python3.pkgs.pygobject-stubs: init at 2.8.0

Description of changes
Typing Stubs for PyGObject
This package is useful for development and type checking tests.
Things done

Built on platform(s)

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

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

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

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

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

[x] Fits CONTRIBUTING.md.

If there are no tests, please add doCheck = false; with a comment and pythonImportsCheck is possible.

I have added doCheck = false. I don't think there's actually anything to import here though, as this package only provides type annotations for other modules.

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/prs-ready-for-review/3032/2599


No rotation props in bitmamp layer

I'm trying to make an application where the user can georeference scanned maps.
Any information maybe help or an example  ?
Thanks

You need to pass the rotated corners as four points with bounds.


Add support to Tizen

How to use:

Install Tizen Studio (latest version)
Install the Native CLI, Web CLI, TV and Certficate Manager packages.  (Using the "Package Manager")
Set TIZEN_CLI environment variable to the Tizen CLI folder. (Usually <TIZEN_STUDIO>/tools/ide/bin)
Setup a certificate using the "Certficate Manager"
Execute react-tv run-tizen inside a react-tv application 😄

Benchmark

Amazing @dead!
Can you update the README and add info about Tizen?
I'll test this PR on this weekend. 👍  ❤

I'll close #63 #58 for finish 0.3.0 and then I'll work on it.

🙌

@raphamorim done 😄

@dead I solved other conflicts and create another PR with your commits.
I'll go on with #104 (some things to do yet: adjust for macos env).
When it ends/merged I'll notify you and ask if it's still working on Windows Env.


OTEL Instrumentation w/ docker-compose

Closes #18
Closes https://github.com/ai-cfia/howard/issues/272

Another PR is open for this specific problem


Update bluebird to 3.x

Bookshelf has bluebird 2.x and promises produced by it don't provide bluebird features, such as:
.catch() now supports an object predicate as a filter: .catch({code: 'ENOENT'}, e => ...).
http://bluebirdjs.com/docs/new-in-bluebird-3.html
ref. tgriesser/bookshelf#1137

@wubzz updated bluebird


Clicking on a Category link in https issue

When ever you click on a category link when viewing the shopping cart over https, the redirect all ways defaults back to http.
jquery is submitting a form and sending the data to js function submitForm()
is this a codeigniter issue ot jquery issue?
ps
strangely this also happens to the home link, altthough viewing the html code quite clearly shows as https://

@matthaselip Somewhere you missed changing from http to https. Check the code from where the redirect comes from.


Type traits for GridMap

Useful for pulling the data and container types from the class if it has been passed as a template parameter to a template method/class.

Could be more formally embedded in an external traits class, but since there is access to do it internally this is simpler.

Dropping this in favour of having it embedded in #84 where it gets used.


Spacy Extractor not working

Tried with a simple rule
{
            "rules": [
                {
                    "polarity": "true",
                    "description": "",
                    "pattern": [
                        {
                            "prefix": "",
                            "suffix": "",
                            "capitalization": [],
                            "part_of_speech": [],
                            "length": [
                                "3"
                            ],
                            "maximum": "",
                            "minimum": "",
                            "shapes": [],
                            "token": [],
                            "numbers": [
                                ""
                            ],
                            "is_in_vocabulary": "false",
                            "is_out_of_vocabulary": "false",
                            "is_required": "true",
                            "type": "number",
                            "is_in_output": "true",
                            "match_all_forms": "false",
                            "contain_digit": "false"
                        }
                    ],
                    "output_format": "",
                    "is_active": "true",
                    "dependencies": [],
                    "identifier": "current rule"
                }
            ],
            "test_text": "432",
            "field_name": "phone",
            "test_tokens": [
                {
                    "index": 0,
                    "whitespace": "",
                    "text": "432"
                }
            ],
            "results": []
        }

Does not produce any output

Seems like it was working except for the case I tested: Number with a certain length. Seems to be working now. Closing this issue


It seems afl mutator never grows a buffer

Hi!
I'm playing with manul, and have a simple fuzz function like this:
void fuzz() {
	FILE* fd = fopen(g_path, "r");
	static char tgt[] = "tgt";

	if (fgetc(fd) == tgt[0] &&
		fgetc(fd) == tgt[1] &&
		fgetc(fd) == tgt[2]) {
		*(char*)0 = 0;
	}

	fclose(fd);
}

I noticed that if I provide input corpus as a one file one byte long, it never grows to 2 bytes. If I provide input corpus 3 bytes long or more it finds a crash quite fast. So, it seems to me that alf mutator can't grow mutating buffer size. Could you please give me some pointers to resolve this issue?
Thanks!

Yep, there is such a problem in AFL mutator. I believe the original AFL has the same issue (may be not). The whole logic is implemented here: https://github.com/mxmssh/manul/blob/master/afl_fuzz.py. I think it is a corner case that should be handled specifically. I have never expected input to be 1 byte long :)

@mxmssh thank you for response!
I'm just playing with it and looking what it is capable of. I've verified that AFL can grow input buffer from 1 byte without any hesitation (at least it's true for WinAFL's which is using a bit outdated version of AFL 2.43b). For example, I provided input corpus of one byte and the binary was checking 16 bytes byte-by-byte and then crash, WinAFL found a crash in 2-3mins single threaded . I've also checked manul's AFL python mutator on corpus from 1 to 16 bytes. In each case it was not able to grow buffer even on a single bite. So, it may be a bug which doesn't allow to grow input bigger no matter what size it is. So far I didn't look at mutator sources it's just some conclusions basted on testing.
Can I ask how are you debugging python code? I want to use interactive debuggin and I was trying using VSCode. It can't step inside of code which is behind multiprocessing.Process(), so I just patched the code to not to use this module and then I was able to attach interactive debugging to mutator's code. I'm just curious how are you doing this? :)
Btw, should radamsa mutator work on Windows? (I'm asking this because I've quickly checked it and wasn't able to leverage it)
Thanks!

Seems like a bug in Manul :)
I don't usually use any IDE or step-by-step debugging for Python code, static code analysis + debug printing helps me to find 99% of the problems.

Radamsa mutator should work on windows

It should work better now.

It should work now.

Thanks a lot! I've checked 9c5fe26c458ddc79651db0e8a7576ffd5f55800e revison, but I couldn't verify it. It seems AFL mutator is not able neither grow nor shrink sizes of input files. The sizes of files in "queue" directory is always equal to the corresponding sample in "input" directory.

Could you try the latest version?

Oh, sorry it was wrong revision given. I've tried 7c6037b08a0308f75d4ea6ebc2e1856da0a4d5c8 just now, same result. No growing, no shrinking.

That's weird :) Can you copy-paste manul.config that you are using for fuzzing? Are you doing coverage-guided fuzzing on Linux, right?

Can you copy-paste manul.config that you are using for fuzzing?

sure, here you are:
dbi = dynamorio
dbi_root = z:\s\tools\dr791\bin32\drrun.exe
dbi_client_root = z:\s\git\manul\dbi_clients_src\client_32\RelWithDebInfo\binafl.dll
dbi_persistence_mode = 1
dbi_target_module = manul_test.exe
dbi_target_method = fuzz
dbi_fuzz_iterations = 20000

Are you doing coverage-guided fuzzing on Linux, right?

Nope, I'm on Windows. Here is the binary if want to try along.
manul.py -i in -o out -n 1 "...manul_test.exe @@"

For input corpus try just one file with one random byte.

I see, do you allocate 100% for AFL mutator, right?

Yeah, correct. That part is just default:
mutator_weights=afl:10,radamsa:0

Ok, now it is finally fixed :)  I have also compared winAFL and Manul on test32.exe distributed with Manul. Both fuzzers were able to identify crash. winAFL managed to identify the problem faster than Manul due to deadlock problem in Python3. However, the implementation seems to be correct.
Please take a look into current config if you want to test it on your own.


provide a way to create reserved ip independently from vpe creation

Description
Use case: ensure that consumer has got control on reserved ip. This is used full in the scenario where a consumer want to have the same ip for a given vpe type across vpcs.

Suggested approach is to:

add an optional input variable to the vpe module that takes a list of reserved ips - eg: reserved_ips
extract out the existing logic that reserve ips as a submodule
refactor root module to use the new submodule to reserve ips when there is not reserved ips passed in the optional input variable


Could not find Qt platform

Hi,
I'm trying to set up this pysot environment on maxOS 10.15. However, an error of Qt support arises to me. The error message goes
qt.qpa.plugin: Could not find the Qt platform plugin "cocoa" in "" This application failed to start because no Qt platform plugin could be initialized. Reinstalling the application may fix this problem.
Is there anyone who has suffered from this problem?

I fixed this problem by changing the opencv-python version to <IP_ADDRESS>. I hope this can help you guys.


[Bug]: precedence/ordering of @@access decorators is unclear

Describe the bug
I've got a question about @@access, when there are rules that overlap.
In our service we were attempting to make an operation public, only for the scope "go", but internal for everyone else. However, we couldn't do this:
@@access(TestThing, Access.internal);
@@access(TestThing, Access.public, "go");

This generates this type graph:
ModelTestThing
  properties:
    ModelPropertyname
      # extra stuff elided
      data:
         # NOTE that it just gave us all the same access.
         Symbol(@azure-tools/typespec-client-generator-core.access): { }

You can fix this by just ordering them differently:
@@access(TestThing, Access.public, "go");
@@access(TestThing, Access.internal);

This generates this type graph:
ModelTestThing
  properties:
    ModelPropertyname
      # extra stuff elided
      data:
         Symbol(@azure-tools/typespec-client-generator-core.access): { go: "public" }

I'm not entirely sure which behavior is the correct behavior, but I did find it surprising that the more specific directive was overridden by the least specific directive. The ordering of their declarations in the file doesn't seem like it should be a critical factor, especially given how these @@access's could be in separate files altogether.
Including @l0lawrence and @lmazuel in case I've misstated the bug.
Reproduction
Playground Link
Checklist

[X] Follow our Code of Conduct
[X] Check that this issue is about the Azure libraries for typespec. For bug in the typespec language or core libraries file it in the TypeSpec repo
[X] Check that there isn't already an issue that request the same bug to avoid creating a duplicate.
[X] The provided reproduction is a minimal reproducible example of the bug.

@iscai-msft, @lmazuel asked that this be assigned to you specifically.

this seems like a bug, let me take a look at it today

@iscai-msft, just a note, there's another issue that @lmazuel filed about handling CSV lists inside of the 'scope' string as well. The use case was similar to what we were trying to accomplish here.
Issue: https://github.com/Azure/typespec-azure/issues/978

@richardpark-msft after looking into it more, we don't want people to set multiple access decorators, because it gets complicated if they conflict with each other. Instead, I think the way around this is adding the ability to do a list of languages, and also adding support for ~ to exclude a language from the list. I'm going to get started on that, and close this issue in favor of #978 if you're ok with that

@richardpark-msft after looking into it more, we don't want people to set multiple access decorators, because it gets complicated if they conflict with each other. Instead, I think the way around this is adding the ability to do a list of languages, and also adding support for ~ to exclude a language from the list. I'm going to get started on that, and close this issue in favor of #978 if you're ok with that

I think so. If the order is ambiguous then it seems like multiple decorators should cause an outright error otherwise your result might be non-deterministic. What do you think of that?

Yeah that's definitely why we decided originally to not allow multiple instances of either augmentation or direct decorating with @access and @usage. With the pr adding list of scopes, you should be able to do @@access("internal", "python,csharp,go,java,javascript"), which is definitely kind of long. I'm going to start another PR as well in the meantime adding support for ~, but that will require more review just because we have to determine whether we want to add support for tilde

Just to make sure we're talking about the same thing - in the example I gave I am applying it twice though, and there wasn't (AFAICT) an error. Should there have been? Right now it kind of appears to work, but if the resolution of that is ambiguous, depending on order, it seems like it should fail or provide some sort of warning you're putting yourself in that situation.
(the comma separated list is awesome, but I think the error condition is a separate issue)

Oops I missed this comment. Yeah you're right, there should be a warning raised here. Let me make this a bug and make sure we raise

from our test, this will report an diagnostics. i wonder if it is because the lint rule is not enabled when compiling.

@timotheeguerin in tcgc, i used a core api to report diagnostics (code here). it could work when test, but with the real typespec compile, there is no diagnostic reported. could you help to identify if the usage is wrong?

the root cause is previous check does not work on augment decorator.


initial values for semiconductors and switches

Reported by ahaumer on 8 Feb 2016 11:27 UTC
When checking Modelica.Electrical.Machines.Examples.SynchronousInductionMachines.SMEE_LoadDump for fixed initial conditions, I realized that the switches with arc (Modelica.Electrical.Analog.Ideal.{OpenerWithArc, CloserWithArc, ControlledOpenerWithArc, ControlledCloserWithArc}, as well as the ideal switches Modelica.Electrical.Analog.Ideal.{IdealOpeningSwitch, IdealClosingSwitch, ControlledIdealOpeningSwitch, ControlledIdealClosingSwitch} are implemented sligthly different and not all offer the possibility to set the initial conditions with fixed=true (for Boolan variable off).
I suggest to implement 2 partial models Modelica.Electrical.Analog.Interfaces.{IdealSwitch, IdealSwitchWithArc} and extend the above mentioned switch models from these two partial models.
Additionally it would be a great advantage for maintenance to implement a partial model Modelica.Electrical.Analog.Interfaces.IdealSemiconductor and extend Modelica.Electrical.Analog.Ideal.{IdealDiode, IdealThyristor, IdealGTOThyristor} from that partial model.
These changes ar backwards compatible, and would be an improvement already for MSL 3.2.2 (possitiblity to set the initial conditions consistently, much easier maintenance).

Migrated-From: https://trac.modelica.org/Modelica/ticket/1903

Comment by ahaumer on 8 Feb 2016 11:28 UTC
resolved by ac510b5a3533002c7e666344c72aa7322b8f1960


Shellcheck fixes

this is build on top of https://github.com/abaker/implant/pull/6

Merged, thanks


Delegations Dashboard

This suggestion came from WiiMee:
There are several services used for "wallet delegations", such as Delegate.xyz and Warm.xyz. It would be useful to have a "Delegations" tab next to Approvals and Signatures which displays a list of delegations for a wallet with the option to revoke the delegations.
I don't know enough about how these delegations work in particular to know how viable this is, but I think it is definitely a good idea to explore it.

Delegate.xyz v1 has contract view functions that return lists of given delegations (cold -> hot wallet):
https://etherscan.io/address/0x00000000000076a84fef008cdabe6409d2fe638b#readContract
Delegate.xyz v2 has view functions that return lists of given and received delegations (cold <> hot wallet):
https://etherscan.io/address/0x00000000000000447e69651d841bd8d104bed493#readContract
Warm.xyz has view functions that return a single given delegation or a list of received delegations (cold <> hot wallet):
https://etherscan.io/address/0xc3aa9bc72bd623168860a1e5c6a4530d3d80456c#readProxyContract
So it looks like we can definitely display given delegations for all of these platforms with just a few smart contract calls. We should also be able to display received delegations for Delegate v2 and Warm easily, but not for Delegate v1. From a security perspective, inspecting / revoking given delegations is the important part in any case.
If we wanted full support for given + received delegations and/or if we wanted to display delegations/revokals in a future "History" tab, then we may need to look at Delegation events as well.

My idea around implementation for this would be that we create a "DelegationsPlatform" class similar to the "Chain" class, which can be instantiated with a "name" and a "getter" function. Alternatively we could also create it in a way that looks closer to the PriceStrategy, where each platform gets its own subclass.


Add option to export data class to JS caller

Provides an additional method that returns a data class directly to the caller in JS.

Rebased into main but GitHub did not recognise my interactive rebase correctly


Log the death location and publish to websocket

Heinermann — Yesterday at 11:49 PM
Code for retrieving cause of death that I mentioned in the Twitch chat (for leaving death messages behind if you ever wanted to add that): https://noita.wiki.gg/wiki/Modding:_Utilities#Retrieving_the_Cause_of_Death

Heinermann — Today at 12:00 AM
and then on the receiver end, make a tombstone or whatever (I guess similar to the messaging system, or just straight up use the messaging system temporarily for it)


[WFLY-16975] Removing TokenUtilsEncryptTest workaround after upgrade to MP JWT 2.1

https://issues.redhat.com/browse/WFLY-16975

Thanks @ropalka


powershell_script's default guard_interpreter should be :powershell_script

Description
powershell_script's default guard_interpreter should be :powershell_script. The vast majority of PowerShell script guards are also written in PowerShell, so having to add guard_interpreter :powershell_script to every single powershell_script resource seems unnecessary and confusing.
The default used to be :powershell_script, but was changed here: https://github.com/chef/chef/commit/a3aba411ccdf1a0a5f236ed3ce2a678a1892e29b#diff-fbc7a88e488de87fe1086188141990e8, was this intentional?
Chef Version
12.4.0.rc1 and up
Platform Version
Any windows version

doesn't look remotely intentional as far as i can tell.
PR to revert that change would be fine.


Record .svo file and run object detection at the same time

Preliminary Checks

[X] This issue is not a duplicate. Before opening a new issue, please search existing issues.
[X] This issue is not a question, bug report, or anything other than a feature request directly related to this project.

Proposal
It would be great if the wrapper could record a .svo file and run object detection in parallel.
Use-Case
Doing some test outdoors with active object detection.
Afterwards rerun the ros2 wrapper in the lab with different parameters to see if different parameter set would have led to a better result.
Anything else?
No response

Hi @JWaynee
this is already available. You must simply call the services to enable them.
Object Detection can start immediately if you set it to true in common.yaml without using the service call:
https://www.stereolabs.com/docs/ros2/zed-node/#services

Hey @Myzhar,
thanks for the quick response. Sorry for missing this info in the ReadMe. Can you give me some additional information to the parameters of the service call:

bitrate, which bitrate is this referring to.  I assume there is no data transmission but it's directly written on the hard drive
compression_mode, do the modes correspond to the modes listed here: https://www.stereolabs.com/docs/video/recording/ and does 0 correspond to the first mode the list?
input_transcode, what does this parameter do

Thanks
Jeremy

Thanks again for the quick response!


i18n(zh-cn): Update testing.mdx

Description (required)
i18n(zh-cn): Update testing.mdx

Related issues & labels (optional)

#8369

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Contrast issues on Examples page

Hey, I was going through the Examples page today and noticed that the text wasn't showing up correctly on one of the examples so I went through the entire page looking for contrast issues. Here's what I found:
On dark mode

Numbers are dark after typing on keyboard:
https://svelte.dev/examples/component-bindings

Both the button and the text is white but their hover style is fine:
https://svelte.dev/examples/easing

Text is too dark
https://svelte.dev/examples/area-chart

The entire box is white and and illegible
https://svelte.dev/examples/slot-props

Blue text is barely legible
https://svelte.dev/examples/hacker-news

On light mode

Text color is grey and barely legible
https://svelte.dev/examples/bar-chart

The graph's lines aren't visible
https://svelte.dev/examples/scatterplot

Grey text is too light
https://svelte.dev/examples/hacker-news

hackernews, scatterplot and component-bindings should be better now.

closing since the site has been rewritten. please file an issue at https://github.com/sveltejs/svelte.dev if the issue persists


Auto-merge does not wait for approval when used on a PR to a feature branch

https://github.com/Azure/azure-sdk-for-js/pull/17061 is a PR targeting a feature branch and has the label auto-merge.
The expectation was that the PR gets automatically merged after approval.
Turns out the bot does not wait for the approval when the PR is for a feature branch :(
cc @praveenkuttappan, @weshaggard

cc @kurtzeborn
This is because the there are new required checks configured for the target feature/v4 branch. I believe @kurtzeborn has enabled branch protection for release/* and hotfix/* branch patterns did we want to add feature/* pattern to the list of protected branches as well?

I've added feature/* branch protection to all of the public language repos.


intero should stay out of the way when it's not wanted

I'm working on a project that doesn't have a stack.yaml (because I cloned it just to contribute a quick fix upstream - so I don't care about syntax highlighting or flycheck or anything, I just want to get in and make my fix and be done).
This causes intero to hang when I open the project, because it automatically tries to install a bunch of stuff. To fix this, I put a stack.yaml in $HOME/ with use-system-ghc: true, so that intero won't try to do this when I open up random .hs files. That works (though it's a hack and ideally I shouldn't have to do it).
However, now a buffer repeatedly pops up roughly once a second with the following error message.
Warning (intero): Couldn't get the Stack project root.

This can be caused by a syntax error in your stack.yaml file. Check that out.

Otherwise, please report this as a bug!

Hi Anders. What does this say in the shell?
Chriss-MacBook-Pro:~ chris$ stack path --project-root --verbosity silent
/Users/chris/.stack/global

In the first case I described (no stack.yaml to be found anywhere) it returns
/home/anders/.stack/global-project

In the second case (when I put a stack.yaml in $HOME to try to prevent it from installing intero automatically), that command gives
/home/anders

So I reproduced this, it's because you're introducing a parse error:
Chriss-MacBook-Pro:~ chris$ cat stack.yaml
use-system-ghc: true
Chriss-MacBook-Pro:~ chris$ stack path --project-root --verbosity silent
Could not parse '/Users/chris/stack.yaml':
Aeson exception:
Error in $: failed to parse field 'resolver': key "resolver" not present
See http://docs.haskellstack.org/en/stable/yaml_configuration/.

The problem is that stack is supposed to run also when you work on any random .hs file, aka the "global" project. I use this all the time.
I think in your case, you'd perhaps prefer a whitelist of projects. The opposite operation to #285, which suggests a blacklist. I can implement that too. Then you would do something like:
(add-hook 'haskell-mode-hook 'intero-mode-whitelisted)

@anderspapitto I've added whitelist support. Please check out this: https://github.com/commercialhaskell/intero#whitelistingblacklisting-projects Now you can tell Intero where it's wanted, either by specifying project individual directories, or a whole /home/me/projects parent directory.

thanks chris! I've actually gone with a slightly different variant
(use-package intero
  :init
  (defun intero-mode-unless-global-project ()
    "Run intero-mode iff we're in a project with a stack.yaml"
    (interactive)
    (unless (string-match-p
             (regexp-quote ".stack/global-project")
             (shell-command-to-string "stack path --project-root --verbosity silent"))
      (intero-mode)))
  (add-hook 'haskell-mode-hook 'intero-mode-unless-global-project))

this leans on the stack executable to figure out if I'm in a stack-supporting project or not, so I don't have to maintain any explicit lists.

Does anyone know how I could use this in spacemacs? I'm not too sure where in my .spacemacs file I can insert the above code.

@chrissound Did you manage it in spacemacs ?
I have been trying to get black/withlisting in spacemacs without success so far. For instance I am replacing intero-mode with
  (setq intero-whitelist '("/home/vagrant/projects/"))
  (intero-mode-whitelist)

PS: I had to manually change the autoload.el so that emacs recognize intero-mode-whitelist function.
Everything works excepts intero seems to totally ignores the whitelist or blacklist variable. I have been trying to move the setq definition around but no luck.

If it helps there is actually a difference when I change the line (intero-mode) into (intero-mode-whitelist).
In the first case, intero would fail to boot at spacemacs start up time because it tries to do so on the recentf-files (including for instance ~/.xmonad/xmonad.hs).
In the second case, intero does not fail at startup but only when I try to edit the file.

Didn't attempt going  further with this @PierreR. If you get it working though - I'd be keen to have a look!

This warning appears for me while using Eshell over TRAMP.  The remote machine does not have Stack installed and has no Stack projects on it.  I'm using the whitelist but nevertheless it seems Intero is attempting to find a Stack project on this remote machine.  Dired over TRAMP doesn't trigger the warning, though.


GraphiQL peerDepends on React 0.4.0, causing issues when used with Relay (React ^0.4.2)

As in the title, it's kind of hard to satisfy an exact dependency like that. It'd work better if the dependency on React was ^0.4.0.

fixed by #51


Update "About" section

On this page:
https://pymc-data-umbrella.xyz/en/latest/about/index.html
We should add actual text about PyMC and Data Umbrella in addition to the links that are already there.
Data Umbrella is a global community for underrepresented persons in data science.  It is a fiscally hosted project of Open Collective, a registered 501(c)(3) non-profit based in California, USA. Data Umbrella: organizes online speaker series on data science and open source, organizes sprints / hackathons, curates resources on inclusive practices.  All levels are welcome, beginners and experts.
PyMC is a probabilistic programming package for Python that allows users to fit Bayesian models using a variety of numerical methods, most notably Markov chain Monte Carlo (MCMC) and variational inference (VI). Its flexibility and extensibility make it applicable to a large suite of problems.  PyMC is a non-profit project under NumFOCUS.
cc:  @mjhajharia @OriolAbril

done, thanks reshama


Annotation Support

Hey, this looks like a great library, and I have been exploring using it.  I know you guys have quite done quite a bit of research regarding Anotations vs Method Naming, but overall I really feel like Annotations are a much cleaner and more flexible solution.
I added annotations to my local branch.  You can create a new EventBus that uses annotations like this new EventBus(DeclarationType.ANNOTATIONS).  Then you can subscribe to receive events on any method like this:
@Subscribe
public void onMyEvent(CustomEvent e)
This uses the caller chooses thread method.  We can also change this by adding an argument.
@Subscribe(threadMode = ThreadMode.Background)
public void onMyEvent(CustomEvent e)
This uses the background thread and is definitely a more explicit syntax.
Here is a link to my repo where I implemented the changes.
https://github.com/rjbrock/EventBus
I would still need to add unit tests before submitting a pull request so I just wanted to see what your thoughts were first.
Rick

@greenrobot awesome, thanks for taking a look at this.  Any help you need from me?  L

@greenrobot  and @rjbrock: I have been extensively using EventBus in projects I work on and I have been tracking the progress and changes you're making to switch annotations. I see that anonymous class support may get dropped because they cannot be annotated. I assume many people have been registering anonymous classes to cope with Activity/Fragment lifecycle hell and ensure events get delivered only in proper state of components. Is it possible to add as a feature partial object subscription (eg. add something like EventBus.register(Object subscriber, Class eventTypes) and a corresponding unregister(Object subscriber, Class eventTypes)). Would adding some sort of filtering to SubscriberMethodFinder hurt performance too much?
The reason to suggest that is that it would make subscriptions more flexible and would reduce boilerplate when using with Activity/Fragments when there would be events requiring view interaction/updating or Fragment transactions which can be done only while some tricky conditions are met.
I am willing to help if you think that is feasible to add my suggestion as feature.

I see. Anyway, a big "Thank you" to you and all other contributors for the
wonderful library.
On Tue, Apr 7, 2015 at 7:53 AM, greenrobot<EMAIL_ADDRESS>wrote:

@g-neykov https://github.com/g-neykov Agreed. I think there is no way
to detect anonymous classes by the annotation processor. Anyone is welcome
to verify this shortcoming, maybe there's some work around. Thanks!
I don't want to (re-)inroduce "EventBus.register(Object subscriber,
Class<?> eventTypes)" to keep the API simple.
—
Reply to this email directly or view it on GitHub
https://github.com/greenrobot/EventBus/issues/126#issuecomment-90357486.

--

When will snapshot builds be available?  They are not currently available on Sonatype's snapshot repository (as stated in README.md).

@greenrobot i can confirm that anonymous classes are not available for annotation processing.
Do you plan to release a snapshot which contains the annotations branch?

Could you build a release including this? Thanks.

+1 Awesome! Love it

Awesome！

This feature is implemented and can be closed.


Add OpenFunscripter as media source

Api: OpenFunscripter/OFS/issues/59

If you have suggestions on what this should look like feel free to make them.
I want to get this right the first time and not have breaking changes later down the line. 🙂
Currently I have these events.
project_change indicates that you have clear everything after which you would receive a chain of events to reinitialize to the new project.
And this funscript_change event (which looking at the code should also be defined in the other file).
The axis mapping can only be determined by looking at the name field and checking for the conventional .roll, .sway,... extensions.
Note this event still needs an additional identifier because the name can change.
So I will add an additional field index because the order can't change to uniquely identify the script.
There are no commands yet.

Yup, will make any suggestions in your issue to not mix things up 👍
I had it working very quickly, I just have to make some internal changes in MFP because the axis mapping is done very late now. Probably have to make it a global utility method.


Replace Container with KeyedSubtree.

For there is a Widget designed for this kind of usage.

This has been merged
Thank you so much @cenumi
You're now officially a contributor to the package!


Netopeer2 server v2.0.0 seems to send malformed notifications to clients

since migrating a Raspberry Pi4 / Ubuntu 20.10 64bit server from v1.1.70 to v2.0.0, notifications sent from application plugins arrive corrupted at the netconf client side with following pattern:

the first notification arrives with contents as expected, but with an empty notification timestamp and an additional error message by the client regarding some invalid, resp. non-UTF-8 characters
no further notifications will arrive except error messages, with some clients terminating the ssh connection as a consequence.

Netopeer2-cli:

notification ()
<switch-pressed xmlns="urn:sysrepo:raspi-blink">
  <led-control-status>false</led-control-status>
</switch-pressed>

>
ly ERROR: Invalid character 0x9e. (Line number 1.)
>
nc ERROR: Session 2: received an invalid message (Invalid character 0x9e.)

Netopeer2-Log:
[INF]: SR: Processing "/notifications:create-subscription" "rpc" event with ID 1 priority 0 (remaining 1 subscribers).
[INF]: SR: Successful processing of "rpc" event with ID 1 priority 0 (remaining 0 subscribers).
[INF]: SR: Event "rpc" with ID 1 priority 0 succeeded.
[INF]: NP: Session 2: thread 1 event new RPC.
[INF]: SR: Processing "notif" "raspi-blink" event with ID 1.
[INF]: SR: Successful processing of "notif" event with ID 1 priority 0 (remaining 0 subscribers).
[INF]: SR: Processing "notif" "raspi-blink" event with ID 2.
[INF]: SR: Successful processing of "notif" event with ID 2 priority 0 (remaining 0 subscribers).
[INF]: SR: Processing "notif" "raspi-blink" event with ID 3.
[INF]: SR: Successful processing of "notif" event with ID 3 priority 0 (remaining 0 subscribers).

netconf-console:

netconf> create-subscription raspi-blink
<?xml version='1.0' encoding='UTF-8'?>
<ok xmlns="urn:ietf:params:xml:ns:netconf:base:1.0"/>
netconf> <notification xmlns="urn:ietf:params:xml:ns:netconf:notification:1.0"><eventTime></eventTime><switch-pressed xmlns="urn:sysrepo:raspi-blink"><led-control-status>false</led-control-status></switch-pressed></notification>

netconf>

Netopeer2-log:
[INF]: NP: Generated new event (netconf-session-start).
[INF]: SR: Published event "rpc" "/notifications:create-subscription" with ID 1 priority 0 for 1 subscribers.
[INF]: SR: Processing "/notifications:create-subscription" "rpc" event with ID 1 priority 0 (remaining 1 subscribers).
[INF]: SR: Successful processing of "rpc" event with ID 1 priority 0 (remaining 0 subscribers).
[INF]: SR: Event "rpc" with ID 1 priority 0 succeeded.
[INF]: NP: Session 1: thread 3 event new RPC.
[INF]: SR: Processing "notif" "raspi-blink" event with ID 1.
[INF]: SR: Successful processing of "notif" event with ID 1 priority 0 (remaining 0 subscribers).
[INF]: SR: Processing "notif" "raspi-blink" event with ID 2.
[INF]: SR: Successful processing of "notif" event with ID 2 priority 0 (remaining 0 subscribers).
[2021/06/10 13:06:57.270592, 1] ssh_socket_exception_callback:  Socket exception callback: 2 (104)
[2021/06/10 13:06:57.270720, 1] ssh_socket_exception_callback:  Socket error: Connection reset by peer
[ERR]: LN: Session 1: SSH channel poll error (Socket error: Connection reset by peer).
[INF]: NP: Session 1: thread 4 event session terminated.
[INF]: SR: There are no subscribers for "ietf-netconf-notifications" notifications.
[INF]: NP: Generated new event (netconf-session-end).

Custom client / netconf-client Python library:

First session, intentionally terminated after notification: response looks fine except empty eventTime
<notification xmlns="urn:ietf:params:xml:ns:netconf:notification:1.0"><eventTime></eventTime><switch-pressed xmlns="urn:sysrepo:raspi-blink"><led-control-status>false</led-control-status></switch-pressed></notification>

[INF]: NP: Generated new event (netconf-session-start).
[INF]: SR: Published event "rpc" "/notifications:create-subscription" with ID 1 priority 0 for 1 subscribers.
[INF]: SR: Processing "/notifications:create-subscription" "rpc" event with ID 1 priority 0 (remaining 1 subscribers).
[INF]: SR: Successful processing of "rpc" event with ID 1 priority 0 (remaining 0 subscribers).
[INF]: SR: Event "rpc" with ID 1 priority 0 succeeded.
[INF]: NP: Session 1: thread 4 event new RPC.
[INF]: SR: Processing "notif" "raspi-blink" event with ID 1.
[INF]: SR: Successful processing of "notif" event with ID 1 priority 0 (remaining 0 subscribers).
[INF]: NP: Session 1: thread 3 event new RPC.
[INF]: NP: Session 1: thread 3 event session terminated.
[INF]: SR: There are no subscribers for "ietf-netconf-notifications" notifications.
[INF]: NP: Generated new event (netconf-session-end).

Second session fails:
Exception in thread Thread-3:
Traceback (most recent call last):
  File "/usr/lib/python3.8/threading.py", line 932, in _bootstrap_inner
    self.run()
  File "/usr/lib/python3.8/threading.py", line 870, in run
    self._target(*self._args, **self._kwargs)
  File "/home/ubuntu/.local/lib/python3.8/site-packages/netconf_client/session.py", line 115, in _recv_loop
    ele = etree.fromstring(msg)
  File "src/lxml/etree.pyx", line 3237, in lxml.etree.fromstring
  File "src/lxml/parser.pxi", line 1896, in lxml.etree._parseMemoryDocument
  File "src/lxml/parser.pxi", line 1784, in lxml.etree._parseDoc
  File "src/lxml/parser.pxi", line 1141, in lxml.etree._BaseParser._parseDoc
  File "src/lxml/parser.pxi", line 615, in lxml.etree._ParserContext._handleParseResultDoc
  File "src/lxml/parser.pxi", line 725, in lxml.etree._handleParseResult
  File "src/lxml/parser.pxi", line 654, in lxml.etree._raiseParseError
  File "<string>", line 1
lxml.etree.XMLSyntaxError: Input is not proper UTF-8, indicate encoding !
Bytes: 0xDE 0xF6 0x93 0xF0, line 1, column 83

[INF]: NP: Generated new event (netconf-session-start).
[INF]: SR: Published event "rpc" "/notifications:create-subscription" with ID 1 priority 0 for 1 subscribers.
[INF]: SR: Processing "/notifications:create-subscription" "rpc" event with ID 1 priority 0 (remaining 1 subscribers).
[INF]: SR: Successful processing of "rpc" event with ID 1 priority 0 (remaining 0 subscribers).
[INF]: SR: Event "rpc" with ID 1 priority 0 succeeded.
[INF]: NP: Session 1: thread 3 event new RPC.
[INF]: SR: Processing "notif" "raspi-blink" event with ID 1.
[INF]: SR: Successful processing of "notif" event with ID 1 priority 0 (remaining 0 subscribers).
[INF]: NP: Session 1: thread 2 event new RPC.
[INF]: NP: Session 1: thread 2 event session terminated.
[INF]: SR: There are no subscribers for "ietf-netconf-notifications" notifications.
[INF]: NP: Generated new event (netconf-session-end).

All subsequnt sessions will also fail until netopeer2-server is restarted. Then there will be one notification again, but all other ones failing.
Relevant application plugin snippet:
            if (switch_pressed) {       //notify only "pressed" but not "released" event
              //derive connection context from session context
              ctx = sr_get_context(sr_session_get_connection(sess));
              // read led-control setting from data store
              rc = sr_get_items(sess, "/raspi-blink:gpio-config/switch/led-control", 0, 0, &val, &val_cnt);
              if (rc != SR_ERR_OK) {
                  SRP_LOG_ERR("raspi-blink: 'led-control' state read from datastore failed: %s.", sr_strerror(rc));
              }
              // create the notification
	          rc = lyd_new_path(NULL, ctx, "/raspi-blink:switch-pressed", NULL, 0, &notif);
              if (rc != LY_SUCCESS) {
                SRP_LOG_ERR("raspi-blink: Creating notification failed: %d", rc);
              }
              // add the input value
              if ((rc = lyd_new_path(notif, NULL, "/raspi-blink:switch-pressed/led-control-status", val->data.bool_val ? "true" : "false", 0, 0)) !=LY_SUCCESS) {
                SRP_LOG_ERR("raspi-blink: Creating notification value failed: %d", rc);
              }
              //send notification
              rc = sr_event_notif_send_tree(sess, notif,0,0);
              if (rc != SR_ERR_OK) {
                SRP_LOG_ERR("Raspi-blink: 'Switch-pressed' notification generation failed: %s.", sr_strerror(rc));
              }
              else
                SRP_LOG_DBGMSG("raspi-blink: ‘Switch-pressed’ notification sent.");
              //cleanup
              lyd_free_all(notif);
              sr_free_values(val, val_cnt);
            }

The sysrepo log does not contain any SRP_LOG_ERR messages, so the application code should work correctly- as it did with sysrepo v1.1.43 / netopeer2 v1.1.70
If you need further information, please let me know.
Best regards
Walter

Please use current devel of all the projects, it was already fixed.

Thanks a lot Michal!
I could verify that this issue is solved in the current development branch.


Android: Unable to Take Screenshots

Since release 28 on android, it is no longer possible to take screenshots in the app.
This is similar to my banking apps but not sure if it's a bug as on iPhone I'm still able to take screenshots.
I do see in the changelog android security flags were changed.

We should allow the app to take screenshots. We ran into this problem in the old hotspot app.

If we allow screenshots, the security screen when switching apps will not work. This seems like a binary action, we'll investigate further.


hyprctl doesn't respect XDG_RUNTIME_DIR

Hyprland Version
v0.39.1-107-g62ae2b3f
Bug or Regression?
Bug
Description
Regressed by #5788. On BSDs and non-systemd Linux distros /run/user may not exist while XDG_RUNTIME_DIR points under /var/run/user, /var/run/xdg, /tmp/.xdg-run or similar.
How to reproduce
$ sudo mv /run/user{,-disabled}
$ export XDG_RUNTIME_DIR=$HOME/.run
$ mkdir -m 0700 $XDG_RUNTIME_DIR
$ Hyprland
$ hyprctl monitors
Couldn't connect to /run/user/1234/hypr/62ae2b3f40ffce99e1d94384800e9eba6638f447_1714479208_817877068/.socket.sock. (3)

Crash reports, logs, images, videos
No response

should be fixed with d7a48cf


Add identifier to NVActivityIndicatorView

Thanks for this amazing library.
I have a simple feature request: add an identifier to the NVActivityIndicatorView class:
/// Identifier of activity indicator view
@IBInspectable public var id: String?

Thanks!

@LinusGeffarth: I wonder what is the usage of this since if you want an identifier, UIView.tag might do the job.

If you have multiple activity indicators in one view controller, you wouldn't have to hook each of them up with an @IBOutlet but could access them via their id instead.
Maybe that's too specific to my project, though.


what is error  104?

[user@dhcppc0 ~]$ youtube-dl https://www.youtube.com/watch?v=DJrMpFOOL-U
[youtube] DJrMpFOOL-U: Downloading webpage
ERROR: Unable to download webpage: <urlopen error [Errno 104] Connection reset by peer> (caused by URLError(error(104, 'Connection reset by peer'),))
how to fix it?

Try again. "Connection reset by peer" means that there was a network hiccup of some sort. (You see it all the time as a reason for disconnects from IRC chat servers)

I'm closing it as a network error. If you can watch the video on a browser but youtube-dl fails, post the output with the --verbose option and we will reopen the issue.

[user@dhcppc0 ~]$ youtube-dl --verbose https://www.youtube.com/watch?v=DJrMpFOOL-U
[debug] System config: [u'--prefer-free-formats']
[debug] User config: []
[debug] Command-line args: [u'--verbose', u'https://www.youtube.com/watch?v=DJrMpFOOL-U']
[debug] Encodings: locale UTF-8, fs UTF-8, out UTF-8, pref UTF-8
[debug] youtube-dl version 2015.05.10
[debug] Python version 2.7.9 - Linux-4.0.4-301.fc22.x86_64-x86_64-with-fedora-22-Twenty_Two
[debug] exe versions: ffmpeg 2.6.2, ffprobe 2.6.2
[debug] Proxy map: {}
[youtube] DJrMpFOOL-U: Downloading webpage
ERROR: Unable to download webpage: <urlopen error [SSL: UNKNOWN_PROTOCOL] unknown protocol (_ssl.c:581)> (caused by URLError(SSLError(1, u'[SSL: UNKNOWN_PROTOCOL] unknown protocol (_ssl.c:581)'),))
File "/usr/lib/python2.7/site-packages/youtube_dl/extractor/common.py", line 312, in _request_webpage
return self._downloader.urlopen(url_or_request)
File "/usr/lib/python2.7/site-packages/youtube_dl/YoutubeDL.py", line 1710, in urlopen
return self._opener.open(req, timeout=self._socket_timeout)
File "/usr/lib64/python2.7/urllib2.py", line 431, in open
response = self._open(req, data)
File "/usr/lib64/python2.7/urllib2.py", line 449, in _open
'_open', req)
File "/usr/lib64/python2.7/urllib2.py", line 409, in _call_chain
result = func(*args)
File "/usr/lib/python2.7/site-packages/youtube_dl/utils.py", line 713, in https_open
req, **kwargs)
File "/usr/lib64/python2.7/urllib2.py", line 1199, in do_open
raise URLError(err)

Assuming you can also watch the video using a browser in the same computer, what does echo | openssl s_client -connect youtube.com:443 output? If you have wget installed could you try running wget https://www.youtube.com/watch?v=DJrMpFOOL-U (you can also try with curl?.

youtube for me is Inaccessible but i use browsec plugin in google-chrome to open youtube. I think for this reason can't downlod.

We can't do anything then, you can try to use a proxy with the --proxy option or maybe there's an option on your system to use a VPN in all your programs (I don't know).

sudo apt-get upgrade youtube-dl
worked for me


Request to join the development team to submit new features

Request to join the development team to submit new features
https://github.com/inlhx/a1111-sd-webui-tagcomplete-10w

Please submit pull requests if you want to add new features, it is easier for me to approve or request changes in that way.
I do not speak Chinese, all translation has been done by community members or using machine translation. So it is not as easy to see your changes for me by just using your link.


This doesn't work on production

When trying to use the vite helper to grab the public path of a build file, it fails, with the following error:
In LaravelViteHelper.php line 34:
Unknown Vite entrypoint resources/css/email.css
This is how I'm using it:
public_path(vite('resources/css/email.css', 'build', true))

Hi @kirkbushell
I take it you've run npm run build? Would you be able to send me your manifest file from public/build/manifest.json?
Thanks!

Hi @kirkbushell
I have been unable to replicate this issue so unless you're able to provide more details.
Perhaps you're calling this before you have built the assets and don't have the hot server running?
If it's inside your logic, you can always wrap it in a try/catch to prevent a full failure if you're assets aren't compiled.
For now I'll close this but feel free to get back to me!

Thanks, @chrispage1 - I had built the files, so I wasn't sure what was going on, but it appears to be working now, so I have no idea. Happy to close.

👍🏻 glad you got it sorted!
Thanks,
Chris.


How to explain "algorithm evaluation"

I find it hard to explain what the difference between "model evaluation" and "algorithm evaluation" is.

Can we improve this?

the first tries to answer:
"how good is this specific model I've estimated (on data of this particular size/structure)?"
the 2nd:
"how well does my procedure to estimate models work (on data of this particular size/structure)?"

we still need to make this much clearer. i also think it is confusing to talk about this distinction on the first 2 slides

i think what we should say is this:
the goal of eval is: given some specific data set ( of size n), given a specific learner, with all hyperpars fixed, given a specific performance measure: what is the expected error on new data.
thats how we start. then later we can vary that theme. it is one question.
later we figure out that even that in ML is hard, and not so simple to do. beacause if you fit the model, you have no data left ---> hence the "sidestep" to evaluate the algorithm

a later variant is:

we dont know the hyperpats and have to learn them ---> nested resampling

Ok thanks, this helps a lot. :sunflower:


model.fit() bug when using a zipped Dataset as input for a multiple-input model

("Cross-post" of https://github.com/tensorflow/tensorflow/issues/54271)
System information.

Have I written custom code (as opposed to using a stock example script provided in Keras): yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 18.04
TensorFlow installed from (source or binary): pip
TensorFlow version (use command below): 2.9.0.dev20220202
Python version: 3.10.2

Describe the problem.
With a multi-input model, feding a dataset which returns a tuple of multiple elements to the tf.keras.model.fit() method, instead of using the whole tuple as input (then distributing each element to each input), the first element in the tuple is used as the input for the whole model.
Describe the current behavior
I have a custom model which takes 3 images as input
I have 3 separate (currently unbatched as I debug this error) datasets, classes encoded as categorical, meaning each input tensor has shape ((x, y, z), (c,))
Trying to input the 3 datasets separately fails, either by inputting them as a dict mapping each ds to a named input {"Input1": ds1, "Input2": ds2, "Input3": ds3}, or using a list [ds, ds2, ds3].
I zip the three datasets. Testing the resulting dataset with (using the docs as guidance):
for element in zipped_ds.as_numpy_iterator():
print("element", element)

Outputs:
element [[[x1, y1, z1], [c1,]], [[x2, y2, z2], [c2,]], [[x3, y3, z3], [c3,]]]
element [[[x1, y1, z1], [c1,]], [[x2, y2, z2], [c2,]], [[x3, y3, z3], [c3,]]]
...

Seems to work, right? Every call to the iterator returns 3 elements.
Well, when I use the zipped dataset as input of model_fit(), the first element in the tuple returned by the dataset object is treated as the input for the whole model, meaning that instead of using [[[x1, y1, z1], [c1,]], [[x2, y2, z2], [c2,]], [[x3, y3, z3], [c3,]]] as the input to the model, it uses [[x1, y1, z1], [c1,]], and the training fails.
I've tried many approaches, like using zipped_ds.as_numpy_iterator() or ([ds1, ds2, ds3] for idx, (ds1, ds2, ds3) in enumerate(zipped_ds)), but both fail as the returned item is empty

Standalone code to reproduce the issue
# %%
import os

import tensorflow as tf # tensorflow nightly, version>=2.5
from tensorflow import keras
from tensorflow.image import crop_to_bounding_box as tfimgcrop
from tensorflow.keras.preprocessing import image_dataset_from_directory

BATCH_SIZE=32 # Adjust?

IMG_SIZE=(224, 224)
IMG_SHAPE = IMG_SIZE + (3,)

# %%
_URL = 'https://storage.googleapis.com/mledu-datasets/cats_and_dogs_filtered.zip'
path_to_zip = tf.keras.utils.get_file('cats_and_dogs.zip', origin=_URL, extract=True)
PATH = os.path.join(os.path.dirname(path_to_zip), 'cats_and_dogs_filtered')

train_dir = os.path.join(PATH, 'train')
validation_dir = os.path.join(PATH, 'validation')

train_dataset = tf.keras.preprocessing.image_dataset_from_directory(train_dir,
                                             shuffle=False,
                                             label_mode='categorical',
                                             batch_size=32,
                                             image_size=IMG_SIZE)
validation_dataset = tf.keras.preprocessing.image_dataset_from_directory(validation_dir,
                                             shuffle=False,
                                             label_mode='categorical',
                                             batch_size=32,
                                             image_size=IMG_SIZE)

# %%
base_model1 = tf.keras.applications.MobileNetV3Large(input_shape=(64, 64, 3),
                                               include_top=False,
                                               weights='imagenet',
                                               minimalistic=False,
                                               pooling=max,
                                               dropout_rate=0.2)
base_model2 = tf.keras.applications.MobileNetV3Large(input_shape=(64, 64, 3),
                                               include_top=False,
                                               weights='imagenet',
                                               minimalistic=False,
                                               pooling=max,
                                               dropout_rate=0.2)
base_model3 = tf.keras.applications.MobileNetV3Large(input_shape=(64, 64, 3),
                                               include_top=False,
                                               weights='imagenet',
                                               minimalistic=False,
                                               pooling=max,
                                               dropout_rate=0.2)

# %%
pre_concat_layer1 = tf.keras.layers.Dense(64,
                                        activation='relu',
                                        kernel_initializer='random_uniform',
                                        bias_initializer='zeros')
pre_concat_layer2 = tf.keras.layers.Dense(64,
                                        activation='relu',
                                        kernel_initializer='random_uniform',
                                        bias_initializer='zeros')
pre_concat_layer3 = tf.keras.layers.Dense(64,
                                        activation='relu',
                                        kernel_initializer='random_uniform',
                                        bias_initializer='zeros')

post_concat_layer = tf.keras.layers.Dense(128,
                                        activation='relu',
                                        kernel_initializer='random_uniform',
                                        bias_initializer='zeros')
prediction_layer = tf.keras.layers.Dense(2,
                                        activation='softmax',
                                        kernel_initializer='random_uniform',
                                        bias_initializer='zeros')

# %%
input1 = tf.keras.Input(shape=(64, 64, 3), name="First")
input2 = tf.keras.Input(shape=(64, 64, 3), name="Second")
input3 = tf.keras.Input(shape=(64, 64, 3), name="Third")

x = base_model1(input1, training=False)
x = tf.keras.layers.GlobalAveragePooling2D()(x)
x = tf.keras.layers.Dropout(0.2)(x)
x = tf.keras.layers.BatchNormalization()(x)
x = pre_concat_layer1(x)
x = tf.keras.layers.Dropout(0.2)(x)
outputs = tf.keras.layers.BatchNormalization()(x)
body1 = tf.keras.Model(input1, outputs)

x = base_model2(input2, training=False)
x = tf.keras.layers.GlobalAveragePooling2D()(x)
x = tf.keras.layers.Dropout(0.2)(x)
x = tf.keras.layers.BatchNormalization()(x)
x = pre_concat_layer2(x)
x = tf.keras.layers.Dropout(0.2)(x)
outputs = tf.keras.layers.BatchNormalization()(x)
body2 = tf.keras.Model(input2, outputs)

x = base_model3(input3, training=False)
x = tf.keras.layers.GlobalAveragePooling2D()(x)
x = tf.keras.layers.Dropout(0.2)(x)
x = tf.keras.layers.BatchNormalization()(x)
x = pre_concat_layer3(x)
x = tf.keras.layers.Dropout(0.2)(x)
outputs = tf.keras.layers.BatchNormalization()(x)
body3 = tf.keras.Model(input3, outputs)

# %%
body1.get_layer("MobilenetV3large")._name = "MobilenetV3large1"
body2.get_layer("MobilenetV3large")._name = "MobilenetV3large2"
body3.get_layer("MobilenetV3large")._name = "MobilenetV3large3"

# %%
combinedInput = tf.keras.layers.concatenate([body1.output, body2.output, body3.output])
x = post_concat_layer(combinedInput)
x = tf.keras.layers.Dropout(0.2)(x)
x = tf.keras.layers.BatchNormalization()(x)
foutput = prediction_layer(x)
final_model = tf.keras.Model(inputs=[body1.input, body2.input, body3.input], outputs=foutput)

# %%
def resize_data1(images, classes):
    return (tfimgcrop(images,
                        offset_height=0,
                        offset_width=0,
                        target_height=64,
                        target_width=64),
                    classes)
def resize_data2(images, classes):
    return (tfimgcrop(images,
                        offset_height=0,
                        offset_width=64,
                        target_height=64,
                        target_width=64),
                    classes)
def resize_data3(images, classes):
    return (tfimgcrop(images,
                        offset_height=0,
                        offset_width=128,
                        target_height=64,
                        target_width=64),
                    classes)

# %%
train_dataset_unb = train_dataset.unbatch()
train_dataset1 = train_dataset_unb.map(resize_data1)
train_dataset2 = train_dataset_unb.map(resize_data2)
train_dataset3 = train_dataset_unb.map(resize_data3)
train_dataset_zip = tf.data.Dataset.zip((train_dataset1, train_dataset2, train_dataset3))

validation_dataset_unb = validation_dataset.unbatch()
validation_dataset1 = validation_dataset_unb.map(resize_data1)
validation_dataset2 = validation_dataset_unb.map(resize_data2)
validation_dataset3 = validation_dataset_unb.map(resize_data3)
validation_dataset_zip = tf.data.Dataset.zip((validation_dataset1, validation_dataset2, validation_dataset3))

# %%
final_model.compile()

# %%
history = final_model.fit(train_dataset_zip,
                        epochs=999,
                        validation_data=validation_dataset_zip,
                        validation_steps=32
                        )

The code I posted is executable top to bottom (given you meet the dependency, tensorflow). While it uses the cats and dogs tensorflow dataset, it mimics exactly my real code, down to the same error with model.fit()
The error I get after the last line is:
ValueError: in user code:

    File "/home/ghylander/miniconda3/envs/CH/lib/python3.10/site-packages/keras/engine/training.py", line 1021, in train_function  *
        return step_function(self, iterator)
    File "/home/ghylander/miniconda3/envs/CH/lib/python3.10/site-packages/keras/engine/training.py", line 1010, in step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/home/ghylander/miniconda3/envs/CH/lib/python3.10/site-packages/keras/engine/training.py", line 1000, in run_step  **
        outputs = model.train_step(data)
    File "/home/ghylander/miniconda3/envs/CH/lib/python3.10/site-packages/keras/engine/training.py", line 859, in train_step
        y_pred = self(x, training=True)
    File "/home/ghylander/miniconda3/envs/CH/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 67, in error_handler
        raise e.with_traceback(filtered_tb) from None
    File "/home/ghylander/miniconda3/envs/CH/lib/python3.10/site-packages/keras/engine/input_spec.py", line 200, in assert_input_compatibility
        raise ValueError(f'Layer "{layer_name}" expects {len(input_spec)} input(s),'

    ValueError: Layer "model_3" expects 3 input(s), but it received 2 input tensors. Inputs received: [<tf.Tensor 'IteratorGetNext:0' shape=(64, 64, 3) dtype=float32>, <tf.Tensor 'IteratorGetNext:1' shape=(1,) dtype=float32>]

Regarding what the train_dataset_zip object returns, this code:
for element in zipped_ds.as_numpy_iterator():
print("element", element)

returns:
element [[[x1, y1, z1], [c1,]], [[x2, y2, z2], [c2,]], [[x3, y3, z3], [c3,]]]
element [[[x1, y1, z1], [c1,]], [[x2, y2, z2], [c2,]], [[x3, y3, z3], [c3,]]]

and this code:
for id, (ds1, ds2, ds3) in enumerate(train_dataset_zip):
    print("ds1: ", ds1)
    print("ds2: ", ds2)
    print("ds3: ", ds3)

returns:
ds1:  (<tf.Tensor: shape=(64, 64, 3), dtype=float32, numpy=[(large array with raw pixel values)], , dtype=float32)>, <tf.Tensor: shape=(1,), dtype=float32, numpy=array([0.], dtype=float32)>
ds2:  (<tf.Tensor: shape=(64, 64, 3), dtype=float32, numpy=[(large array with raw pixel values)], , dtype=float32)>, <tf.Tensor: shape=(1,), dtype=float32, numpy=array([0.], dtype=float32)>
ds3:  (<tf.Tensor: shape=(64, 64, 3), dtype=float32, numpy=[(large array with raw pixel values)], , dtype=float32)>, <tf.Tensor: shape=(1,), dtype=float32, numpy=array([0.], dtype=float32)>
ds1:  (<tf.Tensor: shape=(64, 64, 3), dtype=float32, numpy=[(large array with raw pixel values)], , dtype=float32)>, <tf.Tensor: shape=(1,), dtype=float32, numpy=array([0.], dtype=float32)>
ds2:  (<tf.Tensor: shape=(64, 64, 3), dtype=float32, numpy=[(large array with raw pixel values)], , dtype=float32)>, <tf.Tensor: shape=(1,), dtype=float32, numpy=array([0.], dtype=float32)>
ds3:  (<tf.Tensor: shape=(64, 64, 3), dtype=float32, numpy=[(large array with raw pixel values)], , dtype=float32)>, <tf.Tensor: shape=(1,), dtype=float32, numpy=array([0.], dtype=float32)>

Both methods return the 3 elements you'd expect to be returned, ((image1, class1), image2, class2), image3, class3)). On top of that, the traceback already reveals that only 1 image is reaching the model:
    ValueError: Layer "model_3" expects 3 input(s), but it received 2 input tensors. Inputs received: [<tf.Tensor 'IteratorGetNext:0' shape=(64, 64, 3) dtype=float32>, <tf.Tensor 'IteratorGetNext:1' shape=(1,) dtype=float32>]

While I'm at this, I'd also like to inquire about using individual datasets, instead of a zipped one
I tried to do:
    history = model.fit([train_dataset1, train_dataset2, train_dataset3],
                        epochs=epochs,
                        callbacks=callbacks,
                        validation_data=validation_dataset_zip,
                        validation_steps=steps
                        )

but I get this error:
[ValueError: Failed to find data adapter that can handle input: (<class 'list'> containing values of types {"<class 'tensorflow.python.data.ops.dataset_ops.MapDataset'>"}), <class 'NoneType'>]()

If I try to use a dict with the name inputs instead:
    history = model.fit({'Input1': train_dataset1, 'Input2': train_dataset2, 'Input3': train_dataset3},
                        epochs=epochs,
                        callbacks=callbacks,
                        validation_data=validation_dataset_zip,
                        validation_steps=steps
                        )

I get:
[ValueError: Failed to find data adapter that can handle input: (<class 'dict'> containing {"<class 'str'>"} keys and {"<class 'tensorflow.python.data.ops.dataset_ops.MapDataset'>"} values), <class 'NoneType'>]()

I'm confused as to why I get these errors, only thing I can think about is unability of handling Dataset objects nested in the list or dict

@sachinprasadhs Was able to replicate the issue on colab using TF v2.8.0 and tf-nightly(2.9.0.dev20220302) ,please find the gist here.Thanks!

Hi
Any progress on this matter?
I know it's possible to write custom training loops, but this seems like something the built-in training loop should be able to handle

thanks for the input @gowthamkpr, but that's my very own SO issue I opened before I figured out:

How to approach/implement what I wanted to do (use 3 separate datasets as input for a single model with 3 different inputs, and distribute each input accordingly)
How to achieve this (using tf.data.Dataset.zip() ), but there being a bug.

In the issue I mention the only workaround that I can think of, writing a custom training loop.
However, I've kept this open as I fell this kind of behaviour should be supportted by the keras built in model.fit() training loop method

up, I have the same issue

While I'm at this, I'd also like to inquire about using individual datasets, instead of a zipped one
I tried to do:
    history = model.fit([train_dataset1, train_dataset2, train_dataset3],
                        epochs=epochs,
                        callbacks=callbacks,
                        validation_data=validation_dataset_zip,
                        validation_steps=steps
                        )

but I get this error:
[ValueError: Failed to find data adapter that can handle input: (<class 'list'> containing values of types {"<class 'tensorflow.python.data.ops.dataset_ops.MapDataset'>"}), <class 'NoneType'>]()

If I try to use a dict with the name inputs instead:
    history = model.fit({'Input1': train_dataset1, 'Input2': train_dataset2, 'Input3': train_dataset3},
                        epochs=epochs,
                        callbacks=callbacks,
                        validation_data=validation_dataset_zip,
                        validation_steps=steps
                        )

I get:
[ValueError: Failed to find data adapter that can handle input: (<class 'dict'> containing {"<class 'str'>"} keys and {"<class 'tensorflow.python.data.ops.dataset_ops.MapDataset'>"} values), <class 'NoneType'>]()

I'm confused as to why I get these errors, only thing I can think about is unability of handling Dataset objects nested in the list or dict

While working on a project of my own, I have gotten stuck for a day trying to figure out why I can't get the training to work, only to find that I'm having the same issue as described here.

@ghylander
I have a working script (i.e., the model trains smoothly), but I am not sure if that is what you want. Please take a look and let me know:
The key issue here is that we are inspecting only the inputs and not the outputs. Note that the model architecture is 3 inputs, 1 output. Thus, our dataset should be in that format as well. See the image below.
Now, the current dataset has the structure: ((img, label), (img, label), (img, label)) but actually we want  it to be ((img, img, img), label). So, we simply write a function which does exactly this and map the dataset accordingly.
def post_zip_process(example1, example2, example3):
    print((example1[0], example2[0], example3[0]), example1[1])
    return (example1[0], example2[0], example3[0]), example1[1]

train_dataset_zip = train_dataset_zip.map(post_zip_process)
validation_dataset_zip = validation_dataset_zip(post_zip_process)

And the training works just fine. Please take a look at the gist here.

/cc @Faptimus420 @rozhanroukhosh  @gowthamkpr @sushreebarsa

@AdityaKane2001 Thank you very much, that worked. I did have to add a .batch(1) function after .map(post_zip_process) for the network to train (.batch(32) would not work), but it worked.
I feel like I should have been able to realize this myself, though the documentation on the .fit function does not seem to really talk about this situation of using tf.data datasets in a multi-input network well, only about using raw tensors or numpy arrays. Maybe a slight revision there should be considered...
I do have a follow-up question though: Is there a way to combine your solution with passing in a dict for the x argument of .fit, where I could still use the format {'input1': tf.data dataset1, 'input2': tf.data dataset2, ...}?

@ghylander
Requesting to close this issue in case it is resolved. Thank you.

Hi, sorry, just saw this
I'll try your working script and report back

I tried this method you shared on my own dataset and your python notebook and ran into a common problem. In data set training, validation values have a fixed value and no increase occurs. Model training result and my own python notebook are attached. I would be glad if you help.
My Python Notebook: https://github.com/ahmetfurkaann/MultiView-Model/blob/main/MultiView_Model.ipynb
Your dataset result is:

My dataset result is:

@ghylander,
As suggested above, I tried to execute the code with the alternative approach on tensorflow v2.13 and it was executed without any issue/error. Kindly find the gist of it here. Thank you!

Hi, checked this and it seems to work.
It's been quite long, so it's honestly a bit hard to firmly confirm or deny this was the intended behaviour back then.
If I understood correctly from @AdityaKane2001's post, this wasn't really a bug but a result of misinterpretation of the documentation/expected behaviour?

@ghylander Maybe.

@ghylander,
As mentioned, if the issue wasn't really a bug, could you please feel free to move this issue to closed status. Thank you!


Can't deploy ghost on github pages

Hello, I'm trying deploy ghost using your deploy scripts but i have problem with push. Could you help me provide any info what should I do next and if you have time.

Hi @Keidro,
This problem occur due to Github team had replaced the init master brance name with the main branch name at 2020/10 (This repo last update time is 2020/05)
You can replace you git command with
cd $OUTDIR
git init -b main
git remote add origin "$remote_url"

git add .
git commit -m "Initial commit"
git push origin main -f

These code will help you init the main branch name instead of master branch name at the git repo init step (p.s. you need to upade you git version for the latest version, so that you can use the -b parameter)
I also fix some bug in this shell, and I have send the PR to the author, so before he decide to merge it,  maybe you can use my code at #36, or the raw data Fixed deploy.sh
Hope that will help you to enjoly ghost : )


Decryption using DES in ECB mode with the EVP interface is failing

Note that the encryption succeeds and EVP_CipherUpdate() at that point encrypts the entire buffer of 80 bytes.  In reverse, the decryption of the same data returns 72 bytes (1 block of 8 bytes less than the input), and call to EVP_CipherFinal() fails.
Running the following test on Ubuntu 22.04 with openssl installed:
ii  openssl        3.0.2-0ubuntu1.6 amd64        Secure Sockets Layer toolkit - cryptographic utility
#include <string.h>
#include <openssl/evp.h>

int test_des_decrypt()
{
    EVP_CIPHER_CTX* ctx = NULL;
    int success = 0;

    unsigned char key[8] = {
        0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07
    };

    unsigned char cipher[80] = {
        0x5d, 0xa7, 0x47, 0xc5, 0x1a, 0xb1, 0x71, 0xff,
        0xc8, 0x45, 0x7c, 0xa7, 0x07, 0xec, 0x4b, 0x13,
        0x47, 0x55, 0x77, 0xbc, 0xcf, 0x71, 0xd9, 0x27,
        0x23, 0x12, 0x2a, 0x17, 0x20, 0xad, 0xc1, 0x19,
        0x3e, 0x74, 0x38, 0x29, 0x48, 0xb0, 0xd2, 0xe2,
        0x18, 0x45, 0xdd, 0x8a, 0x9b, 0x8d, 0x40, 0xec,
        0x9e, 0x0c, 0x41, 0xa3, 0x36, 0x40, 0xf5, 0x91,
        0x41, 0x44, 0xde, 0xa1, 0xb5, 0x9d, 0x39, 0x99,
        0x23, 0x12, 0x2a, 0x17, 0x20, 0xad, 0xc1, 0x19,
        0xee, 0xe3, 0xbe, 0x0b, 0x83, 0x36, 0xe1, 0x25
    };

    unsigned char expect[80] = {
        0x4f, 0x6e, 0x20, 0x74, 0x68, 0x65, 0x20, 0x63,
        0x6c, 0x69, 0x65, 0x6e, 0x74, 0x20, 0x73, 0x69,
        0x64, 0x65, 0x2c, 0x20, 0x74, 0x68, 0x69, 0x73,
        0x20, 0x69, 0x73, 0x20, 0x74, 0x68, 0x65, 0x20,
        0x73, 0x65, 0x6e, 0x64, 0x20, 0x6b, 0x65, 0x79,
        0x3b, 0x20, 0x6f, 0x6e, 0x20, 0x74, 0x68, 0x65,
        0x20, 0x73, 0x65, 0x72, 0x76, 0x65, 0x72, 0x20,
        0x73, 0x69, 0x64, 0x65, 0x2c, 0x20, 0x69, 0x74,
        0x20, 0x69, 0x73, 0x20, 0x74, 0x68, 0x65, 0x20,
        0x72, 0x65, 0x63, 0x65, 0x69, 0x76, 0x65, 0x20
    };

    unsigned char plain[80] = {};
    int outlen = 0;
    int offset = 0;

    ctx = EVP_CIPHER_CTX_new();
    if (ctx) {

        if (EVP_CipherInit(ctx, EVP_des_ecb(), key, NULL, 0)) {

            if (EVP_CipherUpdate(ctx, plain, &outlen, cipher, sizeof(cipher))) {

                offset += outlen;  // outlen seems to always be nblocks - 1 in length, i.e. (80 - 8)  = 72 bytes; since 80/8 = 10, I'd expect the entire buffer be decrypted.

                if (EVP_CipherFinal(ctx, plain+offset, &outlen)) { // at this point the EVP_CipherFinal returns 0, expected 1, and plain to be complete.

                    if (memcmp(plain, expect, 80) == 0) {

                        success = 1;
                    }
                }
            }
        }
        EVP_CIPHER_CTX_free(ctx);
    }

    return success;
}

            offset += outlen;  // outlen seems to always be nblocks - 1 in length, i.e. (80 - 8)  = 72 bytes; since 80/8 = 10, I'd expect the entire buffer be decrypted.

This is because, by default, standard padding of the data is assumed. OpenSSL is holding back the last block in case it turns out to be one containing padding data that needs to be stripped.

            if (EVP_CipherFinal(ctx, plain+offset, &outlen)) { // at this point the EVP_CipherFinal returns 0, expected 1, and plain to be complete.

It fails because the padding in the decrypted data is not as expected.
If your data is not padded then you need to switch padding off by calling the following immediately after your EVP_CipherInit call:
    EVP_CIPHER_CTX_set_padding(ctx, 0);

If you are not using padding then the plaintext must be a multiple of the blocksize.
Making the above change still does not end up in a "success" result. The memcmp fails. Probably there is something incorrect with the encrypted data.

You are right, when I update the code to disable padding; the decryption succeeds. Not sure why the example failed, but my version of the code worked (including the memcmp()).


RenderTransform doesn't honour the paint offset

@apwilson noticed that if you have a Transform widget inside a Padding widget and the transform is just a scale, the horizontal alignment is off. Looks like _effectiveTransform isn't taking the offset into account when applying the alignment.

Confirmed with @apwilson this is not affecting him currently, removing pink.


Use 'installer' for unpacking wheels into the venv

Currently we assume there's a pip installed in the same bin directory as python, and we assume the version is compatible with the flags passed. If using the hermetic toolchains from rules_python this is generally okay, however if using a different toolchain or that of the host, then we can not guarantee the presence of pip where we expect it.
An alternative would be to use https://github.com/pypa/installer directly and not have pip involved.
Another alternative would be to not to use either for actions, and have bazel layout the venv using the runfiles symlinks.

Closed via https://github.com/aspect-build/rules_py/pull/233


[pkgs.linux_rpi4] Out-of-date & cannot build.

Current version: https://github.com/NixOS/nixpkgs/blob/master/pkgs/os-specific/linux/kernel/linux-rpi.nix#L6
Latest version: https://github.com/raspberrypi/linux/releases/tag/1.20210928
Checklist

[x] Checked the nixpkgs master branch
[x] Checked the nixpkgs pull requests

Project name
nix search name: linux_rpi4
current version: 1.20210805
desired version: 1.20210928
Notify maintainers
maintainers: @thoughtpolice
Note for maintainers
Please tag this issue in your PR.

I assume that I have the same problem.
After setting boot.kernelPackages = pkgs.linuxPackages_rpi3; the build fails with the following error message:
[...]
root module: ext2
  copying dependency: /nix/store/4ahwzl25nz7bqsqydkc7l8q7lnjvj4b7-linux-5.10.52-1.20210805-modules/lib/modules/5.10.52/kernel/fs/ext2/ext2.ko.xz
root module: ext4
  builtin dependency: ext4
root module: ahci
modprobe: FATAL: Module ahci not found in directory /nix/store/4ahwzl25nz7bqsqydkc7l8q7lnjvj4b7-linux-5.10.52-1.20210805-modules/lib/modules/5.10.52
builder for '/nix/store/mrr310qyphcb5mn218547yl9qi96z8gv-linux-5.10.52-1.20210805-modules-shrunk.drv' failed with exit code 1
cannot build derivation '/nix/store/k98qavxcv3qlc8wlkqm2dlq1sbbbrck4-stage-1-init.sh.drv': 1 dependencies couldn't be built
cannot build derivation '/nix/store/r171hpg4d75iyrx0ffjx5h7m3w9ifn3z-initrd-linux-5.10.52-1.20210805.drv': 1 dependencies couldn't be built
cannot build derivation '/nix/store/52r52bw4clbv3jikzawxb98hmy0kn3ja-nixos-system-raspi-21.11.334415.7d5ec2a2b4e.drv': 1 dependencies couldn't be built
error: build of '/nix/store/52r52bw4clbv3jikzawxb98hmy0kn3ja-nixos-system-raspi-21.11.334415.7d5ec2a2b4e.drv' failed

Exit code: 100
I would like to fix this but I do not have enough experience. Could someone help?
Thx!

I found out that I need to set boot.initrd.includeDefaultModules = false; in my configuration.nix. Now, my nixos-rebuild switch runs successfully.
Nevertheless IMHO this should be set automatically when using an RaspberryPi kernel.

I also use option boot.initrd.availableKernelModules = lib.mkForce [ ]; to make this.

I recently rebuilt and updated the packages in #209742


error when running 'test_eval.py'

Hi, thanks for your code, it's great : )
I got an error when running the test and eval command in README.md: python test_eval.py --ckpt <checkpoint> --sampling_type generalized --w_global_pos 1 -- w_global_node 1 --w_local_pos 4 --w_local_node 5.
the error is as follows:
Traceback (most recent call last):
File "/data/0shared/xxx/xxx/MDM/eval.py", line 69, in retrieve_qm9_smiles
with open(file_name, 'rb') as f:
FileNotFoundError: [Errno 2] No such file or directory: '../qm9/temp/qm9_smiles.pickle'
Hope you'll help me with it, thanks a lot!!!

Hi,
Thank you for your interest.
You could run the compute_qm9_smiles function to obtain the desired file.

When run the compute_qm9_smiles function to obtain the desired file，the './data/GEOM/QM9/train_data_40k.pkl' folder was not found.

When run the compute_qm9_smiles function to obtain the desired file，the './data/GEOM/QM9/train_data_40k.pkl' folder was not found.

You could use this link to get access to this data: https://portland-my.sharepoint.com/:u:/g/personal/lhuang93-c_my_cityu_edu_hk/EbpAY1autKdEggYTwGsf44MBtCIRunwncdWa4zUjOswmHQ?e=G8DEmR


Minimum API version

Please tell what is the minimal Android API version for you library?
For example, on API 10 Speech.init() gives java.lang.NoClassDefFoundError: net.gotev.speech.TtsProgressListener.
I've got into trouble with the production version of my app for a user with 2.3.3 version of Android.

 You can find it also here: https://github.com/gotev/android-speech/blob/master/speech/build.gradle
@Ruthvik47 has probably fallen asleep on his keyboard :smiley: Have a nice rest!

Can we use this as wake up word like googe has okay Google ?


Upload progress doesn't get properly recorded

I have some sequences of EXIF-tagged pictures I'd like to upload. For unknown reasons they were interrupted. (Message was: Failed to upload sequence at /path/to/pictures. Restart the script in order to finish you upload for this sequence. and also the thing described in https://github.com/openstreetcam/upload-scripts/issues/86 happened.) I'm not sure if the issue I'm going to describe is a consequence of that...
Whenever I start to upload the sequences the counter says 2605/9267 images. Altough the upload script uploaded gigabytes of data and eventually finished (again with Failed to upload sequence at /path/to/pictures. Restart the script in order to finish you upload for this sequence.), this progress doesn't seem to get recorded:

If I restart the upload of the sequences again, the counter says 2605/9267.
If I cancel the upload and restart again, the counter says 2605/9267.

What I would expect:

Even tough a sequence might not get uploaded completely in the first or second try, some progress should be made and be recorded in the sequence's progress data.
Ctrl-C-ing a running upload should not prevent progress data from being written.

Some infos:

I used version 600c3d4
Python version is 3.6.7 on Ubuntu

Addendum: The upload gets a lot this messages, when run with logging on debug level:
2019-06-09 13:36:53,042 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2651
2019-06-09 13:36:53,419 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2646
2019-06-09 13:36:53,716 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2652
2019-06-09 13:36:53,788 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2650
2019-06-09 13:36:53,970 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2645
2019-06-09 13:36:54,024 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2653
2019-06-09 13:36:54,179 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2649
2019-06-09 13:36:54,414 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2647
2019-06-09 13:36:54,523 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2648
2019-06-09 13:36:54,601 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2651
2019-06-09 13:36:54,703 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2646
2019-06-09 13:36:54,717 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2654
2019-06-09 13:36:54,945 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2652
2019-06-09 13:36:55,221 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2650
2019-06-09 13:36:55,363 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2653
2019-06-09 13:36:55,602 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2649
2019-06-09 13:36:55,653 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2645
2019-06-09 13:36:55,927 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2648
2019-06-09 13:36:55,964 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2647
2019-06-09 13:36:56,161 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2646
2019-06-09 13:36:56,673 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2654
2019-06-09 13:36:57,067 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2650
2019-06-09 13:36:57,174 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2652
2019-06-09 13:36:57,182 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2648
2019-06-09 13:36:57,199 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2651
2019-06-09 13:36:57,218 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2653
2019-06-09 13:36:57,233 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2649
2019-06-09 13:36:57,371 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2647
2019-06-09 13:36:57,387 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2646
2019-06-09 13:36:57,391 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2645
2019-06-09 13:36:58,267 osc_tools.osc_api_gateway          : DEBUG    Failed to upload photo index: 2654

@ltog - an unfortunate storage downtime occurred and it took a while to get it resolved. Everything is up and running now.
@bogdans-telenav - any reason why the upload should't work right now?

Bump -- Would be nice if issues were cleared up :)

Issue should be fixed in the meantime.


BROOKLYN-350 Curl will follow location redirects

externalizing the CURL command
adding default parameter so curl follows location redirects

@ygy Not very intuitive approach with using a ConfigKey. Still could be sensible in some situations.

@bostko @neykov Can you review the new version?

@ygy Looks good!

+1, merging.


Print budget formatting

Please delete/modify if this is not where bugs are to be reported.
Printing budget from Chrome has column heading page 1, rest of budget on following pages.
Printing budget from Firefox 44 returns blank page 1, column headings and first part of budget on page two, following page(s) blank.

This is the perfect place, thank you! I'll label this accordingly and one of the team will look into this for you.

The Chrome issue has been fixed, and the bug fix should be in place in the next release.
The Firefox bug may be fixed already due to the Chrome fix, but I'll have to look at this.

I've just released. @topcat39, are you still having this issue with v0.3.7?

I will check when I get back to my regular, non-Mac computer next week.
I'll be sure to try the new version on my daughter's Mac
On Feb 12, 2016 11:32 PM, "Kevin Brown"<EMAIL_ADDRESS>wrote:

I've just released. @topcat39 https://github.com/topcat39, are you
still having this issue with v0.3.7?
—
Reply to this email directly or view it on GitHub
https://github.com/blargity/toolkit-for-ynab/issues/188#issuecomment-183615525
.

Hi! I'm back from vacation. I've upgrade to 0.3.9 within Firefox 44.0.2. The budget still doesn't print correctly. Page 1: blank, Page 2: a lot of white space, No additional pages to print the rest of the budget.

Thanks for letting me know. I've made some recent changes (not live just yet, but should be coming soon) that may fix the issue, but I'll double check and see if I can get it fixed if it isn't.

Thanks. This is not high on my wish list, so there is no rush, as far as I
am concerned.
On Sun, Feb 21, 2016 at 3:42 PM, Benjamin Falk<EMAIL_ADDRESS>wrote:

Thanks for letting me know. I've made some recent changes (not live just
yet, but should be coming soon) that may fix the issue, but I'll double
check and see if I can get it fixed if it isn't.
—
Reply to this email directly or view it on GitHub
https://github.com/blargity/toolkit-for-ynab/issues/188#issuecomment-186910777
.


feedback on 01-introduction

@boersn
pg 16 object-orientation programming object-oriented programming?
you should add yourself to the presenters/mentors list at the end

Thanks!


Update csproj to work correctly with CI

Update package number and remove auto-generation of nuget package.

no more useful, @peache85 commit the changes directly during commit e8e38a972ac1adcaa264decb35538ffe7f499088


Expire commit container images after 1 week

Prior to podman 4.6.0, there is a bug that would cause the expiration tag to be added to the "main" container image as well in the build.yaml workflow. See the buildah bug report:
https://github.com/containers/buildah/issues/4632
As a workaround, the --no-cache flag is used to build container images with the "build-image" make target.
This workaround, can be removed when we use a runner image that has podman>=4.6.0. Currently, the ubuntu-latest runner image we use has 3.4.4.
close #397

Well that's a bit weird! Do you think we should use the buildah image in our CI[1], or stick with this approach which allows us to keep the core build logic in our Makefile?
[1]https://github.com/redhat-openshift-ecosystem/openshift-preflight/blob/main/.github/workflows/build-main.yml#L31-L43

I think this is a fine workaround. I'm aware of the buildah step that is used in preflight, but I personally like better to build all our images using the make target ("keep the core build logic in our Makefile" as you well put it).

--no-cache: do not use existing cached images for the container build. Build from the start with a new set of cached layers.

So there is a performance hit for using this flag, which IMO is acceptable. If we think this it too annoying (e.g. we run make build-image in our daily workflows locally, and have to wait a considerable amount of time), we can also make this flag optional, something like:
Makefile:
[...]
BUILD_FLAGS=""

[...]
build_image:
    podman build $BUILD_FLAGS -t ....

and in build.yaml:
make build_image BUILD_FLAGS="--no-cache" ...

But I'm not sure this is even necessary... Building images is mostly done is the pipeline, and it's okay if it takes one more minute IMO.

FYI I just amended the commit to improve the readability of the make target with line breaks.


Support ConfigurableFileCollection = FileCollection assignment for Groovy and Kotlin

Fixes https://github.com/gradle/gradle/issues/23546

I implemented it here a bit differently as it is for property:
For property, we generate a setter even if property is writable and with the argument "Object". I guess this is because we use .setFromAny().
For ConfigurableFileCollections we generate a setter only if the property is read-only and with the argument "FileCollection".

@bot-gradle test this

@bot-gradle test this

I've triggered the following builds for you:

PullRequestFeedback build

@bot-gradle test this

I've triggered the following builds for you:

PullRequestFeedback build

@bot-gradle test and merge

I've triggered a build for you.

@bot-gradle test and merge

Your PR is queued. See the queue page for details.

I've triggered a build for you.

Pre-tested commit build failed.

@bot-gradle test and merge

Your PR is queued. See the queue page for details.

I've triggered a build for you.

Pre-tested commit build failed.

@bot-gradle test and merge

I've triggered a build for you.


IndexedDB Recognition fails on Safari 11 when using Angular 5

Tested on macOS with Safari 11.0.1 and iOS 11.2
Safari itself is detected correctly, however the hasFetch check doesn't work.
var hasFetch = typeof fetch === 'function' && fetch.toString().indexOf('[native code') !== -1;
The first part evaluates to true, but the [native code] can not be found and thus hasFetch is false.

Can you share the result of fetch.toString()?

Sorry should have done that immediately.
It turns out that Angular 5 (or something Angular uses) is monkey patching fetch to intercept it, and thus breaks localforage.
You can test it e.g. on https://angular.io:
> console.log(fetch.toString())
[Log] function (){var t=e.apply(this,arguments);if(t instanceof E)return t;var n=t.constructor;return n[Z]||p(n),t}

It works as expected on non Angular apps

Actually the patching is done by Zone.js (which is used by Angular).
See https://github.com/angular/zone.js/blob/326a07fb9095e4a87ff7561cb45fe1d4917c2174/lib/common/promise.ts

I guess we can plan to change that in v2.0 to use a regex and explicitelly detect safari < 10.2.
We should probably also release a new version for the  localforage compatibility plugin.
@tofumatt what do you think?

I agree. Our feature detection is roundabout (we aren’t actually checking for fetch because we use it) and it’s probably better to do a new compatibility release too. 👍🏻

Is the IndexedDB support still buggy on iOS Safari 10.0 through 10.2, or do we just not have an easy way of detecting them?

It's still light in safari <10.2 and we didn't expect monkey patching the fetch API to be so widely used and stop our 10.2 detection from working.

We could do something like https://github.com/DamonOehlman/detect-browser/blob/master/index.js for our safari detection.

See: Pouch DB merged PR
See: Pouch DB dropping Safari < 10.1 support and the fetch check

See: Pouch DB merged PR
See: Pouch DB dropping Safari < 10.1 support and the fetch check

Interestingly enough canIUse shows Safari v10.0 as fully compatible as well, but PouchDB guys test cases only passed on 10.1+ .

@fifafu, @lfairy and anybody interested on this issue getting resolved, can you try out #799 and share some feedback?


src/cipher: engine support sm4 and des-ede3

1.add sm4 and des-ede3
2.init cipher first before do_cipher
Signed-off-by: linwenkai<EMAIL_ADDRESS>

have repeat uninit problem, please not merge now, thx


New version: Robotlib v1.0.0

Registering package: Robotlib
Repository: https://github.com/baggepinnen/Robotlib.jl
Created by: @baggepinnen
Version: v1.0.0
Commit: ccc876b393fb993a2d5947f3b07c1d168a569aa7
Reviewed by: @baggepinnen
Reference: https://github.com/baggepinnen/Robotlib.jl/issues/26#issuecomment-691671857

I'm not sure why auto-merging has not happened for this PR?

[noblock]

Please re-trigger Registrator. This will fix the merge conflicts.

Please edit all of your comments to include the text [noblock]. Otherwise, AutoMerge will not happen.

[noblock]
cc: @baggepinnen


Can't Download Past Trips (UWP)

I can record trips (using an paired OBD) and when finished and I stop the recording I get a the screen that says it is saving the trip.  The trip shows up in the past trips list but when I try to retrieve one it says Unable to load Trip...Please check internet connection and try again.  I'm connected to the internet because I can browse with IE.
Nokia 635 phone running Windows 10 Mobile (10.0.10586.107 OS).

Hello elwardrm,
Thanks for reporting this issue. Do you see the same issue when you restart the app ? This might also happen due to a weak/faulty network connection as the error says it is unable to find the network. Please let us know if you see this issue even after restart or joining a WIFI network.
Thanks,
VJ

VJ,
I rebooted the phone to be sure the application was reloaded.  I also made sure I was under a Wi-Fi access point with as strong Wi-Fi signal.  Still tunable to load the past trips from today.  The interesting thing is that this has been flaky all week.  I have three trips from 2 and 3 days ago that I can load the past trip.  But those trips would have been with an earlier version as I am trying to load each new release to see if it fixes the problem.
Thanks,
Bob

Bob Elward, P.E. | Director, IT Materials Technologies Separation
Air Products & Chemicals Inc. | 7201 Hamilton Blvd. | Allentown, PA 18195
elwardrm<EMAIL_ADDRESS>| •610-481-6644
This communication is intended solely for the person addressed and is confidential and may be privileged. If you receive this communication incorrectly, please return it immediately to the sender and destroy all copies in your files. If you have questions, please contact the sender of this message.
From: VaijanathA<EMAIL_ADDRESS>Sent: Wednesday, April 13, 2016 2:27 PM
To: Azure-Samples/MyDriving
Cc: Elward,Bob
Subject: Re: [Azure-Samples/MyDriving] Can't Download Past Trips (UWP) (#502)
Hello elwardrm,
Thanks for reporting this issue. Do you see the same issue when you restart the app ? This might also happen due to a weak/faulty network connection as the error says it is unable to find the network. Please let us know if you see this issue even after restart or joining a WIFI network.
Thanks,
VJ
—
You are receiving this because you authored the thread.
Reply to this email directly or view it on GitHubhttps://github.com/Azure-Samples/MyDriving/issues/502#issuecomment-209581058

VJ,
I was able to get a trip saved and then retrieve it as a post trip.  Aging this seems to be very hit and miss.  I'm pretty sure it's not my network connection as I check each time to see if I can browse the web with IE.
Additionally, the "profile" page shows the summary of all my trips but doesn't score my driving skills.  All I get is 0%.
Thanks,
Bob

Android -- I wasn't able to view an individual Past Trip when I tried on April 14 and April 15. This morning it pulls up fine though. On WiFi now and the previous times I was not but had strong signal. I would tap the trip and it would flash a loading dialog and immediately go back to the Past Trips screen.
Now that I can actually see Past Trips for the first time, it's pretty nifty to slide through the trip! Cool!

Hello Elwardrm/Dankraus,
We are tracking this as #508 I will go ahead and close this. Thanks for reporting these issues.
~VaijanathA


Fix generated OB data-model equals methods to use compareTo for DateTime types

DateTime.equals expects the objects to both use the same timezone, issues have been observed where the TZ inputs differ but the times are equivalent i.e. if converted to epoch time then would be identical.
We had a similar issue previously with BigDecimals where scale needs to match, this was fixed by using compareTo see: https://github.com/SecureApiGateway/secure-api-gateway-ob-uk-common/pull/101
Update generated code to use compareTo for DateTime objects.

This is causing issues with the new Consent Store API in the RCS, as MongoDB by default stores are times in UTC. Whereas our test data all uses machine default timezone, which at the time of writing is BST.

Currently, there are 465 fields in the data model of type DateTime!

Won't fix this, as too many instances to change.
Our jackson config will negate the issue, as we always convert incoming DateTime data to UTC. Therefore, we just need to force UTC time in unit tests which do not do Jackson serialization.


Config option exclude_input not recognized by HTMLExporter.

Hi
In one of my computer (windows) I am routinly using the command:
jupyter-nbconvert -to html --TemplateExporter.exclude_input=True --execute --output output_html notebook.ipynb
However when trying the same command on another (linux) I get the header massage.:
Config option exclude_inputnot recognized byHTMLExporter.
I did update  nbconvert , so it does not seem to be the reason. Can anyone suggest what am I missing? Or another procedure for printing notebook to html?

You should probably ask at https://github.com/jupyter/nbconvert/issues?


Update to arrow2 0.16

arrow2 0.16.0 was just released!
I would very much appreciate if you could release a new arrow2-convert as soon as you can 🙏❤
PS: Thanks for such a great crate!

thanks 🙏