Rollup "mwc-notched-outline" has already been used with this registry** when importing mwc-select

Describe the bug
Using rollup to build a bundle fails when adding mwc-select
I am importing following components
import { LitElement, html, css } from 'lit-element';
import '@material/mwc-icon'
import '@material/mwc-icon-button'
import '@material/mwc-button'
import '@material/mwc-menu';
import<EMAIL_ADDRESS>import '@material/mwc-fab';
import '@material/mwc-circular-progress';
import '@material/mwc-dialog';
import '@material/mwc-textfield';

Rollup config
export const translateAddonPageScriptConfig = {
  input: `src/contentscript/taskview/translate-addon.js`,
  output: {
    file: `dist/translate_addon.js`,
    format: 'iife',
  },
  plugins: [resolve()]
};

The bundle builds fine. Now installing and adding mwc-select to the imports
import '@material/mwc-select';
translate_addon.js:2288 Uncaught DOMException: Failed to execute 'define' on 'CustomElementRegistry': the name "mwc-notched-outline" has already been used with this registry

This issue often presents itself when multiple components are installed with different versions. Most likely @material/mwc-textfield and @material/mwc-select have different versions in your package.json or package-lock.json file. Since they require different versions of the notched outline, they both bundle it, causing the duplicate registry at runtime.
The solution is to ensure all @material/mwc-* dependencies are the same version. When installing, be sure to add a version number. For example:
npm i<EMAIL_ADDRESS>
To resolve this, uninstall mwc-select and re-install it with the same version as your other mwc components. Alternatively, you may update your other mwc components to the same version as the new mwc-select that you installed (which is likely the latest version).
Let us know if you have any questions!


Using Qwen2.5-Coder with LM Studio

I am trying to setup code completion with the Qwen2.5-Coder models. I have tested different model versions and different settings for "Request Strategy" but it is not working well. Either the configuration is not compatible with LM Studio or otherwise the model responds with `` or  most times. So the model tries to use format tags.
The best configuration for Qwen would be the "Naive" setting as the models are trained for this situation.
source: https://github.com/QwenLM/Qwen2.5-Coder?tab=readme-ov-file#1-basic-usage
However it is not working because LM Studio doesn't accept an empty system prompt like this:
{
"role": "system",
"content": ""
},
Maybe there could be a new option added to set a custom system prompt or to remove this empty message.
The Qwen2.5-Coder models are also trained for fill in the middle. This is the prompt format:
prompt = '<|fim_prefix|>' + prefix_code + '<|fim_suffix|>' + suffix_code + '<|fim_middle|>'
source: https://github.com/QwenLM/Qwen2.5-Coder?tab=readme-ov-file#3-file-level-code-completion-fill-in-the-middle
I did put the following in the 'FIM Template' text field but I am still getting responses like ``.
<|fim_prefix|> {prefix} <|fim_suffix|> {suffix} <|fim_middle|>
Maybe there is a conflict with the given system prompt which instructs to use other strings. The fill in the middle setting without system prompt is not working for the same reason as the "Naive" setting.

I am no expert to LLM so I honestly don't know how the prompt template actually works. My guess is when you use the API from LM Studio, it will fill your input into the built-in prompt template so the input from the FIM strategy will be embedded into another template. You can try changing the template of the model in LM Studio to see if there is any difference.
If you find that any change is needed from this project, let me know. And pull requests are always welcome.

I got it working now by using the setting "Completion API" instead of "Chat Completion API". It works because this setting does not send an empty system prompt. It would still be nice if one could set a custom system prompt instead of an empty one.
You don't have to worry about the chat template (like ChatML for Qwen). By default this is handled by the server but for completion tasks the chat template is not even required.

As mentioned in the README, it's not recommended to use the chat completions API because the LLM will tend to respond as if it's chating with you.
If you are using the FIM strategy, you are basically sending the raw prompt that contains the prompt template (for example <|fim_prefix|> is a template token). The behavior will be different between LLM though.

@intitni @c0008
#19
It seems that the stream was not properly detecting completion state in chat responses. I've changed the done condition to check for finish_reason presence instead of relying on content parsing. This fixes premature stream termination and ensures all response chunks are properly processed.

After giving the Qwen 2.5 Coder coder instruct 7B a try in LM Studio, I noticed that the default prompt template is just incorrect because they don't have a preset for Qwen. As long as you select a preset like ChatML, The response will be in the correct format (But you should always use the official template).
I tried the changes from #19 in Copilot for Xcode and it can still generate <tags> sometimes when the template is incorrect.

I noticed that the default prompt template is just incorrect because they don't have a preset for Qwen.

A correct prompt template should come with the gguf or mlx file but of course it depends on who created this file. In doubt the easiest thing to do is to download the same model from another source.


Repository 'PSGallery' is not a known repository type that is supported.

Prerequisites

[X] Write a descriptive title.
[X] Make sure you are able to repro it on the latest released version
[X] Search the existing issues.

Steps to reproduce
Reproduced on two entirely different machines.

Update-Module -Name Microsoft.PowerShell.PSResourceGet -AllowPrerelease
Set-PSResourceRepository -Name PSgallery -Trusted
Install-PSResource -Name Benchpress -Repository PSGallery -Scope CurrentUser

I even tried re-registering PSGallery:
Register-PSResourceRepository -PSGallery -Force
Set-PSResourceRepository -Name PSGallery -Trusted
Install-PSResource -Name Benchpress -Verbose -Scope CurrentUser

Expected behavior
Should install the Benchpress module in my account's scope.
Actual behavior
Fails with Install-PSResource: Repository 'PSGallery' is not a known repository type that is supported. Please file an issue for support at https://github.com/PowerShell/PSResourceGet/issues
Error details
Exception             :
    Type        : System.Management.Automation.PSInvalidOperationException
    ErrorRecord :
        Exception             :
            Type    : System.Management.Automation.ParentContainsErrorRecordException
            Message : Repository 'PSGallery' is not a known repository type that is supported. Please file an issue for support at
https://github.com/PowerShell/PSResourceGet/issues
            HResult : -2146233087
        CategoryInfo          : InvalidOperation: (:) [], ParentContainsErrorRecordException
        FullyQualifiedErrorId : InvalidOperation
    Message     : Repository 'PSGallery' is not a known repository type that is supported. Please file an issue for support at
https://github.com/PowerShell/PSResourceGet/issues
    HResult     : -2146233079
TargetObject          : Microsoft.PowerShell.PSResourceGet.Cmdlets.InstallHelper
CategoryInfo          : InvalidArgument: (Microsoft.PowerShel…dlets.InstallHelper:InstallHelper) [Install-PSResource],
PSInvalidOperationException
FullyQualifiedErrorId : RepositoryApiVersionUnknown,Microsoft.PowerShell.PSResourceGet.Cmdlets.InstallPSResource
InvocationInfo        :
    MyCommand        : Install-PSResource
    ScriptLineNumber : 1
    OffsetInLine     : 1
    HistoryId        : 9
    Line             : Install-PSResource -Name Benchpress -Repository PSGallery -Scope CurrentUser
    PositionMessage  : At line:1 char:1
                       + Install-PSResource -Name Benchpress -Repository PSGallery -Scope Curr …
                       + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    InvocationName   : Install-PSResource
    CommandOrigin    : Internal
ScriptStackTrace      : at <ScriptBlock>, <No file>: line 1
PipelineIterationInfo :

Environment data
ModuleType Version    PreRelease Name                                ExportedCommands
---------- -------    ---------- ----                                ----------------
Binary     0.5.23     beta23     Microsoft.PowerShell.PSResourceGet  {Find-PSResource, Get-InstalledPSResource, Get-PSResourceRepos…
Name                           Value
----                           -----
PSVersion                      7.3.6
PSEdition                      Core
GitCommitId                    7.3.6
OS                             Microsoft Windows 10.0.22621
Platform                       Win32NT
PSCompatibleVersions           {1.0, 2.0, 3.0, 4.0…}
PSRemotingProtocolVersion      2.3
SerializationVersion           <IP_ADDRESS>
WSManStackVersion              3.0

Visuals
No response

@variableresistor thanks for reaching out, this will be resolved in our next release.

@anamnavi I've just hit this issue with the latest version of PSResourceGet. Can I ask why the issue has been closed?

I've just tested Microsoft.PowerShell.PSResourceGet version 0.5.23 and I still have this problem, under both PowerShell 5.1 and 7.3.6. Can the issue be reopened until there is a solution? Is there any additional data I can provide (I am essentially doing the same as the original post, though)?

This was a workaround for me.

@robinmalik the fix will be present in our very next release, the solution is in our codebase and will be available as soon as we release.
For now the workaround you mentioned is the way to go. I'll reopen this if this still persists after our release.


IndexOf not working on String JArray

Expected behavior
Have IndexOf returning 1 with one of the IndexOf cases
Actual behavior
it returns -1
Steps to reproduce
JArray.Parse("['Name', 'Column2']").IndexOf(new JValue("Column2"))
//-1
JArray.Parse("['Name', 'Column2']").IndexOf("Column2")
//-1
JArray.Parse("['Name', 'Column2']").TakeWhile(x => x.ToString() != "Column2").Count()
//1

JContainer.IndexOf() searches for items using reference equality not value equality.  See JArray.Remove(JToken) does not delete on Stack Overflow for a discussion of why, as well as some workarounds.

Great answer 👍


IG Error with empty item

If you have a row with a required item, empty it, go to another row , go back to it you get
TypeError: pValue is null

@michele-pauluzzi
I assume it is after you downloaded not released v1.1.0? ;-) just asking.

Yes

fixed


[Bug]: Remove the term free from BE sign up page

Is there an existing issue for this?

[X] I have searched the existing issues

Description

In the sign up page the word free in business edition throws people off
Steps To Reproduce

Go to business edition sign up page
Observe the term free to create an account

Public Sample App
No response
Environment
Production
Issue video log
No response
Version
Business

Free word won't be available in cloud version, is this discussed? @jsartisan

Yes @kamakshibhat-appsmith anyone who comes to signup page of cloud is mostly aware it's free

Moving this to Done


PHPORM-60 Fix Query on whereDate, whereDay, whereMonth, whereYear

Fix PHPORM-60
Created from https://github.com/jenssegers/laravel-mongodb/pull/2376

So basically, current whereDate, whereDay, whereMonth and whereYear is query on different column with specific need (like whereDate you need column that has value YYYY-MM-DD etc) using basic comparison.
As we all know that isnt how whereDate works on sql, this PR will generate query using built in $dayOfMonth, $month, $year on whereDay, whereMonth, and whereYear, while whereDate basically generate range date(since mongodb doesnt have date() equivalent like on sql).

whereDate uses $lt & $gt comparison with UTCDateTime objects
whereDay uses $dayOfWeek
whereMonth uses $month
whereYear uses $year
whereTime uses $dateToString to format into H:M:S

Moved to https://github.com/jenssegers/laravel-mongodb/pull/2572


fix(react-query): QueryErrorResetBoundaryValue as class

not sure what the advantage of this PR would be, but the disadvantage is that you can't destruct classes, yet this is what the docs suggest and probably everyone is doing:
const { reset } = useQueryErrorResetBoundary()

⬆ this will fail to work because of this bindings.


Variable inlining increases bundle size in some cases

Advanced mode. Consider the following example:
for(let i = 0; i < items.length; i++){window['b']+i}
// vs
var a='length';
for(let i = 0; i < items[a]; i++){window['b']+i}

If we use variable length certain amount of times instead of accessing property directly we can benefit from second approach becase variable name can get mangled and array property cant.
I am wondering why compiler doesn't output something like
var a='length';for(var i=0;i<b[a];i++){}
when a certain amount of occurrences of variable length is met? In the above example 10 for loops with an extracted variable can be expressed in 395 chars vs 420 now. And the more occurrences of word length the more we can benefit from extracting string variables or global objects properties.
Here is sandbox with this example: https://closure-compiler.appspot.com/home#code%3D%252F%252F%2520%253D%253DClosureCompiler%253D%253D%250A%252F%252F%2520%2540output_file_name%2520default.js%250A%252F%252F%2520%2540compilation_level%2520ADVANCED_OPTIMIZATIONS%250A%252F%252F%2520%253D%253D%252FClosureCompiler%253D%253D%250A%250Avar%2520a%253D'length'%253B%250Afor(let%2520i%2520%253D%25200%253B%2520i%2520%253C%2520items%255Ba%255D%253B%2520i%252B%252B)%257Bwindow%255B'b'%255D%252Bi%257D%250Afor(let%2520i%2520%253D%25200%253B%2520i%2520%253C%2520items%255Ba%255D%253B%2520i%252B%252B)%257Bwindow%255B'b'%255D%252Bi%257D%250Afor(let%2520i%2520%253D%25200%253B%2520i%2520%253C%2520items%255Ba%255D%253B%2520i%252B%252B)%257Bwindow%255B'b'%255D%252Bi%257D%250Afor(let%2520i%2520%253D%25200%253B%2520i%2520%253C%2520items%255Ba%255D%253B%2520i%252B%252B)%257Bwindow%255B'b'%255D%252Bi%257D%250Afor(let%2520i%2520%253D%25200%253B%2520i%2520%253C%2520items%255Ba%255D%253B%2520i%252B%252B)%257Bwindow%255B'b'%255D%252Bi%257D%250Afor(let%2520i%2520%253D%25200%253B%2520i%2520%253C%2520items%255Ba%255D%253B%2520i%252B%252B)%257Bwindow%255B'b'%255D%252Bi%257D%250Afor(let%2520i%2520%253D%25200%253B%2520i%2520%253C%2520items%255Ba%255D%253B%2520i%252B%252B)%257Bwindow%255B'b'%255D%252Bi%257D%250Afor(let%2520i%2520%253D%25200%253B%2520i%2520%253C%2520items%255Ba%255D%253B%2520i%252B%252B)%257Bwindow%255B'b'%255D%252Bi%257D%250Afor(let%2520i%2520%253D%25200%253B%2520i%2520%253C%2520items%255Ba%255D%253B%2520i%252B%252B)%257Bwindow%255B'b'%255D%252Bi%257D%250Afor(let%2520i%2520%253D%25200%253B%2520i%2520%253C%2520items%255Ba%255D%253B%2520i%252B%252B)%257Bwindow%255B'b'%255D%252Bi%257D%250A
Now compiler always inlines length variable. Am I missing something?

We optimize for gzipped size, and gzip is pretty good at getting rid of recurring strings.
It's unlikely that we'd implement this optimization unless you can show real-world examples where it yields significant post-gzip gains.

@tjgq I missed the point about gzipped size, thanks!


QA

We need to perform full QA of the entire module.
During QA, please refer to README.md contents: https://github.com/creatuity/magento2-order-status-adjust/blob/main/README.md

Tests completed.
Local tests of whole module according to the documentation - TestRail.pdf

Closing this one


Fix #20797: Added a message when no result is found.

Fixes-#20797.
This pr, adds a no result found tag when a search for an item is made is in the filter which is not in the list.  It's a similar approach when we try to find a user which is not on the list

@timabbott ping

@YashRE42 could you review this one too?

Closing as this is stale enough it'll be easier to address https://github.com/zulip/zulip/issues/20797 from scratch.


Rustbox seems thread safe to me

I've been using rustbox across multiple threads and as long as I wrapped it in Arc::new(Mutex::new()) it's been fine.

@pythonesque can you comment on this? I can't remember what we talked about before surrounding this issue...thanks!

Just updating so you don't think I've forgotten this...I'm going to be testing this out in the morning. I've never tried using Rustbox over multiple threads, so it'll be interesting to see! Will come back once I've tested this out. Thanks for submitting!

What's the state of this?

It's not thread safe because it writes to a shared static buffer without synchronizing.

Sorry didn't see the update here.
Thanks for the reply @pythonesque.
It's the c termbox that's using the shared static buffer right?
If the rust library ensures thread safety then it's threadsafe right?

Sorry didn't see the update here.
Thanks for the reply @pythonesque.
It's the c termbox that's using the shared static buffer right?
If the rust library ensures thread safety then it's threadsafe right?

What's the state on this? It seems to me like this PR is an improvement for sure.

Termbox is actually (partially) thread safe. This is the primary workflow I imagine for threaded Rustbox programs (and one I'm trying to leverage myself): one thread blocks on poll/peek_event, another thread renders using print.
To flag the Rustbox type as Sync and not introduce threading issues, we would need to handle synchronization internally: calls to mutating methods like print would need to acquire a lock, where as poll/peek_event would be available at any time.

@gchp I think we can safely close this, as it's addressed by #81.

Thanks everyone for your comments and input, and apologies for the lack of movement. If you have any further issues/thoughts on this feel free to reach out.
And thanks @sebglazebrook for the original work.


Write some documentation about the build rules (followup to #3429)

The one comment I'd like you to follow up on eventually is:
"Please make a docs\MSBuildWizardry.md with all the rules and nuances here."
I feel like we're doing a lot of custom or interesting MSBuild stuff which should be documented somehow like:

Moving the properties up to the top above the pre props so we can selectively pick them out in the pre files
List out what's supposed to go in pre (properties) and post (item groups) and when exceptions are OK (when stuff like link dependencies has to be in a specific spot)
Talk about the nuance of why most things are .vcxitems for just "grab bags" except the one that the WAP project references which is just .items (because the WAP project throws a fit and it is doing a simple extension match and will ignore it as just .items).

And so on and so forth. Maybe also include a link to that log debugging tool you used and how to generate a binlog.
Originally posted by @miniksa in https://github.com/microsoft/terminal/pull/3429#issuecomment-550048345

document the GetPackagingOutputs


don't use qHash() for permanent data, use CRC32 instead

qHash() doesn't specify some algorithm, so it is not suitable for
permanent data as so as returned value may be changed depending on
Qt version (more correctly on used underlying algorithm)
CRC32 is very lightweight checksum algorithm, so it will not have
significant impact to performance (especially for such small data)
CRC32 implementation is available in Zlib, which is already used in
the project, so it costs nothing using CRC32 implementation from it

Considering the amount of problems we had with "duplicate definitions" caused by changing the hash functions, this change has got me worried, will it cause another wave of those?

CRC32 is also not a defined algorithm, you have to specify the polynom to get same results.
But what is more important: CRC is NOT a hash function. The purpose of a hash function is to generate results maximum apart for even tiny changes in input. This is a property to ensure avoiding collisions. CRC does not have this property, it is a very old algorithm to detect (single) transmission errors and to be extremely efficient to be implemented with discrete hardware gates.
I would also assume that we have a higher likelihood to get collisions now.

@Kolcha is right: we should use a stable and defined hashing function that does not change with Qt implementation
@madmaxoft concern is valid, we have to verify behavior with many combinations of old definition files in folder and version upgrade scenarios. But the automatic repair function should fix most of that now (compared to the mess in the past).

My proposal would be to use a "real" hash function. Even MD5 or SHA1 are suited for our use case. They are designed for this purpose, they are very well tested and easy available. There is no strong need to use more modern ones like SHA256 as we do not do cryptography. Something that is used inside container (hash map) implementations is sufficient.


[SCB-1376] Use the internal event to trigger SagaActor stop

Coverage increased (+0.3%) to 83.12% when pulling f514fd5816e31e4051349427dfe941d5d35af65b on coolbeevip:SCB-1376 into 694b8d701097226d898e7a342c902ff711caa3cf on apache:master.

It looks when SagaActor is in the Suspended status then it will switch stopped stated.
What if we need to keep the status information of Suspended into DB first?

SagaActor will call stopSagaData method of SagaDataExtension after stopped, we can persist here.

What if there is another event is fired which could bring the Suspended SagaActor into other status.

There are two possibilities for entering the suspended state, the first is a timeout, and the second is an abnormal event sequence.
timeout to suspended: Only when the timeout parameter is set will it enter the suspended state because of the timeout. If the timeout parameter is less than the request timeout, an exception will be thrown to the user.
abnormal event sequence: We don't need to pay attention to subsequent events


Allow sharding fine tuned misaligned models

What does this PR do?
When loading large models, weights are sharded across a mesh of TPUs,
splitting the original weights into smaller tensors, each one with the
same shape.
This is not possible, however, if the original weights shape is not
divisible across the number of TPUs, because it results in a smaller
tensor for the last TPU.
This change pads the tensor with zeros, making it splittable across the
TPUs.
I expected this to cause a change in the model, but apparently that is not the case, and the model still has the same shape and produces a correct output. I suspect this might be due to the way the weight is loaded on the mesh, and the fact that the model figures out the part it should use, but I hadn't got the change to try many "misaligned" models,
the only one I used here it works now.
Fixes #67
Before submitting

[x] Did you write any new necessary tests?

@baptistecolle I could try it but RLHFlow/ArmoRM-Llama3-8B-v0.1 is aLlamaForRewardModelWithGating model (see the config.json), and we only support AutoModelForCausalLM so far. So I think this will raise issues unrelated to the fact that this model is fine-tuned.


bugfix: 跨页全选情况下安装通道没有默认值 (closed #377)

Codecov Report

Merging #386 (326fea2) into V2.1.362-rc (a53cc55) will not change coverage.
The diff coverage is n/a.

@@             Coverage Diff              @@
##           V2.1.362-rc     #386   +/-   ##
============================================
  Coverage        62.74%   62.74%
============================================
  Files              246      246
  Lines            19966    19966
============================================
  Hits             12528    12528
  Misses            7438     7438

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update a53cc55...326fea2. Read the comment docs.


fix: upload unique file when POSTing to /files endpoint

Make sure files with the same name do not overwrite each other
Update Swagger API docs
Remove unused GET /files endpoint
Remove unused fast-glob dependency

Each file we POST to the file endpoint will now have a unique name. The uniqueness is determined by the nano id library, and a timestamp.

This works as expected. But I noticed that when I delete a mission model, the jar for that mission model remains in the files directory.


Use a different base distro for AWS AMIs

Description
Change the default base linux distribution for AWS AMIs to a modern base image of Ubuntu or Amazon Linux. This would allow for Amazon's EC2 Instance Connect out of the box and allow for easy SSH directly from the AWS cloud console without any additional config. As far as I can tell, it doesn't seem like Debian is strictly necessary and that just dropping the existing config into a different distribution should just work out of the box.
Basic example
The docs could be updated to have users log in via the EC2 instance connect console and manual creation of SSH keys in AWS would be unnecessary, as the auto-generated keys would be sufficient.

If we could make any type of improvements by doing that, we definitely should do it! Thanks for the suggestion, PR's are welcome!


Add action, reward and obs wrappers

Summary
This PR adds various env wrappers:

ClipAction
NormalizeObservationWrapper: inspired by the NormalizeObservation, applies normalization to Dict spaces
NormalizeReward
Observation clip: clip the observations in a specified range (only for vector obs)

Type of Change
Please select the one relevant option below:

Bug fix (non-breaking change that solves an issue)
New feature (non-breaking change that adds functionality)
Breaking change (fix or feature that would cause existing functionality to not work as expected)
Documentation update
Other (please describe):

Checklist
Please confirm that the following tasks have been completed:

[x] I have tested my changes locally and they work as expected. (Please describe the tests you performed.)
[x] I have added unit tests for my changes, or updated existing tests if necessary.
[x] I have updated the documentation, if applicable.
[x] I have installed pre-commit and run locally for my code changes.

Screenshots or Visuals (Optional)
If applicable, please provide screenshots, diagrams, graphs, or videos of the changes, features or the error.
Additional Information (Optional)
Please provide any additional information that may be useful for the reviewer, such as:

Any potential risks or challenges associated with the changes.
Any instructions for testing or running the code.
Any other relevant information.

Thank you for your contribution! Once you have filled out this template, please ensure that you have assigned the appropriate reviewers and that all tests have passed.

@michele-milesi One problem is the obs normalization statistics: if one wants to test an algo trained with normalized obs then (s)he needs to also apply the same statistics to the test env I suppose. A simple solution would be to pass the same env used for training to the test function, but this does not solve the offline test. To solve that we should maybe save also the RunningMeanStd. What do you think?

Another issue: the obs and rewards normalization is done per-env since the wrappers are created inside the make_env method, then called in the agent code by the SyncVectorEnv or AsyncVectorEnv.  Do we want to maintain the normalization independent per env or do we want to apply the normalization on the overall vector-env?
For reference

I was thinking of creating custom normalizers with a standard format (that works with numpy arrays), e.g., a class that must define 3 methods:

__call__() or normalize() for applying the normalization.
state_dict() to save the state of the normalizer.
load_state_dict() is used to load the state of the normalizer (as for torch modules).

I propose to normalize the observations returned by the env.step() function, in this way, we do not have a normalizer for each environment, but one global normalizer.
@belerico what do you think?


Town with Parking lot

I am working with Carla version 0.8.4. Is there any town contains parking lot?

Hi, @MariamEssam
In that version, I think there are only 2 maps Town01 and Town02. On Town02 there is a space that simulates parking but in fact, But it's just a visualization. Those maps haven't parking lots.

That's say I have to upgrade so starting from which version I can find it and in which town?


Json Dump

Can you please help me creating a json dump for interop for a particular session . Having a problem creating the json dump.

https://docs.djangoproject.com/en/1.9/ref/django-admin/#dumpdata


Define entities on README mermaid figure

Current figure:
flowchart LR
    remote['archived data'] --download--> lvl0['Level 0 data']
    remote --'create'--> meta['data annotations']
    lvl0 --pivot--> lvl1['Level 1 data']
    meta --join--> lvl1
    lvl1 --curate--> lvl2['Level 2 data']
    lvl1a[['Other level 1 data']] --curate--> lvl2

Example table

Entity
Definition
notes

archived data
TBD
TBD

level 0 data
primary?
TBD

level 1 data
corrected?
TBD

level 2 data
model output?
TBD

other level 1 data
TBD
TBD

data annotations
what is being annotated?
TBD

From our meeting earlier this week:

level0 is long read
level 1 is subset of original file (this used to link in)


Bump Cosmos SDK to v0.46.3

Description

closes: #XXXX

Before we can merge this PR, please make sure that all the following items have been
checked off. If any of the checklist items are not applicable, please leave them but
write a little note why.

[ ] Targeted PR against correct branch (see CONTRIBUTING.md)
[ ] Linked to Github issue with discussion and accepted design OR link to spec that describes this work.
[ ] Code follows the module structure standards.
[ ] Wrote unit and integration tests
[ ] Updated relevant documentation (docs/) or specification (x/<module>/spec/)
[ ] Added relevant godoc comments.
[ ] Added a relevant changelog entry to the Unreleased section in CHANGELOG.md
[ ] Re-reviewed Files changed in the Github PR explorer
[ ] Review Codecov Report in the comment section below once CI passes

Thanks, @faddat. Can you also please add a changelog entry?

@crodriguezvega, this is not ready to be merged yet. I think we have to address this PR first

I can get a change log entry on here in a few hours

Codecov Report

Merging #2566 (e4f911c) into main (6927904) will decrease coverage by 0.01%.
The diff coverage is 100.00%.

:exclamation: Current head e4f911c differs from pull request most recent head c80ae83. Consider uploading reports for the commit c80ae83 to get more accurate results

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2566      +/-   ##
==========================================
- Coverage   78.74%   78.72%   -0.02%
==========================================
  Files         178      178
  Lines       12298    12299       +1
==========================================
- Hits         9684     9683       -1
- Misses       2190     2192       +2
  Partials      424      424

Impacted Files
Coverage Δ

...7-interchain-accounts/controller/keeper/account.go
85.00% <100.00%> (ø)

...27-interchain-accounts/controller/keeper/keeper.go
92.59% <100.00%> (+0.05%)
:arrow_up:

...les/apps/27-interchain-accounts/host/ibc_module.go
90.00% <0.00%> (-5.00%)
:arrow_down:

@crodriguezvega, this is not ready to be merged yet. I think we have to address this PR first

Should we make it a draft PR then?

I think we should take out the changes of #2452 from this PR. Those changes relay on an API breaking change of the SendPacket API which will be released in v6.0.0. But we would also like to release the bump of the SDK to v0.46.3 in v5.0.x and v5.1.x, so in order to be able to backport this PR to those release branches we cannot bring the API breaking change.

ok.

Will do v5 manually.


custom css class for single panel instance

Basically it's the same issue like this one https://github.com/surveyjs/surveyjs/issues/396 but for panels.
Also, I'm not sure why, when changing options.cssClasses in onUpdatePanelCssClasses, it has impact on all the panel instances in the survey. If that is the case, then what is the purpose of calling onUpdatePanelCssClasses on each panel. And I actually have noticed it's called multiple times even on the same panel.
Thanks,
Daniel

This event is fired in the getter of the cssClasses property:
  public get cssClasses(): any {
    var classes = { error: {} };
    this.copyCssClasses(classes, this.css);
    this.copyCssClasses(classes.error, this.css.error);
    if (this.survey) {
      this.survey.updatePanelCssClasses(this, classes);
    }
    return classes;
  }

As you can see, each time a new copy of CSS classes is created and customizations are appplied for the each call. That's why this event fires many times, probably too many.
Two arguments are being passed as otions of this event:
   {
      panel: panel,
      cssClasses: cssClasses
    }

so you can patch css classes for the cretain panel.

I created a Plunker example:
https://plnkr.co/edit/Ko9Trw?p=preview
Maybe I'm doing something wrong, but in this example I want only "panel1" to have a red border.
As you can see changing cssClasses will apply the custom style to both panels.

I see the issue now. Probably it's a bug. I'll take a look.

We've fixed the issue. Fix will be available in the nearest update, most likely tomorrow.


Feature/cable validation

Refactor trace convergence validation tests, adding Rallpack1 test.

New test cell: make_cell_simple_cable(). Emulates Rallpack1 model electrical behaviour, while working around current inability to set membrane conductance.
Re-organize validation data generation: moves validation reference models to validation/ref, and adds appropriate amounts of CMake cruft to generate the data as required.
Tidy up BUILD_VALIDATION_DATA and VALIDATION_DATA_DIR testing and setting in CMake. (These are now cache variables.)
Bug fixes in numeric models: voltage scaling in hh_soma.jl (since rolled into a Julia module HHChannels.jl; improper scaling by length in PassiveCable.jl (not convinced it is correct now, but certainly it is less wrong.)
Use numeric solution for reference data for validate_soma.cpp
Bug fix in validation trace comparison, when neither trace has any local maxima.
Consolidate common trace convergence testing code in validate_ball_and_stick.cpp (this file should probably be renamed to something better representing its contents).
Allow multiple -s selection options for tsplot, acting disjunctively.

This PR doesn't have the partial frustrum compartment modelling, so ball_and_taper results still poor. Hope that merge of complex compartment code will demonstrate a closer match with NEURON. With some more maths work (for the future!) could derive taper version of analytic cable model.


Start fitting the Stan models too

Might want to suppress rstan sampling output: it's getting in the way of my nice progress bar :(

https://github.com/stan-dev/rstan/issues/665


Fullscreen & AspectRatio

Hello,
I need the YouTube video to scale/resize fullscreen depending on the browser size or device width.
Actually, I have black borders on screen resize.
Here's my pen : http://codepen.io/blancfonce/pen/obxVXm
Any tips ?
Thx

If you want the width/height ratio to always be kept on video.js, you can set the fluid option. I've updated your example here:
http://codepen.io/anon/pen/pgyMxm
This should close https://github.com/videojs/video.js/issues/2935 too :)

It seems to work for larger screen, but not for smaller (kinda the whole point). I'll look on what I can do to fix this.

Thanks for your quick response :-)
Ok for the fluid option but i need to scale the video in fullscreen without black borders.
For now i get this result
(have a look at my screen capture)

Un peu comme ça dans l'idée :

I would like to have the video in full screen like this pen: http://codepen.io/ccrch/pen/VYoYOx

Set data-setup option to true and set the div width and height as per your need.
It will show video in full size of container div.
<div class="full-vid">
    <video id="vid1" class="video-js vjs-default-skin vjs-big-play-centered"
        controls
        width="100%"
        height="100%"
        data-setup='{
            "techOrder": ["youtube"],
            "aspectRatio":"16:9", "fluid": true,
            "sources": [{ "type": "video/youtube", "src": "https://www.youtube.com/watch?v=PjGkVCAo8Fw"}]
        }'
      ></video>
</div>


Issue accessing graph API with access token acquired after successful login

Environment

Spring boot starter:

active directory spring boot starter

OS Type: MacOS

Java version:

1.8

Summary

The access token generated after successful login cannot be used to make graph api call (https://graph.microsoft.com) since the access token generated can only be used with the old AD graph API (https://graph.windows.net).  Tried to override the service endpoint to point to new graph API but the that requires to update the oauth endpoint to v2.0 endpoints but the library still fails, since the AzureADGraphClient hard coded header to point to version 1.6.
Reproduce steps

Attaching the configuration in comment that can reproduce the issue.
Expected Results

There should be way to make it work with the new graph api to take advantage of the java graph sdk.
Actual Results

Fails with we update the service endpoint to use new graph apis (https://graph.microsoft.com)

`azure:
activedirectory:
tenant-id: <teanant_id>
active-directory-groups:
service:
endpoints:
global:
aadGraphApiUri: https://graph.microsoft.com/
aadMembershipRestUri: https://graph.microsoft.com/v1.0/me/memberOf
spring:
security:
oauth2:
client:
registration:
azure:
client-id: <client_id>
client-secret: <client_secret>
client-name: Azure
provider: azure-oauth-provider
scope: openid, https://graph.microsoft.com/user.read
client-authentication-method: post
authorization-grant-type: authorization_code
userNameAttribute: name
    provider:
      azure-oauth-provider.token-uri: "https://login.microsoftonline.com/<teant_id>/oauth2/v2.0/token"
      azure-oauth-provider.authorization-uri: "https://login.microsoftonline.com/<teant_id>/oauth2/v2.0/authorize"
      azure-oauth-provider.user-info-uri: "https://graph.microsoft.com/oidc/userinfo"
      azure-oauth-provider.jwk-set-uri: "https://login.microsoftonline.com/<teant_id>/discovery/v2.0/keys"
      azure-oauth-provider.user-name-attribute: "name"`

azure:
activedirectory:
tenant-id: <teanant_id>
active-directory-groups:
service:
endpoints:
global:
aadGraphApiUri: https://graph.microsoft.com/
aadMembershipRestUri: https://graph.microsoft.com/v1.0/me/memberOf
spring:
security:
oauth2:
client:
registration:
azure:
client-id: <client_id>
client-secret: <client_secret>
client-name: Azure
provider: azure-oauth-provider
scope: openid, https://graph.microsoft.com/user.read
client-authentication-method: post
authorization-grant-type: authorization_code
userNameAttribute: name
    provider:
      azure-oauth-provider.token-uri: "https://login.microsoftonline.com/<teant_id>/oauth2/v2.0/token"
      azure-oauth-provider.authorization-uri: "https://login.microsoftonline.com/<teant_id>/oauth2/v2.0/authorize"
      azure-oauth-provider.user-info-uri: "https://graph.microsoft.com/oidc/userinfo"
      azure-oauth-provider.jwk-set-uri: "https://login.microsoftonline.com/<teant_id>/discovery/v2.0/keys"
      azure-oauth-provider.user-name-attribute: "name"

azure:
  activedirectory:
    tenant-id: <teanant_id>
    active-directory-groups:  <group>
  service:
    endpoints:
      global:
        aadGraphApiUri: https://graph.microsoft.com/
        aadMembershipRestUri: https://graph.microsoft.com/v1.0/me/memberOf
spring:
  security:
    oauth2:
      client:
        registration:
          azure:
            client-id: <client_id>
            client-secret: <client_secret>
            client-name: Azure
            provider: azure-oauth-provider
            scope: openid, https://graph.microsoft.com/user.read
            client-authentication-method: post
            authorization-grant-type: authorization_code
            userNameAttribute: name

        provider:
          azure-oauth-provider.token-uri: "https://login.microsoftonline.com/<teant_id>/oauth2/v2.0/token"
          azure-oauth-provider.authorization-uri: "https://login.microsoftonline.com/<teant_id>/oauth2/v2.0/authorize"
          azure-oauth-provider.user-info-uri: "https://graph.microsoft.com/oidc/userinfo"
          azure-oauth-provider.jwk-set-uri: "https://login.microsoftonline.com/<teant_id>/discovery/v2.0/keys"
          azure-oauth-provider.user-name-attribute: "name"

ext {
  set('azureVersion', '2.1.2')
}

dependencies {

  //Azure Dependency
  implementation 'com.microsoft.azure:azure-active-directory-spring-boot-starter'
  implementation 'com.microsoft.azure:azure-spring-boot-starter'
  implementation 'org.springframework.security:spring-security-oauth2-client'
  implementation 'org.springframework.security:spring-security-oauth2-jose'
  implementation 'com.microsoft.azure:applicationinsights-spring-boot-starter:1.1.2'
  implementation 'com.microsoft.azure:applicationinsights-logging-logback:2.3.1'
  implementation 'com.nimbusds:oauth2-oidc-sdk:5.64.4'
}

Following is the version information.

Also this document recommends using microsoft graphs over AD graphs https://blogs.msdn.microsoft.com/aadgraphteam/2016/07/08/microsoft-graph-or-azure-ad-graph/

@jaimodha
Thanks for issue this, currently only the AD graphs is supported. We can add this as our feature list or you can contribute code if urgent.

@Incarnation-p-lee is there a published date/time for this to be released ? and if its far in the roadmap, how do we change in the code to allow such change ?

@alaahusseiny you can take a look at my forked repo to see code changes needed to change it to the microsoft graph api, 41a4ec88cd2d3dc31af2e19319dab4aeda103663
commit 1 is for code changes needed, and commit 2 is for changes to test it out locally.
if wanting to test it out, in the second commit check out the test-local-ReadMe.txt file.

I want to make a get request to the following endpoint after successfully login
https://graph.windows.net/myorganization/users/{userID}/manager.
But for this endpoint I need the graphapitoken. How can I extrect this from the user?
The normal access token for the ad, which i can get per
Authentication authentication = SecurityContextHolder.getContext().getAuthentication(); DefaultOidcUser principal = (DefaultOidcUser) authentication.getPrincipal(); OidcIdToken idToken = principal.getIdToken(); String accessToken = idToken.getTokenValue();
does not fit.
In the Class com.microsoft.azure.spring.autoconfigure.aad.AADOAuth2UserService is the  graphApiToken initialized. How can I get this token in a controller?

@wandrille-hubert how can I include your commit in my project, where I map the azure-spring-boot as maven dependency?

@einue  I have made more recent commits to my forked repo where the graphApiToken can be acquired:

If utilizing the oidcUserService flow, then how you can get the graph api token is as follows:

import com.microsoft.azure.spring.autoconfigure.aad.GraphOidcUser;
GraphOidcUser graphUser = (GraphOidcUser)SecurityContextHolder.getContext().getAuthentication().getPrincipal();
String token =  graphUser.getGraphApiToken();
Note: since GraphOidcUser implements OidcUser, you are still able to do:
OidcUser userTest = (OidcUser)SecurityContextHolder.getContext().getAuthentication().getPrincipal();
in case that is still needed.
Note2: GraphOidcUser is a custom class that I had to add in, in order to be able to add the token property along with a function to get the token as seen above.

If utilizing the AADAuthenticationFilter flow, then the token has been set as part of the details.
This can be gotten as follows:
String token = (String)SecurityContextHolder.getContext().getAuthentication().getDetails();

@wandrille-hubert I look forward to find your code in the master-Repo.  The PR for this stuff is still open, isn't it https://github.com/microsoft/azure-spring-boot/pull/680? I like using maven dependencies and I don't know how to integrate your code repo instead of using the maven dependency. So I'm looking forward...
Thank you very much!

The PR #680 of updating to new Graph API's been merged. Close this issue.


⚠ Samsung has degraded performance

In 95d2ce1, Samsung (https://samsung.com) experienced degraded performance:

HTTP code: 200
Response time: 2335 ms

Resolved: Samsung performance has improved in 28494f4.


Docker install fails on default packer script

the packer script fails as the way to install docker in amazon linux 2 has changed.
if you the script as it is now , you get the following error, i have put a pr #2 to fix this, also introduce nfs utils, if you want I can remove that PR and create a new one only with the change to the installer.
    amazon-ebs: Complete!
    amazon-ebs: Loaded plugins: priorities, update-motd
    amazon-ebs: No package docker available.
    amazon-ebs: Error: Nothing to do
==> amazon-ebs: Terminating the source AWS instance...
==> amazon-ebs: Cleaning up any extra volumes...
==> amazon-ebs: No volumes to clean up, skipping
==> amazon-ebs: Deleting temporary security group...
==> amazon-ebs: Deleting temporary keypair...
Build 'amazon-ebs' errored: Script exited with non-zero exit status: 1

==> Some builds didn't complete successfully and had errors:
--> amazon-ebs: Script exited with non-zero exit status: 1

==> Builds finished but no artifacts were created.
make: *** [ami] Error 1

This is related to https://github.com/awslabs/amazon-eks-ami/issues/7. In the LTS AMI, the Docker extra is enabled by default. In the LTS Candidate AMI, a version of Docker was available in the core repositories.

This was written just before the official release of AL2, so we'll get this fixed

@micahhausler , the pull request #2 address this issue.


EMEA Masters matches are missing

European Masters League is now called EMEA Masters.
There are currently no matches scheduled in the produced ical file even though EMEA Masters is currently ongoing.

Thank you for reporting this issue. Unfortunately this happens somewhat regularly. Match information on PandaScore is only updated shortly before the events sometimes. And since I currently update the icals only once daily, there might be periods where they are empty.
I plan to improve this in the near future, so I will keep this issue open for now.


Performance improvements with many predicates

Reporting on the google group - imposters with several predicates make the imposter unusable for performance testing

I responded to a thread regarding load testing with mountebank when a service has a downstream dependency that requires complex predicates to emulate the services provided by the dependency.  My impression was that complex predicates can severely slow down response times from Mountebank.  Someone suggested using javascript injection to speed up the handling of the request to response match.  I don't think this is a solution (unless I'm missing something) since I would need to code how to match to the request body in Javascript in the same manner predicates have to match.
Am I off base or missing something?
Here are the CPU loads with 3 instances of mountebank running behind an nginx load balancer on a 4 CPU box with 16 GB RAM.  As you can see, node/Mountebank is eating the CPU while the java service is idling comparatively.
Any suggestions???
Tasks: 133 total,   4 running, 129 sleeping,   0 stopped,   0 zombie
%Cpu(s): 84.5 us,  0.8 sy,  0.0 ni, 14.7 id,  0.0 wa,  0.0 hi,  0.1 si,  0.0 st
KiB Mem : 15791924 total, 10643204 free,  3123688 used,  2025032 buff/cache
KiB Swap:        0 total,        0 free,        0 used. 12207476 avail Mem
PID USER      PR  NI    VIRT    RES    SHR S  %CPU %MEM     TIME+ COMMAND
12105 root      20   0<PHONE_NUMBER>28  11052 R 101.7  0.6   4:49.97 node
12133 root      20   0  719176  98488  11056 R 101.3  0.6   4:50.00 node
12072 root      20   0  719252  97924  11056 R 101.0  0.6   4:50.04 node
12581 root      20   0 6885316   1.5g  19024 S  34.6  9.9   3:24.88 java
1047 root      20   0  832280  93536  25232 S   0.7  0.6   0:23.57 dockerd

They're using xpath to do matching.
"predicates": [
{  "and": [
{
"equals": {
"method": "POST",
"path": "/"
}
},
{
"exists": { "body": true },
"xpath": {
"selector": "//*[local-name() = 'SomeXmlElement']"
}
},
{
"equals": { "body": "160418" },
"xpath": {
"selector": "//a:xmlElement1/a:xmlElement2/a:xmlElement3/a:date",
"ns": {
"a": "http://some-name-space"
}
}
}
]
}
]
I took a simple 2 predicate imposter that I was running at 18 req/sec with a 28ms response time using 36 threads in jmeter and added about 30-40 additional predicates (that I knew would never match).  After adding the no-match predicates, the request rate couldn't get over about 8/sec and the response times went to 4+ seconds.  This was done without docker.
AcesHigh | AcesHigh | Thu, Oct 4, 9:28 AM (2 days ago) |   |
-- | -- | -- | -- | --
AcesHigh
to mountebank-discuss | to mountebank-discuss
to mountebank-discuss

We are also running into performance issues using imposters with tons of stubs (500+) and each stub having 3-4 simple predicates (mostly all equals or deepEquals). We are seeing timings around 300ms at 1 TPS on a 16 CPU box with 120GB of ram. The real issue is when the TPS increases (e.g 20 QPS) and requests are getting queued causing them to take upwards of 6+ seconds.

Thanks for the details @colinschoen. I'm pushing to get the current release out, but will include this in the next one.

Thanks for the response!

No problem - the response is easy. The fix... less so :) I think it'll
require some additional infrastructure for storage and querying.
On Mon, Jun 10, 2019 at 12:46 PM Colin Schoen<EMAIL_ADDRESS>wrote:

Thanks for the response!
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/bbyars/mountebank/issues/382?email_source=notifications&email_token=AAARFP53Y4LPC5MUSQWAOATPZ2HPDA5CNFSM4FYEGJ52YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGODXKTIYA#issuecomment-500511840,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AAARFP6EHR5OZW2AJULTIDTPZ2HPDANCNFSM4FYEGJ5Q
.

Left initial solution idea on #279. Feedback welcome.

Awesome. I'll take a look!


pr_curve gives error regardless of label type

Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template
System information

I'm Trying to use pr_curve with tensorboard, and in one case I get an error telling me by labels need to be of type bool.  If I change it to a bool, I get an error from deep within the tf code that the type need to be float.  Everything else is working great.
Linux Ubuntu 16.04
Source compiled for CUDA 10 and CDNN 7.4.2
TensorFlow version: 1.13.0-dev20190218
Python version: 3.6
Bazel version (if compiling from source): 0.18.1
GCC/Compiler version (if compiling from source): 7.3.0
CUDA/cuDNN version: 10/7.4.2
GPU model and memory: 1070ti with 4GB

I'm trying to use pr_curve with tensorboard, and when I issue the pr_curve command I get an error telling me the labels (parameter 3) are supposed to by of type bool.  If I set it to a bool, the command runs, but later from deep within tf code errors with parameter is to be of type float, which is was originally.
If I remove the pr_curve command, I no longer get any errors.
Code to reproduce the issue  Problem is line 109 or 110.
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pdb
import numpy as np
import math, time
import tensorflow as tf
from tensorboard import summary as summ_lib
import flags as f
import input, lenet5, evaluate

tf.logging.set_verbosity(tf.logging.INFO)
similar results every run)
tf.set_random_seed(1)
np.random.seed(10)

summaries = {'train': [], 'validate': [], 'test': []}

def main(unused_argv):
     train_dataset, validate_dataset, test_dataset =
input.input(shuffle_files=False)
     info = tf.constant(
            ["Batch size = %s" % f.FLAGS.batch_size,
             "Epochs = %s" % f.FLAGS.num_epochs,
             "Learning rate = %s" % f.FLAGS.learning_rate,
             "Batch normalization = No",
             "Window size = %s" % f.FLAGS.window_size,
             "Shuffle Files = No",
             "CNN model = %s" % f.FLAGS.cnn_model,
             "Shuffle Samples = YES"]
      )
      with tf.name_scope('input'):
            x = tf.placeholder(tf.float32, [None, input.SAMPLE_DEPTH,
input.SAMPLE_HEIGHT, input.SAMPLE_WIDTH])
            y_ = tf.placeholder(tf.float32, [None, 2])
            dropout_rate = tf.placeholder(tf.float32)
            is_training = tf.placeholder(tf.bool)

      with tf.name_scope('logits'):
            if f.FLAGS.cnn_model == "lenet5":
                  logits = lenet5.model_fn(sample_input = x,
is_training=is_training, summaries=summaries)

      with tf.name_scope('loss'):
            cross_entropy = tf.nn.softmax_cross_entropy_with_logits_v2(labels=y_, logits=logits)
            mean_cross_entropy_loss = tf.reduce_mean(cross_entropy)

            loss_summ = tf.summary.scalar('Mean_cross_entropy_loss', mean_cross_entropy_loss)
            summaries['train'].append(loss_summ)

      with tf.name_scope('adam_optimizer'):
            optimizer = tf.train.AdamOptimizer(f.FLAGS.learning_rate).minimize(mean_cross_entropy_loss)

      with tf.name_scope('accuracy'):
            preds = tf.argmax(logits, 1)
            correct_preds = tf.argmax(y_, 1)
            equal = tf.equal(preds, correct_preds)
            training_accuracy_op = tf.reduce_mean(tf.cast(equal, tf.float32))

summaries['train'].append(tf.summary.scalar('Training_Accuracy', training_accuracy_op))

      with tf.name_scope('Evaluation_Metrics'):
            tp_op = evaluate.tp(logits=logits, labels=y_)
            fp_op = evaluate.fp(logits=logits, labels=y_)
            tn_op = evaluate.tn(logits=logits, labels=y_)
            fn_op = evaluate.fn(logits=logits, labels=y_)

            tp_sum = tf.placeholder(tf.float32)
            tn_sum = tf.placeholder(tf.float32)
            fp_sum = tf.placeholder(tf.float32)
            fn_sum = tf.placeholder(tf.float32)

            precision_op = evaluate.precision(tp=tp_sum, fp=fp_sum, tn=tn_sum, fn=fn_sum)
            accuracy_op = evaluate.accuracy(tp=tp_sum, fp=fp_sum, tn=tn_sum, fn=fn_sum)
            recall_op = evaluate.recall(tp=tp_sum, fp=fp_sum, tn=tn_sum, fn=fn_sum)
            fscore_op = evaluate.fscore(tp=tp_sum, fp=fp_sum, tn=tn_sum, fn=fn_sum)

            precision_summ = tf.summary.scalar('Precision', precision_op)
            accuracy_summ = tf.summary.scalar('Accuracy', accuracy_op)
            recall_summ = tf.summary.scalar('Recall', recall_op)
            fscore_summ = tf.summary.scalar('Fscore', fscore_op)

            summaries['validate'].append(accuracy_summ)
            summaries['validate'].append(precision_summ)
            summaries['validate'].append(recall_summ)
            summaries['validate'].append(fscore_summ)

            summaries['test'].append(accuracy_summ)
            summaries['test'].append(precision_summ)
            summaries['test'].append(recall_summ)
            summaries['test'].append(fscore_summ)

      print ("Saving graph to %s" % f.FLAGS.log_dir)
      mAP_summ = summ_lib.pr_curve(name='mAP',predictions=logits,labels=y_,num_thresholds=11)
      # OR THIS ONE mAP_summ = summ_lib.pr_curve(name='mAP',predictions=logits,labels=tf.cast(y_,tf.bool),num_thresholds=11)

      train_writer = tf.summary.FileWriter(f.FLAGS.log_dir + "/train")
      validate_writer = tf.summary.FileWriter(f.FLAGS.log_dir + "/validate")
      test_writer = tf.summary.FileWriter(f.FLAGS.log_dir + "/test")
      train_writer.add_graph(tf.get_default_graph())

      train_summaries = tf.summary.merge(summaries['train'])
      validate_summaries = tf.summary.merge(summaries['validate'])
      test_summaries = tf.summary.merge(summaries['test'])

      with tf.Session() as sess:
            train_writer.add_summary(sess.run(tf.summary.text("Information", info)))
            train_iter = train_dataset.make_initializable_iterator()
            train_next_elem = train_iter.get_next()
            sess.run(tf.global_variables_initializer())
            global_step = 0
            display_freq = 10
            validate_freq = 50
            test_freq = 50
            for epoch in range(1, f.FLAGS.num_epochs+1):
                  sess.run(train_iter.initializer)
                  step_time = 0.0
                  fetch_time = 0.0
                  while True:
                        try:
                              a = time.time()
                              global_step += 1
                              #print(make_bread())
                              sample, label = sess.run(train_next_elem)
                              fetch_time += time.time() - a
                              a = time.time()
                              _, summ = sess.run([optimizer, train_summaries], feed_dict={x: sample, y_: label, dropout_rate: 0.5, is_training: True})
                              train_writer.add_summary(summ, global_step)
                              step_time += time.time() - a
                        except tf.errors.OutOfRangeError:
                              break

                        if global_step % display_freq == 0:
                              batch_loss, batch_accuracy = sess.run([mean_cross_entropy_loss, training_accuracy_op],
                                                                    feed_dict={x: sample, y_: label, dropout_rate: 1.0, is_training: False})
                              print ("Epoch {:3}\t Step {:5}:\t Loss={:.3f}, \tTraining Accuracy={:.5f} \tStep Time {:4.2f}m, Fetch Time {:4.2f}m".
                                     format(epoch, global_step, batch_loss, batch_accuracy, step_time/60, fetch_time/60))
                              step_time = 0.0
                              fetch_time = 0.0

                  #Validate and test after each epoch
                  val_it = validate_dataset.make_one_shot_iterator()
                  val_next_elem = val_it.get_next()
                  tot_tp, tot_tn, tot_fp, tot_fn = 0, 0, 0, 0
                  while True:
                        try:
                              sample, label = sess.run(val_next_elem)
                              tp, fp, tn, fn = sess.run([tp_op, fp_op, tn_op, fn_op],
                                                        feed_dict={x: sample, y_: label, dropout_rate: 1.0, is_training: False})
                        except tf.errors.OutOfRangeError:
                              break
                        tot_tp += tp
                        tot_fp += fp
                        tot_fn += fn
                        tot_tn += tn
                  precision, recall, accuracy, fscore, summ = sess.run([precision_op, recall_op, accuracy_op, fscore_op, validate_summaries],
                                                                       feed_dict={tp_sum: tot_tp, tn_sum: tot_tn, fp_sum: tot_fp, fn_sum: tot_fn})
                  validate_writer.add_summary(summ, global_step)
                  print ("Epoch %d, Step %d" % (epoch, global_step))
                  print ("="*10, "Validating Results", "="*10)
                  print ("TP: %g\nTN: %g\nFP: %g\nFN: %g" % (tot_tp, tot_tn, tot_fp, tot_fn))
                  print ("\tPrecision: %g\n\tRecall: %g\n\tF1_score: %g\n\tAccuracy: %g" % (precision, recall, fscore, accuracy))

                  test_it = test_dataset.make_one_shot_iterator()
                  test_next_elem = test_it.get_next()
                  tot_tp, tot_tn, tot_fp, tot_tn = 0, 0, 0, 0
                  while True:
                        try:
                              sample, label = sess.run(test_next_elem)
                              tp, fp, tn, fn, pred, lab = sess.run([tp_op, fp_op, tn_op, fn_op, logits, y_],
                                                        feed_dict={x: sample, y_: label, dropout_rate: 1.0, is_training: False})
                        except tf.errors.OutOfRangeError:
                              break
                        tot_tp += tp
                        tot_fp += fp
                        tot_fn += fn
                        tot_tn += tn
                  precision, recall, accuracy, fscore, summ = sess.run([precision_op, recall_op, accuracy_op, fscore_op, test_summaries],
                                                                       feed_dict={tp_sum: tot_tp, tn_sum: tot_tn, fp_sum: tot_fp, fn_sum: tot_fn})

                  test_writer.add_summary(summ, global_step)

                  print ("="*10, "Testing Results", "="*10)
                  print ("TP: %g\nTN: %g\nFP: %g\nFN: %g" % (tot_tp, tot_tn, tot_fp, tot_fn))
                  print ("\tPrecision: %g\n\tRecall: %g\n\tF1_score: %g\n\tAccuracy: %g" % (precision, recall, fscore, accuracy))
                  print ("="*10, "===============", "="*10)
            map_writer = tf.summary.FileWriter(f.FLAGS.log_dir + "/mAP")
            map_writer.add_summary(sess.run(mAP_summ),global_step=0)
            map_writer.close()

if __name__ == "__main__":
      tf.app.run()

Other info / logs  Here are the errors depending on the pr_curve command used around line 110.
10:06:00:26.03.2019:/media/randy/Data1/Python/Machine_Learning/3d_cnn ./run2.sh
Number of training files:  68
Number of validation files:  23
Number of testing files:  23
W0326 22:06:28.115116<PHONE_NUMBER>48896 deprecation.py:506] From /home/randy/.local/lib/python3.6/site-packages/tensorflow/python/training/slot_creator.py:187: calling Zeros.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
Saving graph to /media/randy/Data1/log/proc_order/ABS-Correlated
Traceback (most recent call last):
  File "cnn_model.py", line 208, in <module>
    tf.app.run()
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 40, in run
    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
  File "/home/randy/.local/lib/python3.6/site-packages/absl/app.py", line 300, in run
    _run_main(main, args)
  File "/home/randy/.local/lib/python3.6/site-packages/absl/app.py", line 251, in _run_main
    sys.exit(main(argv))
  File "cnn_model.py", line 108, in main
    mAP_summ = summ_lib.pr_curve(name='mAP',predictions=logits,labels=y_,num_thresholds=11)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorboard/plugins/pr_curve/summary.py", line 94, in op
    tf.compat.v1.assert_type(labels, tf.bool)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/ops/check_ops.py", line 1502, in assert_type
    tf_type))
TypeError:   input/Placeholder_1:0 must be of type <dtype: 'bool'>

10:06:28:26.03.2019:/media/randy/Data1/Python/Machine_Learning/3d_cnn ./run2.sh
Number of training files:  68
Number of validation files:  23
Number of testing files:  23
W0326 22:07:04.819849<PHONE_NUMBER>22528 deprecation.py:506] From /home/randy/.local/lib/python3.6/site-packages/tensorflow/python/training/slot_creator.py:187: calling Zeros.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
Saving graph to /media/randy/Data1/log/proc_order/ABS-Correlated
2019-03-26 22:07:04.963555: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-03-26 22:07:04.966910: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened CUDA library libcuda.so.1
2019-03-26 22:07:05.054544: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1010] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-03-26 22:07:05.054971: I tensorflow/compiler/xla/service/service.cc:162] XLA service 0x4dd1b80 executing computations on platform CUDA. Devices:
2019-03-26 22:07:05.054985: I tensorflow/compiler/xla/service/service.cc:169]   StreamExecutor device (0): GeForce GTX 1070 Ti, Compute Capability 6.1
2019-03-26 22:07:05.072833: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:<PHONE_NUMBER> Hz
2019-03-26 22:07:05.073556: I tensorflow/compiler/xla/service/service.cc:162] XLA service 0x4d5bc70 executing computations on platform Host. Devices:
2019-03-26 22:07:05.073585: I tensorflow/compiler/xla/service/service.cc:169]   StreamExecutor device (0): <undefined>, <undefined>
2019-03-26 22:07:05.073788: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1464] Found device 0 with properties:
name: GeForce GTX 1070 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.683
pciBusID: 0000:01:00.0
totalMemory: 7.93GiB freeMemory: 7.53GiB
2019-03-26 22:07:05.073797: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1543] Adding visible gpu devices: 0
2019-03-26 22:07:05.073837: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened CUDA library libcudart.so.10.0
2019-03-26 22:07:05.074339: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1015] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-03-26 22:07:05.074346: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1021]      0
2019-03-26 22:07:05.074349: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1034] 0:   N
2019-03-26 22:07:05.074521: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1146] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7324 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1070 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
W0326 22:07:05.090326<PHONE_NUMBER>22528 deprecation.py:323] From cnn_model.py:122: DatasetV1.make_initializable_iterator (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `for ... in dataset:` to iterate over a dataset. If using `tf.estimator`, return the `Dataset` object directly from your input function. As a last resort, you can use `tf.compat.v1.data.make_initializable_iterator(dataset)`.
2019-03-26 22:07:06.920871: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened CUDA library libcublas.so.10.0
2019-03-26 22:07:07.021886: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened CUDA library libcudnn.so.7
Epoch   1        Step    10:     Loss=0.723,    Training Accuracy=0.75977       Step Time 0.57m, Fetch Time 0.01m
Epoch   1        Step    20:     Loss=0.528,    Training Accuracy=0.80859       Step Time 0.55m, Fetch Time 0.00m
Epoch   1        Step    30:     Loss=0.399,    Training Accuracy=0.86523       Step Time 0.55m, Fetch Time 0.00m
W0326 22:09:01.058223<PHONE_NUMBER>22528 deprecation.py:323] From cnn_model.py:157: DatasetV1.make_one_shot_iterator (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `for ... in dataset:` to iterate over a dataset. If using `tf.estimator`, return the `Dataset` object directly from your input function. As a last resort, you can use `tf.compat.v1.data.make_one_shot_iterator(dataset)`.
Epoch 1, Step 35
========== Validating Results ==========
TP: 980
TN: 3093
FP: 302
FN: 1257
        Precision: 0.764431
        Recall: 0.438087
        F1_score: 0.556976
        Accuracy: 0.723189
========== Testing Results ==========
TP: 1124
TN: 3500
FP: 272
FN: 2505
        Precision: 0.805158
        Recall: 0.309727
        F1_score: 0.447363
        Accuracy: 0.62478
========== =============== ==========
Traceback (most recent call last):
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1335, in _do_call
    return fn(*args)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1320, in _run_fn
    options, feed_dict, fetch_list, target_list, run_metadata)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1408, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'input/Placeholder_1' with dtype float and shape [?,2]
         [[{{node input/Placeholder_1}}]]
         [[mAP/stack/_199]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "cnn_model.py", line 208, in <module>
    tf.app.run()
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 40, in run
    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
  File "/home/randy/.local/lib/python3.6/site-packages/absl/app.py", line 300, in run
    _run_main(main, args)
  File "/home/randy/.local/lib/python3.6/site-packages/absl/app.py", line 251, in _run_main
    sys.exit(main(argv))
  File "cnn_model.py", line 204, in main
    map_writer.add_summary(sess.run(mAP_summ),global_step=0)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 930, in run
    run_metadata_ptr)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1153, in _run
    feed_dict_tensor, options, run_metadata)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1329, in _do_run
    run_metadata)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1349, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'input/Placeholder_1' with dtype float and shape [?,2]
         [[node input/Placeholder_1 (defined at cnn_model.py:50) ]]
         [[mAP/stack/_199]]

Original stack trace for 'input/Placeholder_1':
  File "cnn_model.py", line 208, in <module>
    tf.app.run()
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 40, in run
    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
  File "/home/randy/.local/lib/python3.6/site-packages/absl/app.py", line 300, in run
    _run_main(main, args)
  File "/home/randy/.local/lib/python3.6/site-packages/absl/app.py", line 251, in _run_main
    sys.exit(main(argv))
  File "cnn_model.py", line 50, in main
    y_ = tf.placeholder(tf.float32, [None, 2])
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 2084, in placeholder
    return gen_array_ops.placeholder(dtype=dtype, shape=shape, name=name)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 6098, in placeholder
    "Placeholder", dtype=dtype, shape=shape, name=name)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 800, in _apply_op_helper
    op_def=op_def)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3473, in create_op
    op_def=op_def)
  File "/home/randy/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1961, in __init__
    self._traceback = tf_stack.extract_stack()

Hi @rklepetko! Thanks for the report. I can’t reproduce the problem with
our unit tests or end-to-end demos, with any versions of TF and Python.
I can’t run your example, because it relies on external libraries that
we don’t have access to (input, lenet5, evaluate, …). But, reading
the code and the error message, it appears that the error is unrelated.
The problem is that your sess.run(mAP_summ) command near the very
bottom of the program does not feed a value for the y_ placeholder,
even though mAP_summ depends on y_.
If you’re still experiencing this problem, please provide a minimal,
self-contained example to reproduce the problem.


Expose Wizard through fec config

This exposes additional modules through fec config.
Depends on https://github.com/RedHatInsights/frontend-components/pull/1623

Lets try :)


TransactionError: Tx dropped without known replacement: - When I run set_tokenuri.py

I ran brownie run scripts/rizer_incept/set_tokenuri.py --network rinkeby and I got this error
TransactionError: Tx dropped without known replacement: 0x0a3c830623e6cd6d07783902f418cd1c3e169ebf1bcb08390f32ddf7aadae291

and when I ran it again I got this
Running 'scripts/rizer_incept/set_tokenuri.py::main'...
Working on rinkeby
The number of tokens you've deployed is: 1
Skipping 0, we already set that tokenURI!

The problem is that there is no image for the token on opensea:
https://testnets.opensea.io/assets/0x85994881438ed80948e2abacf9be29bf3d49f595/0

I correctly uploaded the json metadata and image to ipfs. See these content hashes
QmdxacdJ3VAXThKB2xbYCPBE9KWq8VfGHhdKhrFWMKGVij - metadata json file
QmNfavcLue8H9bsY5CC4v9rx4DSpwrVmEiC5ndjEsM8v1R - png image

Do you know what the problem is?

Looks like your transactions are going through fine: https://rinkeby.etherscan.io/address/0x85994881438ed80948e2abacf9be29bf3d49f595
This is a known issue, it just means brownie is unsure if the transaction went through correctly.

Even though the transaction went through it looks like the token uri and/or metadata wasn't set. See


Spring Boot release notes doesn't contain supported artifacts

Some components we deliver with Spring Boot are supported AFAIK; that mainly includes Tomcat. The RN only contains one giant table of "tested and supported" components, which contains the community Tomcat version. That implies that it's not supported. Funnily enough, the version of org.eclipse:jdt in that table is 4.4.2.redhat-1, which is a productized version -- unlike all other components in the same table, which are included in their community version (even though we actually ship a productized one).
Or, to make it shorter: the listing of Spring Boot artifacts in the release notes is a mess.

@Ladicek Thank you.
It is not just the listing, IMHO it is the entire support situation :)
The Spring Boot team requested that we use  Tested and Verifed instead of Supported when referring to Spring Boot artifacts shipped with RHOAR.
John and Jay have also requested that we specify in the RN that Spring Boot is maintained by pivotal, so we can not provide support for it.
I have sourced the version information and artifact names for SpringBoot version from the 1.5.8.Final BOM.
When I asked the Spring Boot team to check the artifact list and versions, nobody objected to the current state.
I'll make sure to re-check again and update the list. We will not be shipping the RN  with incorrect information:)

Yea agreed about the support situation :-) FTR, we use "tested and verified" for Spring Boot and "tested" for other runtimes, which is weird :-), and also we use the word "certified" for this kind of stuff in the WildFly Swarm guide...

Currently Investigating this...


New version of Chapel cripples Chrest

@benharsh updated chapel to be much more strict in error checking.  My experience has been that putting a try! in front gets past the error, but may not be the best solution.
Users/buddha/github/buddha314/chrest/src/ChrestRequestResponse.chpl:144: In function 'InputJson':
/Users/buddha/github/buddha314/chrest/src/ChrestRequestResponse.chpl:154: error: call to throwing function _cast without throws, try, or try! (relaxed mode)
$CHPL_HOME/modules/internal/StringCasts.chpl:86: note: throwing function _cast defined here
/Users/buddha/github/buddha314/chrest/src/ChrestRequestResponse.chpl:154: error: call to throwing function _cast without throws, try, or try! (relaxed mode)
$CHPL_HOME/modules/internal/StringCasts.chpl:86: note: throwing function _cast defined here
/Users/buddha/github/buddha314/chrest/src/ChrestRequestResponse.chpl:154: error: call to throwing function _cast without throws, try, or try! (relaxed mode)
$CHPL_HOME/modules/internal/StringCasts.chpl:172: note: throwing function _cast defined here
/Users/buddha/github/buddha314/chrest/src/ChrestRequestResponse.chpl:144: In function 'InputJson':
/Users/buddha/github/buddha314/chrest/src/ChrestRequestResponse.chpl:154: error: call to throwing function _cast without throws, try, or try! (relaxed mode)
$CHPL_HOME/modules/internal/StringCasts.chpl:46: note: throwing function _cast defined here
make: *** [default] Error 1

I will try to reproduce the error.

Reproduced on my machine
bk@bk:/projects/ayatollah$ chpl --version
chpl version 1.17.0 pre-release (aaa4f37)
Copyright (c) 2004-2018, Cray Inc.  (See LICENSE file for more details)
bk@bk:/projects/ayatollah$ printchplenv
machine info: Linux bk 4.13.0-32-generic #35~16.04.1-Ubuntu SMP Thu Jan 25 10:13:43 UTC 2018 x86_64
CHPL_HOME: /projects/chapel *
script location: /projects/chapel/util
CHPL_TARGET_PLATFORM: linux64
CHPL_TARGET_COMPILER: gnu
CHPL_TARGET_ARCH: native
CHPL_LOCALE_MODEL: flat
CHPL_COMM: none
CHPL_TASKS: qthreads
CHPL_LAUNCHER: none
CHPL_TIMERS: generic
CHPL_UNWIND: none
CHPL_MEM: jemalloc
CHPL_ATOMICS: intrinsics
CHPL_GMP: gmp
CHPL_HWLOC: hwloc
CHPL_REGEXP: re2
CHPL_AUX_FILESYS: none

bk@bk:/projects/ayatollah$ make
chpl -M/projects/chingon/src -M/projects/cdo/src -M/projects/numsuch/src -M/projects/chrest/src --fast --print-callstack-on-error --print-commands -I/usr/include -I/usr/local/Cellar/openblas/0.2.20/include -I/usr/include/postgresql -L/usr/local/Cellar/openblas/0.2.20/lib -lblas -o bin/ayatollah src/Ayatollah.chpl
/projects/chrest/src/ChrestRequestResponse.chpl:144: In function 'InputJson':
/projects/chrest/src/ChrestRequestResponse.chpl:154: error: call to throwing function _cast without throws, try, or try! (relaxed mode)
$CHPL_HOME/modules/internal/StringCasts.chpl:86: note: throwing function _cast defined here
/projects/chrest/src/ChrestRequestResponse.chpl:154: error: call to throwing function _cast without throws, try, or try! (relaxed mode)
$CHPL_HOME/modules/internal/StringCasts.chpl:86: note: throwing function _cast defined here
/projects/chrest/src/ChrestRequestResponse.chpl:154: error: call to throwing function _cast without throws, try, or try! (relaxed mode)
$CHPL_HOME/modules/internal/StringCasts.chpl:172: note: throwing function _cast defined here
/projects/chrest/src/ChrestRequestResponse.chpl:144: In function 'InputJson':
/projects/chrest/src/ChrestRequestResponse.chpl:154: error: call to throwing function _cast without throws, try, or try! (relaxed mode)
$CHPL_HOME/modules/internal/StringCasts.chpl:46: note: throwing function _cast defined here
Makefile:17: recipe for target 'default' failed
make: *** [default] Error 1

Seems to be fixed, will have @tshimanga confirm when he can.

Yep, all clear! @buddha314 @marcoscleison

What was the fix?

Just to clarify, I think these failures were a result of this PR that adds throwing errors to string casts:
https://github.com/chapel-lang/chapel/pull/8547
When I mentioned "error checking" offline I meant semantic errors related to initializers like use-before-def errors with fields.

Hi all,
I have some Reflexion module usage. Inside the reflection, I use type cast. the compiler was crying because the code block that uses type casts was not with try{}.
I added try{} and silenced the compiler for while.

@marcoscleison: More information on error handling approaches can be found here, so you can avoid fighting the compiler in the future.


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Endless AJAX requests.
As example:
GET | xhr | 200 | /app_dev.php/admin/ajax/products/search?phrase=&_=1510959359857 | 667ms | 4596d2
-- | -- | -- | -- | -- | --
GET | xhr | 200 | /app_dev.php/admin/ajax/products/search?phrase=&_=1510959359856 | 267ms | 5d0764
GET | xhr | 200 | /app_dev.php/admin/ajax/products/search?phrase=&_=1510959359855 | 250ms | bacf43
GET | xhr | 200 | /app_dev.php/admin/ajax/products/search?phrase=&_=1510959359854 | 285ms | 04b45c
GET | xhr | 200 | /app_dev.php/admin/ajax/products/search?phrase=&_=1510959359853 | 353ms | 02da46
GET | xhr | 200 | /app_dev.php/admin/ajax/products/search?phrase=&_=1510959359852 | 244ms | e76459
GET | xhr | 200 | /app_dev.php/admin/ajax/products/search?phrase=&_=1510959359851 | 320ms | cd5d1d
GET | xhr | 200 | /app_dev.php/admin/ajax/products/search?phrase=&_=1510959359850 | 255ms | 0fc0

Any idea?
Mike

@patrick477, any idea?

As far as I am concerned, these requests are made on the keyup event in the products/sections association form field. From what I can see, they're referring to specific phrases. Are you typing them in the form field?

If i type them in - nothing found. (No results found.) When i press the arrow - endless request.

on the backend，admin user use the en_US language? if not, it will display no results found

@benyang2015 , no i don't use en_US at all. de_CH is what the Admin reads.

you can set the admin language to en_US,select the product you want,the set the admin language to de_CH

update to cmsplugin 1.2.2,can not select product and Sections!
display not result to find

@damonsson, @shinoks, could you guys give it a look?

Hello,
I have the same problem!
I am using pt_PT language as a primary language on my system. When I want to select a section on block or page admin view, the background scripts cannot find any data.
The reason is because it is hardcoded on DI as en language, so you will never get any data at all. If try to see the profiler you will find the queries with language filter with "en".
It would be better the DI could get the system or the user session language...

Could you provide a PR with Behat scenario?

Channel locale is set to "nl" and when admin language is not set to "nl" it can't find sections or products in the page edit screen. Will this be fixed?

I also confirm this. when admin user's locale differs from channel default locale, the product & section loaders cannot find anything

@thelegendtwentyseven Sure, we'll check and try fix it in the coming days cause we see that a lot of people have a problem with it


CLI tests frequently hits the timeout for me

Description
(The rust ones)
E.g.
---- test_data_dir stdout ----
thread 'test_data_dir' panicked at /rustc/a28077b28a02b92985b3a3faecf92813155f1ea1/library/core/src/ops/function.rs:250:5:
Unexpected failure.
code=<interrupted>
stderr=```""```
command=`"/Users/sean/Code/github.com/glaredb/glaredb/target/debug/glaredb" "-f" "/var/folders/4l/fnrk81pn6nj924xq52rwxnbc0000gn/T/.tmpkUFDJZ" "-q" "create table test as select 1"`
code=<interrupted>
stdout=""
stderr=""

This can happen in any of the tests for me. Sometimes everything passes, sometimes one test fails, sometimes many tests fail.
Increasing DEFAULT_TIMEOUT to 5 secs makes the tests consistently pass for me. Why was this lowered?

I set it lower to speed up the testing suite. happy to bump it back up to 5s. Originally, I wanted to send a sigkill to the application, but assert_cmd doesn't seem to support that. So the timeout is still a bit of a hack, but it seems the best available without manually spawning the task.

Is there a test that depends on hitting this timeout? When would we expect the binary to hang?

Is there a test that depends on hitting this timeout? When would we expect the binary to hang?

it's when we run the ./glaredb server commands. those run indefinitely.  Since assert_cmd doesn't support sending signals, we just set a timeout.

I don't know what changed, but I don't seem to be hitting this now. Will reopen if I see it again.
I'd like to do proper signal sending to make that all more robust, but timeouts work for us right now.


Update README.md

Fixed the array syntax

Coverage remained the same at 90.65% when pulling 5993b5e4dab409f6005834560528546ea93069ee on davidyell:patch-1 into eb0a72042cb4979e2a03d994d69859573979c885 on FriendsOfCake:master.


Torsion

Description
Update torsion profile plotting routine
Todos

[ ] Allow for only endstate torsion profile to be plotted
[ ] add test coverage

Status

[ ] Ready to go

Codecov Report

Merging #48 (4ceba99) into main (74fda67) will increase coverage by 3.47%.
The diff coverage is 50.00%.


[Feature]: NexusMods: Update changelog on upload

Problem
NexusMods has a changelog feature for versions. The program does not currently seem to interact with it.
Solution
Add a changelog argument which accepts a text string, which will be added to the changelog for the mod, under the provided version from -v.
Alternatives
No response
Screenshots
No response
Relevant log output
No response
Code of Conduct

[X] I agree to follow this project's Code of Conduct

BTW I can't describe how useful this program is, thank you so very much. Interacting with NexusMods is a pain and a half.

I want to add this


Top arrow overflows on Github logo

The poor octocat can be hidden by the top arrow when scrolling down.

PR #36


Agenda content object requirements

Some change requests for related agenda item information provided by rest api (if possible):

I need the content object real name in singular (e.g. "motion", "election", "agenda item") to show it in delete confirm message ("Do you really want to delete the Motion/Election/agenda item?"). I want to provide a delete link in agenda for the related items.
item.content_object.collection should get a string with "." instead of "/" separator; e.g. "motions.motion" instead of "motions/motion"
string of (JS-Data) Object name, e.g. "Agenda", "Motion", "Assignment". I want to use it for auto delete command $ObjectName.destroy(item.content_object.id)

I added a new field element display_name. See #1695.
Why do you want a string with . instead of /? We defined the collection name used for autoupdate stuff with /.
The server does not know the JSData string (i. e. Angular factory service name). The mapping between collection names and these string should be done in the client. -> @ostcar

Why do you want a string with . instead of /? We defined the collection name used for autoupdate
stuff with /.

I need it for ui-sref links, e.g. motions.motion.detail:
https://github.com/OpenSlides/OpenSlides/pull/1698/files#diff-3f7cf361bcdcee23fe42ded55a85d33bR119
But I can use the replace command if other code needs the / separator.

We can close this. I don't need any more special content object updates...


No Updates in Feeds anymore

It looks like feeds aren't working anymore.
Can you have a look @ajmaradiaga , please?

Oh my... you are right, I don't see any commits in the last few days. Sorry about that. I will try accessing the service and see how I can get it running again remotely. 🤞

@abap-weasel I fixed the issue. The feeds are working now. Apologies for the inconvenience. I need to set up an alerting mechanism so that this doesn't happen again.


Locale Formatted Timestamps

As a user involved in the governance, risk, and compliance of systems and components, I want to any date/time timestamps current displayed that are strongly typed in the OSCAL model to be presented in the proper locale format  so that I can more easily interpret their values.
Acceptance Criteria

All date/time timestamps that are specified as such in the OSCAL data model are locale formatted

A default locale of EN/US would be sufficient for this iteration, future implementations may grab the locale configured in the browser.

Something like moment.js might work here.

@rgauss Are there places other than OSCALMetadata that strongly typed dates occur? Looking through the examples we have, that is the only place I see it occur.


provideSignatureHelp does seem to ever be cancelled

From https://github.com/Microsoft/TypeScript/issues/23458
Steps to Reproduce:

In extensions/typescript-language-features/src/features/signatureHelpProvider.ts
At top of provideSignatureHelp, add:

		token.onCancellationRequested(() => {
			console.log(`cancel  #`);
		});
		await new Promise(resolve => setTimeout(resolve, 5000));

Restart code dev so that the modified ts extension is running
In a ts file in the dev instance of code:

function foo(x: number) { }

foo()

Request signature help in foo() but then move the cursor up or down a line

Bug
Even though we likely no longer need the signature help result, it appears that we never actually cancel SignatureHelpProvider request

Cases where we may want to cancel the request:

Selection change
Document contents change
Active document changes
Suggestions requested

Should be fixed for the following cases:

Document changes
Request cancelled by user
Mouse selection
Re-trigger hints


API displays fewer (if any at all) results on the source collection page for Europeana than it does when filtering by source=europeana

Description

Originally reported by @obulat
The API returns significantly fewer results for the source collection view than it does for the search view filtered by source for Europeana. At the time of writing this, the following links showcase this discrepancy:

https://api.openverse.engineering/v1/images/?source=europeana (full page of results)
https://api.openverse.engineering/v1/images/source/europeana/ (takes time to load and only shows 9 or 10 results)

On staging this contrast is even more stark:

https://api-staging.openverse.engineering/v1/images/?source=europeana (full page)
https://api-staging.openverse.engineering/v1/images/source/europeana/ (no results)

I suspect this has to do with dead link filtering. My guess is that the filtering which is done on search (which continues searching over wider and wider windows to fill up a page of results) is not happening for the collections view. Thus if all the queried results for a collection fail the dead link step, than an empty (or smaller) response is returned. This is just supposition and I haven't looked into the code for it yet.
Additional context

May be related to #3480 and #2293

Update: Okay so I was able to track down a single request I made to https://api.openverse.engineering/v1/images/source/europeana/ and sure enough there are pages and pages and pages of deleted results for Europeana due to dead link filtering 😅 I don't know that this is a problem we can solve right now, but certainly the dead link pipeline project (#3585) will help!
Screenshot as an example:

What's not shown there are hundreds, if not thousands, of dead link requests as it tries to fill the results 🙃

Great find!
The difference between the collection views and search views is mainly in the way the query is created. Search execution is the same, so collection views do filter out dead links.
I suspect the reason for different responses is sorting: search views sort results by relevance, while collection views  sort them by the time of ingestion into Openverse. Which might mean that we've ingested a lot of dead links recently, worth investigating 🤔

Hi there! I'm Jolan, I work as an API outreach staff member at Europeana. I see you're working on the connection between OpenVerse and Europeana, I just wanted to pop in and say that if there's anything we can do to help on the Europeana side, please let us know! You can always get in contact with us using our<EMAIL_ADDRESS>email address.

Hi @Hobbesball, thank you for reaching out to us! Nice to meet you, and I'm sure we'll be in contact with more questions :)
This particular issue seems to have been partly resolved, you can see the Europeana images on Openverse staging site: https://staging.openverse.org/image/source/europeana (this feature is not launched yet, so you can only see the staging version for now)

@AetherUnbound, do you think we can close this issue now?
One thing I realized is that the deep pagination limits we set for search might need to be relaxed for the additional search views. Otherwise we should adjust the results label to say something like "More than 10000 results found, showing the newest 100" (for the 5 pages we show)

Thank you @Hobbesball! I think we can, we can re-open if the issue comes back up again 🙂
@obulat would you mind making a separate issue for the behavior you're describing?


feat: Enable forbididgo linter and forbid RegisterTestingT

Description
gomega's RegisterTestingT is now deprecated. NewWithT should be used instead.
This PR enables the goforbidid linter that allows to forbid regular expressions. Due to RegisterTestingT keyword seems to be quite specific I think it would be safe to set the keyword to detect and forbid appearences of it.
Verification Steps

Checklist (Definition of Done)

[ ] All acceptance criteria specified in JIRA have been completed
[ ] Unit and integration tests added that prove the fix is effective or the feature works (tested against emulated and non-emulated OCM environment)
[ ] Documentation added for the feature
[ ] CI and all relevant tests are passing
[ ] Code Review completed
[ ] Verified independently by reviewer
[ ] All PR comments are resolved either by addressing them or creating follow up tasks
[ ] Required metrics/dashboards/alerts have been added (or PR created).
[ ] Required Standard Operating Procedure (SOP) is added.
[ ] JIRA has been created for changes required on the client side

Refactor work done by @VanillaSpoon has been included in the PR

This PR is ready

Awesome work @miguelsorianod @VanillaSpoon love it!


rebase-merge Error Every Time I brew update

Describe the bug

Almost every time if not every time I run brew update I get the following:
brew update
fatal: It seems that there is already a rebase-merge directory, and
I wonder if you are in the middle of another rebase.  If that is the
case, please try
	git rebase (--continue | --abort | --skip)
If that is not the case, please
	rm -fr ".git/rebase-merge"
and run me again.  I am stopping in case you still have something
valuable there.

fatal: It seems that there is already a rebase-merge directory, and
I wonder if you are in the middle of another rebase.  If that is the
case, please try
	git rebase (--continue | --abort | --skip)
If that is not the case, please
	rm -fr ".git/rebase-merge"
and run me again.  I am stopping in case you still have something
valuable there.

Updated Homebrew from da74e4dc2 to 377ac6475.
Updated 2 taps (homebrew/core and homebrew/cask).

Of course, that's really unhelpful but that's probably an issue with brew itself. It should probably tell you where this rebase-merge directories are, but that's another issue for another time. I was able to locate them myself:
% cd /opt/homebrew

% find . -type d -name rebase-merge
./Library/Taps/shivammathur/homebrew-php/.git/rebase-merge
./Library/Taps/shivammathur/homebrew-extensions/.git/rebase-merge

PHP versions

N/A
To Reproduce

Not sure what .yml file this is asking about... 🤷🏼
Expected behavior

I would expect these rebase-merge directories to not exist and cause issues.
Screenshots/Logs

N/A
Additional context

To resolve this I usually just do a brew update-reset. Ideally though we should figure out the root cause of this issue and fix it 😁
% brew config
HOMEBREW_VERSION: 3.3.16-55-g377ac64
ORIGIN: https://github.com/Homebrew/brew
HEAD: 377ac6475c8785dc80d50df3c6b173065d32183d
Last commit: 28 hours ago
Core tap ORIGIN: https://github.com/Homebrew/homebrew-core
Core tap HEAD: f80d456d46ba490c39f804cb7d3bad28171b6650
Core tap last commit: 13 hours ago
Core tap branch: master
HOMEBREW_PREFIX: /opt/homebrew
HOMEBREW_CASK_OPTS: []
HOMEBREW_CORE_GIT_REMOTE: https://github.com/Homebrew/homebrew-core
HOMEBREW_EDITOR: nano
HOMEBREW_MAKE_JOBS: 8
Homebrew Ruby: 2.6.8 => /System/Library/Frameworks/Ruby.framework/Versions/2.6/usr/bin/ruby
CPU: octa-core 64-bit arm_firestorm_icestorm
Clang: 13.0.0 build 1300
Git: 2.35.1 => /opt/homebrew/bin/git
Curl: 7.77.0 => /usr/bin/curl
macOS: 12.2.1-arm64
CLT: <IP_ADDRESS>.1.1638488800
Xcode: N/A
Rosetta 2: false

Are you willing to submit a PR?

No, because I don't know enough about what is going on and causing this issue.

Please run
rm -rf $(brew --repo shivammathur/php) $(brew --repo shivammathur/extensions)
brew tap shivammathur/php
brew tap shivammathur/extensions

Then you should be able to run brew update without any errors


Add trigger and function for setting first chapter as last_chapter_id_seen in user_course

This pull request adds a trigger and a function to set the first chapter as the last_chapter_id_seen in the user_course table. The trigger is fired after an insert on the user_course table and calls the function set_first_chapter_on_user_course(). The function finds the first module and the first chapter of the course and updates the last_chapter_id_seen field in the user_course table with the first chapter's id. This ensures that the first chapter is marked as viewed when a user starts a course.

LGTM :smiling_imp: