Warning for unreachable devices in wrong place

custom_component/hahomematic version (if applicable):
latest
Home Assistant version (if applicable):
latest
CCU version:
CCU3 with RaspberryMatic
Describe the bug
Unreachable devices generate a persistent notification:

To Reproduce
Steps to reproduce the behavior:

Unplug Hm device with regular status messages
Wait until the CCU notices that the device is unreachable
See error

Expected behavior
The usual way would be to instead mark the entities as "not reachable" as it is done in the old homematic integration:

Screenshots
see above

I would like to see this persistent notification disabled/removed as well. The user, who needs it, can automate it.
My setup: I have a outdoor sensor and know, that this has sometime problems. But that doesn't matter, some seconds afterwards it is back again, so I don't care. But the persistent notification is generated.

@eikowagenknecht : Thanks for reporting a bug. Unreach should be displayed on an entity_level. (device is not posible)
@emufan: I don't think an issue is the correct place to discuss a feature

If you prefer to discuss it over at discussions, I just created a thread there: https://github.com/danielperna84/hahomematic/discussions/161

I like these notifications. They are the equivalent of the "Servicemeldungen" on the CCU. That's a feature other users actually requested for the old integration. And in my case they also disappeared in HA automatically once the device was reachable again. So essentially you get the relevant message from the HA UI without having to look at the CCU to know what the problem is.

Unreach is fixed now. Will be displayed at entity_level again.

Nice, closing this. The discussion can be continued in the discussion thread.


Uncaught TypeError: Cannot read property 'replace' of undefined

[Enter steps to reproduce:]

...
...

Atom: 1.15.0 x64
Electron: 1.3.13
OS: Ubuntu 16.04.1
Thrown From: atom-latex package 0.7.2
Stack Trace
Uncaught TypeError: Cannot read property 'replace' of undefined
At /home/lukas/.atom/packages/atom-latex/lib/locator.coffee:62

TypeError: Cannot read property 'replace' of undefined
    at /packages/atom-latex/lib/locator.coffee:62:42
    at ChildProcess.exithandler (child_process.js:209:7)
    at emitTwo (events.js:106:13)
    at ChildProcess.emit (events.js:191:7)
    at maybeClose (internal/child_process.js:877:16)
    at Socket.<anonymous> (internal/child_process.js:334:11)
    at emitOne (events.js:96:13)
    at Socket.emit (events.js:188:7)
    at Pipe._handle.close [as _onclose] (net.js:493:12)

Commands

Non-Core Packages
atom-ctags 5.0.0
atom-latex 0.7.2
autocomplete-clang 0.10.0
ctags-status 1.3.7
git-plus 7.3.3
language-cpp14 0.6.2
language-latex 1.0.0
latex-plus 0.9.1
latexer 0.3.0
linter 1.11.23
linter-chktex 1.3.0
minimap 4.26.8
pdf-view 0.56.0
symbols-tree-view 0.13.2
Zen 0.16.4

Please provide more information on the issue.


Move to using webpack for building the library

This allows us to remove the dependency on browserify
completely.
The problem is that the size of the compiled library is 719 kB unminified and 190 kB minified.  The current implementation via browserify produces 49 kB unminified and 21 kB minified.  That's quite the difference.
Any ideas on how to get that down?

Marking react and react-dom as externals in the webpack config significantly reduces build size.

@claydiffrient, this PR is great + @doque's PR.
This needs to be merged!! :)

@diasbruno Looks like there's some conflicts, and I don't have the time right now to resolve them.  I'll take a look tonight :)

No problem. Just trying to keep this update.

...and thanks to take the time to respond.

@doque @diasbruno now released as v1.1.1

awesome, @claydiffrient!


challenge: make functions compatible with the tidyverse

I'm trying to use the tidyverse more and bleutils functions are prime candidates to use in "pipes". There's a pattern of writing functions so that they are pipeable. Let's do that.

huh, I'm finding that a lot of the functions as they stand work just fine already. Yay, past me who wrote them!


Windows version of harp missing binaries

During my testing for the windows build. I got errors regarding missing dlls namely:
VCRuntime 140-1.dll
ucrtbased.dll
MSVCP140d.dll
VCRUNTIME140.dll
However from testing, these were all resolved after I installed the windows visual studio 11 SDK

Fixed in 9c996c8903c0d52374f858b9260f3a14e2256ce2


Closes #1194. Adding key to Widget to re render

Adding the key prop with the value of now.timezone  to re-render with the updated reasons.

Coverage report
Branches coverage not met for global: expected >=90%, but got 78.125%

St.:grey_question:
Category
Percentage
Covered / Total

🟢
Statements
95.08%
58/61

🟡
Branches
78.13%
25/32

🟢
Functions
95%
19/20

🟢
Lines
95%
57/60

Test suite run success
24 tests passing in 2 suites.
Report generated by 🧪jest coverage report action from 72a08c26969238d566413e5814fe53eadec760ca


[DotNetBackend] Support for .NET functions in isolated worker mode

It seems that in the future the preferred way of running Azure Functions will be in isolated worker mode. It would be nice to have support for it.

I just noticed, that version 6.1.0 added a dependency on Microsoft.NET.Sdk.Functions package that is incompatible with isolated worker mode:

Microsoft.NET.Sdk.Functions package is meant to be used with in-proc function apps. Please remove the reference to this package in isolated function apps.

Version 6.0.0 doesn't work with isolated worker mode either but it does not cause errors.

Thanks for that @oleks9o6 !
Indeed, Microsoft.NET.Sdk.Functions (and hence DurableFunctionsMonitor.DotNetBackend) is incompatible with .NET Isolated, so to be able to "inject" DfMon into .NET Isolated projects we would need to reimplement and push the backend as a separate NuGet package anyway.
Let's track that activity under this ticket.

NET Isolated support would be most welcome! 🥳

Just published an alpha version of DurableFunctionsMonitor.DotNetIsolated, which can be 'injected' into your .NET 7 Isolated Function.
Would greatly appreciate any feedback.
How to use

Install from NuGet: dotnet add package DurableFunctionsMonitor.DotNetIsolated --version 6.3.0-alpha2
Initialize by calling .UseDurableFunctionMonitor() extension method, like this:     var host = new HostBuilder()
         .ConfigureFunctionsWorkerDefaults((hostBuilderContext, workerAppBuilder) => {

             workerAppBuilder.UseDurableFunctionsMonitor();

         })
         .Build();

By default all settings are read from env variables (all the same config settings are supported), but those can be programmatically (re)configured like this:
        var host = new HostBuilder()
            .ConfigureFunctionsWorkerDefaults((hostBuilderContext, workerAppBuilder) => {

                workerAppBuilder.UseDurableFunctionsMonitor((settings, extensionPoints) =>
                {
                    // Override DfMon's settings here
                    settings.Mode = DfmMode.ReadOnly;
                    // ....
                });

            })
            .Build();

Limitations

No way to configure path to DfMon's endpoint, so it will always appear at the API root (http://localhost:7071/my-route-prefix). If you have other HTTP endpoints and any of them got overshadowed, then you'll need to move them to some other path.
Multiple Storage connection strings are not supported, only the default one (AzureWebJobsStorage).
Support for Durable Entities is limited (since they are not supported in Isolated mode yet anyway).
For non-default durability providers you'll need to provide custom routines for retrieving instance history etc.. This should be done via extensionPoints parameter of .UseDurableFunctionsMonitor() configuration method. Code for MSSQL storage provider can be directly copied from here.

Please, let me know how it works for you.

Just published an alpha version of DurableFunctionsMonitor.DotNetIsolated, which can be 'injected' into your .NET 7 Isolated Function.
Would greatly appreciate any feedback.

Thanks for the update and instructions!
I tried it and was able to run it in our solution - durable functions on-premises with MSSQL as storage. So, the extensionPoints section came in handy🤗
The issue I faced (and you mentioned it in limitations) is HTTP endpoints overshadowing. I did not dig too deep yet, but all the GET requests were replaced, nevertheless, the POST ones were not.
I'm going to look into authentication options and try more advanced scenarios in the forthcoming weeks.

The issue I faced (and you mentioned it in limitations) is HTTP endpoints overshadowing.

Yeah, I'm afraid there is no easy way to make DfMon endpoint's path configurable in Isolated mode. HttpTrigger.Route value can only be a constant, and changing it would require a rebuild.
I can only think of injecting DfMon as a source code, using a Roslyn code generator, but really not sure it is worth the effort.
Maybe @fabiocav has any better ideas...

Yeah, I'm afraid there is no easy way to make DfMon endpoint's path configurable in Isolated mode. HttpTrigger.Route value can only be a constant, and changing it would require a rebuild.

It looks like DFM intercepts all the requests because of DfmServeStaticsFunction that uses the route {p1?}/{p2?}/{p3?}. So, it is impossible to have its own function that is triggered with a GET request.
I'm not sure how to fix this in the right way but, maybe, using a hardcoded prefix e.g. statics/ or some route constraints to p1, p2, and p3 parameters could solve the problem.

Then I'm afraid we have no other option than to lock DfMon's path prefix to something unique (as you suggested).
I've just set it to /durable-functions-monitor and pushed the updated package as https://www.nuget.org/packages/DurableFunctionsMonitor.DotNetIsolated/6.3.0-beta1 .
DfMon should now appear at http://localhost:7071/durable-functions-monitor and shouldn't hide anything anymore.
And then at the root you can always do a redirect, if needed:
        [Function(nameof(HttpRoot))]
        public HttpResponseData Run([HttpTrigger(AuthorizationLevel.Anonymous, "get", Route = "/")] HttpRequestData req)
        {
            var response = req.CreateResponse(HttpStatusCode.TemporaryRedirect);
            response.Headers.Add("Location", "durable-functions-monitor");
            return response;
        }

Please, tell me if it works better.

Please, tell me if it works better.

It works much better now, thank you😊

I've been using it for quite some time - and it works nicely (.NET8 in isolated mode).
The only issue I have is lots of timeouts when there are thousands of instances that are processing at the same time but I assume it is rather an issue with the storage (MS SQL server in my case) itself.
I think the issue can be closed.


Workflow for ZPPY- PCMDI for E3SM diagnostics

Issue resolution

Closes #<ISSUE_NUMBER_HERE>

Select one: This pull request is...

[ ] a bug fix: increment the patch version
[ ] a small improvement: increment the minor version
[ ] an incompatible (non-backwards compatible) API change: increment the major version

1. Does this do what we want it to do?
Objectives:

Objective 1
Objective 2
...
Objective n

Required:

[ ] Product Management: I have confirmed with the stakeholders that the objectives above are correct and complete.
[ ] Testing: I have added or modified at least one "min-case" configuration file to test this change. Every objective above is represented in at least one cfg.
[ ] Testing: I have considered likely and/or severe edge cases and have included them in testing.

If applicable:

[ ] Testing: this pull request introduces an important feature or bug fix that we must test often. I have updated the weekly-test configuration files, not just a "min-case" one.
[ ] Testing: this pull request adds at least one new possible parameter to the cfg. I have tested using this parameter with and without any other parameter that may interact with it.

2. Are the implementation details accurate & efficient?
Required:

[ ] Logic: I have visually inspected the entire pull request myself.
[ ] Logic: I have left GitHub comments highlighting important pieces of code logic. I have had these code blocks reviewed by at least one other team member.

If applicable:

[ ] Dependencies: This pull request introduces a new dependency. I have discussed this requirement with at least one other team member. The dependency is noted in zppy/conda, not just an import statement.

3. Is this well documented?
Required:

[ ] Documentation: by looking at the docs, a new user could easily understand the functionality introduced by this pull request.

4. Is this code clean?
Required:

[ ] Readability: The code is as simple as possible and well-commented, such that a new team member could understand what's happening.
[ ] Pre-commit checks: All the pre-commits checks have passed.

If applicable:

[ ] Software architecture: I have discussed relevant trade-offs in design decisions with at least one other team member. It is unlikely that this pull request will increase tech debt.

Thanks @zhangshixuan1987 for working on this! Let me know when it's ready for me to review. On my review, I can:

Note code blocks that should be generalized/abstracted with parameters rather than hard-coded (e.g., how to take the code from prototype to production code).
Confirm the checkboxes on the PR template above are fully met.
Confirm the objectives / expected behavior, again noted on the PR template above.

@forsyth2 : Hi Ryan, based on what you mentioned above, I would like to ask you to review this commit first. This pull request have already included the key part for the workflow:

the control script for job dependency: pcmdi_diags.py
the control template for the main calculation of pcmdi metrics:  pcmdi_diags.bash
the parameter files needed for certain process (template/pcmdi_diags/)

I think that it would be better for you to provide some high-level comments on the overall structure and the coding style which should be first fulfilled to meet the requirment by Zppy.
Thank you!
With best wishes,
Shixuan

@zhangshixuan1987 and @forsyth2 I will begin reviewing this PR later next week.
Shixuan, thank you for your hard work putting together this PR!

Hi @forsyth2 and @chengzhuzhang :  I am not sure if it is properate, but I want to share the sample .cfg files and the run output examples I created for the PCMDI here:
- cfg file for v3.LR.hisotical simulation, which is adapted from Jill's cfg file

sample output from the pcmdi, which is applied to the v3.LR.historical simulations during 1985-2014 period.

In addition, I also tested the workflow with AMIP and piControl simulations, which can work reasonably as well.  I need to further work on following things:

verify the "model vs model" function
discuss with you and Ryan for a. final www directory structure, and b. the viewer page.

@chengzhuzhang : Hi Jill, if you check my comments https://github.com/E3SM-Project/zppy/pull/624#issuecomment-2392406822. You will find the e3sm diag cfg file that I shared for you and Ryan to test. please take a look and let me know if you have any questions.

Hi @forsyth2 and @chengzhuzhang : I am not sure if it is properate, but I want to share the sample .cfg files and the run output examples I created for the PCMDI here:
* [ cfg file for v3.LR.hisotical simulation](https://web.lcrc.anl.gov/public/e3sm/diagnostic_output/ac.szhang/e3sm-pcmdi/post.v3.LR.historical.cfg), which is adapted from Jill's cfg file

* [sample output from the pcmdi](https://web.lcrc.anl.gov/public/e3sm/diagnostic_output/ac.szhang/e3sm-pcmdi/v3.LR.historical_0051/pcmdi_diags/), which is applied to the v3.LR.historical simulations during 1985-2014 period.

In addition, I also tested the workflow with AMIP and piControl simulations, which can work reasonably as well. I need to further work on following things:
1. verify the "model vs model" function

2. discuss with you and Ryan for a. final www directory structure, and b. the viewer page.

When reviewing the results, in the parallel coordinate figure: example. The prw, rldscs, sfcWind show large bias between v3, and CMIP MME, I think the legend might be mixed? Red line should be MME and black for v3?
When going over the results, I agree strongly that it would be much easier to navigate the results with a viewer page! @mingxuanwupnnl

The *.py files under template/pcmdi_diags  are not installed correctly.
Example:
`jinja2.exceptions.TemplateNotFound: pcmdi_diags/generate_sftlf.py
I think it is due to the constraint in setup:
https://github.com/E3SM-Project/zppy/blob/408e9ade87db8d0d5322c01186564df1392282be/setup.py#L20-L21

Hi @forsyth2 and @chengzhuzhang : I am not sure if it is properate, but I want to share the sample .cfg files and the run output examples I created for the PCMDI here:
* [ cfg file for v3.LR.hisotical simulation](https://web.lcrc.anl.gov/public/e3sm/diagnostic_output/ac.szhang/e3sm-pcmdi/post.v3.LR.historical.cfg), which is adapted from Jill's cfg file

* [sample output from the pcmdi](https://web.lcrc.anl.gov/public/e3sm/diagnostic_output/ac.szhang/e3sm-pcmdi/v3.LR.historical_0051/pcmdi_diags/), which is applied to the v3.LR.historical simulations during 1985-2014 period.

In addition, I also tested the workflow with AMIP and piControl simulations, which can work reasonably as well. I need to further work on following things:
1. verify the "model vs model" function

2. discuss with you and Ryan for a. final www directory structure, and b. the viewer page.

When reviewing the results, in the parallel coordinate figure: example. The prw, rldscs, sfcWind show large bias between v3, and CMIP MME, I think the legend might be mixed? Red line should be MME and black for v3?
When going over the results, I agree strongly that it would be much easier to navigate the results with a viewer page! @mingxuanwupnnl

Hi @chengzhuzhang : I did not notice this message as you may @ the wrong people. As for your questions here:

Yes, the legend for CMIP MME and v3 in parallel coordinate plots was wrong, the fixed code with improvements in the mean climate metrics plots has been merged to my github branch.
As for the  issues for prw, rldscs, sfcWind, this is partly related to the issues in the CMIP6 reference datasets. Jiwoo and I are working together to check the consistency of the units between two datasets, and will update this part.

I accidentally tagged @mingxuanwupnnl, Sorry!
@zhangshixuan1987 sounds good, I will try test the new PR for now.


Duplicate local variable name bitmap$0 on 2.10/2.11 for some weird lazy vals

Discovered in #3178.
2 partests fail to IR-check: run/t6272.scala and run/t3877.scala, on 2.11 (and also if ported to 2.10). On 2.12+, the produced IR is correct. Given that they are caused by lazy vals, this is not surprising, since scalac significant changed its treatment of lazy vals in 2.12. The errors (for t6272) are:
[error] Test.scala(30:7:VarDef): Duplicate local variable name bitmap$0.
[error] Test.scala(2:10:VarDef): Duplicate local variable name bitmap$0.

The issue is reproducible in 0.6.x and on master.
The IR looks like this:
  def init___() {
    this.O::init___();
    mod:LA$<-this;
    val bitmap$0: sr_VolatileByteRef = new sr_VolatileByteRef().init___B(0);
    try {
      val x1$lzy: sr_IntRef = new sr_IntRef().init___I(0);
      mod:s_Predef$.println__O__V(this.x1$1__p1__sr_IntRef__sr_VolatileByteRef__I(x1$lzy, bitmap$0));
      mod:s_sys_package$.error__T__sr_Nothing$("!")
    } catch (e) {
      val e$2: jl_Throwable = mod:sjsr_package$.wrapJavaScriptException__O__jl_Throwable(e);
      val x2$lzy: sr_IntRef = new sr_IntRef().init___I(0);
      mod:s_Predef$.println__O__V(this.x2$1__p1__sr_IntRef__sr_VolatileByteRef__I(x2$lzy, bitmap$0))
    } finally {
      val x3$lzy: sr_IntRef = new sr_IntRef().init___I(0);
      mod:s_Predef$.println__O__V(this.x3$1__p1__sr_IntRef__sr_VolatileByteRef__I(x3$lzy, bitmap$0))
    };
    if (mod:sjsr_RuntimeString$.isEmpty__T__Z("")) {
      val x4$lzy: sr_IntRef = new sr_IntRef().init___I(0);
      mod:s_Predef$.println__O__V(this.x4$1__p1__sr_IntRef__sr_VolatileByteRef__I(x4$lzy, bitmap$0))
    };
    this.b$1 = true;
    while (this.b__Z()) {
      val bitmap$0: sr_VolatileByteRef = new sr_VolatileByteRef().init___B(0);
      val x5$lzy: sr_IntRef = new sr_IntRef().init___I(0);
      mod:s_Predef$.println__O__V(this.x5$1__p1__sr_IntRef__sr_VolatileByteRef__I(x5$lzy, bitmap$0));
      this.b$und$eq__Z__V(false)
    }
  }

and
  def method__V() {
    val bitmap$0: sr_VolatileByteRef = new sr_VolatileByteRef().init___B(0);
    try {
      val x6$lzy: sr_IntRef = new sr_IntRef().init___I(0);
      mod:s_Predef$.println__O__V(this.x6$1__p1__sr_IntRef__sr_VolatileByteRef__I(x6$lzy, bitmap$0));
      mod:s_sys_package$.error__T__sr_Nothing$("!")
    } catch (e) {
      val e$2: jl_Throwable = mod:sjsr_package$.wrapJavaScriptException__O__jl_Throwable(e);
      val x7$lzy: sr_IntRef = new sr_IntRef().init___I(0);
      mod:s_Predef$.println__O__V(this.x7$1__p1__sr_IntRef__sr_VolatileByteRef__I(x7$lzy, bitmap$0))
    } finally {
      val x8$lzy: sr_IntRef = new sr_IntRef().init___I(0);
      mod:s_Predef$.println__O__V(this.x8$1__p1__sr_IntRef__sr_VolatileByteRef__I(x8$lzy, bitmap$0))
    };
    if (mod:sjsr_RuntimeString$.isEmpty__T__Z("")) {
      val x9$lzy: sr_IntRef = new sr_IntRef().init___I(0);
      mod:s_Predef$.println__O__V(this.x9$1__p1__sr_IntRef__sr_VolatileByteRef__I(x9$lzy, bitmap$0))
    };
    var b: boolean = true;
    while (b) {
      val bitmap$0: sr_VolatileByteRef = new sr_VolatileByteRef().init___B(0);
      val x10$lzy: sr_IntRef = new sr_IntRef().init___I(0);
      mod:s_Predef$.println__O__V(this.x10$1__p1__sr_IntRef__sr_VolatileByteRef__I(x10$lzy, bitmap$0));
      b = false
    }
  }

Sure enough, -Xprint:mixin shows 2 declarations of the same variable:
    def <init>(): A.type = {
      A.super.<init>();
      {
        @volatile var bitmap$0: runtime.VolatileByteRef = new runtime.VolatileByteRef(0);
        try {
          lazy var x1$lzy: runtime.IntRef = new runtime.IntRef(0);
          scala.this.Predef.println(scala.Int.box(A.this.x1$1(x1$lzy, bitmap$0)));
          scala.sys.`package`.error("!")
        } catch {
          case (_: Throwable) => {
            lazy var x2$lzy: runtime.IntRef = new runtime.IntRef(0);
            scala.this.Predef.println(scala.Int.box(A.this.x2$1(x2$lzy, bitmap$0)))
          }
        } finally {
          lazy var x3$lzy: runtime.IntRef = new runtime.IntRef(0);
          scala.this.Predef.println(scala.Int.box(A.this.x3$1(x3$lzy, bitmap$0)))
        }
      };
      if ("".isEmpty())
        {
          lazy var x4$lzy: runtime.IntRef = new runtime.IntRef(0);
          scala.this.Predef.println(scala.Int.box(A.this.x4$1(x4$lzy, bitmap$0)))
        }
      else
        ();
      A.this.b = true;
      while$1(){
        if (A.this.b())
          {
            @volatile var bitmap$0: runtime.VolatileByteRef = new runtime.VolatileByteRef(0);
            {
              lazy var x5$lzy: runtime.IntRef = new runtime.IntRef(0);
              scala.this.Predef.println(scala.Int.box(A.this.x5$1(x5$lzy, bitmap$0)));
              A.this.b_=(false)
            };
            while$1()
          }
        else
          ()
      };
      ()
    }
  };

It could be that it's only the same name, but that they have different symbols. But if that were true, our encodeLocalSym should have disambiguated them, so that's unlikely. If they indeed have the same symbol, I'll be angry at scalac ...

Yup ... it's the same symbol 😱
Not sure what to do to work around this.

Minimization:
object Test {
  def main(args: Array[String]): Unit = {
    method()
  }

  def method(): Unit = {
    lazy val x6 = 6
    println(x6)

    do {
      lazy val x10 = 10
      println(x10)
    } while (false)
  }
}

It seems a loop is necessary to trigger the issue. So it's probably related to LabelDefs inside scalac.

The code produced by scalac is actually wrong even on the JVM, as it does the wrong thing in some corner cases:
> scala
Welcome to Scala 2.11.11 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_60).
Type in expressions for evaluation. Or try :help.

scala> def method(): Unit = {
     |   var x1InitCount = 0
     |   lazy val x1 = { x1InitCount += 1; 1 }
     |   assert(x1InitCount == 0)
     |   println(x1)
     |   assert(x1InitCount == 1)
     |
     |   do {
     |     lazy val x2 = 2
     |     assert(x1InitCount == 1)
     |     println(x2)
     |     assert(x1InitCount == 1)
     |   } while (false)
     |
     |   println(x1)
     |   assert(x1InitCount == 1)
     | }
method: ()Unit

scala> method()
1
2
1
java.lang.AssertionError: assertion failed
  at scala.Predef$.assert(Predef.scala:156)
  at .method(<console>:26)
  ... 32 elided

The last assertion fails, because the bitmap$0 has been reset to 0 when entering the do loop, because of the redefinition of bitmap$0. This causes x1 to be reinitialized on the last access.
So it does seem that, the way this is compiled on the JVM, it behaves as if bitmap$0 was declared once at the beginning of the method, and then each ValDef declaring bitmap$0 is like an Assign instead.
I guess we could reproduce this behavior in our back-end as follows: in 2.10/2.11, we track which local vars have been declared. If we declare a variable twice in a method, we schedule the IR of that method for a fixup round, where we 1) declare all such variables as mutable at the beginning of the method, initialized with the zero of their type and 2) turn all their ValDefs into Assigns. It will incur some performance overhead even for sane methods, though, because of the tracking.
@gzm0 WDYT?

Since the JVM compiler is wrong anyway, I am also tempted to call it a won't fix, and blacklist the two faulty partests on 2.11 instead.

I suggest closing as wontfix.

Won't-fixed in dec5c945dd0aabf03bb5d071007d9e21563f8d98.


[0.8.1 Linux] Doesn't detect manually downloaded language models (and can't download new ones)

Version [0.8.1 Linux].
Downloading a new model gives me:
Download failed: [Errno 18] Invalid cross-device link: '/tmp/tmp02obn3np' -> '/home/user/.cache/whisper/tiny.pt'
Which seems to be related to the fact that tmp and home are on different file systems. (Is it?)
I then downloaded the model from:
https://github.com/openai/whisper/discussions/63
And pasted it into:
/home/user/.cache/whisper/large.pt
But when I open buzz, go to help->preferences->models the large model doesn't show as downloaded.
Do I have to alter some config file?
Is the only way to alter Buzz python scripts?
What can I do?

The large model should be named large-v2.pt, I believe

The cross-device link error has been addressed in https://github.com/chidiwilliams/buzz/issues/454 and should be fixed in the next release


parse_subexpr doesn't handle alias

It seems like parse_subexpr doesn't handle alias.
Here is some example:
1 + 3 * col0 as new_col0

It returns...
BinaryOp { left: Value(Number("1", false)), op: Plus, right: BinaryOp { left: Value(Number("3", false)), op: Multiply, right: Identifier(Ident { value: "col0", quote_style: None }) } }

I would like to work on this, but I have almost no experience writing parser, would probably need some help.

Sorry for filling bad issue, I think maybe using parse_identifier_with_alias would be the correct way to do handle alias

I think parse_subexpr is not responsible for handling alias, and making parse_expr_with_alias public should serve the purpose.


extract method just for one java class/method

hello, i wonder if i can use your algorithm to extract method just for one single java class/method.
Because i see your algorithm is designed for a java project, and when running the algorithm for a single java class, i am not sure weather it will take the information(data/call dependency) from other java class into account. If the algorithm need information from other class, maybe it is not suitable to extract method for a single java class/method?

Dear @zhipeng-cai,
Typically, no class is used in isolation. A better approach, I think, is to use the mock and stub objects to make your class ready for use in isolation. It is because at least the call graph construction used in our approach requires compilable Java code.
Such behavior is also observed in other Java Extract method refactoring tools. For example, JDeodrant requires all dependencies to extract object-based slices and the given project must be compilable.
I hope this would be helpful.


Home: Flag canceled events - High Priority

Flag canceled events on the home page as "canceled" (similar to the solution on the comprehensive meetings view).
On the meeting page, increase the size of and make more prominent the "canceled" flag.
If possible, also use strike-through on the meeting name on the meeting page, home page, and comprehensive meeting page.

@shrayshray - I implemented the above suggestions. See below for examples of the three affected pages.
Examples
Meetings: I moved the "Cancelled" label to the far right and increased its size.

Meeting detail: I moved the "Cancelled" label inline with the event name

Home

@reginafcompton this looks great and ready to go live!

It's live - example event.
Closing!


Service worker not getting registered

Bug Report or Feature Request (mark with an x)
- [x ] bug report -> please search issues before submitting
- [ ] feature request

Command (mark with an x)
- [ ] new
- [ ] build
- [ x] serve
- [ ] test
- [ ] e2e
- [ ] generate
- [ ] add
- [ ] update
- [ ] lint
- [ ] xi18n
- [ ] run
- [ ] config
- [ ] help
- [ ] version
- [ ] doc

Versions

Repro steps
Followed steps in the official doc for setting up the service worker: https://angular.io/guide/service-worker-getting-started
The log given by the failure

No errors, all goes well but when loading the app in the browser the service worker is not being registered.
Mention any other details that might be useful
Temp solution: manually registering the service worker in the main.ts file solves the issue:
platformBrowserDynamic().bootstrapModule(AppModule).then(() => {
  if ('serviceWorker' in navigator && environment.production) {
    navigator.serviceWorker.register('/ngsw-worker.js');
  }
}).catch(err => console.log(err));

Does it have anything to do with this https://github.com/angular/angular-cli/issues/8779#issuecomment-350737663 ?
We were having the same issue and it turned out we were using intervals from within the zone.

Hi, indeed this might be the case that the application doesn't get in a stable state.
However, the issue will be closed since the issue template was not followed. Ie no reproduction, nor details about the versions were provided.
If the problem persists kindly open a new issue and kindly fill the issue template and ideally provide a reproduction.
A good way to make a minimal repro is to create a new app via ng new repro-app and adding the minimum possible code to show the problem. Then you can push this repository to github and link it here.
This might be related to your directory structure so its really important to get an accurate repro to diagnose this.

I had the same problem but found a fix.
In app.module.ts the following was added:
        ServiceWorkerModule.register('ngsw-worker.js', {
            enabled: environment.production
        })

but this needed to be:
        ServiceWorkerModule.register('/ngsw-worker.js', {
            enabled: environment.production
        })

with the / in front of the ngsw-worker.js.
Hope this helps.

Same issue for me too!

I used the temporary solution that is mentioned here and now I have a different problem. Can this cause the service worker to be also working locally(ng serve)? (I know that the service worker shouldn't be working locally but somehow it does)

+1 We are experiencing the same problem.
/cc @unsafecode

Same problem here ... I cant register my service worker :-(

I have the same issue. Was working before I update to version 7.2.11.
"@angular/animations": "7.2.11",
"@angular/common": "7.2.11",
"@angular/compiler": "7.2.11",
"@angular/core": "7.2.11",
"@angular/forms": "7.2.11",
"@angular/http": "7.2.11",
"@angular/platform-browser": "7.2.11",
"@angular/platform-browser-dynamic": "7.2.11",
"@angular/platform-server": "7.2.11",
"@angular/pwa": "^0.10.2",
"@angular/router": "7.2.11",
"@angular/service-worker": "7.2.11",

Receiving the same issue.
"@angular/animations": "^7.1.1",
"@angular/cdk": "^6.3.3",
"@angular/common": "^7.1.1",
"@angular/compiler": "^7.1.1",
"@angular/core": "^7.1.1",
"@angular/flex-layout": "^7.0.0-beta.19",
"@angular/forms": "^7.1.1",
"@angular/http": "^7.1.1",
"@angular/material": "^6.3.3",
"@angular/material-moment-adapter": "^6.4.6",
"@angular/platform-browser": "^7.1.1",
"@angular/platform-browser-dynamic": "^7.1.1",
"@angular/pwa": "^0.13.7",
"@angular/router": "^7.1.1",
"@angular/service-worker": "^7.1.1",

+1

I have the same issue and the workaround doesn't seem to help either.

Why is this issue closed when it hasn't been solved yet?

same problem, I hope that in angular 8 it is solved

I am disappointed that this kind of bug exists and I would love to see it resolved without the need to apply a fix on my own code nevertheless as far as I saw, a developer issue.
I was able in a first time to apply a dirty code to force the service worker to register itself.
main.ts
if ('serviceWorker' in navigator && isProduction) {
    navigator.serviceWorker.register('./ngsw-worker.js');
}

Note: the ./ is very important to avoid an error with custom base href.
And after more search, I figured out that the culprit was my code...
These issues helped me:

https://github.com/angular/angular/issues/20970
https://github.com/angular/angular-cli/issues/8779

Basically, I made two mistakes while using:

fromEvent
SwUpdate

To fix them, I used applicationRef.isStable.
Example:
this.isStableSubscription = this.applicationRef.isStable.subscribe(isStable => {
    if (isStable) {
        fromEvent(window, 'resize').pipe(
            distinctUntilChanged(),
            debounceTime(30)
        ).subscribe(() => {

            // Do some stuff here
        });
        this.isStableSubscription.unsubscribe();
    }
});

Note: if applicationRef is causing a cyclic dependency, you shloud:

Use private injector: Injector in the constructor
Create a property and set it this.applicationRef = this.injector.get(ApplicationRef);

I just hit this bug with Angular 7.3.1. Why is the bug closed?

+1

This help me : https://github.com/angular/angular-cli/issues/8515#issuecomment-486017106

Same problem for me with angular-cli 7.3.9

And for me with Angular CLI 8.2.0-rc.0

It works if with angular-cli 7.3.9 with this solution:

add to main.ts:
platformBrowserDynamic().bootstrapModule(AppModule).then(() => {
if ('serviceWorker' in navigator && environment.production) {
navigator.serviceWorker.register('./ngsw-worker.js');
}
})
.catch(console.error);

in the app module set:
ServiceWorkerModule.register('./ngsw-worker.js', { enabled: environment.production })

in the manifest.json:
"scope": "/",
"start_url": "//",

Found a solution:
I too had this problem with my project, and spent a whole day trying to figure it out. Yes, starting a clean new project and installing the @angular/pwa works out of the box. But as soon as you start building a bit on your project, it silently fails / just doesn't load ngsw-worker.js.
Finally I downloaded the angular code and looked at the sources. It appears that there is a 'registrationStrategy' which has to do with if angular waits with the registration until your app is 'stable'. Now I have a bunch of stuff I'm loading at the beginning of my project (like oidc client and building websocket connections) and angular apparently thinks my app never is stable.
Fortunately you can override the registrationStrategy like so:
ServiceWorkerModule.register('ngsw-worker.js', { enabled: environment.production, registrationStrategy: 'registerImmediately' }),
See for the documentation here
After this the serviceworker will load, whatever the state of your app. There's also an option to pass an observable, so you can have it loaded whenever you think it's right.
I think this really really needs to be documented somewhere, preferably in the top of the docs with capital letters. Also, when the ngsw-worker doesn't load whenever it isn't stable, it would be VERY helpful to at least log something in the console!

@elgerm thank you very much!
And team, what about main problem? How to debug my application stabilization? Thanks!


Fixed typo.

It is still wrong, it should be createinstallmedia. :)

@Eitot That's what I get for trying to make a PR while reading on my iPad at 11pm :-P.
I think this should be better.


feat: check available tools in new command

fix https://github.com/denoland/wasmbuild/issues/48

side note: maybe deno should make console.warn and console.error more special , maybe some color changes or prefix them with warning/error emoji


Fix bugs & add feature

Currently under review.

@manusfreedom: Looks good!
@fichtner: Please merge.

Will bump version too, thanks @manusfreedom and @fraenki  :)


Deploy form validation updates

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

127 of 143 (88.81%)  changed or added relevant lines in 13 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.6%) to 85.034%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

people/models.py
3
5
60.0%

people/views.py
18
24
75.0%

accounts/views.py
17
25
68.0%

Totals

Change from base Build 997966525:
0.6%

Covered Lines:
875

Relevant Lines:
1029

💛  - Coveralls


⚠ Bofrost.be has degraded performance

In 1ff5f9b, Bofrost.be (https://www.bofrost.be) experienced degraded performance:

HTTP code: 200
Response time: 1869 ms

Resolved: Bofrost.be performance has improved in f66b615.


Migrate shares

Description
This PR adds a migrate command to the ocis cli with subcommands for migrating shares and public shares between providers.
Related Issue

https://github.com/owncloud/ocis/pull/3697

Types of changes

[ ] Bug fix (non-breaking change which fixes an issue)
[X] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)
[ ] Technical debt
[ ] Tests only (no source changes)

Checklist:

[X] Code changes
[ ] Unit tests added
[ ] Acceptance tests added
[ ] Documentation ticket raised:

:boom: Acceptance test localApiTests-apiSpaces-ocis failed. Further test are cancelled...


"Nicolae Bălcescu" is listed in the drop-down menu

Description:
"Nicolae Bălcescu" is listed in the drop-down menu alongside its corresponding county and commune, according to the law
Precondition:
The website is up an running.

Step 1
Type "Nicolae Bălcescu" in the search bar.

Expected results
The location is listed in the drop-down menu as "Nicolae Bălcescu, Botoșani (Flămânzi)".

ATTENTION:
Request - "Nicolae Bălcescu, Botoșani (Flămânzi)"
In dropbox, the request is displayed correctly. - "Nicolae Bălcescu, Botoșani (Flămânzi)"
After you click on the text, what is displayed in the window this is different - "Nicolae Bălcescu, Botoșani (FLĂMÂNZI)"


[Feature] Adding error code for unknown table

Search before asking

[X] I had searched in the issues and found no similar issues.

Description
In mysql, code 1146, 1049, 1051 represent  Table '%s.%s' doesn't exist, Unknown database '%s' and Message: Unknown table '%s' respectively. But I cannot find relevent error code in error table. Perhaps adding these error code will improve the user experience.
Use case
Run
DESCRIBE test_table -- non-existent table

current
ERROR 1105 (HY000): errCode = 2, detailMessage = Unknown table 'test_table'

expectation
ERROR <specialized error code> (HY000): errCode = 2, detailMessage = Unknown table 'test_table'

Related issues
No response
Are you willing to submit PR?

[ ] Yes I am willing to submit a PR!

Code of Conduct

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

i will look into it. pls assign to me


Raise minimum supported Swift version from 5.4 to 5.5

Motivation:
We periodically drop support for older Swift versions. Now that 5.7 has been released, 5.4 can be dropped.
Modifications:

Remove 5.4 specific Package.swift and docker-compose
Update the 5.7 docker-compose to use the released 5.7 and move from focal (2004) to jammy (2204)

Results:
Minimum Swift version is 5.5

CI updated. @swift-server-bot test this please


Set "public": true for sap.cloud to enable Workzone SE deployment

@nicoschoenteich We used your sample in our project, but had the issue that without the additional parameter for "public": true in sap.cloud the Build Workzone, standard edition was not able to find the HTML5 App.

For us this did the trick. If this is not the right way and we misconfigured the Workzone we can also close this one :)

Hi @RaphaelReply,
Thanks for the suggestion. All other samples in this repo are set to public too, so this makes sense.
Best, Nico


Export edition as app

Instead of hosting, authors should be able to export an edition for hosting elsewhere. We already build these in hosting; just bundle them as a zip instead. This will be easier after #282.
It should:

Download everything
Construct a book.json
Download all images
Grab bookish-reader repo
Build the book
Export a zip file

The resulting build should be suitable for hosting elsewhere.

Actually, this is easier than hosting. I'm working on this first so I can migrate existing books on my faculty webpage.

I got stuck on this: there's no way to build the book in a cloud function, since I can't run Sveltekit or Vite on the command line. But we can enable an export of the edition.json and chapter files so that at least authors can get an archive of the book text to store elsewhere. See the commented out code in functions/publishEdition.


iOS “Add to Home Screen” Incorrect URL

⚠ Please verify that this bug has NOT been raised before.

[X] I checked and didn't find similar issue

🛡 Security Policy

[X] I agree to have read this project Security Policy

Description
Hi,
I have found an issue where if I were to open a status page, and want to add it to the homescreen of my iOS device, that instead of making the web link https://yourserver.com/status/page1 it will make the shortcut https://yourserver.com instead.
I believe this article relates to it. Looks like that a manifest file needs to be updated to make it work. Is this something that could be fixed to automatically work?
Article: https://apple.stackexchange.com/questions/385417/add-to-home-screen-saves-wrong-url
👟 Reproduction steps

Open Safari
Navigate to your status page (ie. https://yourserver.com/status/page1)
click the Share icon in Safari
Scroll down and select “Add to Home Screen”
When it pops up asking what you want to call it, you can see that the url it is trying to add is https://yourserver.com instead of https://yourserver.com/status/page1
Click Add
Navigate to home screen and open new link
Find that it has directed to https://yourserver.com

👀 Expected behavior

Open Safari
Navigate to your status page (ie. https://yourserver.com/status/page1)
click the Share icon in Safari
Scroll down and select “Add to Home Screen”
When it pops up asking what you want to call it
Click Add
Navigate to home screen and open new link
Opens to specified status page

😓 Actual Behavior

Open Safari
Navigate to your status page (ie. https://yourserver.com/status/page1)
click the Share icon in Safari
Scroll down and select “Add to Home Screen”
When it pops up asking what you want to call it, you can see that the url it is trying to add is https://yourserver.com instead of https://yourserver.com/status/page1
Click Add
Navigate to home screen and open new link
Find that it has directed to https://yourserver.com

🐻 Uptime-Kuma Version
1.15.0
💻 Operating System and Arch
Raspian on RPi4
🌐 Browser
Safari on iOS and iPadOS
🐋 Docker Version
Docker 20.10.14
🟩 NodeJS Version
No response
📝 Relevant log output
No response

It is because currently start_url is pointing to /.
https://github.com/louislam/uptime-kuma/blob/d39dc944960fa9c75ee6d3b95637ff6566bd09b5/public/manifest.json#L4
If it is needed, I think we need to add a dynamic manifest file.

Hi @louislam, first time commenting here.
I think it would be really useful to make a dynamic manifest file for the status pages.
As I see it, you can create a handful of different status pages for each group or area and each member can add it to the home screen as needed.
Thanks by the way, really great job!

Maybe this could be a solution...
[...] However, this will also map https://example.com/test/manifest.json to https://example.com/, which fails because it's in a folder outside the scope of the manifest.
Instead, if you are using a sub-directory you need to set both a scope and the start_url:
"start_url": "./"
"scope": "."
This will cause https://example.com/test/manifest.json to map to https://example.com/test/ as expected.
full post on: https://stackoverflow.com/a/56128412


Only one plugin in the js directory

The only plugin in the js directory is SVG.
I keep getting an error, "Uncaught Error: The "sideTip" plugin is not defined."
This is after very basic config.
Under CSS you have a ton of plugins.
I'm assuming the bundle is supposed to include the plugins?  Not there either.
Looked in your github source.  Not there either.

Hello, the bundle file includes Tooltipster's core + sideTip. You must have used the '.core.js' file if you get this error.

My bad.  I was absolutely sure I was grepping the bundle source.  Must be lack of sleep.

No problem.


Being able to interact programatically with DHCP/TFTP

I would like to be able to define some callbacks in the DHCP/TFTP code. Examples:

Reply only to some clients.
Being able to reply DHCP with some extra vendor values.
Being able to serve TFTP from Python objects instead of filesystem objects (synthetic filesystem). For instance, PXE configuration files could be synthetically generated by client.

I could volunteer if you are interested in those features. I need them for my own purposes.

PyPXE isn't meant to be a general purpose DHCP system, but I can see these being useful for its purpose.

Replying to some clients can somewhat be done with --dhcp-whitelistwhitelist and --static-config, if you enumerate the clients you want to reply to. This is how I use it.
Programatic control over vendor options would be useful. I would happily accept a PR.
Programatic TFTP/HTTP responses would be useful. I would happily accept a PR. I want to keep this lightweight, but maybe something like the routes in Bottle with fewer verbs (only GET) implemented for TFTP and HTTP.


Df.iloc impl

Hello @1e-to! Thanks for opening this PR. We checked the lines you've touched for PEP 8 issues, and found:

In the file sdc/datatypes/hpat_pandas_dataframe_functions.py:

Line 1803:107: W291 trailing whitespace

add reviewers pls


fix($location): handle plus character in query strings

Closes #3042

I faced this problem on 1.3.15 and reading this I upgraded to 1.3.16. The result is that now I have no idea what the URL will contain! Sometimes + is encoded as %20 and sometimes as %2B and this is really random. I also upgraded to 1.4.3 and problem was there, as in 1.3.15. For my case this fix made it even worse.


eth_estimate_gas error in testnet

I'm using zkSync Era testnet for test transfer eth use python code, but it had ContractLogicError(execution reverted) when use zksync.eth_estimate_gas method,  I'm sure the wallet has enough eth(0.00988 eth) only transfer 0.0001 eth to other wallet,
my python envoriment: python 3.10 & zksync2 0.6.0
the code is forked from examples/02_transfer.py
could someone help me to fix it?

same problem

same as well

This should be resolved with latest release. Also you cen checkout examples here


Unable to copy folder content from network folder

Node version (or tell us if you're using electron or some other framework):
Node 10.21.0
ShellJS version (the most recent version/Github branch you see the bug on):
0.8.5
Operating system:
Windows 10
Description of the bug:
When I try to copy all content (*) from a network folder I get an error saying "No such file or directory". Copying the folder itself works fine.
If I try to copy all content (*) from a folder on a local drive to another local folder it works as expected.
Example ShellJS command to reproduce the error:
var shell = require("shelljs");
shell.cp('-rf', '//SERVER/Products/MyProduct/*', 'C:\\Temp');   //Fails
shell.cp('-rf', 'C:\\Products\\MyProduct\\*', 'C:\\Temp');         //Works
shell.cp('-rf', '//SERVER/Products/MyProduct', 'C:\\Temp');     // Works

Sounds like the glob expansion is failing for the network drive. This is probably an issue specific to how Windows works, since it sounds like it's not returning the directory listing.
Can you test what https://github.com/isaacs/node-glob does for the same path?


Generates Python reserved words

When processing https://github.com/srdja/Collections-C/blob/master/src/include/array.h#L110 , the following definition is created:
cc_stat array_subarray(Array* ar, size_t from, size_t to, Array** out)

Cython throws an error at this line because from is a Python reserved word. Can a list of such words be maintained so those words are mangled in the pxd?

I'm working on a fix for this, by appending underscores and including the C name as a string, which is how cython allows you to get around this issue when you're manually making pxd files.
So for example:
typedef int class;
void global(class foo);

becomes
ctypedef int class_ 'class'
cdef void global_ 'global'(class_ foo)

A remaining question I have is, should we escape names that are python/cython reserved words only, or should we also escape ones that shadow built in names, but are not actually syntax errors to include?

Decided it would be too intrusive to disallow shadowing builtins, it would come up very often. There are workarounds if shadowing a builtin, so I'll leave it. Whereas keywords are syntax errors.

Fixed by #9


Error: couldn't find provider | M1 Macbook | iOS

I keep getting Error: couldn't find provider | M1 Macbook every time I call ShareMenuReactView.data() or ShareMenuReactView.continueInApp().
It occurs under index.share.js file.
Code is as follows:

/**
 * @format
 */

import {AppRegistry} from 'react-native';
import React, {useEffect} from 'react';
import {View} from 'react-native';
import {ShareMenuReactView} from 'react-native-share-menu';

const Share = () => {
  useEffect(() => {
    ShareMenuReactView.data().then(({mimeType, data}) => {
      ShareMenuReactView.continueInApp({data, mimeType});
    });
  }, []);

  return <View />;
};

AppRegistry.registerComponent('ShareMenuModuleComponent', () => Share);

It only occurs on iOS builds generated using M1 Macbooks. Works fine on Intel Macbooks.
PS: Use of useEffect doesn't influence the outcome. Even if I run the exact same index.share.js file as in the example, it gives me the same issue.

Hey, I also have the same issue and just as @m-zaink  has state it only occurs in IOS builds which is being generated in M1 Pro macbook.

Also encountered this issue when building in M1 Mac Mini. Is there any updates or more details on what caused the error?

is there any update for this problem right now? I still got the issue with my M1 Mac Mini.

@kubik369 Hi Kubik, thanks for the alternative solution. I think I use "react-native-share-menu": "^5.0.4" and it was working fine on the device but not on the emulator (Error: couldn't find provider | M1 Macbook still exists). how about you?

Hm, that's interesting. For me, it works on both the emulator and on real devices. Have you tried selecting/downloading a clean simulator device? Are you running it through rosetta or natively?

Any update of this issue?

I also the same issue, any solution for this? I'm using macbook air M1 @m-zaink

confirm it's working on ios actual device, and not working on the simulator and gets Error: couldn't find provider. I'm using M1 macbook

I will reiterate that it is working for me on M1 Macbook Air, so you most probably have to change something in your config, either you are running xcode or some other part of the toolchain through rosetta or (I am not sure whether this is still required) you don't have the swift bridging file, or something else :)


load_model fails with error ValueError: axes don't match array

The model includes a custom loss and 2 outputs.
The below is the dump
In [3]: keras.version
Out[3]: '2.1.3'
In [5]: tf.version
Out[5]: '1.6.0-rc0'
In [6]: model=load_model("/home/julian/kaggle/sbowl2018/saved_models/model.h5")
AttributeError                            Traceback (most recent call last)
~/virtualenvs/tensorflowgpu/lib/python3.6/site-packages/numpy/core/fromnumeric.py in _wrapfunc(obj, method, *args, **kwds)
51     try:
---> 52         return getattr(obj, method)(*args, **kwds)
53
AttributeError: 'Dataset' object has no attribute 'transpose'
During handling of the above exception, another exception occurred:
ValueError                                Traceback (most recent call last)
 in ()
----> 1 model=load_model("/home/julian/kaggle/sbowl2018/saved_models/model.h5")
~/virtualenvs/tensorflowgpu/lib/python3.6/site-packages/keras/models.py in load_model(filepath, custom_objects, compile)
244
245         # set weights
--> 246         topology.load_weights_from_hdf5_group(f['model_weights'], model.layers)
247
248         # Early return if compilation is not required.
~/virtualenvs/tensorflowgpu/lib/python3.6/site-packages/keras/engine/topology.py in load_weights_from_hdf5_group(f, layers)
3151                                                        weight_values,
3152                                                        original_keras_version,
-> 3153                                                        original_backend)
3154         if len(weight_values) != len(symbolic_weights):
3155             raise ValueError('Layer #' + str(k) +
~/virtualenvs/tensorflowgpu/lib/python3.6/site-packages/keras/engine/topology.py in preprocess_weights_for_loading(layer, weights, original_keras_version, original_backend)
3048                 weights[1] = conv_utils.convert_kernel(weights[1])
3049         if K.int_shape(layer.weights[0]) != weights[0].shape:
-> 3050             weights[0] = np.transpose(weights[0], (3, 2, 0, 1))
3051             if layer.class.name == 'ConvLSTM2D':
3052                 weights[1] = np.transpose(weights[1], (3, 2, 0, 1))
~/virtualenvs/tensorflowgpu/lib/python3.6/site-packages/numpy/core/fromnumeric.py in transpose(a, axes)
573
574     """
--> 575     return _wrapfunc(a, 'transpose', axes)
576
577
~/virtualenvs/tensorflowgpu/lib/python3.6/site-packages/numpy/core/fromnumeric.py in _wrapfunc(obj, method, *args, **kwds)
60     # a downstream library like 'pandas'.
61     except (AttributeError, TypeError):
---> 62         return _wrapit(obj, method, *args, **kwds)
63
64
~/virtualenvs/tensorflowgpu/lib/python3.6/site-packages/numpy/core/fromnumeric.py in _wrapit(obj, method, *args, **kwds)
40     except AttributeError:
41         wrap = None
---> 42     result = getattr(asarray(obj), method)(*args, **kwds)
43     if wrap:
44         if not isinstance(result, mu.ndarray):
ValueError: axes don't match array

+1

Hi,
We could work on this better if you could provide a standalone reproducible example.
Some advices:

Don't use custom data or custom paths.
Use random arrays or even np.ones, np.zeros.
The example should run with Keras (and deps) alone.
Should be Python3 compatible.
Should not be OS specific.
The file should reproduce the bug with *high fidelity.
Link to a gist would be appreciated.

Thanks!
Dref360

Hi,
this has been overtaken by events / used a workaround time ago. I do no longer have the code for these tests. I regret I can't pitch in.
JC

I got the similar problem when I load a model trained by 2 GPUs. However, the loading model trained by 1 GPU works good.
"ValueError: axes don't match array"

I get the same problem.
If I train a model using 2 GPUs, using multi_gpu_model and ModelCheckpoint callback to save best, it gives this error when calling load_model on the checkpoint saved model.
I want to train the model using multi gpus but run it again on a single GPU. this seems to fail

model = load_model(model_to_use, custom_objects={'mean_iou': mean_iou,'iou_bce_loss':iou_bce_loss})
produces the axes don't match array error - model file from checkpoint has same result as a model saved after completion of model.fit_generator.  Two GPU's used for training.  Model ran for three days.
ValueError                                Traceback (most recent call last)
 in
1 #model = load_model(model_to_use, custom_objects={'mean_iou': mean_iou,'iou_bce_loss':iou_bce_loss})
----> 2 model = load_model(model_to_use)
~\Anaconda3\lib\site-packages\keras\engine\saving.py in load_model(filepath, custom_objects, compile)
417     f = h5dict(filepath, 'r')
418     try:
--> 419         model = _deserialize_model(f, custom_objects, compile)
420     finally:
421         if opened_new_file:
~\Anaconda3\lib\site-packages\keras\engine\saving.py in _deserialize_model(f, custom_objects, compile)
272                                                        original_keras_version,
273                                                        original_backend,
--> 274                                                        reshape=False)
275         if len(weight_values) != len(symbolic_weights):
276             raise ValueError('Layer #' + str(k) +
~\Anaconda3\lib\site-packages\keras\engine\saving.py in preprocess_weights_for_loading(layer, weights, original_keras_version, original_backend, reshape)
680         weights = convert_nested_time_distributed(weights)
681     elif layer.class.name in ['Model', 'Sequential']:
--> 682         weights = convert_nested_model(weights)
683
684     if original_keras_version == '1':
~\Anaconda3\lib\site-packages\keras\engine\saving.py in convert_nested_model(weights)
668                     weights=weights[:num_weights],
669                     original_keras_version=original_keras_version,
--> 670                     original_backend=original_backend))
671                 weights = weights[num_weights:]
672         return new_weights
~\Anaconda3\lib\site-packages\keras\engine\saving.py in preprocess_weights_for_loading(layer, weights, original_keras_version, original_backend, reshape)
680         weights = convert_nested_time_distributed(weights)
681     elif layer.class.name in ['Model', 'Sequential']:
--> 682         weights = convert_nested_model(weights)
683
684     if original_keras_version == '1':
~\Anaconda3\lib\site-packages\keras\engine\saving.py in convert_nested_model(weights)
656                     weights=weights[:num_weights],
657                     original_keras_version=original_keras_version,
--> 658                     original_backend=original_backend))
659                 weights = weights[num_weights:]
660
~\Anaconda3\lib\site-packages\keras\engine\saving.py in preprocess_weights_for_loading(layer, weights, original_keras_version, original_backend, reshape)
799             weights[0] = np.reshape(weights[0], layer_weights_shape)
800         elif layer_weights_shape != weights[0].shape:
--> 801             weights[0] = np.transpose(weights[0], (3, 2, 0, 1))
802             if layer.class.name == 'ConvLSTM2D':
803                 weights[1] = np.transpose(weights[1], (3, 2, 0, 1))
~\Anaconda3\lib\site-packages\numpy\core\fromnumeric.py in transpose(a, axes)
596
597     """
--> 598     return _wrapfunc(a, 'transpose', axes)
599
600
~\Anaconda3\lib\site-packages\numpy\core\fromnumeric.py in _wrapfunc(obj, method, *args, **kwds)
49 def _wrapfunc(obj, method, *args, **kwds):
50     try:
---> 51         return getattr(obj, method)(*args, **kwds)
52
53     # An AttributeError occurs if the object does not have
This seems to be an issue that your letting lie and festering so not going to bother spending time to further document the issue as I don't really have the skill set to get all you want.   Will try the workaround.

For the solution of this problem, i got the suggestion saying that instead of saving 'multi_gpu_model' and loading  'multi_gpu_model' . I should:

define a model
define and  compile a multi_gpu_model
training using the multi_gpu_model
during the saving, still saving the model instead of the multi_gpu_model
load the model.
So the trick should be:

multi_gpu_model = multi_gpu_model(model, gpus=G)
model.save_model(...)

Instead of
multi_gpu_model = multi_gpu_model(model, gpus=G)
multi_gpu_model.save_model(...)

Please pay attention to the slight difference. I got this suggestion, however, I did't try it as I don't have time and I gave up using multiple GPU to train the model.  Hope it is helpful on this problem.

Thanks jimmy shen
I have had great success over the last 6 weeks using two GPU’s to train a bunch of different models on two different PC’s.
Today’s failure is very unique – but I did something different.  I trained the model.  Saved it and its weights.  Loaded it and ran it some more with different parameters, all within the same script.   Don’t think I have done this before.   But – to add mystery to the issue I had to do a full clean install of Windows, anaconda, etc.  So the versions of the various stuff that worked for the last 6 weeks are not the same versions as this mornings failure.  Later I will try to load the model into my 2nd PC that still has all versions from 5-6 weeks ago rather than the latest and often not the greatest versions.
Pretty new to Python – 8 weeks and counting – I am finding that keeping Python running is harder task than learning the code.  It seems to be a very unstable process.
Will try the suggestion later today.
Thanks from another Jimmy
Sent from Mail for Windows 10
From: jimmy shen
Sent: Thursday, October 18, 2018 10:52 AM
To: keras-team/keras
Cc: PCJimmmy; Comment
Subject: Re: [keras-team/keras] load_model fails with error ValueError: axesdon't match array (#9562)
For the solution of this problem, i got the suggestion saying that instead of saving 'multi_gpu_model' and loading 'multi_gpu_model' . I should:

define a model
define and compile a multi_gpu_model
training using the multi_gpu_model
during the saving, still saving the model instead of the multi_gpu_model
load the model.
So the trick should be:
multi_gpu_model = multi_gpu_model(model, gpus=G)
model.save_model(...)
Instead of
multi_gpu_model = multi_gpu_model(model, gpus=G)
multi_gpu_model.save_model(...)
Please pay attention to the slight difference. I got this suggestion, however, I did't try it as I don't have time and I gave up using multiple GPU to train the model. Hope it is helpful on this problem.
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub, or mute the thread.

I just had this problem and just wanted to let any future readers know that @liketheflower and @PCJimmmy have it right. Save the model, not the multi_gpu_model.

Closing as this is resolved

But what if I want to save the multi_gpu_model during the training? And not necessarily its last epoch?

Does anyone know any workaround to simply load the problematic multiple GPU weight? I mean I now know the right way to save the weights, but I don't have time to retrain a model. Is it still possible to load a (problematic) weight file?

Solution of @liketheflower works well. As for someone may want to save the multi_gpu_model during the training, solution of @RaiAbhishek can helps but not that easily to implement. Here is my solution for saving model with callbacks:
class MyModelCheckPoint(ModelCheckpoint):
model = create_model()
parallel_model = multi_gpu_model(model, gpus=n)
parallel_model.compile(...)

class MyModelCheckPoint(ModelCheckpoint):
    def __init__(self, model, *args, **kwargs):
        self.model = model
        super(MyModelCheckPoint, self).__init__(*args, **kwargs)
checkpoint = MyModelCheckPoint(model, filepath, ...)

parallel_model.fit(..., callbacks=[checkpoint])

For those who want to save multi_gpu model during training. You can change the model in callback to do it: (inspired by @RaiAbhishek )
single_model = create_model()
parallel_model = multi_gpu_model(single_model, gpus=n)
parallel_model.compile(...)

class MyModelCheckPoint(ModelCheckpoint):

    def __init__(self, singlemodel, *args, **kwargs):
        self.singlemodel = singlemodel
        super(MyModelCheckPoint, self).__init__(*args, **kwargs)
    def on_epoch_end(self, epoch, logs=None):
        self.model = self.singlemodel
        super(MyModelCheckPoint, self).on_epoch_end(epoch, logs)

checkpoint = MyModelCheckPoint(single_model, filepath, save_best_only=True, ...)
parallel_model.fit(..., callbacks=[checkpoint])

The discussion moved towards multi-gpu but the problem persists in even single gpu setups. I have written a dummy script to reproduce the error as @Dref360 asked.
First the error doesn't show up if we use only basic layers. The InceptionResNetV2 brings out the issue.
Secondly, the load_model takes an insanely long duration to execute.
The code:
import numpy as np
import os
from keras.layers import Input, Flatten, Dense, Dropout, Lambda, Conv2D, MaxPooling2D, Concatenate
from keras.models import Model, load_model
from keras import backend as K
from keras.optimizers import RMSprop
from keras.losses import cosine_proximity
from keras.applications.inception_resnet_v2 import InceptionResNetV2

os.environ['CUDA_VISIBLE_DEVICES'] = '0'

def euclidean_distance(vects):
	x, y = vects
	sum_square = K.sum(K.square(x - y), axis=1, keepdims=True)
	return K.sqrt(K.maximum(sum_square, K.epsilon()))

def eucl_dist_output_shape(shapes):
	shape1, shape2 = shapes
	return (shape1[0], 1)

def dummy_train_case():
	tr_pairs = np.array(np.zeros((10, 2, 128, 128, 3)))
	tr_y = np.array(np.zeros((10,)))
	te_pairs = np.array(np.zeros((11, 2, 128, 128, 3)))
	te_y = np.array(np.zeros((11,)))
	input_shape = tr_pairs.shape[2:]

	input = Input(shape=input_shape)
	base_model = InceptionResNetV2(include_top=False, weights=None, input_shape=input_shape)
	x = base_model(input)
	x = Flatten()(x)
	x = Dense(1024, activation='relu')(x)
	x = Dense(128, activation='relu')(x)
	base_network = Model(input, x)

	input_a = Input(shape=input_shape)
	input_b = Input(shape=input_shape)

	processed_a = base_network(input_a)
	processed_b = base_network(input_b)
	distance = Lambda(euclidean_distance, output_shape=eucl_dist_output_shape)([processed_a, processed_b])
	model = Model([input_a, input_b], distance)
	rms = RMSprop(lr=0.001)
	model.compile(loss=cosine_proximity, optimizer=rms)

	model.fit([tr_pairs[:, 0], tr_pairs[:, 1]], tr_y,
			  batch_size=48,
			  epochs=10,
			  validation_data=([te_pairs[:, 0], te_pairs[:, 1]], te_y))
	model.save(model_save_path)

if __name__ == '__main__':
	model_save_path = '/path/to/models/siamese_models/1.hf5'
	dummy_test_case()
	print('model saved')
	model = load_model(model_save_path)
	print('model loaded. Summary: {}'.format(model.summary()))

The full error stack:
Traceback (most recent call last):
File "/home/walle/PycharmProjects/keras_siamese/tests.py", line 60, in
model = load_model(model_save_path)
File "/home/walle/virtual_environments/tf1.13/lib/python3.5/site-packages/keras/engine/saving.py", line 419, in load_model
model = _deserialize_model(f, custom_objects, compile)
File "/home/walle/virtual_environments/tf1.13/lib/python3.5/site-packages/keras/engine/saving.py", line 274, in _deserialize_model
reshape=False)
File "/home/walle/virtual_environments/tf1.13/lib/python3.5/site-packages/keras/engine/saving.py", line 682, in preprocess_weights_for_loading
weights = convert_nested_model(weights)
File "/home/walle/virtual_environments/tf1.13/lib/python3.5/site-packages/keras/engine/saving.py", line 670, in convert_nested_model
original_backend=original_backend))
File "/home/walle/virtual_environments/tf1.13/lib/python3.5/site-packages/keras/engine/saving.py", line 682, in preprocess_weights_for_loading
weights = convert_nested_model(weights)
File "/home/walle/virtual_environments/tf1.13/lib/python3.5/site-packages/keras/engine/saving.py", line 658, in convert_nested_model
original_backend=original_backend))
File "/home/walle/virtual_environments/tf1.13/lib/python3.5/site-packages/keras/engine/saving.py", line 801, in preprocess_weights_for_loading
weights[0] = np.transpose(weights[0], (3, 2, 0, 1))
File "/home/walle/virtual_environments/tf1.13/lib/python3.5/site-packages/numpy/core/fromnumeric.py", line 639, in transpose
return _wrapfunc(a, 'transpose', axes)
File "/home/walle/virtual_environments/tf1.13/lib/python3.5/site-packages/numpy/core/fromnumeric.py", line 56, in _wrapfunc
return getattr(obj, method)(*args, **kwds)
ValueError: axes don't match array

For the solution of this problem, i got the suggestion saying that instead of saving 'multi_gpu_model' and loading 'multi_gpu_model' . I should:

define a model
define and  compile a multi_gpu_model
training using the multi_gpu_model
during the saving, still saving the model instead of the multi_gpu_model
load the model.
So the trick should be:

multi_gpu_model = multi_gpu_model(model, gpus=G)
model.save_model(...)

Instead of
multi_gpu_model = multi_gpu_model(model, gpus=G)
multi_gpu_model.save_model(...)

Please pay attention to the slight difference. I got this suggestion, however, I did't try it as I don't have time and I gave up using multiple GPU to train the model. Hope it is helpful on this problem.

I don't know, I am having this issue and I have proceeded as you indicate by using model.save instead of multi_gpu.save

I just had this problem and just wanted to let any future readers know that @liketheflower and @PCJimmmy have it right. Save the model, not the multi_gpu_model.

But is this really saving the trained weights? I made a little sample at https://github.com/LeninGF/Mnist_ConvNet_MultiGPU it happened that saving and loading with the model.save returned a model, was able to load it, but it had no trained weights

#10949 #13392 I came acrossed this issue and fixed it by setting the same weights to frozen as when training before loading the model. You can then unfreeze the weights and do what you like. For example
def fix_this_stupid_bug():
    # get model
    model = create_model()

    # freeze layers that were frozen during training
    for layer in model.layers:
        if should_freeze(layer):
            layer.trainable = False

    # load weights
    model.load_weights(weights_path)

    # unfreeze model
    for layer in model.layers:
        layer.trainable = True

    # save unfrozen weights
    model.save_weights(out_path)

you can check whether the model is trainable,  if its trainable is false,  maybe encounter this error.


Update Technical Master Plan

Intention:  1) eliminate redundancies; 2) bring statements of OVN vision, mission, and objectives up to date with Fall 2000 Steering Committee decisions; 3) align research on prior standards to Master Plan sections on critical OVN components.  A tighter, stronger document to start the new year, suitable for viewing by prospective sponsors.

@oitacoleman approves this pull request #111

@oitacoleman approves this pull request #111

Reviewed, corrected conflicts within JCStine-patch-7 branch pull request to Master Plan.  Believe all is set to go.

Reviewed, corrected conflicts within JCStine-patch-7 branch pull request to Master Plan.  Believe all is set to go.

Hi @jcstine - you can now merge this.

Hi @jcstine - you can now merge this.

Merged as of 2021.01.22 per Maridob

Merged as of 2021.01.22 per Maridob


os.detected.classifier from transient dependancy not set and gioving build errors

Is there a preconfiguration needed for {os.detected.classifier} to be populated?
Errors occurred while build effective model from /.gradle/caches/modules-2/files-2.1/org.microbean/microbean-helm/<IP_ADDRESS>.0.4/44fb98754ff742b4a237718238bd9cced7906ffd/microbean-helm-<IP_ADDRESS>.0.4.pom:     'build.resources.resource.directory' is missing. in org.microbean:microbean-helm:<IP_ADDRESS>.0.4 Errors occurred while build effective model from /.gradle/caches/modules-2/files-2.1/org.microbean/microbean-development-annotations/0.1.3/abaddafbff41cfff5f9332014aa30a7506498e6d/microbean-development-annotations-0.1.3.pom:     'build.resources.resource.directory' is missing. in org.microbean:microbean-development-annotations:0.1.3 Errors occurred while build effective model from /.gradle/caches/modules-2/files-2.1/org.microbean/microbean-kubernetes/0.1.1/7fdace2d7ffa0c5e56e9f588ecc632a6333fe655/microbean-kubernetes-0.1.1.pom:     'build.resources.resource.directory' is missing. in org.microbean:microbean-kubernetes:0.1.1 <ij_msg_gr>Project resolve errors<ij_msg_gr><ij_nav>/build.gradle<ij_nav>root project 't-admin': Unable to resolve additional project configuration.<eol>Details: org.gradle.api.internal.artifacts.ivyservice.DefaultLenientConfiguration$ArtifactResolveException: Could not resolve all files for configuration ':compileClasspath'.<eol>Caused by: org.gradle.internal.resolve.ArtifactNotFoundException: Could not find netty-tcnative-boringssl-static-${os.detected.classifier}.jar (io.netty:netty-tcnative-boringssl-static:2.0.6.Final).<eol>Searched in the following locations:<eol>    https://binrepo.target.com/artifactory/tgt-repo/io/netty/netty-tcnative-boringssl-static/2.0.6.Final/netty-tcnative-boringssl-static-2.0.6.Final-${os.detected.classifier}.jar <ij_msg_gr>Project resolve errors<ij_msg_gr><ij_nav>/t-admin/build.gradle<ij_nav>root project 't-admin': Unable to resolve additional project configuration.<eol>Details: org.gradle.api.artifacts.ResolveException: Could not resolve all dependencies for configuration ':compileClasspath'.<eol>Caused by: org.gradle.internal.resolve.ArtifactNotFoundException: Could not find netty-tcnative-boringssl-static-${os.detected.classifier}.jar (io.netty:netty-tcnative-boringssl-static:2.0.6.Final).<eol>Searched in the following locations:<eol>    .../2.0.6.Final/netty-tcnative-boringssl-static-2.0.6.Final-${os.detected.classifier}.jar

duplicate

solution is in #135


Add ijl box variations

Codecov Report

Merging #374 (4e95474) into main (08cc624) will decrease coverage by 3.81%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main     #374      +/-   ##
==========================================
- Coverage   76.09%   72.27%   -3.82%
==========================================
  Files          17       17
  Lines        4074     3878     -196
==========================================
- Hits         3100     2803     -297
- Misses        974     1075     +101

Impacted Files
Coverage Δ

src/compiler.jl
74.46% <100.00%> (-0.30%)
:arrow_down:

src/compiler/orcv2.jl
0.00% <0.00%> (-72.39%)
:arrow_down:

src/compiler/interpreter.jl
30.95% <0.00%> (-69.05%)
:arrow_down:

src/compiler/utils.jl
43.54% <0.00%> (-36.14%)
:arrow_down:

src/logic.jl
75.00% <0.00%> (-5.00%)
:arrow_down:

src/compiler/validation.jl
62.05% <0.00%> (-2.96%)
:arrow_down:

src/compiler/pmap.jl
79.45% <0.00%> (-1.70%)
:arrow_down:

src/api.jl
51.11% <0.00%> (-1.38%)
:arrow_down:

src/pmap.jl
83.33% <0.00%> (-1.29%)
:arrow_down:

src/typeanalysis.jl
90.00% <0.00%> (-0.91%)
:arrow_down:

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@wsmoses can you add a test?

bump on test?


Preserve alpha for small enough PNG media

Describe the Feature
As it stands and I understand it right now, Bluesky performs lossy compression on all media uploaded. It is possible to get a less artifacted version from an image uploaded in the CDN with the (at)png URL suffix, but I feel this may be overkill for images that are already tiny or preoptimized, such as PNG-8 with an alpha channel.
Currently, the alpha channel even for very small images is crunched down into black. Optimizations can be put in place to reduce a small image's filesize without compromising this or 1x quality.
Attachments
In X (formerly Twitter), PNG images with an alpha channel—presumably under a certain filesize—have their alpha channel and other features intact. This is visible when using the lightbox:

Describe Alternatives
No response
Additional Context
The implementation of this may help pixel artists and preoptimizing artists greatly. I suppose this also has to do with how the images are presented, but I believe that's fit for another issue.

do note that this is more for the processing and the CDN, but I could not think of a better place to write this issue in.

This might overlap with #5855 and the mentioned issue #1101
I agree though, alpha should work in PNGs

It's possible, but I believed it to be sufficiently scoped to be something to focus on specifically thus I made it a separate issue.

The sense I'm getting is that how media is prepared for the frontend needs some significant attention to make it suitable for artistic content, or any content that requires the author to have control of its presentation. Mashing quality into paste is basically fine for meme-generator content and rough cellphone video, half of which already blurry and artifacted to start with, but a lot of the primary content that drives the platform requires some level of artistic control.
I ran into this on my first day on the platform—I tried posting a very small (in terms of file size) visual showcase of a user interface element I'd coded, and despite trying different tricks to try to get it to display cleanly, it always came out as a blurry mess served at 360p tops. That's just one little example with its own separate issue, but there are a ton rough spots all affecting file uploads, and they interact with each other. Makes the platform feel bad for creators, and creators are a large part of what keeps the social network healthy. I think it deserves serious attention.

I know hosting high-resolution content is expensive! I don't think the answer is to just crank up all the dials indiscriminately. But I do think it deserves serious attention.

Especially when it's been discussed that sometimes Bluesky's compression algorithm INCREASES the file size compared to original, much more apparent when it is pixel art (my main type of content). Hitting the sweetspot for quality, data saving and artist satisfaction is difficult indeed


Disable / hide buttons (ideally through config) on NMRium

Buttons with icons such as save, help etc, are confusing and often misleading the users on a repository-embedded nmrium instance. It makes perfect sense as a standalone but now that we have plenty of users using nmrium on nmrxiv and chemotion, these options needs to be configurable and be hidden on a repository setup

Resolved through workspace settings


Recommened property

Would there be any way to throw an exception upon a recommended property?
Ie:
{
    "type": "object",
    "properties": {
        "data": {
            "oneOf": [
                { "$ref": "#/definitions/integerData" },
                { "$ref": "#/definitions/stringData" }
            ]
        },
        "name": {
            "type": "string",
            "maxLength": 25
        },
    },
    "required": ["data"],
    "recommended": ["name"]
    "definitions": {
        "integerData" : {
            "type": "integer",
            "minimum" : 0
        },
        "stringData" : {
            "type": "string"
        }
    }
}

Result (if missing):
Recommended property name is missing.

Unfortunately not in this library - recommended is not part of the JSON Schema specification.


DNS resolve issue of workers

Unable to execute mpiexec because of failure of name resolution of workers dns.Kindly guide me what is wrong and what need to  checked
kubectl -n mpi get po
NAME            READY   STATUS    RESTARTS   AGE
mpic-master     2/2     Running   0          14m
mpic-worker-0   1/1     Running   0          14m
mpic-worker-1   1/1     Running   0          14m
mpic-worker-2   1/1     Running   0          14m
kubectl -n $KUBE_NAMESPACE exec -it $MPI_CLUSTER_NAME-master /bin/bash
root@mpic-master:/# cat /kube-openmpi/generated/hostfile
mpic-master.mpic
mpic-worker-0
mpic-worker-1
mpic-worker-2
mpirun --allow-run-as-root  --display-map -n 1 -npernode 1 --hostfile /kube-openmpi/generated/hostfile   -- hostname
ssh: Could not resolve hostname mpic-worker-0: Temporary failure in name resolution
ORTE was unable to reliably start one or more daemons.
This usually is caused by:

not finding the required libraries and/or binaries on
one or more nodes. Please check your PATH and LD_LIBRARY_PATH
settings, or configure OMPI with --enable-orterun-prefix-by-default

lack of authority to execute on one or more specified nodes.
Please verify your allocation and authorities.

the inability to write startup files into /tmp (--tmpdir/orte_tmpdir_base).
Please check with your sys admin to determine the correct location to use.

compilation of the orted with dynamic libraries when static are required
(e.g., on Cray). Please check your configure cmd line and consider using
one of the contrib/platform definitions for your system type.

an inability to create a connection back to mpirun due to a
lack of common network interfaces and/or no route found between
them. Please check network connectivity (including firewalls
and network routing requirements).

ssh: Could not resolve hostname mpic-master.mpic: Temporary failure in name resolution
ssh: Could not resolve hostname mpic-worker-2: Temporary failure in name resolution
ssh: Could not resolve hostname mpic-worker-1: Temporary failure in name resolution

Above issue is not related to openmpi. It was related to dns issue to kubenetes setup and solved by upgrading to 1.13.
Thanks


Tinkers Con Capacitor Modifier

Enigmatica 6 (expert): 0.5.24
Forge: 36.2.22
Tcon:<IP_ADDRESS>4
Materialis: 1.16.5-2.4.2
Having an issue with the capacitor modifiers

tool does not seem to use RF just durability

Thanks

A response from the Materials dev would be helpful, but I believe this is meant for tools that already use FE. Not to add FE usage to tools that normally use durability:

Since we don't have Draconic, we might be missing some other modifiers that would make this make more sense.

materialis 2.5.0 has been released, redstone arsenal compatibility was added and the capacitor modifier is only enabled if draconic evolution or redstone arsenal is installed.

Awesome, thanks!


[ISSUE #3932] refactor shenyu-client-websocket

About #3932
Make sure that:

[x] You have read the contribution guidelines.
[x] You submit test cases (unit or integration tests) that back your changes.
[x] Your local test passed ./mvnw clean install -Dmaven.javadoc.skip=true.

Codecov Report

Merging #3946 (12987ce) into master (3995940) will decrease coverage by 0.65%.
The diff coverage is n/a.

@@             Coverage Diff              @@
##             master    #3946      +/-   ##
============================================
- Coverage     70.35%   69.70%   -0.66%
+ Complexity     6748     6634     -114
============================================
  Files           922      923       +1
  Lines         25318    25071     -247
  Branches       2297     2262      -35
============================================
- Hits          17813    17476     -337
- Misses         6136     6228      +92
+ Partials       1369     1367       -2

Impacted Files
Coverage Δ

...cket/ShenyuSpringWebSocketClientConfiguration.java
100.00% <ø> (ø)

...admin/listener/nacos/NacosDataChangedListener.java
53.33% <0.00%> (-40.15%)
:arrow_down:

...n/alibaba/dubbo/cache/AlibabaDubboConfigCache.java
47.12% <0.00%> (-31.04%)
:arrow_down:

.../client/server/consul/ShenyuConsulConfigWatch.java
60.41% <0.00%> (-25.00%)
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...controller/ShenyuClientHttpRegistryController.java
77.77% <0.00%> (-22.23%)
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...che/shenyu/sync/data/http/HttpSyncDataService.java
70.40% <0.00%> (-19.39%)
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...yu/sync/data/http/refresh/AbstractDataRefresh.java
68.96% <0.00%> (-13.80%)
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...ruptor/RegisterClientServerDisruptorPublisher.java
52.94% <0.00%> (-11.77%)
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...min/listener/consul/ConsulDataChangedListener.java
85.71% <0.00%> (-11.48%)
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...a/org/apache/shenyu/common/utils/VersionUtils.java
67.85% <0.00%> (-10.72%)
:arrow_down:

... and 42 more

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


Module Loader

Yes, you might be asking yourself 'what??? there are people out there not using Module Loaders?'. But yeah, you are correct. I am not using RequireJS or any similar Environment.
And correct me if i'm wrong, for this - lets call it Component - a Module Loader is required, because i am getting the Error - Uncaught ReferenceError: MagicMove is not defined
This Library seems freaking awesome, i would love to give it a try :)
thanks for the help

I am having this same problem! Any help would be much appreciated!


Types for typescript

Looks way cleaner and easier to use than vue-color but cannot use as there are no types - it is this already in progress?

I do want to add types to the project, yes. I’m also considering to write it in TypeScript entirely but for that, I want to finish the migration to Vue.js 3 first. The migration to Vue.js 3 is currently blocked on a couple of issues documented in https://github.com/kleinfreund/vue-accessible-color-picker/issues/4 so this will have to wait.
I’ll have a look at what I can do to expose type definitions for the project with the current major version 1.

I added some basic type definitions to the project in v1.1.0. Many parts of the code base were also covered with type annotations. The currently existing type definitions should be sufficient to annotate most things in relation to this plugin, but I don’t consider this work to be quite done, yet. I will see how the typing situation can be improved both in the source code and for package consumers.


is it possible to fix the distribute_items=True

when I set the parameter to distribute_items=True, it reported error at :
File "C:\Users\usr\Desktop\3DBP\py3dbp\main.py", line 513, in pack
    self.items.remove(item)
ValueError: list.remove(x): x not in list

is this issue easy to fix?

Hi @Westlife1002,
Can you share the input that you used to get this error?

is this repo supports multiple bin and item distribution now?

is this repo supports multiple bin and item distribution now?

I fixed this issue in the latest version, please refer to the Readme.

This issue has been resolved, please reopen if you have other questions.


Add new red_hat_migration_analytics product feature

This PR switches the new API endpoint from the existing red_hat_cloud_services product feature to a new red_hat_migration_analytics feature. (see https://github.com/RedHatCloudForms/cfme-migration_analytics/pull/8#discussion_r311688618)
This PR also converts all 'single-quotes' in the repo's Ruby files to "double-quotes". (see https://github.com/RedHatCloudForms/cfme-migration_analytics/pull/8#discussion_r311680773)

Ivanchuk backport details:
$ git log -1commit 710ce763f1feb4d780c5c12dec201766ac8491a2
Author: Adam Grare<EMAIL_ADDRESS>Date:   Thu Aug 8 12:34:09 2019 -0400

    Merge pull request #10 from mturley/rhma-product-feature

    Add new red_hat_migration_analytics product feature

    (cherry picked from commit ac7f1fd0b182d089218c5328eb734305a1816bd4)


Fix: Path should be a string

This PR

[x] uses a type declaration and removes a docblock from the constructor of OpenCFP\Application

Thanks @localheinz

Thank you, @chartjes!


Update sample_distorted_bounding_box to use v2 kernel

This fix is a follow up of #10840 so that sample_distorted_bounding_box uses _v2 kernel to follow the
API compatibility workflow (3 weeks).
This fix updates related tests so that redudant tests could be removed.
This fix fixes #10715.
Signed-off-by: Yong Tang<EMAIL_ADDRESS>

Can one of the admins verify this patch?

@tensorflow-jenkins test this please


Misleading warning regarding old story format

Rasa Core version: 0.11.*, master
Issue: Wrong deprecation message
This deprecation message is misleading:
https://github.com/RasaHQ/rasa_core/blob/95e430f3a6307b82cac0509f0db9d4472fd46709/rasa_core/processor.py#L236
In fact, the interpreter checks for brackets, not for leading _. The check was updated but the deprecation message wasn't.

Thanks for raising this issue, @MetcalfeTom  will get back to you about it soon.

Hi @benjamin-work,
Agreed, it's wrong!  I'll add it to the inbox but it is an easy fix.  We will need to have two warnings in this case - one for the deprecated _intent format and another for the deprecated [name=Rasa] format

I think we should remove the _ parsing now, it has been deprecated for 2 major versions.


Add missing input/output mappings to scale layer

These are needed if we want to use a detector that has some kind of channel attention (I found it the hard way :P)

as an additional experiment, I am training the dnn_mmod_train_find_cars_ex program with only one change: I added the following just after the last convolutional layer
scale1<sig<con<55,1,1,1,1,avg_pool_everything<tag1<

So, the network architecture now looks like this:
using net_type = loss_mmod<con<1,9,9,1,1,
scale1<sig<con<55,1,1,1,1,avg_pool_everything<tag1<
rcon5<rcon5<rcon5<downsampler<input_rgb_image_pyramid<pyramid_down<6>>>>>>>>>>>>>;

I will let you know how it goes.

Looking at the network you pasted, you have this in it
layer<2>	output size=(num:1, k:384,  nr:54,  nc:16)	scale1
layer<3>	output size=(num:1, k:384,  nr:1,   nc:1) 	sig
layer<4>	output size=(num:1, k:384,  nr:1,   nc:1) 	con	 (num_filters=384, nr=1, nc=1, stride_y=1, stride_x=1, padding_y=0, padding_x=0) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0
layer<5>	output size=(num:1, k:384,  nr:1,   nc:1) 	avg_pool (nr=0, nc=0, stride_y=1, stride_x=1, padding_y=0, padding_x=0)
layer<6>	output size=(num:1, k:384,  nr:54,  nc:16)	tag1

The stuff between the scale1 and tag1 applies a bunch of identity transforms, so it just happens to work out to the mapping you want.  But that's just sort of lucky.

There should probably be a scale_prev layer that's just like scale except the two input tensors are reversed.

Oh, I see! Thank you for the insight!
The dnn_mmod_train_find_cars_ex didn't converge with my modification, so finally I got something that doesn't work.
With regards, of the scale_prev that is actually what I am doing right now. I am retraining with a scale_ layer with swapped inputs, so now it looks like this:
...
scale_prev2<skip1<tag2<sig<con<55,1,1,1,1,avg_pool_everything<tag1<
...

If that works, I will modify this PR to include the scale_prev layer. Unless you want me to close this one and make a new one.

Cool. However you want to organize it is fine.


Fix clo second param.

It should be the same param, as it is faster for typing :) you just add string with the same name as variable


Distributed Training

Thank you for doing this excellent work. May I ask if there is a way to conduct distributed training using multiple GPUs?

Hi, at the moment, there isn't. But incorporating DDP should not be that difficult. Let us know if you try it and face any issues.
Moreover, all the methods should run comfortably on single GPU as peak memory usage is <5GB for all with a batch size 256.


LetsEncrypt root cert expiration errors in ubuntu container builds

ERROR: could not open HSTS store. HSTS will be disabled.
--2021-10-04 11:25:04--  https://partner-images.canonical.com/core/focal/current/ubuntu-focal-core-cloudimg-amd64-root.tar.gz
Resolving partner-images.canonical.com... <IP_ADDRESS>
Connecting to partner-images.canonical.com|<IP_ADDRESS>|:443... connected.
ERROR: cannot verify partner-images.canonical.com's certificate, issued by 'CN=R3,O=Let\'s Encrypt,C=US':
  Issued certificate has expired.
To connect to partner-images.canonical.com insecurely, use `--no-check-certificate'.
ERROR 2021-10-04T11:25:04Z: vagga::capsule::download: Error downloading "https://partner-images.canonical.com/core/focal/current/ubuntu-focal-core-cloudimg-amd64-root.tar.gz", wget Exited(5)

Pushed the fix to master. Although, building a nightly and release can take more time :(


Coinbase

Is there planned support for Coinbase Exchange?
Thanks

Never mind I am using gdax.
Thanks

@screwfaze I think your question is one I'm also interested in. Is there going to be a support for coinbase??

@screwfaze I think your question is one I'm also interested in. Is there going to be a support for coinbase??

gdax is coinbase pro

because they've changed the name from GDAX to Coinbase Pro, can anyone confirm that the API works the same, and is still working?

I am unfortunately not maintaining this project anymore. I'm marking the whole repo as read only.
Read more here: https://medium.com/@gekkoplus/archiving-open-source-gekko-dba02e6efc7


added flat function

As you said in https://github.com/sithmel/iter-tools/issues/75#issuecomment-444634511, flatten infinitely seems impossible, but what about flatten(fn, iterable)?

@KSXGitHub can you please have a look at the TS signature? you can now use a function instead of a depth

@sithmel

@KSXGitHub can you please have a look at the TS signature? you can now use a function instead of a depth

I had a look at that, and it isn't correct.
BTW, I already created https://github.com/sithmel/iter-tools/pull/81 for flat(iterable) and flat(depth, iterable). I will correct your type definition of flat(fn, iterable) when this pull is merged (so that I don't have to change my type definition every time you add changes to the code)

@conartist6 I would prefer string not to be flatten

When will you guys merge this? I have a project that uses R.flatten() right now and I would be happy to switch to this.

@KSXGitHub I will merge tomorrow, unless there is some objection


Codeunit Names Should be on the Page

[Enter feedback here]
Hello, instead of the codeunit IDs I think the names of the codeunits should be on this page.  There is no way in v16 to simply lookup a codeunit by ID easily.

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

ID: e66c0ad5-98e3-370e-2e24-c17c698fc24a
Version Independent ID: 72059311-bb4e-e2fb-e6a8-e3ebbb2fdf1b
Content: Transitioning from Codeunit 1 - Business Central
Content Source: dev-itpro/upgrade/transition-from-codeunit1.md
Service: dynamics365-business-central
GitHub Login: @jswymer
Microsoft Alias: solsen

Thanks for the feedback! We have updated the article to include the codeunit names. The updated article will be published soon.


Improve roles:  'repositories_client' 'repositories_server'

Hi,
It is possible to add a feature allowing to access an external repos ?
For exemple : EPEL, Erratas, or others
internal_repo:
 - os
 - repo1

external_repo:
  - { name: epel, url: ... }
  - { name: errata, url: ... }

Best regards,

https://github.com/oxedions/bluebanquise/pull/44

Hello @hmeAtos
Many thanks for this FR.
@bouriquet Propose a PR, merged. However, I let this feature request open, as I am not satisfied with current naming convention.
Ben

Fixed by https://github.com/oxedions/bluebanquise/commit/d60214be34d6083c7b29922e4ddb8d9aaf745672


NNStorage does not synchronize iteration on a synchronized list

64

 Quality gate: Failed
9 Issues

 9 Code issues

Details


NameError: name 'RandomSampler' is undefined

When running main.py, I ran into the following problem, can the author please answer it?
“Traceback (most recent call last):
File “/home/sjz/RS/ELCRec-main/src/main.py”, line 234, in <module
main()
File “/home/sjz/RS/ELCRec-main/src/main.py”, line 169, in main
train_sampler = RandomSampler(train_dataset)
NameError: name 'RandomSampler' is undefined”

from torch.utils.data import DataLoader, SequentialSampler, RandomSampler
we update the code.

we clear up and update the code, please check the latest code.


Fix Carthage support

Might need some testing to make sure I didn't break Pods or anything else. Updated the framework scheme to be shared and then updated some project settings for the framework target. It now builds, installs and runs via Carthage. Fixes an issue mentioned in #144 and #155.

thanks @swemoney ✌