.shape
    startx = x//2-(cropx//2)
    starty = y//2-(cropy//2)
    return img[starty:starty+cropy,startx:startx+cropx]

def rescale(img, input_height, input_width):
    print("Original image shape:" + str(img.shape) + " and remember it should be in H, W, C!")
    print("Model's input shape is %dx%d") % (input_height, input_width)
    aspect = img.shape[1]/float(img.shape[0])
    print("Orginal aspect ratio: " + str(aspect))
    if(aspect>1):
        # landscape orientation - wide image
        res = int(aspect * input_height)
        imgScaled = skimage.transform.resize(img, (input_width, res))
    if(aspect<1):
        # portrait orientation - tall image
        res = int(input_width/aspect)
        imgScaled = skimage.transform.resize(img, (res, input_height))
    if(aspect == 1):
        imgScaled = skimage.transform.resize(img, (input_width, input_height))
    pyplot.figure()
    pyplot.imshow(imgScaled)
    pyplot.axis('on')
    pyplot.title('Rescaled image')
    print("New image shape:" + str(imgScaled.shape) + " in HWC")
    return imgScaled
print "Functions set."

# set paths and variables from model choice and prep image
CAFFE2_ROOT = os.path.expanduser(CAFFE2_ROOT)
CAFFE_MODELS = os.path.expanduser(CAFFE_MODELS)

# mean can be 128 or custom based on the model
# gives better results to remove the colors found in all of the training images
MEAN_FILE = os.path.join(CAFFE_MODELS, MODEL[0], MODEL[3])
if not os.path.exists(MEAN_FILE):
    mean = 128
else:
    mean = np.load(MEAN_FILE).mean(1).mean(1)
    mean = mean[:, np.newaxis, np.newaxis]
print "mean was set to: ", mean

# some models were trained with different image sizes, this helps you calibrate your image
INPUT_IMAGE_SIZE = MODEL[4]

# make sure all of the files are around...
if not os.path.exists(CAFFE2_ROOT):
    print("Houston, you may have a problem.")
INIT_NET = os.path.join(CAFFE_MODELS, MODEL[0], MODEL[1])
print 'INIT_NET = ', INIT_NET
PREDICT_NET = os.path.join(CAFFE_MODELS, MODEL[0], MODEL[2])
print 'PREDICT_NET = ', PREDICT_NET
if not os.path.exists(INIT_NET):
    print(INIT_NET + " not found!")
else:
    print "Found ", INIT_NET, "...Now looking for", PREDICT_NET
    if not os.path.exists(PREDICT_NET):
        print "Caffe model file, " + PREDICT_NET + " was not found!"
    else:
        print "All needed files found! Loading the model in the next block."

# load and transform image
img = skimage.img_as_float(skimage.io.imread(IMAGE_LOCATION)).astype(np.float32)
img = rescale(img, INPUT_IMAGE_SIZE, INPUT_IMAGE_SIZE)
img = crop_center(img, INPUT_IMAGE_SIZE, INPUT_IMAGE_SIZE)
print "After crop: " , img.shape
pyplot.figure()
pyplot.imshow(img)
pyplot.axis('on')
pyplot.title('Cropped')

# switch to CHW
img = img.swapaxes(1, 2).swapaxes(0, 1)
pyplot.figure()
for i in range(3):
    # For some reason, pyplot subplot follows Matlab's indexing
    # convention (starting with 1). Well, we'll just follow it...
    pyplot.subplot(1, 3, i+1)
    pyplot.imshow(img[i])
    pyplot.axis('off')
    pyplot.title('RGB channel %d' % (i+1))

# switch to BGR
img = img[(2, 1, 0), :, :]

# remove mean for better results
img = img * 255 - mean

# add batch size
img = img[np.newaxis, :, :, :].astype(np.float32)
print "NCHW: ", img.shape

with open(INIT_NET) as f:
    init_net = f.read()
with open(PREDICT_NET) as f:
    predict_net = f.read()

p = workspace.Predictor(init_net, predict_net)

# run the net and return prediction
results = p.run([img])

# # turn it into something we can play with and examine which is in a multi-dimensional array
# results = np.asarray(results)
# print "results shape: ", results.shape

This is the log:
WARNING:root:This caffe2 python run does not have GPU support. Will run in CPU only mode.
WARNING:root:Debug message: No module named caffe2_pybind11_state_gpu
Required modules imported.
Config set!
Functions set.
mean was set to:  128
INIT_NET =  /usr/local/caffe2/python/models/squeezenet/init_net.pb
PREDICT_NET =  /usr/local/caffe2/python/models/squeezenet/predict_net.pb
Found  /usr/local/caffe2/python/models/squeezenet/init_net.pb ...Now looking for /usr/local/caffe2/python/models/squeezenet/predict_net.pb
All needed files found! Loading the model in the next block.
Original image shape:(751, 1280, 3) and remember it should be in H, W, C!
Model's input shape is 227x227
Orginal aspect ratio: 1.70439414115
/usr/local/anaconda3/lib/python2.7/site-packages/skimage/transform/_warps.py:84: UserWarning: The default mode, 'constant', will be changed to 'reflect' in skimage 0.15.
  warn("The default mode, 'constant', will be changed to 'reflect' in "
New image shape:(227, 386, 3) in HWC
After crop:  (227, 227, 3)
NCHW:  (1, 3, 227, 227)
Segmentation fault: 11

What I've done before:
python -m caffe2.python.models.download -i squeezenet

My computer configs:
OS: MacOS High Sierra 10.13
which python:/usr/local/anaconda3/bin/python
python --version: Python 2.7.14 :: Anaconda custom (x86_64)
Thanks in advance!

Could you run the Python script under lldb and get a stack trace (thread backtrace) after the segfault?

@Maratyszcza thanks for your response! Sorry, but i've never used lldb in python before. Can you show me how to do that please? I'd really appreciate that !

In the command line, execute lldb python to start Python under lldb debugger
After lldb prompt shows up (in a few seconds), type run your-python-script.py <arguments for python script>
When Python (with Caffe2 inside) hits a segmentation fault, it will not exit, but open lldb command line instead. There, type thread backtrace. lldb will print details about where the crash happened. Post them here.
Type quit to close the lldb session.

@Maratyszcza
the part where should be Segfault 11:
Process 27782 stopped
* thread #1, queue = 'com.apple.main-thread', stop reason = EXC_BAD_ACCESS (code=1, address=0x0)
    frame #0: 0x000000010b59017e libcaffe2.dylib`caffe2::Tensor<caffe2::CPUContext>::dim32(int) const + 30
libcaffe2.dylib`caffe2::Tensor<caffe2::CPUContext>::dim32:
->  0x10b59017e <+30>: cmpq   $0x7fffffff, (%rcx,%rax,8) ; imm = 0x7FFFFFFF
    0x10b590186 <+38>: jge    0x10b59019a               ; <+58>
    0x10b590188 <+40>: movq   0x8(%rbx), %rcx
    0x10b59018c <+44>: movl   (%rcx,%rax,8), %eax
Target 0: (python) stopped.

after thread backtrace
(lldb) thread backtrace
* thread #1, queue = 'com.apple.main-thread', stop reason = EXC_BAD_ACCESS (code=1, address=0x0)
  * frame #0: 0x000000010b59017e libcaffe2.dylib`caffe2::Tensor<caffe2::CPUContext>::dim32(int) const + 30
    frame #1: 0x000000010b5e0da1 libcaffe2.dylib`caffe2::ConvOp<float, caffe2::CPUContext>::RunOnDeviceWithOrderNCHW() + 113
    frame #2: 0x000000010b5c26a6 libcaffe2.dylib`caffe2::ConvPoolOpBase<caffe2::CPUContext>::RunOnDevice() + 134
    frame #3: 0x000000010b57dd01 libcaffe2.dylib`caffe2::Operator<caffe2::CPUContext>::Run(int) + 129
    frame #4: 0x000000010b54882a libcaffe2.dylib`caffe2::SimpleNet::RunAsync() + 650
    frame #5: 0x000000010b57920f libcaffe2.dylib`caffe2::Workspace::RunNet(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> > const&) + 79
    frame #6: 0x000000010b5667aa libcaffe2.dylib`caffe2::Predictor::run(std::__1::vector<caffe2::Tensor<caffe2::CPUContext>*, std::__1::allocator<caffe2::Tensor<caffe2::CPUContext>*> > const&, std::__1::vector<caffe2::Tensor<caffe2::CPUContext>*, std::__1::allocator<caffe2::Tensor<caffe2::CPUContext>*> >*) + 138
    frame #7: 0x000000010b47fb34 caffe2_pybind11_state.so`void pybind11::cpp_function::initialize<caffe2::python::addObjectMethods(pybind11::module&)::$_31, std::__1::vector<pybind11::object, std::__1::allocator<pybind11::object> >, caffe2::Predictor&, std::__1::vector<pybind11::object, std::__1::allocator<pybind11::object> >, pybind11::name, pybind11::sibling, pybind11::is_method>(caffe2::python::addObjectMethods(pybind11::module&)::$_31&&, std::__1::vector<pybind11::object, std::__1::allocator<pybind11::object> > (*)(caffe2::Predictor&, std::__1::vector<pybind11::object, std::__1::allocator<pybind11::object> >), pybind11::name const&, pybind11::sibling const&, pybind11::is_method const&)::'lambda'(pybind11::detail::function_record*, pybind11::handle, pybind11::handle, pybind11::handle)::__invoke(pybind11::detail::function_record*, pybind11::handle, pybind11::handle, pybind11::handle) + 340
    frame #8: 0x000000010b468065 caffe2_pybind11_state.so`pybind11::cpp_function::dispatcher(_object*, _object*, _object*) + 837
    frame #9: 0x000000010015d6a7 libpython2.7.dylib`PyEval_EvalFrameEx + 22391
    frame #10: 0x0000000100157cd4 libpython2.7.dylib`PyEval_EvalCodeEx + 2164
    frame #11: 0x0000000100157452 libpython2.7.dylib`PyEval_EvalCode + 34
    frame #12: 0x0000000100184e3d libpython2.7.dylib`PyRun_FileExFlags + 157
    frame #13: 0x0000000100184980 libpython2.7.dylib`PyRun_SimpleFileExFlags + 816
    frame #14: 0x000000010019b572 libpython2.7.dylib`Py_Main + 3506
    frame #15: 0x00007fff7f14b145 libdyld.dylib`start + 1
    frame #16: 0x00007fff7f14b145 libdyld.dylib`start + 1
(lldb)

Thanks in advance!

maybe related to https://github.com/caffe2/caffe2/issues/1377

Got same error while trying to reproduce this example:
https://caffe2.ai/docs/tutorial-loading-pre-trained-models.html
Thread 1 "python" received signal SIGSEGV, Segmentation fault.

0x00007fffc113c32b in caffe2::Tensor<caffe2::CPUContext>::dim32(int) const () from /usr/local/lib/libcaffe2.so

(gdb) where

#0  0x00007fffc113c32b in caffe2::Tensor<caffe2::CPUContext>::dim32(int) const () from /usr/local/lib/libcaffe2.so
#1  0x00007fffc12788db in caffe2::ConvOp<float, caffe2::CPUContext>::RunOnDeviceWithOrderNCHW() () from /usr/local/lib/libcaffe2.so
#2  0x00007fffc113c1f2 in caffe2::ConvPoolOpBase<caffe2::CPUContext>::RunOnDevice() () from /usr/local/lib/libcaffe2.so
#3  0x00007fffc111ba9a in caffe2::Operator<caffe2::CPUContext>::Run(int) () from /usr/local/lib/libcaffe2.so
#4  0x00007fffc11e0fe9 in caffe2::SimpleNet::DoRunAsync() () from /usr/local/lib/libcaffe2.so
#5  0x00007fffc11a7c2b in caffe2::NetBase::RunAsync() () from /usr/local/lib/libcaffe2.so
#6  0x00007fffc1166fa2 in caffe2::Workspace::RunNet(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) () from /usr/local/lib/libcaffe2.so
#7  0x00007fffc1183170 in caffe2::Predictor::run(std::vector<caffe2::Tensor<caffe2::CPUContext>*, std::allocator<caffe2::Tensor<caffe2::CPUContext>*> > const&, std::vector<caffe2::Tensor<caffe2::CPUContext>*, std::allocator<caffe2::Tensor<caffe2::CPUContext>*> >*) () from /usr/local/lib/libcaffe2.so
#8  0x00007fffc1ad6b02 in void pybind11::cpp_function::initialize<caffe2::python::addObjectMethods(pybind11::module&)::{lambda(caffe2::Predictor&, std::vector<pybind11::object, std::allocator<pybind11::object> >)#31}, std::vector<pybind11::object, std::allocator<pybind11::object> >, caffe2::Predictor&, std::vector<pybind11::object, std::allocator<pybind11::object> >, pybind11::name, pybind11::is_method, pybind11::sibling>(caffe2::python::addObjectMethods(pybind11::module&)::{lambda(caffe2::Predictor&, std::vector<pybind11::object, std::allocator<pybind11::object> >)#31}&&, std::vector<pybind11::object, std::allocator<pybind11::object> > (*)(caffe2::Predictor&, std::vector<pybind11::object, std::allocator<pybind11::object> >), pybind11::name const&, pybind11::is_method const&, pybind11::sibling const&)::{lambda(pybind11::detail::function_call&)#3}::_FUN(pybind11::detail::function_call) ()
   from /opt/caffe2/build/caffe2/python/caffe2_pybind11_state.so
#9  0x00007fffc1b01c83 in pybind11::cpp_function::dispatcher(_object*, _object*, _object*) () from /opt/caffe2/build/caffe2/python/caffe2_pybind11_state.so
#10 0x00000000004cada2 in PyEval_EvalFrameEx ()
#11 0x00000000004c2765 in PyEval_EvalCodeEx ()
#12 0x00000000004c2509 in PyEval_EvalCode ()
#13 0x00000000004f1def in ?? ()
#14 0x00000000004ec652 in PyRun_FileExFlags ()
#15 0x00000000004eae31 in PyRun_SimpleFileExFlags ()
#16 0x000000000049e14a in Py_Main ()
#17 0x00007ffff7810830 in __libc_start_main (main=0x49dab0 <main>, argc=2, argv=0x7fffffffe5c8, init=<optimized out>, fini=<optimized out>, rtld_fini=<optimized out>,
    stack_end=0x7fffffffe5b8) at ../csu/libc-start.c:291
#18 0x000000000049d9d9 in _start ()

Same issue:
keith@machine:~/Documents/learn_machine_learning/caffe2/experiments$ python squeezer.py
WARNING:root:This caffe2 python run does not have GPU support. Will run in CPU only mode.
WARNING:root:Debug message: No module named caffe2_pybind11_state_gpu
Required modules imported.
Config set!
Functions set.
mean was set to:  128
INIT_NET =  /Users/keith/Documents/learn_machine_learning/caffe2/caffe2/build/caffe2/python/models/squeezenet/init_net.pb
PREDICT_NET =  /Users/keith/Documents/learn_machine_learning/caffe2/caffe2/build/caffe2/python/models/squeezenet/predict_net.pb
Found  /Users/keith/Documents/learn_machine_learning/caffe2/caffe2/build/caffe2/python/models/squeezenet/init_net.pb ...Now looking for /Users/keith/Documents/learn_machine_learning/caffe2/caffe2/build/caffe2/python/models/squeezenet/predict_net.pb
All needed files found! Loading the model in the next block.
Original image shape:(751, 1280, 3) and remember it should be in H, W, C!
Model's input shape is 227x227
Orginal aspect ratio: 1.70439414115
/usr/local/lib/python2.7/site-packages/skimage/transform/_warps.py:84: UserWarning: The default mode, 'constant', will be changed to 'reflect' in skimage 0.15.
  warn("The default mode, 'constant', will be changed to 'reflect' in "
2017-11-30 15:36:17.607 Python[82945:8404154] ApplePersistenceIgnoreState: Existing state will not be touched. New state will be written to /var/folders/4c/06q896nj59n90klmblw2bmc00000gn/T/org.python.python.savedState
New image shape:(227, 386, 3) in HWC
After crop:  (227, 227, 3)
NCHW:  (1, 3, 227, 227)
Segmentation fault: 11

Mac: 10.12.5
Python: 2.7.9
Caffe2 built from source

A workaround is to use one of the other available pre-trained models. For example, bvlc_alexnet or blvc_googlenet work. Just download them and change the name in the MODEL tuple.

@bddppq Could this be related to the system/brew/conda Python runtime mismatch that we have seen for ONNX a few weeks ago?

@pietern No, the stack trace shows that the segfault happens in our c++ code (more specifically ConvOp:: RunOnDeviceWithOrderNCHW), not in the Python or pybind11 level.


chore(deps): update renovate/renovate docker tag to v37.6.2

This PR contains the following updates:

Package
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37.5.3 -> 37.6.2

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renovatebot/renovate (renovate/renovate)
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npm: re-enable lock file maintenance (#25045) (0c5df8e)

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drop status:ready and improve triage docs (#25023) (378e9bb)

v37.6.1
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Bug Fixes

go: Ignore mod type of go-import header (#25039) (e504997)

v37.6.0
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Features

terraform-module: always use 'source' as sourceUrl when available (#25008) (3758782)

Miscellaneous Chores

deps: update dependency @types/moo to v0.5.7 (#25031) (ee02ddc)

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allow null value and undefined for validateURL (#25014) (b73cf03)
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drop priority-5-triage label (#25024) (6ab3f46)
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deps: update dependency @types/ms to v0.7.32 (#25026) (c94136b)

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data-min-options

Can we have a data-min-options? So we can set the minimum options allowed to select just like in data-max-options?

This has already been discussed in #1010 and #1022.

I'm not really sure how something like this would be implemented as a feature. This is a validation thing on your end, and you'll want to check that the select has an option selected before submitting the form.

Hrmm...that seems like poor UX. What if they want to deselect that option and select another option?


ImageNet DET Dataset

Hello,
How can I reproduce ImageNet DET dataset results (19.6 mAP)? Will you publish code & model for this dataset?
Thanks.

Hi, I feel so sorry for that I have not implemented the dataset loader for ImageNet DET for this PyTorch version. In addition, I falsely deleted the implementation for the Caffe version. Maybe you can try to implement the dataset loader for ImageNet DET by yourself, following the implementation details described in our paper.

Hi @ppengtang ,
I also want to train my detector on ImageNet Det.
I would ask do you use rbgirshick's  RCNN code and random seed to sample the train1k images? Or it's okay to sample the train1k images randomly by ourselves?

Hi @ppengtang ,
I also want to train my detector on ImageNet Det.
I would ask do you use rbgirshick's RCNN code and random seed to sample the train1k images? Or it's okay to sample the train1k images randomly by ourselves?

Hi @XuYunqiu , in our experiments, I just randomly sample 1k images for each class.

Hi @ppengtang ,
I also want to train my detector on ImageNet Det.
I would ask do you use rbgirshick's RCNN code and random seed to sample the train1k images? Or it's okay to sample the train1k images randomly by ourselves?

Hi @XuYunqiu , in our experiments, I just randomly sample 1k images for each class.

Got it. Thanks for your quick reply.

Hi @ppengtang, sorry to bother you again.
I try to sample images from training set use the train_pos_.txt in ILSVRC2013_devkit/data/det_lists. But ~131K images could be obtained.
Did you also sampled any negative images from ILSVRC2013_DET_train_extra using train_neg_.txt.

Hi @ppengtang, sorry to bother you again.
I try to sample images from training set use the train_pos__.txt in ILSVRC2013_devkit/data/det_lists. But ~131K images could be obtained. Did you also sampled any negative images from ILSVRC2013_DET_train_extra using train_neg__.txt.

Hi @XuYunqiu , sorry I missed your question. I do not sample any negative images from ILSVRC2013_DET_train_extra. Hope you have already fixed this issue.
Btw, next time you could reopen the issue to remind me ^ ^

Hi @ppengtang, sorry to bother you again.
I try to sample images from training set use the train_pos__.txt in ILSVRC2013_devkit/data/det_lists. But ~131K images could be obtained. Did you also sampled any negative images from ILSVRC2013_DET_train_extra using train_neg__.txt.

Hi! Have you fixed this problem? I also meet it. Looking forward to your apply

Hi @ppengtang, sorry to bother you again.
I try to sample images from training set use the train_pos__.txt in ILSVRC2013_devkit/data/det_lists. But ~131K images could be obtained. Did you also sampled any negative images from ILSVRC2013_DET_train_extra using train_neg__.txt.

Hi! Have you fixed this problem? I also meet it. Looking forward to your apply

Hi, I did not fix the issue. I just trained my model with the sampled ~131K images. And promising results can be achieved.

Hi @ppengtang, sorry to bother you again.
I try to sample images from training set use the train_pos__.txt in ILSVRC2013_devkit/data/det_lists. But ~131K images could be obtained. Did you also sampled any negative images from ILSVRC2013_DET_train_extra using train_neg__.txt.

Hi! Have you fixed this problem? I also meet it. Looking forward to your apply

Hi, I did not fix the issue. I just trained my model with the sampled ~131K images. And promising results can be achieved.

懂了~谢谢~

Hi @ppengtang, sorry to bother you again.
I try to sample images from training set use the train_pos__.txt in ILSVRC2013_devkit/data/det_lists. But ~131K images could be obtained. Did you also sampled any negative images from ILSVRC2013_DET_train_extra using train_neg__.txt.

Hi! Have you fixed this problem? I also meet it. Looking forward to your apply

Hi, I did not fix the issue. I just trained my model with the sampled ~131K images. And promising results can be achieved.

Sorry to bother you again. How did you get the region proposals of the ILSVRC2013 training set ? I just search out the val set
proposals from the MCG boxes pagehttp://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/mcg/ , but not find the train set.

Hi @ppengtang, sorry to bother you again.
I try to sample images from training set use the train_pos__.txt in ILSVRC2013_devkit/data/det_lists. But ~131K images could be obtained. Did you also sampled any negative images from ILSVRC2013_DET_train_extra using train_neg__.txt.

Hi! Have you fixed this problem? I also meet it. Looking forward to your apply

Hi, I did not fix the issue. I just trained my model with the sampled ~131K images. And promising results can be achieved.

Sorry to bother you again. How did you get the region proposals of the ILSVRC2013 training set ? I just search out the val set
proposals from the MCG boxes pagehttp://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/mcg/ , but not find the train set.

You could generate proposals for the sampled training images by yourself, by using a proposal generation method (e.g. MCG, SS, EB).

Hi @ppengtang, sorry to bother you again.
I try to sample images from training set use the train_pos__.txt in ILSVRC2013_devkit/data/det_lists. But ~131K images could be obtained. Did you also sampled any negative images from ILSVRC2013_DET_train_extra using train_neg__.txt.

Hi! Have you fixed this problem? I also meet it. Looking forward to your apply

Hi, I did not fix the issue. I just trained my model with the sampled ~131K images. And promising results can be achieved.

Sorry to bother you again. How did you get the region proposals of the ILSVRC2013 training set ? I just search out the val set
proposals from the MCG boxes pagehttp://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/mcg/ , but not find the train set.

You could generate proposals for the sampled training images by yourself, by using a proposal generation method (e.g. MCG, SS, EB).

Thanks!


Certificate Issue

Hello team!
I want to use this approach of browser as custom browser for a client but their sites run via certificate based auth, we must implement that certifcation dialog like IE or Edges does, but dunno how can archive that and dunno the state of this project if it is viable to make something out of a demo...
Is there a plan to improve this project?
some kind of documentation to improve the "back-end" part by ourselves?
Thanks for your time!

It really depends, I highly doubt this project will kick off. It was made then abandoned pretty well it seems.
I do not really know how to answer your question but I found something that is in JS but is kinda old, but still could work.  Find that here
It requires Node.js to work.
As far as improving this project, you could locate and fix misc bugs (and add them in a PR it would be appreciated 👍  )

From the readme:

This project is a tutorial demonstrating the capabilities of the web platform on Windows 10.

Nothing more, nothing less.


Adds Jersey 2.x server tracing support

This uses an application event listener to do a better job tracing
Jersey servers than what can be done with JAX-RS. For example, the event
listener can handle errors natively, and act more precisely with regards
to jersey-specifics like ManagedAsync
Fixes #611

cc @jplock (as this was for dropwizard)
cc also @pavelbucek who wrote something similar for opentracing in jersey's experimental section. Brave has a standard http layer which allows us to configure all http server tracing libraries with the same data policy. You'll notice the data collection here is a bit stingy, but that's intentional as uniform spans are the goal. There's more on the data policy here https://github.com/openzipkin/brave/tree/master/instrumentation/http

Ps test fail is a java 9 module thing. Will need to copy something similar
to what is in dropwizard-zipkin to the failsafe args

ok crossing fingers build is working

I ran benchmarks individually to compare. It is not apples and apples as the jaxrs benchmarks use a resteasy-undertow bridge which is more efficient. There's no jersey-undertow bridge to do a fair comparison, so I had to route over the servlet layer which adds baseline overhead.  If not, we should probably expose the client interceptor public as that way you can use it with jersey without using the jaxrs container instrumentation

suppose that was more a question about jersey cc also @pavelbucek


Update to allow doing a 'Move' of a NFS PV from source to destination

Assume we will need to open up some networking rules in AWS to allow access of the NFS shares from 3.x env in 4.x

Initial investigation :
The NFS is installed on support host of 3.x environments. This host does not have a Route 53 public record created. There is an internal record which only works within the VPC of 3.x cluster (support1.<guid>.internal)
There are no security groups on 3.x side which might block the connection (checked security groups on support instance)
Investigation continues...


Functionality management at startup and runtime

Enable and disable modules conditionally at runtime and startup, e.g. disabling AprilFools after :disable AprilFools (just an idea, can be flexible).
Idea owed from Gregory Greggs.

I know we want run-time management, but using a pre-processor like hspec-discover would allow us to import conditionally at compile-time also.
Might be useful if we want to provide a release build that doesn't have the git features or something.


OAuth Doc Persists Despite Merged PR

http://docs.docker.com/v1.1/reference/api/docker_io_oauth_api/
This is no longer a valid doc and it needs to be removed, per this PR: https://github.com/docker/docker/pull/7193

@SvenDowideit status on this

@jfrazelle looks like this is fixed, if I visit that page, I get a redirect page;
This documentation has been removed. Redirecting you to the relevant
pull request on GitHub.
https://github.com/docker/docker/pull/7193

Oh, shucks. Looks like I got confused; this link redirects:
http://docs.docker.com/reference/api/docker_io_oauth_api/
but this one doesn't:
http://docs.docker.com/v1.1/reference/api/docker_io_oauth_api/

@svendowedit can you take care of this is it a matter of deleting the pages?
On Saturday, February 28, 2015, Sebastiaan van Stijn <
<EMAIL_ADDRESS>wrote:

Oh, shucks. Looks like I got confused; this link redirects:
http://docs.docker.com/reference/api/docker_io_oauth_api/
but this one doesn't:
http://docs.docker.com/v1.1/reference/api/docker_io_oauth_api/
—
Reply to this email directly or view it on GitHub
https://github.com/docker/docker/issues/7630#issuecomment-76557560.

Done.
notes for later:
export BUCKET BUCKET=beta-docs.docker.io
export AWS_CONFIG_FILE=$(pwd)/awsconfig
aws s3 --profile $BUCKET ls s3://$BUCKET
aws s3 --profile $BUCKET rm s3://$BUCKET/v1.0/reference/api/docker_io_oauth_api/index.html
aws s3 --profile $BUCKET rm s3://$BUCKET/v1.1/reference/api/docker_io_oauth_api/index.html

Ah great! Do you think it would it be possible to create something similar to the https://github.com/docker/docker/blob/master/docs/s3_website.json file to mark files as "to be invalidated/removed" upon merge? (Possibly too much work for something that only happens occasionally)

yeah - next time it happens maybe :)

Yeah, it isn't needed often, the instructions just looked complicated :smile:


controller: add unit test to prove debug and metrics are served

Seems like what you really want to do is create an e2e test that checks every operator pod to see if it serves debug endpoints.


Error getting result from polling source java.sql.SQLSyntaxErrorException: Table 'cattle.setting' doesn't exist

Sometimes I got this ERROR, too.
What's is problem?
2015-04-01 08:52:37,944 INFO    [main] [ConsoleStatus] [1/104] [0ms] [0ms] Loading bootstrap
2015-04-01 08:52:38,263 INFO    [main] [ConsoleStatus] [2/104] [319ms] [298ms] Loading config-defaults
2015-04-01 08:53:06,829 ERROR [:] [] [] [] [igurationSource] [c.n.config.AbstractPollingScheduler ] Error getting result from polling source java.sql.SQLSyntaxErrorException: Table 'cattle.setting' doesn't exist
at org.mariadb.jdbc.internal.SQLExceptionMapper.get(SQLExceptionMapper.java:138) ~[mariadb-java-client-1.1.7.jar:na]
at org.mariadb.jdbc.internal.SQLExceptionMapper.throwException(SQLExceptionMapper.java:106) ~[mariadb-java-client-1.1.7.jar:na]
at org.mariadb.jdbc.MySQLStatement.executeQueryEpilog(MySQLStatement.java:264) ~[mariadb-java-client-1.1.7.jar:na]
at org.mariadb.jdbc.MySQLStatement.execute(MySQLStatement.java:288) ~[mariadb-java-client-1.1.7.jar:na]
at org.mariadb.jdbc.MySQLStatement.executeQuery(MySQLStatement.java:302) ~[mariadb-java-client-1.1.7.jar:na]
at org.mariadb.jdbc.MySQLPreparedStatement.executeQuery(MySQLPreparedStatement.java:112) ~[mariadb-java-client-1.1.7.jar:na]
at org.apache.commons.dbcp.DelegatingPreparedStatement.executeQuery(DelegatingPreparedStatement.java:96) ~[commons-dbcp-1.4.jar:1.4]
at org.apache.commons.dbcp.DelegatingPreparedStatement.executeQuery(DelegatingPreparedStatement.java:96) ~[commons-dbcp-1.4.jar:1.4]
at com.netflix.config.sources.JDBCConfigurationSource.load(JDBCConfigurationSource.java:107) ~[archaius-core-0.5.14.jar:na]
at com.netflix.config.sources.JDBCConfigurationSource.poll(JDBCConfigurationSource.java:88) ~[archaius-core-0.5.14.jar:na]
at io.cattle.platform.archaius.sources.LazyJDBCSource.poll(LazyJDBCSource.java:30) ~[cattle-framework-archaius-0.5.0-SNAPSHOT.jar:na]
at com.netflix.config.AbstractPollingScheduler$1.run(AbstractPollingScheduler.java:163) ~[archaius-core-0.5.14.jar:na]
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471) [na:1.7.0_75]
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:304) [na:1.7.0_75]
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178) [na:1.7.0_75]
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293) [na:1.7.0_75]
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) [na:1.7.0_75]
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) [na:1.7.0_75]
at java.lang.Thread.run(Thread.java:745) [na:1.7.0_75]
Caused by: org.mariadb.jdbc.internal.common.QueryException: Table 'cattle.setting' doesn't exist
at org.mariadb.jdbc.internal.mysql.MySQLProtocol.getResult(MySQLProtocol.java:942) ~[mariadb-java-client-1.1.7.jar:na]
at org.mariadb.jdbc.internal.mysql.MySQLProtocol.executeQuery(MySQLProtocol.java:991) ~[mariadb-java-client-1.1.7.jar:na]
at org.mariadb.jdbc.MySQLStatement.execute(MySQLStatement.java:281) ~[mariadb-java-client-1.1.7.jar:na]
... 15 common frames omitted

Same issue here:
2015-04-14 22:16:31,778 ERROR [:] [] [] [] [igurationSource] [c.n.config.AbstractPollingScheduler ] Error getting re
sult from polling source java.sql.SQLSyntaxErrorException: Table 'cattle.setting' doesn't exist
        at org.mariadb.jdbc.internal.SQLExceptionMapper.get(SQLExceptionMapper.java:138) ~[mariadb-java-client-1.1.7
.jar:na]
        at org.mariadb.jdbc.internal.SQLExceptionMapper.throwException(SQLExceptionMapper.java:106) ~[mariadb-java-c
lient-1.1.7.jar:na]
        at org.mariadb.jdbc.MySQLStatement.executeQueryEpilog(MySQLStatement.java:264) ~[mariadb-java-client-1.1.7.j
ar:na]
        at org.mariadb.jdbc.MySQLStatement.execute(MySQLStatement.java:288) ~[mariadb-java-client-1.1.7.jar:na]
        at org.mariadb.jdbc.MySQLStatement.executeQuery(MySQLStatement.java:302) ~[mariadb-java-client-1.1.7.jar:na]
        at org.mariadb.jdbc.MySQLPreparedStatement.executeQuery(MySQLPreparedStatement.java:112) ~[mariadb-java-clie
nt-1.1.7.jar:na]
        at org.apache.commons.dbcp.DelegatingPreparedStatement.executeQuery(DelegatingPreparedStatement.java:96) ~[c
ommons-dbcp-1.4.jar:1.4]
        at org.apache.commons.dbcp.DelegatingPreparedStatement.executeQuery(DelegatingPreparedStatement.java:96) ~[c
ommons-dbcp-1.4.jar:1.4]
        at com.netflix.config.sources.JDBCConfigurationSource.load(JDBCConfigurationSource.java:107) ~[archaius-core
-0.5.14.jar:na]
        at com.netflix.config.sources.JDBCConfigurationSource.poll(JDBCConfigurationSource.java:88) ~[archaius-core

@gghonor @corn13read Do you consistently get that error?  What OS and docker version are you running?

@deniseschannon also got this in #581

I also get this error using:

Rancer.io v0.16.3 on Azure Ubuntu VM
Created a empty cattle mysql database running in another container.

My steps are:

I started the rancher.io without starting up MySQL container. It polled continuously for the mysql but can't obtain a connection
I started up the MySQL container.
Rancho can connect but start to throw the cattle.setting doesn't exist error.
Rancho starts up, and I can verify the database was seeded correctly.
I restart Rancho container, but don't get the error anymore. Also all my data have persisted correctly in mysql

Between steps 1-4 do you ever restart rancher/server.  Is the only restart in step 5?

@ibuildthecloud there were no restarts between 1-4. The whole exercise was trying to test if the DB persistence was working. After step 4 I added github authentication and registered all my hosts, then restarted.

Same issue for me on Ubuntu 14.04 64 bits LTS (HVM) on Gandi Hosting
I can give you an access to the VM if you want to look ?
# docker -v
Docker version 1.6.0, build 4749651

# uname -a
Linux server01 3.12.36-guest-27-c9b6624-x86_64 #2 SMP Fri Jan 16 15:04:50 UTC 2015 x86_64 x86_64 x86_64 GNU/Linux

Same here.
docker version
############
Client version: 1.6.0
Client API version: 1.18
Go version (client): go1.4.2
Git commit (client): 4749651
OS/Arch (client): linux/amd64
Server version: 1.6.0
Server API version: 1.18
Go version (server): go1.4.2
Git commit (server): 4749651
OS/Arch (server): linux/amd64
docker info
#########
Containers: 1
Images: 26
Storage Driver: aufs
Root Dir: /var/lib/docker/aufs
Backing Filesystem: extfs
Dirs: 28
Dirperm1 Supported: false
Execution Driver: native-0.2
Kernel Version: 3.13.0-24-generic
Operating System: Ubuntu 14.04.1 LTS
CPUs: 2
Total Memory: 7.798 GiB
Name: myd-vm00483
ID: DFWH:S4WA:IKRW:P7SM:ZEB4:HQ2C:ONVF:AOID:OG5R:WANE:TDJT:OSC5
Http Proxy: http://hahsed-url.hp.com:8080
Https Proxy: http://hahsed-url.hp.com:8080
WARNING: No swap limit support
uname -a:
########
Linux myd-vm00483 3.13.0-24-generic #47-Ubuntu SMP Fri May 2 23:30:00 UTC 2014 x86_64 x86_64 x86_64 GNU/Linux

obsolete.

obsolete?
v1.1.0-dev4
Receiving this error on pulling the latest tag and trying to start rancher container with external DB:
sudo docker run -d --restart=always -p 80:80 \
    -e CATTLE_DB_CATTLE_MYSQL_HOST=XXXX \
    -e CATTLE_DB_CATTLE_MYSQL_PORT=3306 \
    -e CATTLE_DB_CATTLE_MYSQL_NAME=rancher \
    -e CATTLE_DB_CATTLE_USERNAME=root \
    -e CATTLE_DB_CATTLE_PASSWORD=XXXX \
    rancher/server

@andrewmclagan Is that the exact command you used? You would need -p 80:8080 cause we have exposed port 8080 in our container.

Yep using 80:8080
I'm using external MariaDB. Will that be the issue?

MariaDB is MySQL based so it should work.

Still getting this running the rancher test fig yml file, mentioned here: https://github.com/rancher/rancher/blob/master/tests/server/fig-test-env.yml
I only added a data container for data persistence to the mysqlmanual service, and it keeps throwing the error mentioned in the original issue. Is there a new issue to follow, or is this one closed too early?

@MetalArend Can you open a new issue with details of what you did adn the logs that you are getting from it?

Same thing here. It failed for me bootstrapping 1.6.2 but I even went back to 1.5.2 and had similar results
2017-06-23 02:35:06,610 ERROR [:] [] [] [] [igurationSource] [c.n.config.AbstractPollingScheduler ] Error getting result from polling source java.sql.SQLSyntaxErrorException: (conn:65525) Table 'cattle.setting' doesn't exist
Query is: SELECT distinct name, value FROM setting

Here we go, full logs from start to fail: https://gist.github.com/blaggacao/cda58c151168ad8b41c95c4415483eee
I'm working with Google Cloud SQL
Note line:
2017-07-15 22:02:17,704 ERROR [:] [] [] [] [igurationSource] [c.n.config.AbstractPollingScheduler ] Error getting result from polling source java.sql.SQL SyntaxErrorException: (conn:2107) Table 'cattle.setting' doesn't exist

I'm searching in the dark, but "db lock" sounds awful.
mysql> SELECT * FROM DATABASECHANGELOGLOCK                         ;
+----+--------+---------------------+---------------------------+
| ID | LOCKED | LOCKGRANTED         | LOCKEDBY                  |
+----+--------+---------------------+---------------------------+
|  1 |       | 2017-07-15 22:18:43 | 0a11622d11db (<IP_ADDRESS>) |
+----+--------+---------------------+---------------------------+
1 row in set (0.00 sec)

Sounds similar as https://github.com/rancher/rancher/issues/8962, can you continue there and does it complete eventually?

@superseb Thanks, indeed I'll shift there for follow up.