Move crashkernel= parameter from kernel rpm to kexec-tools rpm

Fixes: #5460

Merge Checklist

All boxes should be checked before merging the PR (just tick any boxes which don't apply to this PR)

[ ] The toolchain has been rebuilt successfully (or no changes were made to it)
[x] The toolchain/worker package manifests are up-to-date
[ ] Any updated packages successfully build (or no packages were changed)
[x] Packages depending on static components modified in this PR (Golang, *-static subpackages, etc.) have had their Release tag incremented.
[ ] Package tests (%check section) have been verified with RUN_CHECK=y for existing SPEC files, or added to new SPEC files
[x] All package sources are available
[x] cgmanifest files are up-to-date and sorted (./cgmanifest.json, ./toolkit/scripts/toolchain/cgmanifest.json, .github/workflows/cgmanifest.json)
[x] LICENSE-MAP files are up-to-date (./SPECS/LICENSES-AND-NOTICES/data/licenses.json, ./SPECS/LICENSES-AND-NOTICES/LICENSES-MAP.md, ./SPECS/LICENSES-AND-NOTICES/LICENSE-EXCEPTIONS.PHOTON)
[x] All source files have up-to-date hashes in the *.signatures.json files
[ ] sudo make go-tidy-all and sudo make go-test-coverage pass
[ ] Documentation has been updated to match any changes to the build system
[ ] Ready to merge

Summary

Move crashkernel= parameter from kernel rpm to kexec-tools rpm to solve #5460
Change Log

Move crashkernel= parameter from kernel rpm to kexec-tools rpm
Does this affect the toolchain?

YES
Associated issues

#5460

Test Methodology

Pipeline build id: xxxx

Unfortunately, this isn't a very good approach due to our current image build process.
In Mariner, the /boot/grub2/grub.cfg file isn't actually owned by any package; it's generated by the image build tooling. This unfortunately means we have no (good) way to deliver a fix to this file for existing end users.
This prevents this PR from being mergable as it is now because, if it was, then end users who upgraded to the new kernel package would have the crashkernel= parameter removed from their /boot/mariner.cfg file, and (if they installed or upgraded to the new kexec-tools package) the crashkernel= parameter would be added to the new /boot/kdump.cfg file. However, since we have no way to update the grub.cfg file to include the new configuration from the kdump.cfg file,  their system would no longer include the crashkernel= parameter and they would not be able to capture any kernel crashdumps.
I don't think we can proceed with this PR until we change from our current design of generating the grub.cfg from our image build tooling over to properly using the standard grub-mkconfig tooling to generate the grub configuration based on the standard grub config in /etc. And even then, we need to carefully consider if existing users would be impacted by the change.

Unfortunately, this isn't a very good approach due to our current image build process.
In Mariner, the /boot/grub2/grub.cfg file isn't actually owned by any package; it's generated by the image build tooling. This unfortunately means we have no (good) way to deliver a fix to this file for existing end users.
This prevents this PR from being mergable as it is now because, if it was, then end users who upgraded to the new kernel package would have the crashkernel= parameter removed from their /boot/mariner.cfg file, and (if they installed or upgraded to the new kexec-tools package) the crashkernel= parameter would be added to the new /boot/kdump.cfg file. However, since we have no way to update the grub.cfg file to include the new configuration from the kdump.cfg file, their system would no longer include the crashkernel= parameter and they would not be able to capture any kernel crashdumps.
I don't think we can proceed with this PR until we change from our current design of generating the grub.cfg from our image build tooling over to properly using the standard grub-mkconfig tooling to generate the grub configuration based on the standard grub config in /etc. And even then, we need to carefully consider if existing users would be impacted by the change.

Can we add some logic to kernel.cfg to check for the presence of this file as a stopgap until m3, and use today's default otherwise?
# Inside kernel.cfg
if [ -f /boot/kdump.cfg ]
    load_env -f /boot/kdump.cfg
else
    kdump_cfg="crashkernel=256M"
fi

mariner_cmdline=init=/lib/systemd/systemd ro loglevel=3 no-vmw-sta $kdump_cfg
...

Unfortunately, this isn't a very good approach due to our current image build process.
In Mariner, the /boot/grub2/grub.cfg file isn't actually owned by any package; it's generated by the image build tooling. This unfortunately means we have no (good) way to deliver a fix to this file for existing end users.
This prevents this PR from being mergable as it is now because, if it was, then end users who upgraded to the new kernel package would have the crashkernel= parameter removed from their /boot/mariner.cfg file, and (if they installed or upgraded to the new kexec-tools package) the crashkernel= parameter would be added to the new /boot/kdump.cfg file. However, since we have no way to update the grub.cfg file to include the new configuration from the kdump.cfg file, their system would no longer include the crashkernel= parameter and they would not be able to capture any kernel crashdumps.
I don't think we can proceed with this PR until we change from our current design of generating the grub.cfg from our image build tooling over to properly using the standard grub-mkconfig tooling to generate the grub configuration based on the standard grub config in /etc. And even then, we need to carefully consider if existing users would be impacted by the change.

Can we add some logic to kernel.cfg to check for the presence of this file as a stopgap until m3, and use today's default otherwise?
# Inside kernel.cfg
if [ -f /boot/kdump.cfg ]
    load_env -f /boot/kdump.cfg
else
    kdump_cfg="crashkernel=256M"
fi

mariner_cmdline=init=/lib/systemd/systemd ro loglevel=3 no-vmw-sta $kdump_cfg
...

IMHO we shouldn't further hack things. We should do things right using grub-mkconfig and this PR should wait until that's done.

Closing this in favor of the work @Camelron has been doing to enable grub2-mkconfig and move the crashkernel= parameter to the kexec-tools package.


Improve warning message text for warning 3836

The current message for warning 3836 is confusing, in that it doesn't explain why the binding redirect is "incorrect". This change makes the warning message explicitly say that there is a conflict between the auto generated redirect and the explicit redirect in the app config file.

LGTM

LGTM.


📢please tell us If your project is using alova

We believe that using alova in projects is also a contributor of alova, which is telling people that alova is a trustworthy open source project.🥳🥳🥳
if your project uses alova, please commit a PR that adding it to showcase.json, your project will have the opportunity to be showcased on alova's official website.

我在我公司的项目中使用了alova，非常棒！

我在我公司的项目中使用了alova，非常棒！

哥们比 axios 好用吗


[WIP] DO_NOT_MERGE-Odsc 47451 streaming dataframe support

This is a nice change 💯 . Checklist we need to undergo to release streaming dataframe support

[ ] Integration tests with timeout functionality
[ ] Integration tests on how schema evolution can happen in streaming dataframe
[ ] Unit tests for streaming dataframe materialise operation
[ ] Addition of sample notebooks for showcasing streaming dataframe support


Ability to update app name

This also:

Introduces app context because that object is A) going to be used in many places and B) we now have some functions to encapsulate that update the object.
Moves the app header react component out of "editor" because it's not a header just for the editor.

Would prefer one of those "click and it becomes and input which saves on blur", but this is def good first pass


Error: one of the variables needed for gradient computation has been modified by an inplace operation

I tried this simple example on the provided llama3.1 colab.

and the error is this:

I also tried to set FastLanguageModel.for_training(model). However, if I add left padding, the loss also cannot be backward as indicated by the following issue.
Originally posted by @YZHang2333 in https://github.com/unslothai/unsloth/issues/533#issuecomment-2275972103

Ok that's a weird issue - ye Unsloth does a lot of inplace gradients, so normally it's fine, but I'm unsure why in this case it's not working

Yeah, this is weird, I am currently doing FastLanguageModel.for_training(model) and use right paddings. This works fine.

@danielhanchen Running into the same issue here with Llama 3.2 and Pytorch Lightning + Unsloth.

@calclavia same here


MTP-1451 Changed Credit view navigation to tab based

Don't merge this just yet, Justin's designs didn't have the breadcrumbs, and he wants to think a bit about how the design given that the live version will include breadcrumbs


Branch autodetection and environment creation fails

Describe the bug
If you set up branch auto detection and ask the console to create a new environment for each branch, then some branch names cause the build to fail when creating the new environment. For example, branch names like "feature/JIRA-123-new-thing" will result in invalid environment names. Branch names like this are useful for linking issues in systems like JIRA to git commits.
To Reproduce
Steps to reproduce the behavior:

Go to the amplify console, enable branch autodetection.
Select "create new backend environment for each connected branch"
Push a new branch with a name that contains capitals.
See error in build phase for backend: "Environment name should be between 2 and 10 characters (only lowercase alphabets)."

Expected behavior
New environment for branch should be created. Perhaps instead of using the branch name for the environment, a unique id could be created (the short commit id at the time the branch is first pushed might work). Just lowercasing the branch name will not be enough either - note that branch names following this pattern will not be unique: "feature/SED-123" will be converted to "featureSED" by the current algorithm.

Also attemping to integrate gitlab merge request with autogenerated branch by issue name corrispond to branch named like "1-issue-title-too-long".

Anything new here? This is also blocking my team from moving forward with Amplify.

We hit this issue, too. Seems like Amplify is doing some sanitization (limiting to 10 characters, etc.), but isn't doing enough because branch names with non-alphabetical characters are converted to dashes, which aren't allowed in environment names.

@nomiddlename @colinking @alexkates a fix has been deployed.


Testing ContainerHost implementation - coroutine scope issues

The problem
Consider following example of simple ConteinerHost implementation. Notice, that CounterViewModel receives coroutineScope as a parameter, which is then used to create container()

class CounterViewModel(
   coroutineScope: CoroutineScope
) : ContainerHost<CounterState, CounterSideEffect> {
   override val container: Container<CounterState, CounterSideEffect> = coroutineScope.container(
       CounterState(ctr = 0)
   )

   fun incrementCounter() = intent {
       reduce { state.copy(ctr = state.ctr + 1) }
   }
}

data class CounterState(
   val ctr: Int
)

sealed class CounterSideEffect {}

The test for this ViewModel may look like this:
class CounterViewModelTest {

    @Test
    fun `increment test`() = runTest {
        CounterViewModel(coroutineScope = this).test(testScope = this) {
            expectInitialState()

            invokeIntent { incrementCounter() }

            expectState(CounterState(ctr = 1))
        }
    }

But it turns out that this test throws an Exception:
kotlinx.coroutines.test.UncompletedCoroutinesError: After waiting for 10s, the test coroutine is not completing, there were active child jobs:

The (probable) cause -> scopes

After playing around a little bit I noticed that changing the coroutineScope parameter of CounterViewModel fixes the issue and the test runs just fine.
CounterViewModel(coroutineScope = this).test(testScope = this) //Exception
changed to
CounterViewModel(coroutineScope = backgroundScope).test(testScope = this) //OK

The questions
Why is that?
What it considered the best practice for testing such ContainerHost implementations and which coroutine scopes should be used?

Thanks!

Oooh, that sounds much better than what I used: MyContainerHost(this + Job()), based on the documentation of backgroundScope, it's meant for this.
Whatever the answer will be from the maintainers, I would love to see it listed on https://orbit-mvi.org/Test/new in a section called "Testing pure ContainerHost" (without using a ViewModel).

TL;DR You need to use this.backgroundScope for this :)


Reset request to enter bootloader

After entering the bootloader the request is cleared. This will prevent the bootloader loop that can occur after the update.

Great find!!


Update next 5.0.1-canary.2 to avoid build errors

Please check this link as it has already been discussed,
updating the file so that it is easier for others to start without build errors :)

@loganfsmyth Please review it

There is no need for Logan to look at this 😅, removing the message in the hope it also removed the notification.


Request: Performance timeline polyfill

It would be good if we had a polyfill for performance.getEntriesByName etc. A potential solution could be https://github.com/micro-perf/performance-polyfill .

Im interested in this as it impacts Safari users less than 10.3 i believe...


owner-alias not implemented when filtering AMI using describe_images

As recommended by this error message:

FilterNotImplementedError: The filter 'owner-alias' for DescribeImages has not been implemented in Moto yet. Feel free to open an issue at https://github.com/spulec/moto/issues

I'm opening this issue to keep track of the support for owner-alias filter in the describe_images method of the ec2 client.
Here's a code example of the issue:
ec2_connection = boto3.client('ec2')
images = ec2_connection.describe_images(
    Filters=[
        {
            'Name': 'name',
            'Values': [
                'amzn-ami-hvm-*',
            ]
        },
        {
            'Name': 'owner-alias',
            'Values': [
                'amazon',
            ]
        },
    ]
)['Images']

And here's the exception raised by moto:
caught_exception = FilterNotImplementedError(u"The filter 'owner-alias' for DescribeImages has no...oto yet. Feel free to open an issue at https://github.com/spulec/moto/issues",)

    def _check_caught_exception(self, attempt_number, caught_exception):
        # This is implementation specific, but this class is useful by
        # coordinating with the MaxAttemptsDecorator.
        # The MaxAttemptsDecorator has a list of exceptions it should catch
        # and retry, but something needs to come along and actually raise the
        # caught_exception.  That's what this class is being used for.  If
        # the MaxAttemptsDecorator is not interested in retrying the exception
        # then this exception just propogates out past the retry code.
>       raise caught_exception
E       FilterNotImplementedError: The filter 'owner-alias' for DescribeImages has not been implemented in Moto yet. Feel free to open an issue at https://github.com/spulec/moto/issues

/usr/local/lib/python2.7/site-packages/botocore/retryhandler.py:359: FilterNotImplementedError

This is not a huge deal for me so I'm not planning to open a PR myself. But maybe someone with the same problem will. 😄

We'd need a comprehensive list of what alias's refer to what ownerid, if someone finds me them, i'll add support.

Briefly looking at the docs, it appears it's only three choices: amazon, aws-marketplace, and microsoft: http://docs.aws.amazon.com/AWSEC2/latest/APIReference/API_DescribeImages.html

This was implemented by #4175, and should be available as of moto >= 2.2.3.dev17.
I'll close this, but let us know if we've missed anything.


Lazy init SelectedSelectionKeySet

Lazy init SelectedSelectionKeySet because if maybeSelectorImplClass instanceof Throwable, the initialed SelectedSelectionKeySet is never used.

@carryxyh thanks a lot... Cherry-picked after adjust the commit message:
https://github.com/netty/netty/commit/b53cf045a7718766da8edd9499c657e77b314bbb

Ok, thanks a lot


Simplex method for buy xdc option added

Simplex Method to buy XDCs' in mainnet

Outdated PR hence closing.


New category color encoding

Make category color grey by default
Apply color only on selection or hover a cell

Will be important for the multi condition (dataset) comparison

Notes on that from today's meeting:

Every added dataset gets a unique color
Categories in the conf matrix should be grey
Hovering/selecting a cell will assign two colors to ground truth and predicted category

The single epoch indicator line in the multi epoch case can be a black or gray dotted 1px line. (remove orange). Agreed?


Added the exifForBlueprintChallenge property and its tests

Resolves #1613
Added a property exifForBlueprintChallenge
Added a test for the presence of this property in the image
Added a test to check its presence

I did some changes as you mentioned

Hm ... I guess we could download the file temporarily in the file system to check. what do you think @chinggg

Hm ... I guess we could download the file temporarily in the file system to check. what do you think @chinggg
Great! We have two choices, one is to download the URL to buffer, another is to save the image to locall machine. I prefer the image to be saved to pathToImage since it may be used again (though the product.image will still be URL :smile: )
I have just made a new commit.

Good idea. For reusability the path-to-image would need to be in the frontend/dist/frontend/... folder where the images are downloaded to in datacreator.ts.

The YAML schema validation doesn't work like expected, it would complain about any config that does not use Make as the EXIF property. We might just use an array of strings and check if all of them appear in any of the EXIF properties?

Good idea. For reusability the path-to-image would need to be in the frontend/dist/frontend/... folder where the images are downloaded to in datacreator.ts.

I am not sure whether I should just add frontend/dist before pathToImage for all situations? If product.image is a filename, will it always exist in frontend/dist/...? Since I am modifying the test scripts, I wonder whether this path have the files I need.

The YAML schema validation doesn't work like expected, it would complain about any config that does not use Make as the EXIF property. We might just use an array of strings and check if all of them appear in any of the EXIF properties?

Sir could you tell how to define the schema for it as i am getting some errors

exifForBlueprintChallenge:
  -
    type: string

Should allow to have a list of strings defined under that property.

Can you agree on one of the two PRs for the basis of review/fixes? I'm starting to get confused where to look... :-D

Can you agree on one of the two PRs for the basis of review/fixes? I'm starting to get confused where to look... :-D

I have lesser previous contributions i guess 😅

I don't count commits to decide for GSoC students, trust me... 🤪

Closing this to avoid confusion across PRs. Please commit into #1615 if needed. Thanks!


Custom configuration file detection

Custom syft.yaml file is placed in home directory syft is installed in /usr/local/bin i have made some changes in syft.yaml for eg:pretty print true for parent and cyclonedx-json but not getting reflected ...Will there be any configuration files overwriting my changes while execution ?I want to change the max file scan size to 4GB. How to check whether which config file is taken during execution @tgerla @wagoodman
Please help me to resolve this issue
Thanks in advance!

Hi @Vishnu-2810, you can run syft or grype without any arguments and it will show you the exact configuration file paths it uses. You can also explicitly specify a config file with -c myconfig.yaml to override the search paths. Hope this helps!


date and range_date do not hide datepicker on lost focus.

The wrapper for the date and date_range filters only listen for KeyUp event. The usual way to use the datepicker is via a mouse and therefore the picker doesn't hide when losing focus, or the filter is not triggered when the date changes. What's the best way to accomplish this?

Please provide a better explanation, because I can't understand your current question, the calendars are being closed when mouse is clicked outside and that's ok, see the following date range example a and notice that its behavior is similar to yadcf


OS.get_keycode_string() returns empty string

Godot version
v4.1.3.stable.official [f06b6836a]
System information
Godot v4.1.3.stable - Windows 10.0.22621 - Vulkan (Forward+) - dedicated NVIDIA GeForce RTX 4070 (NVIDIA; <IP_ADDRESS>01) - AMD Ryzen 5 5600X 6-Core Processor (12 Threads)
Issue description
I'm trying to show an interaction hint in UI by getting InputEventKey from InputMap.
Code:
# var interact_event_key: := ...
print(interact_event_key)
print(OS.get_keycode_string(interact_event_key.keycode))

Output:
InputEventKey: keycode=69 (E), mods=none, physical=true, pressed=false, echo=false
<empty-string>

I expect OS.get_keycode_string() returns E in this particular example.
Steps to reproduce
Download reproduction project, run it, look at the Output.
Minimal reproduction project
os_get_keycode_string_bug.zip

Try using event.physical_keycode instead of event.keycode. For me it works fine this way.

It's because you set it as physical keycode in Input map, so the engine just store a None in keycode field ,and so it will print physical=true instead of false.

Seems worth clarifying in the docs.

Thanks, it helped us head toward the right direction. On the issue you see just above, I found limitations when using this for:

default mappings defined e.g. in the Project Settings Input Map, where we can assign non-physical keycodes (as opposed to listening to input)
input with modifiers

Maaack found a solution for this in this PR:
https://github.com/Maaack/Godot-Game-Template/pull/105/files (check InputHelper.gd)
The full get_text method handles various cases including joystick, but since we're focused on key input I'll just copy the InputEventKey case below:
static func get_text(event : InputEvent) -> String:
	# ...
	elif event is InputEventKey:
		var keycode : Key = event.get_physical_keycode()
		if keycode:
			keycode = event.get_physical_keycode_with_modifiers()
		else:
			keycode = event.get_keycode_with_modifiers()
		keycode = DisplayServer.keyboard_get_keycode_from_physical(keycode)
		return OS.get_keycode_string(keycode)

(excerpt should be short enough to be used as a mere code sample, but if you need to copy more and worry about license, know that it's under MIT)


feat: Allow more complex key behavior

Which problem is this PR solving?

People want to use Refinery to help manage their Honeycomb keys.
They've wanted it for a while. See #634.

Short description of the changes

[x] Add SendKeys and SendKeysMode to config
[x] Implement a new route handler for http
[x] Document it in the metadata
[x] Document it in the readme
[x] Implement it for OTLP traces
[x] Implement it for OTLP logs

Closes #634.

It was a good idea to write some more tests. I found a couple of bugs that way. Thanks for the nudge.


Update page - Reserved Instances now also Apply to V3 Premium App Services Plans

This page should be updated to reflect the latest update:
https://techcommunity.microsoft.com/t5/apps-on-azure/migrate-modernize-net-applications-with-azure/ba-p/1696499
"Starting November 1st, customers can save up to 35 percent with a 1-year commitment and up to 55 percent for a 3-year commitment, compared to pay as you go prices. We are also extending our dev/test pricing discounts to Premium v3 as well as Premium v2, making it more affordable (especially for Visual Studio subscribers) to test workloads that require VNet connectivity before deploying."

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

ID: fb1c7712-7798-3505-4545-b44cd9870034
Version Independent ID: 49bd2e58-0d17-784d-26d6-5c1275131d69
Content: Reservation discounts for Azure App Service
Content Source: articles/cost-management-billing/reservations/reservation-discount-app-service-isolated-stamp.md
Service: cost-management-billing
Sub-service: reservations
GitHub Login: @yashesvi
Microsoft Alias: banders

@mapoitras Thanks for the comment
Assigning content owner @yashesvi for visibility, review and document enhancement consideration.

https://github.com/MicrosoftDocs/azure-docs-pr/pull/145253

@mapoitras Updated the article. See https://docs.microsoft.com/en-us/azure/cost-management-billing/reservations/prepay-app-service?toc=/azure/cost-management-billing/reservations/toc.json
#please-close


e2e_inference: update readme with known issue

update about https://github.com/intel/intel-technology-enabling-for-openshift/issues/107
Signed-off-by: vbedida79<EMAIL_ADDRESS>

LGTM!


[All Actors] Notifications should keep a timestamp of its creation instead of localeString date or iso date.

In the notifications view, show it user-friendly (toLocaleString)
Please make all the changes for each notification type: order, shipment.

This is an improvement for #146

Started working on this


Timestamp changed to ISO8601

https://tracker.mender.io/browse/MC-567
Currently it's quite tricky to investigate something when conductor makes relative timestamps in ms from container started. To make operations easier it would be better to have standard timestamp with date and time in it.

log entry example with this change
2019-02-28 16:03:40,566 [main] INFO  com.netflix.conductor.bootstrap.ModulesProvider  - Starting conductor server using dynomite/redis cluster.


Building tutorial code fails with type error

tmp.zip
Error log
(quarterhorse) cmcmanis@quarterhorse:test-amaranth$ python counter-sim.py
Traceback (most recent call last):
  File "/freenas/home/cmcmanis/arm-experiments/projects/test-amaranth/counter-sim.py", line 34, in <module>
    with sim.write_vcd("up_counter.vcd"):
  File "/home/cmcmanis/.local/lib/python3.11/contextlib.py", line 137, in __enter__
    return next(self.gen)
           ^^^^^^^^^^^^^^
  File "/freenas/home/cmcmanis/arm-experiments/projects/amaranth/quarterhorse/lib/python3.11/site-packages/amaranth/sim/pysim.py", line 329, in write_vcd
    vcd_writer = _VCDWriter(self._fragment,
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/freenas/home/cmcmanis/arm-experiments/projects/amaranth/quarterhorse/lib/python3.11/site-packages/amaranth/sim/pysim.py", line 94, in __init__
    if re.search(r"[ \t\r\n]", var_name):
       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/cmcmanis/.local/lib/python3.11/re/__init__.py", line 176, in search
    return _compile(pattern, flags).search(string)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: expected string or bytes-like object, got 'NoneType'
(quarterhorse) cmcmanis@quarterhorse:test-amaranth$

Not sure what is going on here yet, typed in code from the tutorial pages.

Foundational issue was apparently missing ctypes in the Python 3.11 install. Once I did the apt install libffi-dev, rebuilt python 3.11 (.configure <opts> ; make; make install). And then re-installed amaranth pip3 install --editable amaranth the example code I posted in this issue runs without complaint.


Connection refused for URI

When we try to upload image we got below error and exception. Kindly advise us regarding this

Uncaught InvalidArgumentException: League\Flysystem\Filesystem::putStream expects argument #2 to be a valid resource in /vendor/league/flysystem/src/Filesystem.php:111

Error executing "GetObject" on "https://XXXX.ap-south-1.linodeobjects/protected/Uploads/475a86907f/Round130.png"; AWS HTTP error: Connection refused for URI https://XXXX.ap-south-1.linodeobjects.com/protected/Uploads/475a86907f/Round130.png

If you are getting a connection refused error on your 'protected' assets - which are not open to the public, then you are either missing a specific config variable such as your AWS Secret and Key or something is not configured on your bucket properly.
The AWSS3 adapter is from the league/flysystem package not from us.
Please check to ensure your configuration is setup properly based off of our readme.
If you need support on setting up your environment I would recommend hitting the forums - https://forum.silverstripe.org/


NodeGroups ASGs should be per-AZ not balanced over AZs

What
We should have separate AutoScalingGroups for each AvailabilityZone for each NodeGroup
Why

AutoScaling groups attempt to "rebalance" over AZs, which is rarely what we want for our setup and can cause problems for Pods that want EBS volumes since they are AZ-bound
Cluster autoscaler does not support Auto Scaling Groups which span multiple Availability Zones; instead you should use an Auto Scaling Group for each Availability Zone and enable the --balance-similar-node-groups feature. If you do use a single Auto Scaling Group that spans multiple Availability Zones you will find that AWS unexpectedly terminates nodes without them being drained because of the rebalancing feature.
So that we can have more fine grained control over the nodes in each AZ rather than scaling up in 3x nodes each time.

More info here: https://github.com/kubernetes/autoscaler/tree/master/cluster-autoscaler/cloudprovider/aws

Resolved by #600  and friends too ... we have left the kiam/ci nodes as is spanning all AZs as these are not autoscaled


error -9809 when verifying signed string

I am using the below code to sign and verify the signature but getting false always! Digging in further, I found out the error code is -9809 - An underlying cryptographic error was encountered.
Need help in getting this solved please.
Below, am pasting my code -
if let heimdall = Heimdall(tagPrefix: "com.something.myapp") {

            let testString = "123456"

            if let publicKeyDataX509Value = heimdall.publicKeyDataX509() {
                NSLog("Heimdall Public Key \(publicKeyDataX509Value.base64EncodedString())")
            }

            if let signature = heimdall.sign(testString, urlEncode: true) {
                NSLog("signature for 123456 \(signature)")

                var verified = heimdall.verify(testString, signatureBase64: signature, urlEncoded: true)
                NSLog("Verification successful \(verified)") // True

                // If someone meddles with the message and the signature becomes invalid
                verified = heimdall.verify(testString + "injected false message",
                                           signatureBase64: signature)
                NSLog("Verification failed \(verified)") // False
            }
        }

Could you specify which line is getting the false?

@henrinormak - I get a false on both -
var verified = heimdall.verify(testString, signatureBase64: signature, urlEncoded: true)
                NSLog("Verification successful \(verified)") // True

                // If someone meddles with the message and the signature becomes invalid
                verified = heimdall.verify(testString + "injected false message",
                                           signatureBase64: signature)

Could be an interesting observation, I just found out, it returns false on simulator but on my test device. (I get true for the first line, and false for the second line)

@henrinormak - any news you have on this?

No, sorry, I haven't had time to investigate this. I might have some time later this week, but I can't guarantee anything. In general if everything works on the device, it seems like a problem with the entitlements (if you look at some of the other closed issues here, you might get help from those).

I converted your example into a test case and ran it on the simulator, it passed as expected (verification was successful for original data, whilst failing for corrupted data). As such I'm afraid I can't help as I can't reproduce the behaviour you describe.

Thank you for your feedback and time @henrinormak !
I am investigating further on this. Could there be a problem if the simulator/device is connected to a restricted network?

I can't think of a reason why, but the error code is a generic one, so nothing can be completely eliminated as a reason.

Error -9809 equals errSSLCrypto. Maybe your KeyChain is broken. Are you perhaps running on a jailbroken iOS device? It does work for me:
Heimdall Public Key MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEA2ZNKDO8EkPUKnhj2fj+CGNiZNOoh3+YOWlg/iV7aleeW5vJS+KgaT4/GV1d4weBnFxP3ygjNowwNiPnKua2FDx0hHEJAUTtCtMRYTORkH6aNZhp7AiNtJ4//zn4tg6AaWB67XTpNzwbx5RS3tgXjSU7me6MEEv8HlhMU7aW5mYqxdOZqj7yfz8ZkXHUSvhrujSV4ZXxheNRnXOIqTpoK6yIL00vdkvBqRPihDNpfCuvzhOvityRkaEps4e/4lvp6khKFPDwZAQJi/8y3hgt11OS6zgliGuWXUgXwxd3gG2T/ssi4Qii9yaXvjTGtie+rtIYhRk5Y0pThthOy9Zbk0QIDAQAB
signature for 123456 cxuO0e_J5yRi0eqmqceslHU6kA-qTPIYZuhWGWi7GWwxiFfLasnfN61trMhXGQ8DW5bK5dBfqpCOc9ULJCBJIWgrO8a9uO92SBUQgOizab6xvN5DGEalv11bNNDg7mef0D75TpE7nvOKNP-js1Egwx-kZVuXQeVtyS21QUOGngJivNkjaHp2I1YxDHfn3ToyuSaZ57Og7JsWzNmJa8lIIx-WAO2IA7rShkyP7TwTZqclvMAVwFrOMJrkSBpsImCrLcggwKQFoENoA-ZGG3iGKAcjzpd120DW_-hbt96DxdMMp5b1HZd3mqYov6WS-oV_NQlqh7s7cbnlWgRTuPdj9w==
Verification successful true
Verification failed false```

@henrinormak @Craz1k0ek - thanks for your feedback here. It works now. I am honestly not sure why it didn't work before. I haven't made any changes to implementation.
But like I said before, it was working well on a physical device but not on a simulator. Now it works on both device and simulator


Fix S3 backend operations with VersionId

will add tests soon

Hey, yeah get some tests in and i'll merge this :smile: great work as always

@terrycain ok, I've inspired me to write a couple, done!

Coverage decreased (-0.06%) to 92.93% when pulling b266206ae6bb6098d87f97353902a140e1bac06a on thehesiod:fix-s3-copy-src into f408709ef9cec376dabc9d2ba9d7964a27d5a0f3 on spulec:master.

Thanks :smile:


Add support for HLSL include dirs

All HLSL functions now take an optional includeDir parameter. From CLI you can do -i <path> or --include <path> to specify the include dir.
Resolves #53

Is a single include dir sufficient?

The DXC command line tool only allows one include input so I think we're fine with that.


Add endpoint to delete user records

Still needs tested first. @danielgrant do you have some in-flight Terraform changes being applied for the deletion request work? If so I'll get the other PR updated first and test when you're done.

Still needs tested first. @danielgrant do you have some in-flight Terraform changes being applied for the deletion request work? If so I'll get the other PR updated first and test when you're done.

Yeah good shout - if you apply this it'll undo my current working changes.

@garyttierney this has been rebased on main on the Terraform applied - it should be good for testing.


Investigate outliers in rules engine

Does the rules engine calculate outliers in a satisfactory way already? If not, we need to add logic for that.
We also need to add outliers to the Pydantic output classes

engine.py has this functionality


Pop up an error dialog after clicking 'Clear Queue' for one attached queue with SAS

Storage Explorer Version: 1.2.0
Platform: All
Architecture: ia32/x64
Build Number: 20180601.6
Commit: 16083561
Regression From: Not a regression
Steps to Reproduce:

Launch Storage Explorer and expand Storage Accounts.

Select one queue then attach is with SAS.

Open the attached queue -> Click 'Clear Queue' button on the toolbar.

Expected Experience:
No error dialog pops up.
Actual Experience:
An error dialog pops up.

What does your SAS look like? Do you have delete permissions?

Yes, attach the below queue named 'testqueue1' with full permission .
Generated SAS URI like this:
https://e7ikmorgkjtyq101.queue.core.windows.net/testqueue1?st=2018-06-04T05%3A28%3A00Z&se=2018-06-07T05%3A28%3A00Z&sp=raup&sv=2017-07-29&sig=aS0%2BLTwU9enXop3G7SEx5%2Bi1mFn%2BI7Im6dkqp8xgP18%3D

This issue still reproduces on the latest master build 20190703.4

@v-xuanzh The SAS you provided expired a year ago. You'll need a new one. If you can, please provide a valid, current SAS through an email.

Sent a mail to you.

OK, I'm able to reproduce as well. I checked the documentation, and I don't think clearing a queue is possible with a SAS. The "p" permission says you can get and delete messages. However a clear operation is different than a delete permission. Furthermore the Clear Messages REST documentation says only the account owner may call this operation.
Therefore, this is by design.


⚠ Bofrost.be has degraded performance

In 22bacff, Bofrost.be (https://www.bofrost.be) experienced degraded performance:

HTTP code: 200
Response time: 1842 ms

Resolved: Bofrost.be performance has improved in 2e15a6e.


[WIP] server: initial cut of vgo-aware type loader

DO NOT MERGE
Requires vgo as of https://go-review.googlesource.com/c/vgo/+/105855
Note: this is based atop https://github.com/mdempsky/gocode/pull/23
The current diff for this PR can be see here:
https://github.com/myitcv/gocode/compare/import_name_qualify...myitcv:vgo_loader

@myitcv I have forked this package and maintaining it on https://github.com/OneOfOne/gocode for now and with this PR, and I'm using it locally as well.
You are more than welcome to rebase on my fork, or if you update this PR yo ucan tag me and I'll rebase.
I plain on maintaining my fork until mdempsky gets back to this repo or go-langserver implements proper code completion without gocode.

Thanks for working on this. I haven't really kept up with vgo progress, so maybe you can help bring me up to speed on two questions:

Why does gocode need to know about vgo?

Assuming we do need a vgo-aware go/importer.Importer implementation, shouldn't that implementation live within the x/vgo or x/tools repo? I'm assuming we'd want gotype, guru, etc. to work with vgo too. Or is there something gocode-specific about this importer?

@myitcv, could you please stop sending these pull requests to projects, even marked DO NOT MERGE. They're confusing people.

@rsc apologies. I'll close this.


consider turning on noImplicitAny by default

currently our blueprints don't pass the noImplicitAny check - we should fix that.

[ ] understand the impact
[ ] change the config
[ ] update blueprints that fail the check

Current failures for an empty project:
[DiffingTSCompiler]: Typescript found the following errors:
  app/sample-45.spec.ts (7, 71): Parameter 'app' implicitly has an 'any' type.
  app/sample-45.spec.ts (12, 65): Parameter 'app' implicitly has an 'any' type.
  app/sample-45.ts (14, 17): Parameter 'meaning' implicitly has an 'any' type.

@rkirov @alexeagle - what's your guidance on this?

Why is it necessary to "pass the noImplicitAny check" - what is requiring that?
My (our?) guidance is: for someone brand-new to TypeScript, optional typing is a feature and helps them ramp up. Similarly, when migrating an existing codebase (eg what we did for Angular), noImplicitAny is a critical step to make this tractable and incremental.
However, anyone with some experience who is starting a new app that's not just a toy example or rapid prototype is better off with noImplicitAny turned on from the beginning.

I agree that turning on noImplicitAny in the tsconfig file would not be a good idea as it could be cumbersome for someone starting with TypeScript.
That being said, I think that the initial output of the blueprints should be accommodating if the user wants to turn that setting on, they should not have to modify any of the code which is generated via our blueprints.

sgtm - let's update the blueprints but keep the flag off by default.
On Tue, Dec 15, 2015 at 7:34 AM Mike Brocchi<EMAIL_ADDRESS>wrote:

I agree that turning on noImplicitAny in the tsconfig file would not be a
good idea as it could be cumbersome for someone starting with TypeScript.
That being said, I think that the initial output of the blueprints should
be accommodating if the user wants to turn that setting on, they should not
have to modify any of the code which is generated via our blueprints.
—
Reply to this email directly or view it on GitHub
https://github.com/angular/angular-cli/issues/107#issuecomment-164799941
.

Make sure you have some testing with noImplicitAny=true so the invariant
you desire is enforced by the continuous build! :)
On Tue, Dec 15, 2015 at 8:05 AM Igor Minar<EMAIL_ADDRESS>wrote:

sgtm - let's update the blueprints but keep the flag off by default.
On Tue, Dec 15, 2015 at 7:34 AM Mike Brocchi<EMAIL_ADDRESS>wrote:

I agree that turning on noImplicitAny in the tsconfig file would not be a
good idea as it could be cumbersome for someone starting with TypeScript.
That being said, I think that the initial output of the blueprints should
be accommodating if the user wants to turn that setting on, they should
not
have to modify any of the code which is generated via our blueprints.
—
Reply to this email directly or view it on GitHub
<
https://github.com/angular/angular-cli/issues/107#issuecomment-164799941>
.

—
Reply to this email directly or view it on GitHub
https://github.com/angular/angular-cli/issues/107#issuecomment-164809092
.

The PR I submitted (#213) covers all aspects specified here by @IgorMinar.

The noImplicitAny flag is turned off in the blueprints so as to not force developers to have that flag on by default.
All templates have been updated so they compile without issue if the flag is turned on
A test was added to verify compilation if the noImplicitAny flag is turned on, which will capture any errors introduced with blueprint upgrades

Nice! Thanks
On Wed, Feb 17, 2016 at 5:03 AM Mike Brocchi<EMAIL_ADDRESS>wrote:

The PR I submitted (#213 https://github.com/angular/angular-cli/pull/213)
covers all aspects specified here by @IgorMinar
https://github.com/IgorMinar.

The noImplicitAny flag is turned off in the blueprints so as to not
force developers to have that flag on by default.
All templates have been updated so they compile without issue if the
flag is turned on
A test was added to verify compilation if the noImplicitAny flag is
turned on, which will capture any errors introduced with blueprint upgrades

—
Reply to this email directly or view it on GitHub
https://github.com/angular/angular-cli/issues/107#issuecomment-185006516
.


pip install curlylint does not work due to incompatability with click 8.1.0

Describe the bug
Cannot run curlylint with the latest version of click. This is similar to https://github.com/psf/black/issues/2964. Workaround is to pin click<8.1.0.
Which terms did you search for in the documentation and issue tracker?
ImportError: cannot import name '_unicodefun' from 'click'
Environment
Python 3.8
Steps to reproduce
Install from pip with python3 -m pip install curlylint, observe failure.
 james@gazelle  /tmp/curlylint  python3 -m virtualenv .
created virtual environment CPython3.8.10.final.0-64 in 270ms
  creator CPython3Posix(dest=/tmp/curlylint, clear=False, no_vcs_ignore=False, global=False)
  seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=/home/james/.local/share/virtualenv)
    added seed packages: pip==22.0.4, setuptools==60.9.3, wheel==0.37.1
  activators BashActivator,CShellActivator,FishActivator,NushellActivator,PowerShellActivator,PythonActivator

 james@gazelle  /tmp/curlylint  source bin/activate

 james@gazelle   3.8.10  /tmp/curlylint  python3 -m pip install curlylint
Collecting curlylint
  Downloading curlylint-0.13.0-py3-none-any.whl (51 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 51.9/51.9 KB 1.7 MB/s eta 0:00:00
Collecting toml>=0.9.4
  Using cached toml-0.10.2-py2.py3-none-any.whl (16 kB)
Collecting attrs>=17.2.0
  Using cached attrs-21.4.0-py2.py3-none-any.whl (60 kB)
Collecting click>=6.5
  Using cached click-8.1.0-py3-none-any.whl (96 kB)
Collecting pathspec<1,>=0.6
  Using cached pathspec-0.9.0-py2.py3-none-any.whl (31 kB)
Collecting parsy==1.1.0
  Using cached parsy-1.1.0-py3-none-any.whl (6.9 kB)
Installing collected packages: parsy, toml, pathspec, click, attrs, curlylint
Successfully installed attrs-21.4.0 click-8.1.0 curlylint-0.13.0 parsy-1.1.0 pathspec-0.9.0 toml-0.10.2

 james@gazelle   3.8.10  /tmp/curlylint  touch blah.html

 james@gazelle   3.8.10  /tmp/curlylint  curlylint
Traceback (most recent call last):
  File "/tmp/curlylint/bin/curlylint", line 8, in <module>
    sys.exit(patched_main())
  File "/tmp/curlylint/lib/python3.8/site-packages/curlylint/cli.py", line 301, in patched_main
    patch_click()
  File "/tmp/curlylint/lib/python3.8/site-packages/curlylint/cli.py", line 291, in patch_click
    from click import _unicodefun  # type: ignore
ImportError: cannot import name '_unicodefun' from 'click' (/tmp/curlylint/lib/python3.8/site-packages/click/__init__.py)

Expected behavior
Curlylint runs successfully
Actual behavior
ImportError: cannot import name '_unicodefun' from 'click' (/tmp/curlylint/lib/python3.8/site-packages/click/__init__.py)

Thanks! @gasman


proposal: some way to interrupt channel-backed command/function

Is your feature request related something that is currently hard to do? Please describe.
At present it is is possible to interrupt the current (search) command using <C-c> (see :help CTRL-C)
However, this does not appear to translate to a world of channels.
A channel-backed plugin, just like a regular plugin, can get "stuck" running external commands (or the equivalent thereof). So <C-c> ends up being an important "kill" command.
Describe the solution you'd like
Some means by which <C-c> can be used in a channel world to interrupt a ch_evalexpr call.
Describe alternatives you've considered
I can't honestly think of a workaround/alternative here 😄
Additional context
This question is raised in the context of https://github.com/myitcv/govim

Can you please provide a working example?
You probably don't want to disconnect all channels on a CTRL-C.  So what would be OK to cancel?

Can you please provide a working example?

I can probably provide a simulation of a situation that goes "wrong" in this way if that's useful? Would simply be a long sleep that gets triggered as a result of, say, an autocmd on BufWritePre or a regular command call.
My current use case is as follows. Note, it is an exceptional use case, i.e. the user does not want to find themselves in this position, and the tool in question shouldn't really misbehave like this and take so long that the user considers hitting <C-c>
In https://github.com/myitcv/govim we have a BufWritePre autocmd that, via the gopls LSP, effectively runs a tool that checks the buffer/file in question, adds an missing imports, formats the resulting code and returns the results (to Vim to then write).
The problem is that in certain cases, this tool can end up running an extremely expensive query as it tries to determine missing imports.
Now it's absolutely correct to point out the tool should not behave like, but there are plenty of edge cases that lead to pathological behaviour. And it's not necessarily just this tool, could be lack-of-network related etc. Feels like there are a number of cases that might fall under this umbrella.

You probably don't want to disconnect all channels on a CTRL-C

Agreed.

So what would be OK to cancel?

The following guess is based on pure guesswork of what currently happens, so please take it with that pinch of salt.
Let's assume I currently have an autocmd that is "hooked" to run a command-line version of exactly the same tool, but does so via system(). If it ends up taking too long, I can hit <C-c> and I'm guessing a signal is sent to said process.
Would it be possible to achieve much the same with a channel-based setup? At least the way I've implemented https://github.com/vim/vim, if I am in the process of handling a function/command/autocmd callback I am not blocking the read loop, so could happily process a special ch_sendexpr call that included some sort of signal.
But then these are just random thoughts based on zero real understanding of the Vim side of things.
Please let me know if there's anything else I can help answer however.

Ran into a few more instances of this recently whilst trying to debug problems within govim.
The only additional detail to add is that any implementation would of course require the remote plugin to also handle the cancel call, which may have recursively made a call back to Vim etc. It gets complicated quickly.


[SMALLFIX]fix a typo in Mode.java

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/Alluxio-Pull-Request-Builder/13190/
Test PASSed.

Merged build finished. Test PASSed.

LGTM, thanks for the clean up.


Fix issue 750 (Daynaport problems in develop branch)

@akuker With this fix it should be possible to release 22.04 at last.

@rdmark Maybe you can approve, because you are also one of the testers for this issue.

@uweseimet Approved. LGTM. The one thing we should test is compatibility with the Atari ST drivers, I think.

@rdmark It's unlikely that a driver fails only because it is possible to not only request 36 but also 37 bytes. But on the other hand, you never know :). @mzryz, can you please run a quick test with the fix_issue_750 on the Atari?

@mzryz Cool, thank you!


Item runs should log as INFO as they did in Outset Python

Describe the bug
In Outset Python, when an item was run (e.g., a script in login-once), the logs would show a line like:
2024-01-01 00:00:03 AM - INFO: Processing /usr/local/outset/login-every/login_script.sh
In this rewrite of Outset, this has been assigned as a DEBUG entry in the logs:
2024-01-01 00:00:04 DEBUG: Processing script /usr/local/outset/login-every/login_script.sh
Ideally, the behaviour in this implementation of Outset should match the previous behaviour.
To Reproduce

Place a script in the login-once or login-every folder within /usr/local/outset/, set to executable by all users.
Log in to an account so that Outset runs the item placed in the folder.
Examine the logs (/usr/local/outset/logs/outset.log in this version of Outset, /Users//Library/Logs/outset.log in Outset Python).

Expected behaviour
That the output should be the same or similar between this version of Outset and Outset Python.
Actual Behaviour
Outset Python shows a line like:
2024-01-01 00:00:03 AM - INFO: Processing /usr/local/outset/login-every/login_script.sh
This version of Outset only shows this information if verbose_logging is turned on in its preferences.
System Details:

OS: macOS 13.6.4, 17.4RC
Architecture: Intel and Apple Silicon M1 respectively
Version: <IP_ADDRESS>18

Yes, the logs do fix the issue I raised, but as you suggested, I can only get verbose logs now. It would be good if you reverted to the previous behaviour now that Info items are the same as in Outset Python.

yeah, I agree - regarding the level of info to debug, is there anything else currently marked as debug that you think should be in info?

I don't think so. I was used to what the Python version gave me.

this one ok to close?
If there's any additional stuff you want being logged, LMK and we can chuck it into the 4.2.0 release


Kubernetes Discovery Issue

Describe the bug
With following dependencies:
        <dependency>
            <groupId>org.springframework.cloud</groupId>
            <artifactId>spring-cloud-kubernetes-discovery</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-webflux</artifactId>
        </dependency>

the application startup fails with the following error
***************************
APPLICATION FAILED TO START
***************************

Description:

Parameter 0 of method kubernetesReactiveDiscoveryClientHealthIndicator in org.springframework.cloud.kubernetes.discovery.KubernetesDiscoveryClientAutoConfiguration$Reactive required a bean of type 'org.springframework.cloud.kubernetes.discovery.KubernetesReactiveDiscoveryClient' that could not be found.

Action:

Consider defining a bean of type 'org.springframework.cloud.kubernetes.discovery.KubernetesReactiveDiscoveryClient' in your configuration.

Consider replacing first argument KubernetesReactiveDiscoveryClient client of kubernetesReactiveDiscoveryClientHealthIndicator
with ReactiveDiscoveryClient client.
Sample
A simple app to reproduce the error is available here

would be it work for you if you would disable it via:
spring.cloud.discovery.client.health-indicator.enabled=false

?

would it work for you if you would disable it via:
spring.cloud.discovery.client.health-indicator.enabled=false

?

Setting this property the application start succesfully

if this works for you, then we can close this ticket. wdyt?

if this works for you, then we can close this ticket. wdyt?

Replacing first argument KubernetesReactiveDiscoveryClient client of kubernetesReactiveDiscoveryClientHealthIndicator
with ReactiveDiscoveryClient client would definitely solve the problem

it might, I am not very sure to be honest. I propose to leave this one open for some time, and when I gets my hands onto that specific code, we will take a much closer look.

Ok. This simple app can help you to analyze the problem.
I look forward to hearing from you
Bye

Iam also facing the same issue.   Appreciate if you find any solution.  Even tried to add "spring.cloud.discovery.client.health-indicator.enabled=false"  not solving.

APPLICATION FAILED TO START

Description:
Parameter 0 of method kubernetesReactiveDiscoveryClientHealthIndicator in org.springframework.cloud.kubernetes.discovery.KubernetesDiscoveryClientAutoConfiguration$Reactive required a bean of type 'org.springframework.cloud.kubernetes.discovery.KubernetesReactiveDiscoveryClient' that could not be found.
Action:
Consider defining a bean of type 'org.springframework.cloud.kubernetes.discovery.KubernetesReactiveDiscoveryClient' in your configuration.

Why do you have spring-boot-starter-web on the classpath as well?  Can you please remove it and also use spring-cloud-starter-kubernetes-discovery and try again?

If you would like us to look at this issue, please provide the requested information. If the information is not provided within the next 7 days this issue will be closed.

Closing due to lack of requested feedback. If you would like us to look at this issue, please provide the requested information and we will re-open the issue.


gateways, put user back in control of gateway order / precedence

[x] Redmine Issue: https://redmine.pfsense.org/issues/8910
[x] Ready for review

Copying my question here from the Redmine ticket:

Why would that matter now? What loss of functionality is there? You can select it specifically, or setup a gateway group with it on Tier 1.
Not selecting WAN by default was breaking a number of people in unexpected ways based on whether or not another interface with a gateway came before WAN alphabetically.

I'm not seeing what this PR would solve. It's entirely possible I'm overlooking it though. I just need some clarification on what the problem is an the intended effect of this will be.

Thanks jim-p, reply added in redmine.

Apparently no longer required. Please resubmit if still required.

No longer required


Several checkboxes on a same task line

Hi, is it possible to have several checkboxes on a same task line under the todo list, please ?

I'm not sure what you mean by this, can you give me an example?

I mean, grouping several checkboxes on the same line on your checklist instead of one by line.
I am also interested in changing the font size of the checklist.

Do you mean nested items? If you could type an example of the markdown file, and how you'd like it to show up that would be very helpful

It is impossible to markdown several functional checkboxes on the same line, but maybe it could be possible to group them in the check list. To save place when you have a lot of checkboxes. Something like this :
https://nsa40.casimages.com/img/2021/02/22//210222081732504657.jpg

1.2.1 exposes a set of CSS variables, so you can customize font size now. Not planning on supporting multiple checkboxes on a single line. closing


fix: ref.current is not checked to be set

Closes #1549
✅ Pull Request Checklist:

[x] Included link to corresponding React Spectrum GitHub Issue.
[x] Added/updated unit tests and storybook for this change (for new code or code which already has tests).
[x] Filled out test instructions.
[x] Updated documentation (if it already exists for this component).
[x] Looked at the Accessibility Practices for this feature - Aria Practices

📝 Test Instructions:

Call useListBox({ isVirtualized: false }) with virtualization disabled.
🧢 Your Project:

Guess you are quite busy with all sorts of things.
May I ask when the next release is planned?

@AndyOGo Sorry about the delay, I'll merge this and it will go out with the next release (either today or early next week).


node-gyp rebuild fails when npm install nodobjc

Hi, When I try to install nodobjc in my electron project, it seems trigger the node-gyp rebuild
the command is npm install nodobjc --save
and get the output like below

here is my env
npm  6.14.9
node  v10.16.3
electron v11.0.3
node-gyp v7.1.2
Python 2.7.16
os mac-catalina-10.15.7
I also feel strange that node-gyp -v shows v7.1.2 but the error output above shows node-gyp -v v5.1.0

Hi, i have the exact same issue. Just that I am on Windows 10
I face this when trying to install Snowboard API renderer. It fails when trying to install Protagonist

I tried everything from this here but it doesn't help at all.
Any other solutions or things I might try?

those errors suggest that the version of the addon you're using is not compatible with the version of Node.js you're using. You should either find a newer version of the addon that supports your Node.js version, or downgrade Node.js to the maximum supported version for the addon you're using.


Extension seems to not start in VSCode remote container (devcontainer)

Hello,
I am running my Elixir project within a container using VS Code remote container extension (devcontainer) with the ElixirLS extension.
I wanted to try NextLS... However, I can't get it working.
I checked in the troubleshooting section but was not able to find anything obvious..
The integrated terminal output I have for is not labeled Next LS but elixir-tools.vscode (not sure if this is relevant)..
And I only have the following log:
[info] files: undefined..
Also epmd is running..
I can't find anything in there ~/.cache/elixir-tools/nextls/bin/ which is the default value of the Installation Directory setting..
But it seems the extension is installed here ~/.vscode-server/extensions/elixir-tools.elixir-tools-0.15.1/bin
I tried to change the Installation Directory setting to this but without success..
What do I do wrong?
I'm running in Alpine Linux fwiw..

[info] files: undefined..

this log is showing that it couldn't find a mix.exs file in the root of the project.
there might be something related to the remote container extension that i'm not accounting for, will need some investigation


[Windows] Remove fails_on_windows from quic_protocol_integration_test

Signed-off-by: Sotiris Nanopoulos<EMAIL_ADDRESS>Commit Message:
Remove fails_on_windows from quic_protocol_integration_test. I have validated this with a couple of thousand runs. I am greedily enabling this test and if this goes south I will mark it as flaky_on_windows
Risk Level: Low (Test only)
Testing: N/A
Docs Changes: N/A
Release Notes: N/A
Platform Specific Features: N/A

@alyssawilk
cc @envoyproxy/windows-dev for visibility

There is a failure specific to quic_http_integration_test that causes it to time out GCP RBE. I think it is because the test takes too long on Windows so I can't remove it now. I will have to investigate this on further

Got it.  There are a few timeouts which I'm trying to fix with #15812 and a follow-up I have in a local branch.  Once those land I'll see if CI passes or (more likely) if there's still something else up.
Meanwhile as I turn up more tests for QUIC I'll make sure to run them on windows if they pass (e.g. https://github.com/envoyproxy/envoy/pull/15841/files)

Thanks! If there are any Windows specific failures, feel free to open an issue and I will look into them.

Will do!  Also if you can easily sort out which test is hanging in the http_protocol_integration_test feel free to #define it out for windows and have the rest running, just to avoid any other windows regressions in the interim.  Unfortunately it's a lot more frustrating to figure out what's working and not via CI :-P


Add npm run build into Live Playground section

Coverage remained the same at 87.099% when pulling d1626447b2ae53d14035337b07debb24ab3d4d61 on koba04:patch-1 into ed4d06911d3f18c7164b165939713af266f3289d on airbnb:master.

Fixed in 55d6453, please pull the latest master! :)

Thanks!


in detection_voc_evaluator.py, Why observation is empty dict and return?

in detection_voc_evaluator.py,  I can't google more evaluator example, So I just look at your faster RCNN's detection_voc_evaluator.py example? Do you know how to write a myself evalutor? why below code return an empty dict observation ?
        report = {'map': result['map']}

        if self.label_names is not None:
            for l, label_name in enumerate(self.label_names):
                try:
                    report['ap/{:s}'.format(label_name)] = result['ap'][l]
                except IndexError:
                    report['ap/{:s}'.format(label_name)] = np.nan

        observation = {}
        with reporter.report_scope(observation):
            reporter.report(report, target)
        return observation

I am a foreigner , I can't read japanese, I googled a lot of chainer example, But most of them is written in japanese, I want to know how to write a evaluator extension?

Well, I don't know much example other than ones in ChainerCV that modifies Evaluator.
        observation = {}
        with reporter.report_scope(observation):
            reporter.report(report, target)
        return observation

This basically does observation.update(report).
By looking at the source code of the original Evaluator, you can find that our evaluator simply modified parts of it.
While trying to come up with an answer to your question, I realized that it can be simplified to return report.
As a side note, the context with reporter.report_score(observation) is useful when reporter.report is called inside of a function in the with block.
Here is an example.
import chainer
from chainer import reporter as reporter_module

def f():
    reporter.report({'a': 3})

if __name__ == '__main__':
    observation =  {}

    reporter = reporter_module.Reporter()

    with reporter:
        with reporter_module.report_scope(observation):
            f()

    print(observation)

I just can't find where did it reported ?? in which log file path? I don't see any report F1 score or Accuracy in console print?

If you use LogReport in your train loop, the values will be printed to a file.
By default, the log file is result/log.
(https://github.com/chainer/chainercv/blob/master/examples/faster_rcnn/train.py#L100)

@yuyu2172 but you also use PrintReport
trainer.extend(extensions.PrintReport(
  | ['iteration', 'epoch', 'elapsed_time', 'lr',
  | 'main/loss',
  | 'main/roi_loc_loss',
  | 'main/roi_cls_loss',
  | 'main/rpn_loc_loss',
  | 'main/rpn_cls_loss',
  | 'validation/main/map',
  | ]), trigger=print_interval)
```
Does this 2 line conflict with each other, I did not found any report log in my linux filesystem. I am try to find.

mAP gets recorded on the log file only when it gets evaluated.
You will find it in the log file at iteration 5000.
They don't conflict with each other.

If you have more question, please reopen.


Register

@JuliaRegistrator register
Release notes:
This release changes the backend for IntensityMap from AxisKeys to DimensionalData due to its improved maintenance.
Breaking Updates

IntensityMap is now based on DimensionalData and not AxisKeys
AbstractDims has been renamed to AbstractGrid to better represent its meaning
GriddedKeys has been renamed RectiGrid since it is a recti-linear grid
axiskeys has been renamed to axisdims and returns the AbstractGrid for intensity map.

Registration pull request created: JuliaRegistries/General/98836
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.6.0 -m "<description of version>" c65fec9bc2bc8ca29212e0396543f53c7c02ca65
git push origin v0.6.0

@JuliaRegistrator register

Registration pull request updated: JuliaRegistries/General/98836
Tip: Release Notes
Did you know you can add release notes too? Just add markdown formatted text underneath the comment after the text
"Release notes:" and it will be added to the registry PR, and if TagBot is installed it will also be added to the
release that TagBot creates. i.e.
@JuliaRegistrator register

Release notes:

## Breaking changes

- blah

To add them here just re-invoke and the PR will be updated.
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.6.0 -m "<description of version>" 5e3cbbf19d364b4200ce26308c08bf9fd4294d57
git push origin v0.6.0

@JuliaRegistrator register

Registration pull request created: JuliaRegistries/General/98864
Tip: Release Notes
Did you know you can add release notes too? Just add markdown formatted text underneath the comment after the text
"Release notes:" and it will be added to the registry PR, and if TagBot is installed it will also be added to the
release that TagBot creates. i.e.
@JuliaRegistrator register

Release notes:

## Breaking changes

- blah

To add them here just re-invoke and the PR will be updated.
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.6.1 -m "<description of version>" 12da6c75e15876443ef561ab816e20be535ec920
git push origin v0.6.1

@JuliaRegistrator register
Release notes:

Added rrules/ProjectTo for IntensityMap

Registration pull request created: JuliaRegistries/General/99010
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.6.2 -m "<description of version>" ab9c45a36f29960771dbaec2279cf01c66aa440d
git push origin v0.6.2

@JuliaRegistrator register
Release notes:

Improve type stability of RectiGrid (still not perfect but that's a problem with DD)

Registration pull request created: JuliaRegistries/General/99072
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.6.3 -m "<description of version>" 9f8e0d923d8bd2ee1ac5fcaa6e6b614bfd7c8c35
git push origin v0.6.3

@JuliaRegistrator register
Release notes:

Bug fix and better centroid calculation

Registration pull request created: JuliaRegistries/General/99471
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.6.4 -m "<description of version>" 47791d41a169df875dacd7da5499ce0b8c8271b2
git push origin v0.6.4

@JuliaRegistrator register
Release notes:

Add support for composite polarized types

Registration pull request created: JuliaRegistries/General/99590
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.6.5 -m "<description of version>" 77d06f579e54be344d94fb9ac98ba646580a7d01
git push origin v0.6.5

@JuliaRegistrator register
Release notes:

Upgraded to DD 0.26
Denoted various traits as non-differentiable

Registration pull request created: JuliaRegistries/General/103059
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.6.6 -m "<description of version>" a24e77142380ce6a0be36d62a249de1e8deb14b3
git push origin v0.6.6

@JuliaRegistrator register
Release notes:

Completely rewrote the grid backend to allow various executors
Added UnstructuredDomain and UnstructuredMap
Renamed visibilities to visibilitymap
Renamed closures_phases to closure_phasemap
Renamed logclosure_amplitudes to logclosure_amplitudemap
Renamed bispectra to bisprectrummap
Removed StokesIntensityMap
Added various EnzymeRules
Added helper methods for creating maps create_(img/vis)map and allocate_(img/vis)map

Registration pull request created: JuliaRegistries/General/105543
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.7.0 -m "<description of version>" 3f361c71c96005551d04a11749ca88a27323e2db
git push origin v0.7.0

Registration pull request created: JuliaRegistries/General/105558
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.7.1 -m "<description of version>" ea429e57ac34186ad3dc2a27e965e3684c82b61d
git push origin v0.7.1

@JuliaRegistrator register
Release notes:

enhanced baseimage to make it deal with nested structures
fixed a docstring

Registration pull request updated: JuliaRegistries/General/105617
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.7.2 -m "<description of version>" 164c6110f32e420eeb4485a6f4d3e9e58867fe33
git push origin v0.7.2

@JuliaRegistrator register
Release notes:

Fixed various bugs and typos

Registration pull request created: JuliaRegistries/General/105640
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.7.3 -m "<description of version>" 3c28240114145795a797e6a1af7dca4b793f0ea4
git push origin v0.7.3

@JuliaRegistrator register
Release notes:

Added some EnzymeRules.inactive

Registration pull request created: JuliaRegistries/General/106633
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.7.4 -m "<description of version>" 00073895d69f12dd35fe8d2d3d7333c869f91756
git push origin v0.7.4

@JuliaRegistrator register
Release notes:
Fixed docstring

Registration pull request created: JuliaRegistries/General/106722
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.7.5 -m "<description of version>" 3995fbe6d7d99fe29c52bccabbe69767326df248
git push origin v0.7.5

@JuliaRegistrator register
Release notes:

Update compact bounds for DD and StructArrays
Update testing to LTS and 1

Registration pull request created: JuliaRegistries/General/119627
Tagging
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v0.8.5 -m "<description of version>" 4bb894f0e69659011cba17254062c410f2ba7342
git push origin v0.8.5


Post binning from the app

Because
Post-binning is now done by taking the configuration file that is created when training a model, but the model building itself does not require post-binning.
In #46 we added code to allow the classifier to use the post binning when creating timeframes. But we may want to use a different post-binning strategy when running the app. This can now not be done. If we want to do this we have to create a different model and ship it with the app.
Done when
No response
Additional context
No response

Done in https://github.com/clamsproject/app-swt-detection/commit/dc627e6fb90f0c73e34b3e56b8ba07fabb6af07e, https://github.com/clamsproject/app-swt-detection/commit/37b53637dfcecb14ba40ee0b63e56054f6e4a472, https://github.com/clamsproject/app-swt-detection/commit/e8a7172529d5d7b839b1380ceabcf940efa6858b and https://github.com/clamsproject/app-swt-detection/commit/a166be3f6ecc38642383d478161cca16c3d31954. Leaving the issue open awaiting some final testing.


IDE type hinting fix

IDE does not understand object type, and highlights an error.

With mixed type it works.

looks more like a bug of the IDE...

Indeed, it's IDE bug: http://www.phpdoc.org/docs/latest/guides/types.html

Huh, alrighty then, sorry for this.

Report it to JetBrains, they have a tracker here: http://youtrack.jetbrains.net/issues/WI

Yup, that's what I did.. https://youtrack.jetbrains.com/issue/WI-27921


Fix sampling for newer ComfyUI

As of commit 1777b54d0217e77a6a64b0a587b9b11a48e3bf02, ComfyUI sampling changed and broke AIT.
This seems to fix things, and in my quick tests, AIT still produces about the same output as the non-patched model.
It seems to me that subclassing BaseModel would be a cleaner way of handling AIT patching, but that kind of refactoring is a bit more work.

Thanks so much for this!


ERRoR in running with Gpu

How to solve this Error:
InvalidArgumentError (see above for traceback): Cannot assign a device for operation init: Operation was explicitly assigned to /device:GPU:0 but available devices are [ /job:localhost/replica:0/task:0/device:CPU:0 ]. Make sure the device specification refers to a valid device.

Do you have any other logs? Are you using Linux or Windows? What version of tensorflow? Nvidia or AMD GPU? It's easier to help you if you are as descriptive as possible. Thanks!

Hi
thanks for your answer
I tried that statement
the output is:
name: "/device:CPU:0"
2018-11-17 17:25:27.712583: I
tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports
instructions that this TensorFlow binary was not compiled to use: AVX2
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation:<PHONE_NUMBER>7737949935
]
Please install GPU version of TF
But my syatem has Gpu
what can I do?
On Fri, Nov 16, 2018 at 12:00 PM Simhan Ramakrishnan <
<EMAIL_ADDRESS>wrote:

Make sure you have tensorflow GPU version installed or its point to the
write env which has GPU version installed
You also check what devices are getting recognized . If you don't see GPU
then its not the right env or TF. uninstall tensorflow and reinstall
tensorflow-gpu
//////////// Try this below
import tensorflow as tf
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())
/////////// You should get something logs like below
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation:<PHONE_NUMBER>9xxxxxxxxx
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit:<PHONE_NUMBER>
locality {
bus_id: 1
links {
}
}
incarnation:<PHONE_NUMBER>94xxxxxxxxxxxxxxx
physical_device_desc: "device: 0, name: GeForce GTX 970, pci bus id:
0000:02:00.0, compute capability: 5.2"
, name: "/device:GPU:1"
device_type: "GPU"
memory_limit:<PHONE_NUMBER>
locality {
bus_id: 1
links {
}
}
incarnation: 163427xxxxxxxxxxxxxxxxxxxxxxxx
physical_device_desc: "device: 1, name: GeForce GTX 970, pci bus id:
0000:03:00.0, compute capability: 5.2"
]
Try this too
if tf.test.gpu_device_name():
print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
else:
print("Please install GPU version of TF")
////////////////////// output
Default GPU Device: /device:GPU:0
/////////////////////////////
as n0t0ri0us mentioned please provide more details about the
environment(linux,osx,windows,gpu card etc) and show some complete logs.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/23773#issuecomment-439317783,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AqoKEn5ZIRyfCaa5G3DfYAWlM6fcuD0iks5uvneIgaJpZM4Yf3BI
.

As it says "Please install GPU version of TF"
Tensorflow magically cannot run on GPU and i don't know much about your environment . You also have to make sure correct nvidia drivers have been installed.
Please follow these instructions from here and for the right OS. Use anaconda if possible.
https://www.tensorflow.org/install/   and post your comments on stack overflow instead of raising an issue

I'm using Windows10
version of tensorflow 1.12
Nvidia GPU
I installed tensorflow-gpu but  i have these message in my running
environment:
2018-11-18 11:31:18.966801: I
tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports
instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2018-11-18 11:31:20.253752: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with
properties:
name: GeForce GTX 1050 major: 6 minor: 1 memoryClockRate(GHz): 1.493
pciBusID: 0000:01:00.0
totalMemory: 4.00GiB freeMemory: 3.31GiB
2018-11-18 11:31:20.254787: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu
devices: 0
2018-11-18 11:31:21.153266: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect
StreamExecutor with strength 1 edge matrix:
2018-11-18 11:31:21.153661: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:988]      0
2018-11-18 11:31:21.153904: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0:   N
2018-11-18 11:31:21.154529: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow
device (/device:GPU:0 with 3026 MB memory) -> physical GPU (device: 0,
name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
[name: "/device:CPU:0"device_type: "CPU"memory_limit: 268435456locality
{}incarnation:<PHONE_NUMBER>155869145, name: "/device:GPU:0"device_type:
"GPU"memory_limit:<PHONE_NUMBER>locality {  bus_id: 1  links {  }}incarnation:
769163103206302902
physical_device_desc: "device: 0, name: GeForce GTX 1050, pci bus id:
0000:01:00.0, compute capability: 6.1"]
2018-11-18 11:31:21.160132: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu
devices: 0
2018-11-18 11:31:21.160490: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect
StreamExecutor with strength 1 edge matrix:
2018-11-18 11:31:21.160798: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:988]      0
2018-11-18 11:31:21.161001: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0:   N
2018-11-18 11:31:21.161334: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow
device (/device:GPU:0 with 3026 MB memory) -> physical GPU (device: 0,
name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
2018-11-18 11:31:21.163951: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu
devices: 0
2018-11-18 11:31:21.164348: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect
StreamExecutor with strength 1 edge matrix:
2018-11-18 11:31:21.164715: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:988]      0
2018-11-18 11:31:21.164968: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0:   N
2018-11-18 11:31:21.165295: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow
device (/device:GPU:0 with 3026 MB memory) -> physical GPU (device: 0,
name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
Default GPU Device: /device:GPU:0
On Thu, Nov 15, 2018 at 8:55 PM n0t0ri0us<EMAIL_ADDRESS>wrote:

Do you have any other logs? Are you using Linux or Windows? What version
of tensorflow? Nvidia or AMD GPU? It's easier to help you if you are as
descriptive as possible. Thanks!
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/23773#issuecomment-439119890,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AqoKEkslfdTetPHNreb3t6lNMuITGOLrks5uvaOAgaJpZM4Yf3BI
.

I'm using Windows10
version of tensorflow 1.12
Nvidia GPU
I installed tensorflow-gpu but  i have these message in my running
environment:
2018-11-18 11:31:18.966801: I
tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports
instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2018-11-18 11:31:20.253752: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with
properties:
name: GeForce GTX 1050 major: 6 minor: 1 memoryClockRate(GHz): 1.493
pciBusID: 0000:01:00.0
totalMemory: 4.00GiB freeMemory: 3.31GiB
2018-11-18 11:31:20.254787: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu
devices: 0
2018-11-18 11:31:21.153266: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect
StreamExecutor with strength 1 edge matrix:
2018-11-18 11:31:21.153661: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:988]      0
2018-11-18 11:31:21.153904: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0:   N
2018-11-18 11:31:21.154529: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow
device (/device:GPU:0 with 3026 MB memory) -> physical GPU (device: 0,
name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
[name: "/device:CPU:0"device_type: "CPU"memory_limit: 268435456locality
{}incarnation:<PHONE_NUMBER>155869145, name: "/device:GPU:0"device_type:
"GPU"memory_limit:<PHONE_NUMBER>locality {  bus_id: 1  links {  }}incarnation:
769163103206302902
physical_device_desc: "device: 0, name: GeForce GTX 1050, pci bus id:
0000:01:00.0, compute capability: 6.1"]
2018-11-18 11:31:21.160132: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu
devices: 0
2018-11-18 11:31:21.160490: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect
StreamExecutor with strength 1 edge matrix:
2018-11-18 11:31:21.160798: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:988]      0
2018-11-18 11:31:21.161001: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0:   N
2018-11-18 11:31:21.161334: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow
device (/device:GPU:0 with 3026 MB memory) -> physical GPU (device: 0,
name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
2018-11-18 11:31:21.163951: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu
devices: 0
2018-11-18 11:31:21.164348: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect
StreamExecutor with strength 1 edge matrix:
2018-11-18 11:31:21.164715: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:988]      0
2018-11-18 11:31:21.164968: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0:   N
2018-11-18 11:31:21.165295: I
tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow
device (/device:GPU:0 with 3026 MB memory) -> physical GPU (device: 0,
name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
Default GPU Device: /device:GPU:0
On Sun, Nov 18, 2018 at 1:33 AM Simhan Ramakrishnan <
<EMAIL_ADDRESS>wrote:

As it says "Please install GPU version of TF"
Tensorflow magically cannot run on GPU and i don't know much about your
environment . You also have to make sure correct nvidia drivers have been
installed.
Please follow these instructions from here and for the right OS. Use
anaconda if possible.
https://www.tensorflow.org/install/ and post your comments on stack
overflow instead of raising an issue
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/23773#issuecomment-439650709,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AqoKEnQJp7K_S1hF_WvlnAsmKguzpcvIks5uwIe4gaJpZM4Yf3BI
.

@sobhansepid The above message tells you that you have successfully installed TensorFlow GPU and it was able to locate GPU availability on your system.
However the initial error message may have arisen due to ongoing computations on your system. Not sure exactly what can trigger. Try terminate all processes and give a fresh try for your GPU computation process.

thanks a lot for your answer
Does not the following message make any problem? and what can I do?
*I tensorflow/core/platform/cpu_**feature_guard.cc:141] Your CPU supports
instructions that this TensorFlow binary was not compiled to use: AVX AVX2 *
On Tue, Nov 20, 2018 at 1:38 AM ymodak<EMAIL_ADDRESS>wrote:

@sobhansepid https://github.com/sobhansepid The above message tells you
that you have successfully installed TensorFlow GPU and it was able to
locate GPU availability on your system.
However the initial error message may have arisen due to ongoing
computations on your system. Not sure exactly what can trigger. Try
terminate all processes and give a fresh try for your GPU computation
process.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/23773#issuecomment-440057885,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AqoKEmshA7yO70nHasUHwBQbSSEtm85tks5uwyvBgaJpZM4Yf3BI
.

Nagging Assignee @ymodak: It has been 14 days with no activity and this issue has an assignee. Please update the label and/or status accordingly.

Apologies for the delay in response.
The above warning message tells you that AVX AVX2* instruction sets are not enabled. To optimize the CPU performance you have to build TF from sources.
However I won't recommend doing that because you are using TensorFlow GPU version and most expensive ops will be computed on GPU anyway.
So you can safely ignore this warning message.
You avoid seeing those warning messages you can try:

import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'


added two compiler exceptions to the stable API

Description
added two compiler exceptions to the stable API
Self Check:
Strike through any lines that are not applicable (~~line~~) then check the box

[ ] Attached issue to pull request
[ ] Changelog entry
[ ] Type annotations are present
[ ] Code is clear and sufficiently documented
[ ] No (preventable) type errors (check using make mypy or make mypy-diff)
[ ] Sufficient test cases (reproduces the bug/tests the requested feature)
[ ] Correct, in line with design
[ ] End user documentation is included or an issue is created for end-user documentation (add ref to issue here: )

Reviewer Checklist:

[ ] Sufficient test cases (reproduces the bug/tests the requested feature)
[ ] Code is clear and sufficiently documented
[ ] Correct, in line with design

Processing this pull request

Merged into branches master in 03624a3310b602dfa16bf65353df6383015be751

Processing #4949.

Processing #4948.


Stop the iteration of an exhausted, unknown-sized sequence when slicing

Fixes #1256
This PR fixes a bug with the slice operator that caused non-value
iterators of an unknown sized sequence to continue although the source
sequence was exhausted, eventually accessing the value of a key/value
pair that does not exist.
The issue did not happen with fixed sized sequences since we can
calculate resulting size in advance (as sliceSize) and bail out early.
For an unknown sized sequence, however, we can not know this size in
advance (see this comment: 1).
To solve this, we now bail out when we encounter a completed iterator
before proceeding to process it further.

Great, thanks for adding a test!


Various CI changes to unbreak the CI

a few changes:

Add a job to build with rust stable
Add a job to build with rust nightly
Change the list of build to use min rust version

Would Rust beta be interesting to include here?

not sure? Nightly should already catch regressions

@tertsdiepraam the failure is a network issue on freebsd :)


The EventDispatcher should be final

It makes no sense to extends the domain event dispatcher and is a pain for maintainance.

closed by #52


Only count detected events

@OOHehir

Right now, the csv table for detected events creates a new row for every inference (Somehow every row counts as a detected event in the app (getStatus), so the app now shows thousands of detected events). This should be changed to detected trumpets only. Let's set the value to 0.8 for now.
This change should be enough for this new release. Just to avoid any bigger changes. Not too much time for testing any more. So let's keep it as simple as possible.

For the future (after this release) it would be great to integrate these features:
a. The threshold should be able to set in the app (via setConfig)
b. Soon, the model will not only detect trumpets but other sounds as well. So it should be automatically extended to as many features the model brings with it. For example:

trumpets: 24
rumbles: 39
growls: 12

Do you have enough time to implement the first point within the next day? If not. No problem.
If you have more ideas on how to improve. Let me know :)

@EDsteve It seems the latest model changed the label for non-target sounds from 'background' to 'others'. Theses labels are included in the imported EI model code.
I've expanded the labels for non-target sounds here. Sounds other than those listed below will be classified as a 'detected event' & the event recorded.

background
other
others

Note: The only outstanding issue here is to enable the detection threshold to be set via Bluetooth


[BUG] Switched to normal bloxstrapper for now. Bloxstrap causes the graphics slider to not work temporary.

Acknowledgement of preliminary instructions

[X] I have read the preliminary instructions, and I am certain that my problem has not already been addressed.
[X] I have thoroughly looked through the available Wiki articles and could not find a solution to my problem.
[X] I am using the latest version of Bloxstrap.
[x] I did not answer truthfully to all the above checkboxes.

Bloxstrap Version
v2.8.0
What problem did you encounter?
I switched to the normal Roblox client because...
While I was on a Roblox game with a "Future" lighting mode on Roblox,  I tested to see if my graphics slider works, but then my graphics isn't changing as intended with modes either manual or auto . So i tried checking bloxstrap settings to see if it's related to lighting technology, i set it to every option as i can, and I did resetted the FastFlags too if thats the issue. until further i started to reinstall bloxstrap 3 times earlier and the problem didnt fixed at all.
Bloxstrap Log
N/A

SAME!!

SAME!!

also i should not have said it like that ng;

Could this be duplicate of #3435

For coherence, could you upload your configuration please? https://github.com/bloxstraplabs/bloxstrap/wiki/Uploading-your-Bloxstrap-configuration

@Ki3l100 have you seen pizzaboxer's reply?

For coherence, could you upload your configuration please? https://github.com/bloxstraplabs/bloxstrap/wiki/Uploading-your-Bloxstrap-configuration
It's weird you mention that it works fine with the normal bootstrapper because every other report I've received about this indicates that it happens there too


bundling module doesn't exist !

`---> 14 from datashader.bundling import directly_connect_edges, hammer_bundle
15 from datashader.utils import export_image
16
ModuleNotFoundError: No module named 'datashader.bundling'`
Getting the above error, weird because datashader import work just fine. Installed it via Conda as recommended. If not pushed to Conda repos yet any chance it could be pushed in the near future ?

Thanks for reporting this issue!
Edge bundling is only available in the dev releases at this time. You can install datashader with:
conda remove datashader
conda install -c bokeh/label/dev datashader

The remove subcommand is needed to make sure conda doesn't get confused in the future.

Hi, I am getting this same error even after
conda install -c bokeh/label/dev datashader
is there anything else that might be needed to be updated?
We are trying to run an edge bundling tutorial
Thanks

Edge bundling is now fully released, and should work out of the box if you follow the instructions for setting up your environment at https://github.com/bokeh/datashader/tree/master/examples .  If you have any trouble, please post your error messages and we can probably figure it out.

Thank you for the reply, the issue seems to be on our end with anaconda environments.


Status 400 - Axios Bug

Describe the bug
Trying to run a simple test completion using the documentation, and the solution fails with an Axios bug.
I have replicated my settings using Postman and can verify that data is returned as expected.
The error in code shows me no obvious details of what is causing the error in your library.
To Reproduce
Create a new Node project and use the details as shown here:
https://platform.openai.com/docs/api-reference/chat/create?lang=node.js
Run it and you will have a 400 response returned.
Code snippets
const result = await openai.createChatCompletion({
            model: "gpt-3.5-turbo",
            messages: [
                {role: "system", content: "You are a helpful assistant"},
                {role: "user", content: {promptValue}}
            ]
        }, { responseType: 'stream' });

OS
Windows 11
Node version
Node 18.12.1
Library version
v3.3.0

@OldManMeta please try our upcoming v4 of this library, which replaces axios with fetch, and adds support for Streaming.

@rattrayalex thanks for letting me know. I've just built my own library with Fetch and streaming in the last hour.
I can't have these types of issues in production, so while I appreciate you and the teams work on this, stability is needed above features and certainly a big message on the front page indicating this would be really appreciated.


[core] Push v_head when using AutoModelForCausalLMWithValueHead

What does this PR do?
This PR addresses saving v_head weights when calling save_pretrained. Before this PR if a user wanted to share intermediate-trained v_head weights it was not possible. The workaround that I have found needs to load the state dict twice, once by the from_pretrained method that is called by the pretrained_model attribute and once afterwards to manually load the v_head.
This PR introduces a new kwarg on the method from_pretrained termed as resume_training as I think this is quite an edge case.
Added also some tests
TODOs:

test push_to_hub

cc @lvwerra @lewtun

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint.

Actually this was not working in the sharded case, I'd expect users to load large & sharded models too!


[24.05] forgejo: 7.0.7 -> 7.0.8

https://codeberg.org/forgejo/forgejo/milestone/7729
diff: https://codeberg.org/forgejo/forgejo/compare/v7.0.7..v7.0.8
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
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
24.11 Release Notes (or backporting 23.11 and 24.05 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

[ ] Fits CONTRIBUTING.md.

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

It would be a cherry pick in name only, as master has diverged and been split into two packages.

Then pick and amend the forgejo-lts bump.

I wasn't able to amend this PR, so https://github.com/NixOS/nixpkgs/pull/338305