feenableexcept undefined when building on macOS

Output from building on macOS:
[  2%] Building CXX object CMakeFiles/common.dir/mnistreader.cc.o
[  4%] Building CXX object CMakeFiles/common.dir/textsupport.cc.o
clang: clang: warning: argument unused during compilation: '-msse2' [-Wunused-command-line-argument]warning:
clang: warning: argument unused during compilation: '-mavx' [-Wunused-command-line-argument]
argument unused during compilation: '-msse2' [-Wunused-command-line-argument]
clang: clangwarning: : warning: argument unused during compilation: '-mavx' [-Wunused-command-line-argument]
argument unused during compilation: '-mavx2' [-Wunused-command-line-argument]clang:
clangwarning: : argument unused during compilation: '-mavx2' [-Wunused-command-line-argument]warning:
clang: warning: argument unused during compilation: '-mfma' [-Wunused-command-line-argument]
argument unused during compilation: '-mfma' [-Wunused-command-line-argument]
[  4%] Built target common
[ 14%] Building CXX object CMakeFiles/tensor-convo.dir/tensor-convo.cc.o
[ 14%] Building CXX object CMakeFiles/img-ocr.dir/img-ocr.cc.o
[ 14%] Building CXX object CMakeFiles/tensor-convo-par.dir/tensor-convo-par.cc.o
[ 14%] Building CXX object CMakeFiles/tensor-relu.dir/tensor-relu.cc.o
clang: warning: argument unused during compilation: '-msse2' [-Wunused-command-line-argument]
clang: warning: argument unused during compilation: '-mavx' [-Wunused-command-line-argument]
clang: clang: warning: argument unused during compilation: '-msse2' [-Wunused-command-line-argument]
clangwarning: : warning: argument unused during compilation: '-mavx' [-Wunused-command-line-argument]
argument unused during compilation: '-mavx2' [-Wunused-command-line-argument]
clang: clang: clangwarning: warning: : warning: argument unused during compilation: '-mfma' [-Wunused-command-line-argument]argument unused during compilation: '-msse2' [-Wunused-command-line-argument]

clang: argument unused during compilation: '-mavx2' [-Wunused-command-line-argument]warning:
argument unused during compilation: '-msse2' [-Wunused-command-line-argument]
clang: warning: argument unused during compilation: '-mavx' [-Wunused-command-line-argument]
clang: warning: clang: argument unused during compilation: '-mavx2' [-Wunused-command-line-argument]warning:
argument unused during compilation: '-mfma' [-Wunused-command-line-argument]
clang: warning: argument unused during compilation: '-mavx' [-Wunused-command-line-argument]
clang: warning: argument unused during compilation: '-mavx2' [-Wunused-command-line-argument]
clang: warning: clang: warning: argument unused during compilation: '-mfma' [-Wunused-command-line-argument]
argument unused during compilation: '-mfma' [-Wunused-command-line-argument]
/Users/hvanderschuur/Projects/dev/hello-dl/img-ocr.cc:39:27: warning: lambda capture 'rows' is not used [-Wunused-lambda-capture]
  auto getintens=[&data, &rows, &cols](int c, int r) {
                       ~~~^~~~
/Users/hvanderschuur/Projects/dev/hello-dl/tensor-relu.cc:90:3: error: use of undeclared identifier 'feenableexcept'; did you mean 'feraiseexcept'?
  feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW );
  ^~~~~~~~~~~~~~
  feraiseexcept
/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX13.3.sdk/usr/include/fenv.h:299:12: note: 'feraiseexcept' declared here
extern int feraiseexcept(int /* excepts */);
           ^
/Users/hvanderschuur/Projects/dev/hello-dl/tensor-convo.cc:67:3: error: use of undeclared identifier 'feenableexcept'; did you mean 'feraiseexcept'?
  feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW );
  ^~~~~~~~~~~~~~
  feraiseexcept
/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX13.3.sdk/usr/include/fenv.h:299:12: note: 'feraiseexcept' declared here
extern int feraiseexcept(int /* excepts */);
           ^
1 error generated.
make[2]: *** [CMakeFiles/tensor-relu.dir/tensor-relu.cc.o] Error 1
make[1]: *** [CMakeFiles/tensor-relu.dir/all] Error 2
make[1]: *** Waiting for unfinished jobs....
1 error generated.
make[2]: *** [CMakeFiles/tensor-convo.dir/tensor-convo.cc.o] Error 1
make[1]: *** [CMakeFiles/tensor-convo.dir/all] Error 2
[ 17%] Building CXX object CMakeFiles/tensor-convo-par.dir/ext/sqlitewriter/sqlwriter.cc.o
clang: warning: argument unused during compilation: '-msse2' [-Wunused-command-line-argument]
clang: warning: argument unused during compilation: '-mavx' [-Wunused-command-line-argument]
clang: warning: argument unused during compilation: '-mavx2' [-Wunused-command-line-argument]
clang: warning: argument unused during compilation: '-mfma' [-Wunused-command-line-argument]
[ 19%] Building CXX object CMakeFiles/img-ocr.dir/vizi.cc.o
clang: warning: argument unused during compilation: '-msse2' [-Wunused-command-line-argument]
clang: warning: argument unused during compilation: '-mavx' [-Wunused-command-line-argument]
clang: warning: argument unused during compilation: '-mavx2' [-Wunused-command-line-argument]
clang: warning: argument unused during compilation: '-mfma' [-Wunused-command-line-argument]
In file included from /Users/hvanderschuur/Projects/dev/hello-dl/vizi.cc:7:
/Users/hvanderschuur/Projects/dev/hello-dl/ext/stb/stb_image_write.h:776:13: warning: 'sprintf' is deprecated: This function is provided for compatibility reasons only.  Due to security concerns inherent in the design of sprintf(3), it is highly recommended that you use snprintf(3) instead. [-Wdeprecated-declarations]
      len = sprintf(buffer, "EXPOSURE=          1.0000000000000\n\n-Y %d +X %d\n", y, x);
            ^
/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX13.3.sdk/usr/include/stdio.h:188:1: note: 'sprintf' has been explicitly marked deprecated here
__deprecated_msg("This function is provided for compatibility reasons only.  Due to security concerns inherent in the design of sprintf(3), it is highly recommended that you use snprintf(3) instead.")
^
/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX13.3.sdk/usr/include/sys/cdefs.h:215:48: note: expanded from macro '__deprecated_msg'
        #define __deprecated_msg(_msg) __attribute__((__deprecated__(_msg)))
                                                      ^
/Users/hvanderschuur/Projects/dev/hello-dl/vizi.cc:66:22: warning: lambda capture 'out' is not used [-Wunused-lambda-capture]
  auto box = [&pix, &out](int col, int row, int w, int h, uint8_t cr, uint8_t cg, uint8_t cb) {
                  ~~~^~~
1 warning generated.
2 warnings generated.
[ 21%] Linking CXX executable img-ocr
[ 21%] Built target img-ocr
[ 24%] Linking CXX executable tensor-convo-par
[ 24%] Built target tensor-convo-par
make: *** [all] Error 2

Found some articles that seem to provide a solution… unfortunately, I lack the skills to apply it :-)

@hwschuur hello, simply wrap this and the other occurrences in #ifndef __APPLE__ and #endif respectively before and after the offending line, like so (example taken from tensor-convo.cc):
#ifndef __APPLE__
  feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW );
#endif

Be careful, the line that contains feenableexcept might be different in each file, so add the #ifndef __APPLE__ and #endif combo by hand, don't copy/paste the whole block with 3 lines!

Files that need to be adapted:
first-convo.cc:  feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW );
mnistposter.cc:  feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW );
tensor-convo.cc:  feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW );
tensor-relu.cc:  feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW );
try-convo.cc:  feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW );

Note that tensor-convo-par.cc also contains the line, but it is commented out and thefore can be left as is:
  //  feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW );


How to enrich reactions

I want to store reactions as a Laravel eloquent object, so I can enrich it.
How to enrich this data from the feed? I added a model reference in the data field, but i'm not sure if it is possible in this way?

https://github.com/getstream/stream-chat-python


Unable to query by id of collection attribute

I am working on a Waterline query which filters objects by a collection attribute. In this simplified example, I  have two models, Video and Category:
// Video.js

module.exports = {

attributes: {
    title: {
      type: 'string'
    },
    categories: {
      collection: 'Category'
    }
  }
};

// Category.js

module.exports = {

  attributes: {
    name: {
      type: 'string'
    }
  }
};

I want to find all the videos which are associated with a certain category. I have the category id stored in a variable named categoryID and am trying this query:
Video.find('categories': categoryID).exec(function (err, videos) {
    // videos should contain all videos associated with the categoryID
});

However, I always end up with an empty result, even though there are videos associated with the category for which I am looking. I know that waterline does currently not support deep queries for values in collection attributes, but I thought at least a query for the id of the object would work. Am I wrong?
If so, is there an alternative way to achieve the desired result without using native queries?

+1

@schmida1980 this is currently not supported. There is a feature proposal in the roadmap and also #266.


Introduce LangChangeEvent interface

Introduce LangChangeEvent interface

Hello, thanks for the PR.
Is there a reason for this change ?
Also can you add the type on line 69:
public onLangChange = new EventEmitter<LangChangeEvent>();

to
public onLangChange: EventEmitter<LangChangeEvent> = new EventEmitter<LangChangeEvent>();

It's easier to declare a event handler method (in users code) using handle(event: LangChangeEvent) than handle(event: { lang: string, translations: any }).
Adding the type is not necessary since ts will infer the type from the initial assignment.

Good points ! Thanks !
I'll merge it with a few other things for the next release.


fix(CardStack): #37

@LeoLeBras see the PR plz.
Don't know why build failed on Travis :(

Hey @DiMoNTD 🌈 ,
Thanks for this PR ! Travis fails due to this error :

You need to update this snapshot to pass travis.

@LeoLeBras I have problems with run jest testing. I run it from Windows, and I have such Error:
FAIL  modules\__tests__\StackUtils-spec.js
  ● Console

    console.error node_modules\react-test-renderer\cjs\react-test-renderer.development.js:1973
      React caught an error thrown by Route. You should fix this error in your code. Consider adding an error boundary to your tree to customize error handling behavior.

      Error: Cannot find module 'Text' from 'react-native-implementation.js'

      The error is located at:
          in Route
          in Router
....

And such Error everywhere that have react-native Components in test.
So I can't update snapshots.

@LeoLeBras I fixed problems with jest.. just ran it from macOS 🌈 😆
So PR now ready for merge!

Awesome ! ❤


ph.hash hanging indefinitely in 18.3.0?

Setup/Issue
We deploy via a dockerfile to AWS and make rpc calls.   We tracked down the issue to 18.3.0 causing our rpc calls to hang indefinitely at ph.hash(password).   After forcing a revert to 18.1.0 everything works as expected.    The only difference in code or dockerfile is the version of the argon2_cffi package installed.
Strangeness
We have the ability to simply call the rpc method directly in the dockerfile.   Executing the method directly on the aws server through the dockerfile does not hang.   Because of this I actually convinced myself that there was nothing wrong with 18.3.0.   After a lot of headache I was amazed that simply isolating the version fixed our issues.    I have no idea what could possibly be causing the issue.  We are running inside an asyncio eventloop to make rpc calls (specifically uvloop).   Not sure if that could cause the issue but seems that is the only additional puzzle piece.
Sorry we couldn't debug further.   We are reverting and moving on, but figured better to raise an issue.
 I.e. PasswordHasher(time_cost=2, memory_cost=512, parallelism=2, type=argon2.Type.I)
If so, maybe try to isolate which parameter is to blame?

@hynek Works fine with the 18.1.0 parameters.  Seems the issue is the memory cost.   The original memory cost was 512 the new default memory cost in 18.3.0 is 102400? Are you sure you meant to increase the default memory cost that much or is it a typo and you wanted to double it to 1024?   Things start breaking for us at a memory cost of 2**16.
I think what could be happening to us is that we have memory constraints on our container.    If the memory is spiking that could cause problems.   Our containers are set to about 100MB.    Not sure how the memory cost translates to used ram.

Yeah it was on purpose, because the RFC recommends even 1–4 GB so I went for 100 MB as a compromise. So the answer is basically that the hasher made your app swap? :)

Well the issue is that the default values for argon2_cffi went from requiring 512kB of ram to produce a single hash to requiring 100MB of ram for every hash that is generated.    This is a 2 orders of magnitude increase, which for sure caught us off guard.   I don't think programs changing default memory requirements 2 orders of magnitude should be done lightly.   At a minimum I would make this pretty explicit in the docs.
The RFC recommendations state
The Argon2id variant with t=1 and maximum available memory is recommended as a default setting for all environments

More memory is simply better for security, but has tradeoffs.  Your default setting now says that the absolute minimum RAM necessary to run the default argon2_cffi is 100MB.   That is up to you, but that kind of change should be more pronounced.
I think a better default would be something like 1024 meaning that someone trying out argon_cffi won't see these large memory consumptions and then put a comment that "RFC recommendations suggest xMB or yGB for memory cost for maximum security".  Let the user set that parameter to whatever they feel is their available maximum available memory.

I can assure you that that decision hasn’t been made lightly. In fact, I had started working on it at the PyCon US 2018 sprints in May and was procrastinating on it because it is a touchy topic.
My three alternatives basically were:

ignore RFC, get angry issue from security folks that I’m being irresponsible and the world is ending due to my neglect
(somewhat) implement RFC, with the risk of getting issues like this one

I think I picked the right option but the execution might be lacking despite months of work.

Let the user set that parameter to whatever they feel is their available maximum available memory.

This goes against the spirit of PasswordHasher though. You’re supposed to be safe if you use it and again I prefer to introduce some obvious failure than being silently insecure. I’m sure we’ll agree that if I rely on people figuring out their parameter than nobody will do anything at all.

All that said the question is how to proceed since obviously it’s not my intention to tell people “lol your own fault for not reading docs”. The only thing I can think of is a docs & changelog update that warn about the default memory requirement.

@hynek I think the best option is to put a short description of default parameters on the main page of the docs.   A kind of "these are the defaults" and I do think telling your users that they need a minimum of 100MB to run PasswordHasher with the defaults is a good idea.
My point is only that making changes that impact RAM by 2 orders of magnitude probably deserves a pretty bold description.
I get that you probably deal with some pretty stingy security folk.   I still think that any security folk worth their salt agrees that the parameters used do not guarantee anything other than some minimum amount of computation time/memory to try to crack given hashes.    Is 100MB really more secure than 93MB, or less secure than 110MB?   Why not 1GB default, which would be another 10x more memory difficult to break or even 10GB?   The reason not 1GB or 10GB is because there are practical tradeoffs that have to always be made.   It is pretty impractical to have 10GB of RAM dedicated to every single hash.    That said, I understand that you want want a high bar for security as a default in PasswordHasher, but 'safe' isn't a real thing.    It is all just some amount of computational power/time to thwart reasonable effort in the future given the resources of today.
As far as I'm concerned this issue is closed from our end.    Thanks for making PasswordHasher!

@hynek that is awesome:)!   With that, I will for sure come to your defense if anyone even remotely tries to complain like I did.


Issue with apps becoming "third party"

When attempting to run certain apps (i.e. Snapchat), I am warned or locked out of my account for using a "third party" application. I understand that this is because of the way the apk is unpacked and manipulated in order to work on chrome, but is there any feasible away around this using chromeos-apk?

Well for me it would be enought to get sha1 of aplication


remove traling slash in nginx configuration for non-Vue resources

Actually would also suggest to change that line in Ansilbe Nginx configuration: https://github.com/CodeForPoznan/pah-fm/blob/41d44a5a2578792e5480409dce07d86c90ded0bd/ansible/nginx.conf.j2#L10

Good idea!


help something that I want to confirm my understanding is right or not about this article.

background
I have some details need to ask for your help since I am in trouble with reproducing the method (Add+SGD) results in the article "Adding Interpretable Attention to Neural Translation Models Improves Word Alignment".
my anlysis
I have reproduce the method (Rand + SGD) mentioned in this article, so I thought is my errors was caused by forward pass Initialization.
article discription
the article mentioned that: "Therefore, we run a forward pass of the complete Transformer network, extract the attention weights of the alignment layer and start the optimization process with these weights."
my understanding
my understanding is the forward pass model includes the alignment layer and the transformer structure. and I restore all parameters of the forward pass model which has trained.but I got the alignment results is 50% which is lower than your article.

I have reproduce the method (Rand + SGD) mentioned in this article, so I thought is my errors was caused by forward pass Initialization.

Were you able to reproduce the results of the alignment head without optimization (Add)?

my understanding is the forward pass model includes the alignment layer and the transformer structure. and I restore all parameters of the forward pass model which has trained.but I got the alignment results is 50% which is lower than your article.

For debugging I would do the following:

Run the forward pass and extract the attention activations from the alignment layer.
Verify: Check what AER you get from those attention activations.
Initialize the Variable of the Attention Optimization network (which you want to optimize later) with the attention activations and run a forward pass without optimization. Output the variable containing the unchanged activations. (Unchanged because you did not run a backward pass.)
Verify: Verify that the AER does not change when you extract the attention activations from the variable above.
Run a single optimization step (that is backward pass where you only update the single attention variable).
Verify: Extract the values from the optimized variable again and check if the AER improved.
Now you should be able to run the full process with multiple optimization steps.

thank you for your reply, and I have some terminology understanding problem.

Verify: Check what AER you get from those attention activations.

those attention activations is means alignment layer initialized methods?

at present, My reproduce the ADD+SGD get the nearly same AER with the RAND +SGD.

It's important to look at the forward pass and attention optimization as different steps. (The following uses tensorflow concepts of Variables and Tensors.) In the forward pass your attention activations will be a tensor, during attention optimizations you have to store the attention activations in a Variable, because you can only optimize Variables. Therefore your implementation (in tensorflow) of the attention optimization network is slightly different compared to the Alignment Layer for the forward pass, as you have to store the attention activations in a Variable first and then update this variable. In the forward pass the attention is the result of a calculation and thus a Tensor, and you cannot directly optimize Tensors.
When you look at Figure 1 in the Arxiv Paper, during the forward pass you run the whole network and extract A. When doing attention optimization you only evaluate the "Attention Optimization" Subnetwork. A will be a Variable now, and for efficiency you would also cache V' and feed it to the Attention Optimization subnetwork.

those attention activations is means alignment layer initialized methods?

No, you get those attention activations by fetching the values of the attention vector of the alignment layer from the forward pass.

the Attention Optimization network is means alignment layer and transformer standard structure ?

The Attention Optimization subnetwork is (a part of) the Alignment Layer. In contrast to the forward pass the Alignment Layer does not calculate the attentions, but stores those in a Variable, and optimizes only this Variable during backpropagation.

Runing a forward pass without optimization ? without optimization is not update variable usually.

Yes, you run a forward pass through the whole Transformer. You will initialize the Variable A of the subnetwork Attention Optimization with the value extracted from the forward pass.

Thank you for your kindness reply. I have read your reply many times and I have try to understanding your reply and article. I am a student I am not understanding with some description in your reply.
in your description

during the forward pass you run the whole network and extract A.

my understanding is that the transformer network is forward pass and the alingnment layer is trainable parameters which can be update. I have to run the forward pass to attention optimization and then I extract the weights in A. last I start new optimization with restore those weights in A and the transformer parameters is fixed?
in your acticle,

during inference we optimize the attention weights A of the sub-network attetnion optimization.

as usual, the inference step is a process to obtain predicts and no optimization. So I am a little confused.

in your description, "during forward pass and during inference" is means fix other parameters besides attention weights?

as usual, the inference step is a process to obtain predicts and no optimization. So I am a little confused.

Given a trained network (which includes the trained Transformer and the trained alignment head) during attention optimization (which is done during the inference step in the paper) you only optimize the attention activations. In tensorflow you can do this by using the var_list parameter:
opt.minimize(self.loss, var_list=[self.attention_variable])

To optimize the attention activations you have to use a variable instead of a tensor (at least in tensorflow), which changes the implementation of your network slightly.

To optimize the attention activations you have to use a variable instead of a tensor (at least in tensorflow), which changes the implementation of your network slightly.

I thought the attention activations A is means the trainable metrix and then I set it to be trainable=True and other parameters trainable=false, this method is will be ok.
or you are try to explain for me your the attention activation is the result of this Equation？

the attention activation is the result of this Equation？

Yes, also see equation (1) in the arxiv paper. During attention optimization treat A in Figure 1 as a Variable and initialize this variable with the result of equation (1).

A is not a variable in model and it is not a parameters . How can I initialize ? it is confused.

OK, I am sure your expression is that you have said.

I have another things to confirm, so the A is the only parameters which is trainable in attetnion optimization? or the parameters in attention optimization parts on Figure 1 in the Arxiv Paper.

I have another things to confirm, so the A is the only parameters which is trainable in attetnion optimization?

Correct. See: https://github.com/lilt/alignment-scripts/issues/3#issuecomment-498188982

the A is the results of attention and A trainable matrix is related to batch_size, source length and target length. So it is how to choose which batch to extract A and initialize?

You can use a batch size of 1 for attention optimization, a variable of shape (1, max_length, max_length), get the src_len and tgt_len of the current example dynamically using tf.shape and use A[:, :target_length, :source_length] to get a submatrix of A with the right dimensions.

I have try and faild to get the results in your article. RAND SGD and ADD+SGD get the same results 62.2%. you say using the max_length as the attention activations dimensions but the A extracted from forward pass is dynamically different, under this consideration, I using the max_src_length and max_tgt_length in the all training data store and initialize A[:, :target_length, :source_length] = extract_A . (where A.shape=[1,max_length, max_length])

Please verify first if you get a reasonable AER when using the alignment layer without SGD (Add). This probably already fails in your case.

I have verify and get better training loss. But I have got the same alignments AER. I have a problem about understanding, If I using the A as variable and A is attention weights. When I using attention weights to get alignments after training, It will be always be a certain value as long as sentence pair with equal sentence length both source length and target length. according to my knowledge, it is unreasonable since the same length sentence has different structure and alignment.

When I using attention weights to get alignments after training, It will be always be a certain value as long as sentence pair with equal sentence length both source length and target length.

During training you do not use a Variable for the attentions. You can just extract the attention of the alignment head of the trained model, convert it to alignments and score these alignments.
You only use a variable when performing attention optimization. I will close this issue for now as this discussion did not progress anymore recently.

Sorry, my expression is Inaccurate, this reproduce is very important for me.

I have down the alignment layer training and attention optimization. I retell  as follows:
the question is that：after the attention optimization, the attention weights is attention activations A, so A will be unrelated to target sentence information and it is only related to the length of target.
if I did not misunderstanding your former explanation. @thomasZen

@thomasZen Thank you for your kindness help, I have reproduce your work with the results

--
AER (deen)
AER(ende)
BIdir

sgd+ lr0.001(best 6step)
25.6
30.2
23.5

@PlayDeep That's awesome, congratulations!

@thomasZen  help Have any possible reason lead my bidir aer lower than yours?

When using scripts/combine_bidirectional_alignments.py the method grow-diagonal worked better for this scenario than grow-diagonal-final, that could be a possible reason.

I have test all methods and every ende and deen checkpoint combination. and not get a better results.

Interesting, a common mistake after doing multiple SGD steps was that punctuation marks would always get aligned to other punctuation marks. For sentences with a different number of commas, that was not a useful behavior. I could imagine that by doing more (6 instead of 3) optimization steps these errors could appear more often.
If you use --source and --target in scripts/aer.py it will output the most common errors, looking at these is interesting and could be helpful.

@thomasZen Thank you for your insight comments, I using SGD with learning rate 0.001 which differ from yours, That might is the main reason for I using 6 instead of 3 steps. And I thought my learning rate is lower than yours, this might is a mismatch with transformer training parameters. Because I using the default parameters as "attention is all you need". I want to verify this guess.

There are two different learning rates that can be different:

The learning rate for training the alignment layer
The learning rate when performing attention optimization

We tuned the learning rate and the number of optimization steps for attention optimization on the development set.


Improper formatting and code escaping when merging/syncing a PR

I opened #1541 and it was merged, but the formatting of the Details section, specifically the indentation and some escaping within code blocks is wrong. If you look at the JSON file in the PR, you can see that the indenting is correct and there are no improper escapes. How did this happen?
Example of incorrect indents and escaping in current published advisory:

Correct indents and escaping in maintainer alert:

#1554 was opened to address this problem, but that PR does not contain fenced code blocks, so it will not have syntax highlighting.
What I really want is for the GitHub published advisory to exactly match the maintainer advisory.

#1554 was merged despite my protest. While it fixed the indentation, it removed fenced code blocks and there were still improper escapes once the merge was synced with the actual advisory database. I opened #1560 to fix this. Please make sure that it has proper character escaping this time.

Hey @jordanbtucker thanks for the feedback here. We're taking this on as an engineering bug fix and getting it prioritized to resolve.

Hey @jordanbtucker we're looking back into this and no longer seeing any differences between the published global and maintainer advisory. Did you find a way to fix this manually or did we resolve the character escaping issue after all?

@KateCatlin Yes this appears to be fixed now! 🎉 Thanks! 🙏


implemented changes to fix card size

My PR closes #446
Changes proposed
What were you told to do ?
Fix the difference in card sizes issue.
What did you do ?
Implemented changes to fix the card size by changing min height property.

Check List (Check all the applicable boxes)

[x] My code follows the code style of this project.
[x] This PR does not contain plagiarized content.
[x] The title and description of the PR is clear and explains the approach.

Screenshots

Do let me know if you think all the changes are made
( include screenshots )

This screeenshot is without any new changes. Is this not correct?

Here's the height difference.

But in my local it is fine only. No Problem you can close this PR and assign it to someone else.
Thanks.

But in my local it is fine only. No Problem you can close this PR and assign it to someone else. Thanks.

That's why i asked you to check  the deployment preview
The screenshot you sawe, is from the same.


chore: remove unnecessary uses of CategoryTheory.Equivalence.mk

An equivalence of categories consists of a functor, an inverse, and unit and counit isomorphisms which satisfy the same compatibilities as for adjoint functors. However, certain equivalences are constructed via the constructor Equivalence.mk which does not assume these compatibilities: by changing the unit isomorphism, it is possible to satisfy the compatibility. When only the existence of an equivalence matters, we may certainly use Equivalence.mk. However, the more we develop the library, the more we may need to unfold the definitions of unit/counit isomorphisms (as it happened in #12728). Then, if it is possible, we should not use Equivalence.mk. In this PR, most uses of Equivalence.mk are removed: in most cases, the compatibilities satisfied by adjunctions were easy to prove.

maintainer merge

!bench

Very nice.

bors delegate+
Thanks!

Very nice.

Actually, I believe that at some point, some proofs of triangle compatibilities were removed because of performances issues. The situation looks better now :-)

When it passes CI, please merge

Thanks!
bors merge


JuliaCon 2021: The OSCAR Computer Algebra System

Video link: https://www.youtube.com/watch?v=rWQK4mU3jQc
0:07 Introduction
0:34 What is OSCAR?
1:14 Who are we?
2:07 The structure of OSCAR
3:52 Features of OSCAR
5:05 Feature highlight: multivatiate polynomials
6:27 Oscar vs. Symbolics
7:29 Conclusion

@logankilpatrick are you watching this repository or should I tag you on every issue?

Feel free to keep tagging me or not since I am watching the repo. Thanks again for this, really helps!

I'm happy to help, it really pleases me when videos have timestamps. (Besides, noting down the chapters helps me retain the content after I watch the videos! :smile:)


fix errors showed by linters

fix errors showed by linters

/test all

/test pull-warden-integration-test

/test pull-warden-integration-test

/retest

/retest

/test pull-warden-integration-test

/test pre-warden-lint


improvement: org name in project config

Adding a mandatory org key to fern.config.json. The org should get propagated to any nested .fernrc.yml files. This means that fern.config.json is required, but maybe we wind that back.

One other thing to think about is how to handle open source repos (i.e. someone makes an open source contribution to fern which changes the ir, how do they run fern generate) That's why i think specifying orgName in repo and maybe configuring access to the org can be done in a web app.


Update to OpenSearch 1.1

As End User, I would like to take advantage of OpenSearch 1.1 without having to re-create the complete cluster when updating existing stacks.
Currently the update policy of the domain does not allow Version Upgrades. However, we want to make sure existing deployment are not broken and can still be upgraded to the latest version 1.1.

Verified working, but the upgrade itself takes a little time. Just as an FYI.


Added a first draft of the keepAlive mechanism for a pod.

Hello world with keep alive example
What is this
This is an example of a keep alive mechanism with the existing scheduler.
Purpose of this PR
I want to grab some attention and discuss the current scheduler interface. Currently it's not that elegant, and to integrate with it we need some workarounds such as queues.
This PR shows the challenges of integration with the current version.
I think we should discuss a better interface and rewrite it to make it simpler.
How it works
It's similar to @zen-dog PR, but instead of crashing on pod failure we increase the incarnation number and reschedule pod. Underneath, it has a flow that consumes state updates and transforms them into a stream of pod spec changes.
What to look at
Have a look on keepAliveWatcher flow, as well as Sink/Source queues used for integrating with the scheduler.
JIRA issues: DCOS-48963

I'm closing this PR in favor of #82


Document how to #[derive(specta::Type)] a struct with fields of external types

Hello, I have the following type:
#[derive(Debug, Clone, Serialize, Deserialize, specta::Type)]
pub struct Person {
  id: surrealdb::sql::Thing,
}

But the following error occurs: the trait bound `surrealdb::sql::Thing: specta::Type` is not satisfied.
Is there a way to make it work?
Because as a way arround, I used a generic parameter but it takes two type definitions for one:
#[derive(Debug, Clone, Serialize, Deserialize, specta::Type)]
pub struct _Person<I> {
  id: I,
}
pub type Person = _Person<surrealdb::sql::Thing>;

Thanks

You should be able to do use a type override (type =).
#[derive(Debug, Clone, Serialize, Deserialize, specta::Type)]
pub struct ThingDef {
    pub tb: String,
    pub id: Id,

#[derive(Debug, Clone, Serialize, Deserialize, specta::Type)]
pub struct Person {
  #[specta(type = ThingDef)]
  id: surrealdb::sql::Thing,
}

Alternatively, you could just convert surrealdb::sql::Thing into ThingDef using From. That would be required if you want something like HashMap<String, Thing> as type = can't be used on a map key or value.
I know the docs can use some work, I have some thoughts about what I wanted to do in #100 and I do intend to do a "Typing the untyped" sorta page.

Thanks, it looks like https://serde.rs/remote-derive.html.
I will stick with:
#[derive(Debug, Clone, Serialize, Deserialize, specta::Type)]
pub struct Person<I = surrealdb::sql::Thing> {
  id: I,
}


fix: Various LGTM fixes

Description of Change

Various LGTM fixes. - #880
Checklist

[x] Added description of change
[x] PR title follows semantic commit guidelines
[x] Search previous suggestions before making a new one, as yours may be a duplicate.
[x] I acknowledge that all my contributions will be made under the project's license.

Notes:

Both issues should be fixed now.

All issues should be fixed now.
Thanks, @kvedala! 🙂

please ensure all codes

[ ] compile
[ ] execute
[ ] return values as expected

@mishraabhinn @ayaankhan98 please review as well. Thanks

@kvedala all programs seem to be running fine, thanks.
However, the parenthesis_matching.cpp program always prints Wrong Expression, no matter what I type.

@kvedala all programs seem to be running fine, thanks.
However, the parenthesis_matching.cpp program always prints Wrong Expression, no matter what I type.

try this input:
{{(())}}

Thank you, it worked.
Everything seems to be fine with all programs.


Split code in API route handlers into multiple middleware functions

The Problem
I usually see the following pattern in the API route handlers:
if (condition1) {
  if (condition2) {
    if (condition3) {
      try {
        // the portion where we execute the handler routine to manipulate the data
        // this portion is small but gets indented several levels
        // because of the if-else and try-catch error handling blocks
      } catch (err) {
        // err
      }
    } else {
      // error 3
    }
  } else {
    // error 2
  }
} else {
  // error 1
}

I have thought about returning early in the middleware function to avoid nested if-else and try-catch blocks, but there are things that still bug me, such as that

I'm not sure if putting a return in a middleware function will produce any side-effects.
The whole process of checking auth, validating inputs, etc., and then the main logic of what the API route handler is supposed to do is still a big chunk of code inside a single function. The process has multiple steps, and thus we should separate them based on their concerns.

Proposed Solution
For these reasons, I think it'd be better to utilize next() and/or put additional middleware functions in between to handle various errors (like shown in Express's error handling guide). If Express offers us ways to handle errors while processing requests, we should use them.
What It Will Look Like
If we agree on how we should refactor these error handling steps, I think our refactored handlers will look like this (take PATCH /user/:userId as an example) (refer to this page for the syntax):
app.patch("/:userId", [
  // middleware to check for user authentication
  requireAuth,
  // check if the provided `userId` in the route is a positive integer
  (req, res, next) => {
    // do stuff
    // only next() if satisfied
  },
  // check if the authenticated user has permission to perform the action
  (req, res, next) => {
    // do stuff
    // only next() if satisfied
  },
  // validate the request body against the user schema
  (req, res, next) => {
    // do stuff
    // only next() if satisfied
  },
  // THE MAIN LOGIC
  (req, res, next) => {
    try {
      // sanitize the body

      // call the data-access function in the user model

      // respond with success
    } catch (err) {
      // log the error

      // respond with error
    }
  }
]);

What It Will Improve
This solution separates the API route handling process into multiple parts, each of which concerns itself with only what it's supposed to do: auth checking, role checking, request validation, etc., and then the main logic at the end. As a result, the main logic is less indented and thus more readable and maintainable.
Furthermore, since we repeatedly role-check the authenticated user, we can easily put the role-checking code into a function (just like requireAuth) and pass it into this route handler, but that's another refactor for another time--I'm just showing the flexibility of this solution.

I think it would be worthwhile looking into a refactor that is inline with this suggestion, something that might be easier to discuss today in person after our client meeting.
In the above example I wonder if the // check if the provided userId in the route is a positive integer step should be handled by the schema. In general I think it may make sense for the schema validation to happen before any other forms of validation.
I like the idea of avoiding indentation issues by using middleware in general.
I don't think this is an issue or a conflict, but I would like to clarify the basic structure I expect from an endpoint just so we can make sure we are on the same page or find a middle ground:

User is authenticated (We now know the user is who they say they are)
Schema validation (Ensures that the inputs are sanitized / prevents unexpected inputs).
Constraint validation (Follows our client's request to run multiple functions against the input to ensure no constraints are violated - Logic check against inputs).
Requested action is performed.


feat(air): add new constraint to bitwise_pow2 aux_table

This PR address #206.
New constraints have been added to bitwise_pow2 aux_table to assert that the selector values remain same throughout the cycle.

Thanks for the review! I've actioned on the suggested changes.

Looks good, thank you!


OS X fullscreen state not remembered

Unlike TileMill and Apple's OS X apps, if fullscreen mode is on when last quit, Studio doesn't restart in fullscreen.

@incanus this is causing this (seemingly harmless) error for me that pops up when the app starts:

Dupe & already addressing in https://github.com/mapbox/mapbox-studio/pull/1182.


Fixes SPARK-12910: R version for installing sparkR

Testing code:
$ ./install-dev.sh
USING R_HOME = /usr/bin
ERROR: this R is version 2.15.1, package 'SparkR' requires R >= 3.0

Using the new argument:
$ ./install-dev.sh /content/username/SOFTWARE/R-3.2.3
USING R_HOME = /content/username/SOFTWARE/R-3.2.3/bin
* installing *source* package â€˜SparkRâ€™ ...
** R
** inst
** preparing package for lazy loading
Creating a new generic function for â€˜colnamesâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜colnames<-â€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜covâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜na.omitâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜filterâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜intersectâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜sampleâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜transformâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜subsetâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜summaryâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜lagâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜rankâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜sdâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜varâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜predictâ€™ in package â€˜SparkRâ€™
Creating a new generic function for â€˜rbindâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜lapplyâ€™ from package â€˜baseâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜Filterâ€™ from package â€˜baseâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜aliasâ€™ from package â€˜statsâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜substrâ€™ from package â€˜baseâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜%in%â€™ from package â€˜baseâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜meanâ€™ from package â€˜baseâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜uniqueâ€™ from package â€˜baseâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜nrowâ€™ from package â€˜baseâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜ncolâ€™ from package â€˜baseâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜headâ€™ from package â€˜utilsâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜factorialâ€™ from package â€˜baseâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜atan2â€™ from package â€˜baseâ€™ in package â€˜SparkRâ€™
Creating a generic function for â€˜ifelseâ€™ from package â€˜baseâ€™ in package â€˜SparkRâ€™
** help
No man pages found in package  â€˜SparkRâ€™
*** installing help indices
** building package indices
** testing if installed package can be loaded
* DONE (SparkR)

Can one of the admins verify this patch?

Jenkins, ok to test

Merged build finished. Test FAILed.

Test FAILed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/49709/
Test FAILed.

Test build #49721 has started for PR 10836 at commit 0b3960a.

Test build #49721 has finished for PR 10836 at commit 0b3960a.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/49721/
Test PASSed.

LGTM. cc @felixcheung

looks good.

looks good.

Merging this to master


add pdf to the extensions allowed to be precached

Summary
When we use a pdf file in our code, the plugin does not include it in the precache variable of the service worker.
Things done in this PR

[x] add extension pdf to the supported extensions
[x] add a note in the readme about the supported extensions

Does this PR introduce a breaking change? No

thanks for the contribution

new version(v1.1.2) is available now


Github release doc

What is being addressed
Document the release process and include a script that helps include all component versions.

/test-force-approve
not covered by PR tests


add example for normalizr and reselect

Coverage remained the same at 76.842% when pulling 9ed5652dcde74e5133a5c96005969f5c7223ba00 on dev into 7602ba6ed5ca8efbea5dceb6abc886c40011bb38 on master.


[Feature] Add support for in-url base64 encoded images

Reopened this PR to master: https://github.com/pinterest/PINRemoteImage/pull/240#issuecomment-244811759

@Adlai-Holler  should I rebase this branch from master to exclude commits before e1b0a7d?

Rebased: https://github.com/pinterest/PINRemoteImage/pull/246


BadUSB payloads

Free and open-source BadUSB payloads for Flipper Zero.

How do I download it

How do I download it

https://github.com/aleff-github/my-flipper-shits


Add exp of power series

https://codeforces.com/contest/1792/submission/191188773

Implemented in #22


Correct order of steps when using service accounts with IAM role

What happened?
I've created an IAM role, annotated the service account, set an fsgroup and created the required provider config on the security context on the provider's deployment. I'm not sure what happens but I get the following error on resources I try to create:
'connect failed: unable to read web identity token file in pod: open
      : no such file or directory'

After restarting the pod authentication starts to work.
What is the correct order of the following steps?

creating the provider config
annotating the service account
setting the fsgroup on the deployment

I'm installing the provider using the Helm chart's provider.packages option.
Crossplane: 1.0.0
AWS provider: 0.16.0

@hasheddan is this still happening with your recent updates?

@hasheddan is this still happening with your recent updates?

I think the updated doc should work here. @bandesz could you confirm?

I think the updated doc should work here. @bandesz could you confirm?

@hasheddan I just changed our setup to use ControllerConfig today (based on the linked docs), and all seem to work, so I will close this. Good timing with your question :)

@hasheddan I just changed our setup to use ControllerConfig today (based on the linked docs), and all seem to work, so I will close this. Good timing with your question :)


ML Daemon runtime improvement

Hi.
ANT has been using Caffe as the runtime of the ML daemon.
However, the libraries used by Caffe are not optimized for ARM devices, making it difficult to achieve good performance.
In order to achieve good ML performance in IoT devices, it is first necessary to use a good baseline library.

We decided to use TVM instead of Caffe and ArmCL.
I close this issue.


Stabilize Keycloak (New Arch)

As owner of a client app, I want to restrict or enable users to use specific policies regarding the login type.
Description

Eventually, we want to turn off the existing personal BCeID option
BCeID integration will be restricted to 3 realms. Basic, Business or Both
Personal BCeID’s will continued to be used
New requests for integration with personal are restricted with possible exception
ISSUE: Personal BCeID field … email is empty so SAML is invalid
Eventually, we want to turn off the existing personal BCeID

Acceptance Criteria

Scenario 1

GIVEN: Basic Realm
WHEN:
THEN:

Scenario 2

GIVEN: Business Realm
WHEN:
THEN:

Scenario 3 Priority
GIVEN: I'm creating an application that needs basic and business BCeID logins
WHEN: I go through the realm-o-matic process
THEN: I end up with a client that can facilitate logins to basic and business but NOT personal
Scenario 4

GIVEN: Personal BCeID
WHEN: Requests for integration with the everything Realm
THEN: Inform user they need special approval from WAM team

Change Management Plan

New requests will be directed to use new options only
Legacy account migrations TBD

Activities

Document this process within a service blueprint format

Note: Process is for BCeID approval first (This process exists today)

Get a list of Realms that are consuming personal BCeID by querying the end points with user names to establish types (Conrad offered to help pair program) Note: this is needed for migration.
Validate with users which type of realm they require. If a realm has only basic, it’s possible they’ve never had a business logging in. Double check they don’t need “both” even though it looks like they only need “basic”.
Build new segregated realms systems. Test in Sandbox PRIORITY

WAM team has set up test environments and we need to set up the realms
Christine Sutherland is the lead on the WAM team.
iStore ticket from Shelly says that the WAM team is ready.

SAML Config afterwards. However, the playbook is only for IDIR. Need to update Ansible Playbook
Migrate accounts into new realms

Additional Notes

Conrad and Marco are suggesting that the users could participate in the migration.
When we provision using realm-o-matic we should add logic to choose 1, 2, or 3
Maybe a script that users can opt to use and migrate their realm to the new structure via Real o matic interface (Script is needed)
#Timeline
Var suggested alignment with vanilla realm.
Tech tasks

OLD Ticket Description
Create separate realms for BCeID Personal/Basic/Business.
This will allow fine grain access to each of the BCeID account types. (i.e. if an application only supports Basic, only Basic should be available; currently all three types are always available)
What's required?

Three new BCeID realms (one for each type)
New BCeID credentials for each realm (iStore orders)
Migration scripts to allow teams to move to the new model seamlessly
Some work will need to be done to determine what each application supports (Nick Mailhot to support)

Update:

currently waiting for SiteMinder federation services to be ready

have standard realms


[docs] Adding docs and templates

We should be adding some basic documentation with issue and pull request templates for uniformity and consistency throughout the repository.

Closing this against #9


[incubator/vault] allow usage of config in existing configmap

Signed-off-by: Louise Champ<EMAIL_ADDRESS>What this PR does / why we need it:
This PR is intended to support production environments which may want to define the configuration outside of the values file (eg, credentials provided for storage backends and sealing)
Which issue this PR fixes
(optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close that issue when PR gets merged)

fixes #

Special notes for your reviewer:
Checklist
[Place an '[x]' (no spaces) in all applicable fields. Please remove unrelated fields.]

[X] DCO signed
[X] Chart Version bumped
[X] Variables are documented in the README.md

/assign @mattfarina

/ok-to-test
cc @jpds

/lgtm


array_bool_xor not found with MiniZinc 2.0.12

... e.g., on the Challenge 2012 instance ../challenge_from2012/mznc12-problems/parity-learning/parity-learning.mzn ../challenge_from2012/mznc12-problems/parity-learning/44_22_5.2.dzn
Possible add-on to redefinitions.mzn:
predicate array_bool_xor(array[int] of var bool: a) =
let { var 0..(length(a)-1) div 2: m,
var 1..((length(a)-1) div 2)*2+1: ss = sum(i in index_set(a))( bool2int(a[i]) ) }
in
ss == 1 + 2 * m;

It should be fixed in the new version available at Chuffed.


Ability to specify alt/opt/loop blocks in dynamic diagrams

I would like to propose to be able to specify whether a set of interactions (arrows) could be alternatives, optional or looped.
This would be translated to opt, alt or loop blocks in the case of exporting a sequence diagram.

I think a way to write this would be to enclose the instantiation of relationships within such blocks:
    dynamic * {
        a -> b
        optional { b -> c }
        alternative {
            {
                b -> d
            }
            {
                b -> e
            }
        }
    }

and they should be able to be nested.

Any chance this could be specified as a plugin-powered custom view?
The proposal here is that the whole content of the block is passed as-is to the view/exporter plugin.
plugin-view "pluginname" {
     ...
}

so the view/exporter plugin has access to:

The content of the block (and is its responsibility to parse it)
the workspace definitions (model, relationships, etc)
An exporter API which it could output (plantUML?) text.
In this case it is a custom plantUML plugin exporter.

With this, I will be able to blend (plant)UML with Structurizr in a cross-consistent way.

To document this: the way we are solving this issue is to use plantuml sequence diagrams, and check them against a structurizr dsl model, validating the participants and relationships.


Adding Vulkan-style statistics counters where available

Description
Previously, the 'stats' interface only used HWCPipe to interrogate performance counters from the device. HWCPipe is not widely supported, so this really only worked for Arm devices.
This change allows multiple 'StatsProviders' to be used. Each provider can supply all, some, or none of the requested counters depending on its capabilities. Any counters not supplied by one provider will be requested of the next in the list until one is found, or we run out of providers.
A second provider that uses the Vulkan performance counter extension has  been added and will be used where supported if HWCPipe cannot provide an equivalent counter. CPU counters can come from HWCPipe for example, whilst GPU counters come from the Vulkan extension. If TimestampQueries are available, they are used in the Vulkan-extension provider to more accurately measure the time spent executing the command buffer, which should match the time spent collecting counters.
The StatsProvider defines an abstract interface that is implemented by the concrete providers. The parameters used for graphing the statistics have moved from the GUI classes into the StatsProvider also. This allows providers to modify the names, units and scaling of counters where these differ
from the default values. It also feels more logical that the stats themselves should know best how to present themselves.
Since the Vulkan extension uses query pools which have to be begun and ended inside CommandBuffers there have been a few small changes to the examples to allow that to happen.
I have only tested this on embedded Linux.
Fixes #84
General Checklist:
Please ensure the following points are checked:

[x] My code follows the coding style
[x] I have reviewed file licenses
[x] I have commented any added functions (in line with Doxygen)
[x] I have commented any code that could be hard to understand
[x] My changes do not add any new compiler warnings
[x] My changes do not add any new validation layer errors or warnings
[x] I have used existing framework/helper functions where possible
[x] My changes build and run on Windows, Linux, macOS and Android. Otherwise I have documented any exceptions

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

I'd like to sign the CLA but https://cla-assistant.io/ is not responding.

This looks good to me. I just ran this on my desktop with an RTX 2060 and all the samples I checked worked as expected. Can't check Vulkan perf counters though as the extension is not available.

@AlejandroCosin I've made an alternative fix for the WaitIdle problem you saw. Can you check that it has the same effect please. The original code works for me for some reason.

@AlejandroCosin I've made an alternative fix for the WaitIdle problem you saw. Can you check that it has the same effect please. The original code works for me for some reason.

Sure! will test and tell you :)

@gary-sweet I tested in Windows and Android the Wait Idle Sample with your last changes ("Fix for WaitIdle" commit in your branch perf_counters) and everything works great


Copying molfile 3000 and SMILES from the structure view does not work

same problem: when right clicking on the structure to copy mol3000 or SMILES, a popup shows "Nothing placed on clipboard"

Fixed in 2016-10-31 update: Copy SMILES option is removed.  Copy Molfile V2000/V3000 are combined.

Confirmed fixed. Close


Add scripts, docs for migrating message_data code

These describe/implement the process used for #88.
This PR can be updated as #88 (or #86, or another PR) is completed and merged.
How to review
Read the updated documentation.

PR checklist

[ ] Complete and merge #88; rebase this branch.
[ ] Add a reference to the info added to the description of #86 by @glatterf42.
[x] Continuous integration checks all ✅
[x] ~Add or expand tests;~ coverage checks both ✅
[x] Add, expand, or update documentation.
[ ] Update doc/whatsnew.

For reference, here are the duplicates.txt and (manually edited) rebase-todo.txt produced by 2-migrate.sh while applying this process for #88:

duplicates.txt
rebase.txt

For example:

Add water infrasructure [sp] as a commit message appears in duplicates.txt —the development history of the source repo/branch has resulted in duplicates of this commit.
So, in editing rebase-todo.txt to rebase.txt, I removed one of the occurrences of this commit in the list of commands.

@glatterf42 I've now completed the text and TODO list above, so this is ready to be reviewed and, if approved, merged.


Upgrade to 3.39.2

Saw this in the release notes:

The JSON functions are now built-ins. It is no longer necessary to use the -DSQLITE_ENABLE_JSON1 compile-time option to enable JSON support. JSON is on by default. Disable the JSON interface using the new -DSQLITE_OMIT_JSON compile-time option.

We can probably remove this: https://github.com/xerial/sqlite-jdbc/blob/ada2b147dc858ef557a995e2f4ef25f7c65fc6a7/Makefile#L81

I see there is an updated binary for Mac aarch64, just wanted to check, did you compile that on your M1 mac @pyckle ?

The build is failing on armv7 and aarch64. Just to be sure i compared with a recent build from the current master, and those work, so this must be because of the new changes in this PR.
We need to find out why this happens with this PR.

Failed to load native library:sqlite-3.39.2-759e4a1a-cc92-4003-88d4-08cff1551a91-libsqlitejdbc.so. osinfo: Linux/armv7
java.lang.UnsatisfiedLinkError: /tmp/sqlite-3.39.2-759e4a1a-cc92-4003-88d4-08cff1551a91-libsqlitejdbc.so: /lib/arm-linux-gnueabihf/libc.so.6: version `GLIBC_2.33' not found (required by /tmp/sqlite-3.39.2-759e4a1a-cc92-4003-88d4-08cff1551a91-libsqlitejdbc.so)

This is weird that is needs a version of Glibc that is very recent. Dockcross should have -lts versions which use a lower GLibc, i think we need to switch to that. We've already done that for arm-v6, but since then they extended the -lts to other cpu architecture.

I see docker/dockcross-armv7 is replaced with an empty file, can we delete it altogether, since we are using armv7a ?

The M1 build was built on my M1 Mac. It was tested.
I just moved armv7a to lts, and that should only requires glibc 2.28+ according to the dockcross docs.
I will make the same change for aarch64 and get that pushed shortly.
I will also remove the JSON build def, and rebuilt all other binaries.

The M1 build was built on my M1 Mac. It was tested.
Awesome, I was not sure you had an M1.
I just moved armv7a to lts, and that should only requires glibc 2.28+ according to the dockcross docs.
I will make the same change for aarch64 and get that pushed shortly.
I think we should use all the available lts to avoid issues.

arm64 is now moved to lts, and new binaries are pushed I will do it with the rest of the archs in the next couple of days.
If the lts toolchains don't make the build pass, we'll have to hardcode an older version of the dockcross docker images.

Actually, the lts versions are only for arm and mips. All arm builds were moved to lts, and we don't build for mips.
So I think this should be good, unless you'd like me to cleanup the commit log/squash things.

So I think this should be good, unless you'd like me to cleanup the commit log/squash things

I will squash on merge, don't worry. Will review tomorrow 👍🏻


Mistake in TS1.6 breaking changes doc?

The doc gives the following example:
let animalList: Dog | Cat | Turkey = [    // use union type instead of Animal
    {name: "Milo", meow: true },
    {name: "Pepper" , bark: true},
    {name: "koko", gobble: true}
];

I think the type should be wrapped in an array.

You're right, thanks for catching this. I just fixed it.

Thanks @billccn. In the future you can send a PR at https://github.com/TypeScript-wiki


[BEAM-4775] Add GetJobMetrics RPC.

This just adds the RPC to the Jobs API.

Thank you for your contribution! Follow this checklist to help us incorporate your contribution quickly and easily:

[ ] Choose reviewer(s) and mention them in a comment (R: @username).
[ ] Format the pull request title like [BEAM-XXX] Fixes bug in ApproximateQuantiles, where you replace BEAM-XXX with the appropriate JIRA issue, if applicable. This will automatically link the pull request to the issue.
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Post-Commit Tests Status (on master branch)

Lang
SDK
Apex
Dataflow
Flink
Gearpump
Samza
Spark

Go

---
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---
---
---
---

Java

Python

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See .test-infra/jenkins/README for trigger phrase, status and link of all Jenkins jobs.

R: @ryan-williams @ajamato


Make keyboard shortcut activate addon

The add-on defined a shortcut to activate the "org-capture" command but wasn't listening for it anywhere. Changing it to _execute_browser_action makes it act as if a user had clicked the BrowserAction icon without any additional code.
I also submitted a PR to the cask folks to include your example EmacsClient.app as an app installable through brew cask; that was accepted yesterday, and there is a separate PR, #44 to update the README with instructions for installing that via brew cask

@sprig, this problem still exists.
While waiting reaction, @nickbarnwell could you please provide quick&dirty way to hack this around on linux for firefox? I completely new in browser plugin machinery.

You can install my fork instead of the one from the web store.

Thanks for your contribution! Sorry for taking a while to merge this.

@sprig, do you plan to release a new version with this fix in the extension webstores?
That would be super helpful :)

I do - it will be out soon :-)


Refactor the generator to use a helper

Looks so good, huh?
On Sat, Mar 31, 2018, 10:54 Nate Bosch<EMAIL_ADDRESS>wrote:

@natebosch approved this pull request.
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Remove unnecessary ResNet/ResNext shortcut conditions

From Deep Residual Learning for Image Recognition arXiv:1512.03385v1

When dimensions increase, we consider two options....

So I think it is not necessary to determine stride !=1 when determining if shortcut needs to be downsampled or not, This stride condition may be confusing to beginners like me.
I wrote a piece of code to test the difference between the two and found that the output of the model was identical for all resnet families
def compare(model1, model2):
    for (name_1, value_1), (name_2, value_2) in zip(model1.named_parameters(), model2.named_parameters()):
        if name_1 == name_2 and value_1.size() == value_1.size() and name_2 == name_2 and value_2.size() == value_2.size():
            continue
        else:
            return False

    return True

if compare(resnext101_32x8d(), my_resnext101_32x8d()):
    print("True")
else:
    print("False")

I only modified the resnet.py file, why does codecov bot say I modified
torchvision/extension.py
torchvision/ops/deform_conv.py
torchvision/models/detection/rpn.py

@MeepoAII thanks for the PR and pointing out this ! Yes, you are right about the citation from the paper and in all models resnet18,34,50,101,152 this condition can look a bit redundant. However, if you consider complete code of _make_layer, user can create a resnet with other layer's widths (other that 64, 128, 256, 512  : self.layerX = self._make_layer(block, M, layers[X-1], stride=2, ...)) such that the second condition is False but still having stride > 1. In those cases we'll have dimensions mismatch on skip connection.
I think we have to keep the current implementation.

Thank you for your detailed and patient explanation, I get you!


v0.8.0 Subtraction of two bitmaps gives wrong bitmap

sub_assign works as expected while subtract doesn't
    #[test]
    fn test_rbm_sub() {
        let all: RoaringBitmap = (0..5000).collect();
        let all_len = all.len();
        let some = RoaringBitmap::from_iter(all.iter().filter(|i| *i % 7 == 0));
        let rest = &all - &some;
        let rest2 = all - &some;

        assert_eq!(all_len, some.len() + rest2.len());
        assert_eq!(rest2.len(), rest.len()); // Fails with Left: 4285 Right: 5000
    }

When creating a smaller bitmap e.g. 4000, subtract works as expected.

Hey @kolstae, you are right, there is a bug in the sub function in store.rs
that should be:
- BitOrAssign::bitor_assign(&mut lhs, rhs);
+ SubAssign::sub_assign(&mut lhs, rhs);

Unfortunately, I can't fix it this week.
Could you please create a PR adding your test and trying the fix?
Thanks a lot for your issue! 🙂

Sure :)


Remove bundler version constraint

Hey! 👋
I'm the release manager for Bundler and I'm preparing for the upcoming Bundler 2 release. I noticed that middleman-core has Bundler locked to ~> 1.1. This should be removed so that people who only have Bundler 2 installed can install your gem.
You don't have to worry about making sure your Gemfile.lock loads with the correct version of Bundler, it will take care of that itself.
Thanks!

Thank you @colby-swandale


[main] Upgrade to latest dependencies

Cron -knative-prow-robot
/cc knative-sandbox/networking-wg-leads
/assign knative-sandbox/networking-wg-leads
Produced by: knative-sandbox/knobots/actions/update-deps
Details:
bumping knative.dev/hack d1317b0...6887217:
  > 6887217 Update community files (# 232)
  > 9b76387 output certificate as well (# 229)
bumping knative.dev/pkg 5f66ecf...6d71868:
  > 6d71868 Update community files (# 2600)
  > d1d5c84 Define a global for `reconciler.DefaultTimeout`. (# 2597)
  > df29e2a Avoid second lister fetch during finalizer reconciliation. (# 2596)
bumping knative.dev/networking cefed20...c662540:
  > c662540 Update community files (# 713)

/lgtm
/approve

/retest


Error with python airbnb.py -asa "Paris"

Hello I am very interested in your work but I come across this error and I can not solve it
python airbnb.py -asa "City Name"
2017-02-17 23:42:19,461 ERROR   Failed to add survey for Paris
2017-02-17 23:42:19,462 ERROR   Top level exception handler: quitting.
Traceback (most recent call last):
File "airbnb.py", line 2394, in main
db_add_survey(ab_config, args.addsurvey)
File "airbnb.py", line 1613, in db_add_survey
survey_id = cur.fetchone()[0]
TypeError: 'NoneType' object is not subscriptable
Is what you can me debegger
Thanks

python airbnb.py -asa "Paris"

for me it works fine

I have this error
C:\airbnb>python airbnb.py -asv "lisboa" -c u.config
ERROR:root:Failed to add survey for lisboa
ERROR:root:Top level exception handler: quitting.
Traceback (most recent call last):
File "airbnb.py", line 442, in main
db_add_survey(ab_config, args.addsurvey)
File "airbnb.py", line 148, in db_add_survey
survey_id = cur.fetchone()[0]
TypeError: 'NoneType' object is not subscriptable

Have you added "lisboa" as a search_area first? You need to do "python airbnb.py -asa Lisboa -c u.config" first.

C:\airbnb>python airbnb.py -asa Lisboa -c casa.config
OK
C:\airbnb>python airbnb.py -asv "lisboa" -c casa.config
ERROR:root:Failed to add survey for lisboa
ERROR:root:Top level exception handler: quitting.
Traceback (most recent call last):
File "airbnb.py", line 442, in main
db_add_survey(ab_config, args.addsurvey)
File "airbnb.py", line 148, in db_add_survey
survey_id = cur.fetchone()[0]
TypeError: 'NoneType' object is not subscriptable

PostgreSQL is case sensitive, so your second command would have to be -asv Lisboa, not -asv lisboa.

I'm having the same issue, could you please help me solve this?
MacBook-Air-de-Carlos:airbnb-data-collection-master carlosarancibia$ python airbnb.py -asa "Santiago"
MacBook-Air-de-Carlos:airbnb-data-collection-master carlosarancibia$ python airbnb.py -asv "Santiago"
ERROR:root:Failed to add survey for Santiago
ERROR:root:Top level exception handler: quitting.
Traceback (most recent call last):
File "airbnb.py", line 442, in main
db_add_survey(ab_config, args.addsurvey)
File "airbnb.py", line 148, in db_add_survey
survey_id = cur.fetchone()[0]
TypeError: 'NoneType' object is not subscriptable
Thanks

Judging from where the error is, it looks like the -asa command failed to add Santiago to the search_area table. Please could you check that with "SELECT * FROM search_area"?
I'm going to guess that the "name" column of the search_area table holds something different from "Santiago". If that is the case, then you should update the table using "UPDATE search_area SET name = 'Santiago' WHERE search_area_id = ".
Currently I am maintaining only the -sb search type, so you would need to update the row with a bounding box before doing a search.

Thanks Tom, i created the survey id manually and the survey area.
My only issue now is that the bathroom numeric column shows null for all entries. It seems they changed something, but bedrooms are working just fine

Same issue, different error. Could you help?
ERROR   Error collecting city and neighborhood information
ERROR   Error getting city info from website
ERROR   Top level exception handler: quitting.
Thank you.

Tanja what worked for me was manually creating the search_area_id with the bounding box for my city (search_area table) and then creating a survey with that search area in the survey table
Then you just run a -sb search with the survey id code

Thanks carancib for your superfast response! As you said, I manually created the search_area_id as well as the survey_id. Could you tell me how to now run the search with the survey id code? In other words, what should I type after "-sb ..." if the survey I want to run has the survey_id "1"?
Thanks!!

Solved. Thank you carancib :-)


Documentation of RDF Cube Shape Requirements

To make it easier for others to implement pipelines that create "valid" (i.e. valid for the visualization tool) cubes we should document the shape properties that are expected.

These are the main ones currently in use for dimensions:

dataKind: Required for temporal dimensions (spatial not implemented yet)

timeUnits supported: unitYear, unitMonth, unitWeek, unitDay, unitHour, unitMinute, unitSecond

dataType: Required for dimensions containing literal values. Undefined values must be cube.link/Undefined.

datatypes supported: string, gYear, date, dateTime, in, integer, decimal, float, double

scaleType: Only used to distinguish Nominal from Ordinal dimensions
Dimension Types: Required to identify Key and Measure Dimensions (SharedDimension not implemented yet)
sh:in (for nominal/ordinal dimensions) or sh:minInclusive and sh:maxInclusive: Required
schema:name Required

I agree on documentation but we need validation as well so we definitely have to create a SHACL shape that checks for those things. I did that for the cube itself so we should build on that work, see here

@ptbrowne IIUC this documentation has been solved by /docs/ now.
@ktk a valid point, maybe it would help to have cube-creator also validating along these SHACL shapes.

Thanks @Rdataflow , yes the shapes and their understanding by visualize is described in detail at : https://visualize.admin.ch/docs/charts/rdf-to-visualize


Disabling compression for binary output artifact works but gives .gz when downloaded from the UI

Summary
I am using the script template to execute a machine learning training python script which generates the model as a binary file having .sav extension. Then I am exposing the model binary as an artifact, with compression disabled.
In minio, I can see that model file is present uncompressed, but on the UI the same uncompressed file shows up with a ".tgz" extension.
I am using the k8sapi executor to run the workflows
Attachments/Screenshots:
1. File in minio - uncompressed binary as expected

2. UI Screenshot

3. Artifact downloaded from UI
model.tgz which is the same uncompressed binary IrisClassifier.sav is incorrectly named as model.tgz instead of model.sav

4. Executable workflow
sklearn-iris.txt
Rename above attachment to sklearn-iris.yaml and then
argo submit ${workflowFile} --serviceaccount ${serviceaccount} --namespace ${namespace}

Diagnostics
What Kubernetes provider are you using?
Azure Aks
What version of Argo Workflows are you running?
v2.11.2
Paste a workflow that reproduces the bug, including status:
kubectl get wf -o yaml ${workflow}
apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
  creationTimestamp: "2020-10-09T14:20:17Z"
  generateName: sklearn-iris-training-
  generation: 6
  labels:
    workflows.argoproj.io/completed: "true"
    workflows.argoproj.io/phase: Succeeded
  name: sklearn-iris-training-96j9n
  namespace: testing
  resourceVersion: "5619238"
  selfLink: /apis/argoproj.io/v1alpha1/namespaces/testing/workflows/sklearn-iris-training-96j9n
  uid: 28e3f15c-35f9-4caa-a671-8f96840f144c
spec:
  arguments: {}
  entrypoint: iris-model-training
  serviceAccountName: argo-workflow-service-account
  templates:
  - arguments: {}
    inputs: {}
    metadata: {}
    name: iris-model-training
    outputs: {}
    steps:
    - - arguments: {}
        name: generate-iris-model
        template: model-training
  - arguments: {}
    inputs: {}
    metadata: {}
    name: model-training
    outputs:
      artifacts:
      - archive:
          none: {}
        name: model
        path: /workspace/IrisClassifier.sav
    script:
      command:
      - bash
      image: python:3.7
      name: ""
      resources: {}
      source: "cd /workspace\nwget https://raw.githubusercontent.com/SeldonIO/seldon-core/master/examples/models/sklearn_iris/train_iris.py\npip
        install scikit-learn==0.20.3 joblib==0.16.0\npython train_iris.py \nls -lrth\n"
      volumeMounts:
      - mountPath: /workspace
        name: workspace
  volumes:
  - emptyDir: {}
    name: workspace
status:
  conditions:
  - status: "True"
    type: Completed
  finishedAt: "2020-10-09T14:20:37Z"
  nodes:
    sklearn-iris-training-96j9n:
      children:
      - sklearn-iris-training-96j9n-3701877419
      displayName: sklearn-iris-training-96j9n
      finishedAt: "2020-10-09T14:20:37Z"
      id: sklearn-iris-training-96j9n
      name: sklearn-iris-training-96j9n
      outboundNodes:
      - sklearn-iris-training-96j9n-739202604
      phase: Succeeded
      startedAt: "2020-10-09T14:20:17Z"
      templateName: iris-model-training
      templateScope: local/sklearn-iris-training-96j9n
      type: Steps
    sklearn-iris-training-96j9n-739202604:
      boundaryID: sklearn-iris-training-96j9n
      displayName: generate-iris-model
      finishedAt: "2020-10-09T14:20:35Z"
      hostNodeName: *redacted*
      id: sklearn-iris-training-96j9n-739202604
      name: sklearn-iris-training-96j9n[0].generate-iris-model
      outputs:
        artifacts:
        - archive:
            none: {}
          name: model
          path: /workspace/IrisClassifier.sav
          s3:
            accessKeySecret:
              key: accesskey
              name: argo-workflow-minio
            bucket: argo-artifacts
            endpoint: argo-workflow-minio:9000
            insecure: true
            key: sklearn-iris-training-96j9n/sklearn-iris-training-96j9n-739202604/IrisClassifier.sav
            secretKeySecret:
              key: secretkey
              name: argo-workflow-minio
        exitCode: "0"
      phase: Succeeded
      resourcesDuration:
        cpu: 27
        memory: 27
      startedAt: "2020-10-09T14:20:17Z"
      templateName: model-training
      templateScope: local/sklearn-iris-training-96j9n
      type: Pod
    sklearn-iris-training-96j9n-3701877419:
      boundaryID: sklearn-iris-training-96j9n
      children:
      - sklearn-iris-training-96j9n-739202604
      displayName: '[0]'
      finishedAt: "2020-10-09T14:20:37Z"
      id: sklearn-iris-training-96j9n-3701877419
      name: sklearn-iris-training-96j9n[0]
      phase: Succeeded
      startedAt: "2020-10-09T14:20:17Z"
      templateName: iris-model-training
      templateScope: local/sklearn-iris-training-96j9n
      type: StepGroup
  phase: Succeeded
  resourcesDuration:
    cpu: 27
    memory: 27
  startedAt: "2020-10-09T14:20:17Z"

Paste the logs from the workflow controller:
time="2020-10-09T14:20:17Z" level=info msg="Processing workflow" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:17Z" level=info msg="Updated phase  -> Running" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:17Z" level=info msg="Steps node sklearn-iris-training-96j9n initialized Running" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:17Z" level=info msg="StepGroup node sklearn-iris-training-96j9n-3701877419 initialized Running" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:17Z" level=info msg="Pod node sklearn-iris-training-96j9n-739202604 initialized Pending" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:17Z" level=info msg="Created pod: sklearn-iris-training-96j9n[0].generate-iris-model (sklearn-iris-training-96j9n-739202604)" namespace=testing workflow=sklearn-iris-training-96j9
time="2020-10-09T14:20:17Z" level=info msg="Workflow step group node sklearn-iris-training-96j9n-3701877419 not yet completed" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:17Z" level=info msg="Workflow update successful" namespace=testing phase=Running resourceVersion=5619181 workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:18Z" level=info msg="Processing workflow" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:18Z" level=info msg="Updating node sklearn-iris-training-96j9n-739202604 message: PodInitializing"
time="2020-10-09T14:20:18Z" level=info msg="Skipped pod sklearn-iris-training-96j9n[0].generate-iris-model (sklearn-iris-training-96j9n-739202604) creation: already exists" namespace=testing podPhase=Pending workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:18Z" level=info msg="Workflow step group node sklearn-iris-training-96j9n-3701877419 not yet completed" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:18Z" level=info msg="Workflow update successful" namespace=testing phase=Running resourceVersion=5619185 workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:19Z" level=info msg="Processing workflow" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:19Z" level=info msg="Skipped pod sklearn-iris-training-96j9n[0].generate-iris-model (sklearn-iris-training-96j9n-739202604) creation: already exists" namespace=testing podPhase=Pending workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:19Z" level=info msg="Workflow step group node sklearn-iris-training-96j9n-3701877419 not yet completed" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:20Z" level=info msg="Processing workflow" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:20Z" level=info msg="Skipped pod sklearn-iris-training-96j9n[0].generate-iris-model (sklearn-iris-training-96j9n-739202604) creation: already exists" namespace=testing podPhase=Pending workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:20Z" level=info msg="Workflow step group node sklearn-iris-training-96j9n-3701877419 not yet completed" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:21Z" level=info msg="Processing workflow" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:21Z" level=info msg="Updating node sklearn-iris-training-96j9n-739202604 status Pending -> Running"
time="2020-10-09T14:20:21Z" level=info msg="Workflow step group node sklearn-iris-training-96j9n-3701877419 not yet completed" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:21Z" level=info msg="Workflow update successful" namespace=testing phase=Running resourceVersion=5619204 workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:22Z" level=info msg="Processing workflow" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:22Z" level=info msg="Workflow step group node sklearn-iris-training-96j9n-3701877419 not yet completed" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:36Z" level=info msg="Processing workflow" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:36Z" level=info msg="Setting node sklearn-iris-training-96j9n-739202604 outputs"
time="2020-10-09T14:20:36Z" level=info msg="Workflow step group node sklearn-iris-training-96j9n-3701877419 not yet completed" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:36Z" level=info msg="Workflow update successful" namespace=testing phase=Running resourceVersion=5619235 workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="Processing workflow" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="Updating node sklearn-iris-training-96j9n-739202604 status Running -> Succeeded"
time="2020-10-09T14:20:37Z" level=info msg="Step group node &NodeStatus{ID:sklearn-iris-training-96j9n-3701877419,Name:sklearn-iris-training-96j9n[0],DisplayName:[0],Type:StepGroup,TemplateName:iris-model-training,TemplateRef:nil,Phase:Running,BoundaryID:sklearn-iris-training-96j9n,Message:,StartedAt:2020-10-09 14:20:17 +0000 UTC,FinishedAt:0001-01-01 00:00:00 +0000 UTC,PodIP:,Daemoned:nil,Inputs:nil,Outputs:nil,Children:[sklearn-iris-training-96j9n-739202604],OutboundNodes:[],StoredTemplateID:,WorkflowTemplateName:,TemplateScope:local/sklearn-iris-training-96j9n,ResourcesDuration:ResourcesDuration{},HostNodeName:,MemoizationStatus:nil,SynchronizationStatus:nil,} successful" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="node sklearn-iris-training-96j9n-3701877419 phase Running -> Succeeded" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="node sklearn-iris-training-96j9n-3701877419 finished: 2020-10-09 14:20:37.08788491 +0000 UTC" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="Outbound nodes of sklearn-iris-training-96j9n-739202604 is [sklearn-iris-training-96j9n-739202604]" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="Outbound nodes of sklearn-iris-training-96j9n is [sklearn-iris-training-96j9n-739202604]" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="node sklearn-iris-training-96j9n phase Running -> Succeeded" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="node sklearn-iris-training-96j9n finished: 2020-10-09 14:20:37.087981011 +0000 UTC" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="Checking daemoned children of sklearn-iris-training-96j9n" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="Updated phase Running -> Succeeded" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="Marking workflow completed" namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="Checking daemoned children of " namespace=testing workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:37Z" level=info msg="Workflow update successful" namespace=testing phase=Succeeded resourceVersion=5619238 workflow=sklearn-iris-training-96j9n
time="2020-10-09T14:20:38Z" level=info msg="Labeled pod completed" namespace=testing pod=sklearn-iris-training-96j9n-739202604```

Message from the maintainers:
Impacted by this bug? Give it a 👍. We prioritise the issues with the most 👍.

This is a bug in the artifact server. I suspect it just states the wrong file name. Would you like to submit a PR to fix?

Hello @alexec
Unfortunately, my employer's open source contribution policy does not allow me to make open source contributions without first having to go through a bunch of approval processes.
I have tried to look at the code in artifact_server.go
There are two functions GetArtifact and GetArtifactByUID that download an artifact to file system, read its contents and then set Content-Disposition header with filename=artifactName.tgz
I think since argo supports disabling compression, the extension .tgz should not be defaulted, and instead should use whatever extension the artifact originally had.

There isn't anything available in GetArtifact to help make the determination. This large change, small benefit.


FR: Ignore Pattern

When editing Kanban files in markdown, the Linter changes break the Kanban format because they are converted from H2
Is it possible to add a regex like *Kanban* to skip certain files from lint on save? (manual linting should probably override this ignore rule)

Actually closing because manually editing the markdown file doesn't apply changes


Add custom file format

Come up with our own file format for storing traces in. The runtime's trace format is optimized for being cheap to write, but we should be able to optimize for fast parsing and space-efficient storage since we get to do it offline. This will also let us store additional data, such as per-trace settings (active filters, saved filters, …), annotations, etc.
A file saved in our format would be a compact, annotated trace, and it would be stored in a compressed format. Its file extension would therefore be .catz.

The custom file format should be optional, and we should allow storing annotations and settings in a sidecar file instead. This will benefit users who already have systems in place for capturing and storing traces and using them with other analysis tools. This will save them from having to manage two binary blobs.


How to handle external donet libarys

I know dotnet is a sensitive topic.
In some projects / modules I used external dotnet libraries like

https://itextpdf.com/
https://www.cryptosys.net/pki/

I know that I can not use their own dotent code.
But what was a valid solutions or workaround, if I have to use external dotnet libraries?

Hi Hendrik, the way you can still use .net libraries is to wrap them in your own (REST) service layer. And then use the AL HttpClient to consume them. Using the JsonObject and JsonArray functionality. If you need some help with real life application scenarios, I'd be happy to you on your way.

There are three possibilities here:

use OnPremise, dotnet is possible there, unfortunately not in the cloud.
use as microservice a provider e.g. Azure Functions
or write your own microservice e.g. with C#

Hi erikrijn,
hi Gallimathias,
Thank you for your suggestions. These are also the options that I have considered so far.


CI: Fix PolicyConfigurationTest

Description
This test was failing because ImageService.getImage throws an exception when it cannot find an image. This PR turns the loop into a standard withRetry() loop.
Checklist

[x] Investigated and inspected CI test results

Testing Performed
CI is sufficient + OCP tests where this fails most often + 50x run against an infra cluster.

/test

/test ocp-4-10-qa-e2e-tests
/test ocp-4-13-core-bpf-qa-e2e-tests
/test ocp-4-13-qa-e2e-tests

The test failures are due to an unrelated issue: https://github.com/stackrox/stackrox/pull/6941


Typing of isNumeric function is incorrect

The isNumeric function is implemented as a typeguard that returns true for value is number.
The problem is that the function returns true also if the value is a string, that can be parsed to a number.
The typescript type number means strictly a number, not a parseable string.
https://github.com/ReactiveX/rxjs/blob/92dd3d135d3fcf7fa98526a2ba0493754407a94a/src/internal/util/isNumeric.ts
RxJS version: 6.1.0
Code to reproduce:
const a = '10'
isNumeric(a) === true
typeof a === 'string'

if (isNumeric(a)) {
    const b: number = a
}

Expected behavior:
ts compiler should complain, because a ('10') is not assignable to number
Actual behavior:
ts compiler accepts the code, because isNumeric makes an incorrect type guarantee.
Additional information:

This is a bug in the typings, however, isNumeric is internal to the library and not meant for public consumption, really.

@benlesh  I am trying to have a look at this.
is this as simple as putting a check on like typeof value !== 'string' ?

I don't have a problem with it being fixed, as it's incorrectly typed. And I'd favour just changing the type within the type predicate and leaving it as a user-defined type guard. So if you want to submit a PR, sure.
But, as Ben has stated, it's an internal function, so if you are changing it to address an issue in your code base, you should stop importing the function.

No I didn't. Just try to be useful to the community and try to pick something simple to start with

@dkosasih thanks for fixing this :+1:


Correction for raw affiliation Laboratory for X-ray Astrophysics, NASA/Goddard Spaceflight Center, Mail Code 662, Greenbelt, MD 20771, USA; University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA

Correction needed for raw affiliation Laboratory for X-ray Astrophysics, NASA/Goddard Spaceflight Center, Mail Code 662, Greenbelt, MD 20771, USA; University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
raw_affiliation_name: Laboratory for X-ray Astrophysics, NASA/Goddard Spaceflight Center, Mail Code 662, Greenbelt, MD 20771, USA; University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
new_rors: 02qskvh78;0171mag52
previous_rors: 02qskvh78
works_examples: W3100701982;W3215847683
contact: 34e17960de65018292ee4b88dea8aafd:5c09fd8d @ ourresearch.org

This issue was accepted and ingested by the OpenAlex team on 2024-10-10. The new affiliations should be visible within the next 7 days.


License is missing

These is no license and/or copyright statement.

The authors (see AUTHORS) have not decided yet which license to use.

Why is this so hard doe?


Deprecate cost estimation in azure-quantum-python SDK

Description from User Story 26613:
Over time we found that cost estimation logic that we provide in azure-quantum Python SDK is significantly inaccurate and does not provide much benefit for users.
To deprecate cost estimation we need:

Remove all related logic from Python SDK - https://github.com/microsoft/azure-quantum-python/blob/4e5d05dbafb139cb728f7dec692da27e3890893a/azure-quantum/azure/quantum/target/target.py#L320
Remove target.estimate_cost() method from target.py
Remove estimate_cost() methods from target classes that inherit from target.py + cirq-provider and qiskit-backend classes implementing the estimation logic.
Remove related unit-tests
Remove estimate_cost() from Jupyter Notebooks samples - azure-quantum-python/samples at main · microsoft/azure-quantum-python (github.com)

Documentation revisions are addressed in PR 1441

/azp run

/azp run


reeeefs

2019-08-11 19:59:26 CRITICAL (MainThread) [hacs] Missing migration step for 1
2019-08-11 19:59:26 CRITICAL (MainThread) [hacs] Missing migration step for 2
2019-08-11 19:59:26 CRITICAL (MainThread) [hacs] Missing migration step for 3
2019-08-11 19:59:26 CRITICAL (MainThread) [hacs] Missing migration step for 4

HACS version 0.13.0+ can only migrate from version 0.12.0+.\n\nTo fix this issue you need to first upgrade to version 0.12.0, then upgrade to 0.13.0\n\nOr you can delete all the files containing hacs in the .storage directory and restart Home Assistant (NB!: This will delete the status of the repositories you have installed.)
This message was automatically generated🚀

HACS version 0.13.0+ can only migrate from version 0.12.0+.
To fix this issue you need to first upgrade to version 0.12.0, then upgrade to 0.13.0
Or you can delete all the files containing hacs in the .storage directory and restart Home Assistant (NB!: This will delete the status of the repositories you have installed.)
This message was automatically generated🚀

HACS version 0.13.0+ can only migrate from version 0.12.0+.
To fix this issue you need to first upgrade to version 0.12.0, then upgrade to 0.13.0
Or you can delete all the files containing hacs in the .storage directory and restart Home Assistant (NB!: This will delete the status of the repositories you have installed.)
This message was automatically generated🚀

HACS version 0.13.0+ can only migrate from version 0.12.0+.
To fix this issue you need to first upgrade to version 0.12.0, then upgrade to 0.13.0
Or you can delete all the files containing hacs in the .storage directory and restart Home Assistant (NB!: This will delete the status of the repositories you have installed.)
This message was automatically generated🚀

dd


Renew iccluster051 before 2024-04-09

Renewal is allowed starting 10 days before cutoff.

Go to IC Cluster Portal (requires EPFL network or VPN).
Login (top-right)
Click Reservations > View My Reservations
Find the latest iccluster051 reservation (near the top) and extend it by 45 days

Extended until 2024-05-24


Do not mix data and methods in sharedSelector

As discussed on FE tech collab 2023-02-28
This PR propose a new type that ensures that the return type of the selector does not mix methods and data

✅ Only data

✅ Only functions/methods

🛑 Mix data and methods

Discussion

Should this be implemented in other hooks?

Improvements

I wish I could make the error clearer for the consumer.

A new facet API might be introduced soon which will render this PR obselete, consider taking up the effort again after such change is done if it is not already included in the scope of the API change.


Integrated terminal wraps incorrectly on SSH remote.

Does this issue occur when all extensions are disabled?: Yes. All extensions are disabled except the Remote SSH and Remote WSL extensions.

VS Code Version: 1.58.2 & 1.59.0-insider
OS Version: Windows_NT x64 10.0.19041

This issue is similar to the one reported in #126037 but I don't have to generate any control characters for the issue to appear. Additionally, the issue was not fixed in insiders.
Steps to Reproduce:

Open SSH remote.
Open Integrated Terminal.
Enter a long sequence of characters that requires the terminal to wrap.

Undesired/unexpected behavior:

Desired/excepted behavior (on WSL remote):

My remote system is rather old.

CentOS Linux release 7.6.1810 (Core)
Linux lvnvdg0872 3.10.0-1062.1.1.el7.x86_64 #1 SMP Fri Sep 13 22:55:44 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

I confirmed that the incorrect behavior does not occur when SSH'd into the remote, or when using a terminal on the remote system via VNC.

I believe this is already fixed, can you see if you can reproduce in the Insiders build?

It happens for all terminals. I can confirm it happens on the fist, second, and split terminal windows. Resizing the panel, or the window doesn't have an effect.