error w/ google oauth

Hello, I can't made a successful auth against google oauth because an error (that seems related or identical to https://github.com/authlib/loginpass/issues/47).
Here is the relevant code:
config = Config(".env")  # pylint: disable=invalid-name
oauth = OAuth(config)

CONF_URL = 'https://accounts.google.com/.well-known/openid-configuration'
oauth.register(
    name='google',
    server_metadata_url=CONF_URL,
    client_kwargs={
        'scope': 'openid email profile'
    }
)

async def login(request):
    redirect_uri = request.url_for('auth')
    return await oauth.google.authorize_redirect(request, redirect_uri)

async def auth(request):
    logging.critical(request.headers)
    token = await oauth.google.authorize_access_token(request)
    user = await oauth.google.parse_id_token(request, token)
    request.session['user'] = dict(user)
    return RedirectResponse(url='/')

ROUTES = [
    Route('/login', endpoint=login),
    Route('/auth', endpoint=auth),
]

app = Starlette(debug=True, routes=ROUTES)  # pylint: disable=invalid-name

when /auth endpoint is hit after a successful authentication, I get this traceback (first line is mine):
[osso] CRITICAL: Headers({'host': 'osso.dev.scimmia.net', 'x-request-id': '299db1f2a6d8f187459083ed590d4adb', 'x-real-ip': '<IP_ADDRESS>', 'x-forwarded-for': '<IP_ADDRESS>', 'x-forwarded-host': 'osso.dev.scimmia.net', 'x-forwarded-port': '443', 'x-forwarded-proto': 'https', 'x-scheme': 'https', 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64; rv:73.0) Gecko/20100101 Firefox/73.0', 'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8', 'accept-language': 'en-US,en;q=0.5', 'accept-encoding': 'gzip, deflate, br', 'referer': 'https://accounts.google.com/', 'dnt': '1', 'upgrade-insecure-requests': '1'})
[osso] INFO:     <IP_ADDRESS>:0 - "GET /auth?state=VNyCSjjCXSojWBTqNjsm3XlxBSJEgg&code=4%2FwwEnVamW5jzr4hOz4agsa1kjrKBlCOrMJTdO0pbFM9nq9qDbJ7-riJQ4Sh9TeokDyvz47FnRtY4DQsMMNH3N_II&scope=email+profile+openid+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fuserinfo.email+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fuserinfo.profile&authuser=0&prompt=consent HTTP/1.1" 500 Internal Server Error
[osso] ERROR:    Exception in ASGI application
[osso] Traceback (most recent call last):
[osso]   File "/usr/local/lib/python3.7/site-packages/uvicorn/protocols/http/httptools_impl.py", line 385, in run_asgi
[osso]     result = await app(self.scope, self.receive, self.send)
[osso]   File "/usr/local/lib/python3.7/site-packages/uvicorn/middleware/proxy_headers.py", line 45, in __call__
[osso]     return await self.app(scope, receive, send)
[osso]   File "/usr/local/lib/python3.7/site-packages/starlette/applications.py", line 102, in __call__
[osso]     await self.middleware_stack(scope, receive, send)
[osso]   File "/usr/local/lib/python3.7/site-packages/starlette/middleware/errors.py", line 181, in __call__
[osso]     raise exc from None
[osso]   File "/usr/local/lib/python3.7/site-packages/starlette/middleware/errors.py", line 159, in __call__
[osso]     await self.app(scope, receive, _send)
[osso]   File "/usr/local/lib/python3.7/site-packages/starlette_authlib/middleware.py", line 122, in __call__
[osso]     await self.app(scope, receive, send_wrapper)
[osso]   File "/usr/local/lib/python3.7/site-packages/starlette/exceptions.py", line 82, in __call__
[osso]     raise exc from None
[osso]   File "/usr/local/lib/python3.7/site-packages/starlette/exceptions.py", line 71, in __call__
[osso]     await self.app(scope, receive, sender)
[osso]   File "/usr/local/lib/python3.7/site-packages/starlette/routing.py", line 550, in __call__
[osso]     await route.handle(scope, receive, send)
[osso]   File "/usr/local/lib/python3.7/site-packages/starlette/routing.py", line 227, in handle
[osso]     await self.app(scope, receive, send)
[osso]   File "/usr/local/lib/python3.7/site-packages/starlette/routing.py", line 41, in app
[osso]     response = await func(request)
[osso]   File "./osso/app.py", line 79, in auth
[osso]     token = await oauth.google.authorize_access_token(request)
[osso]   File "/usr/local/lib/python3.7/site-packages/authlib/integrations/starlette_client/integration.py", line 58, in authorize_access_token
[osso]     return await self.fetch_access_token(**params)
[osso]   File "/usr/local/lib/python3.7/site-packages/authlib/integrations/base_client/async_app.py", line 105, in fetch_access_token
[osso]     token = await client.fetch_token(token_endpoint, **kwargs)
[osso]   File "/usr/local/lib/python3.7/site-packages/authlib/integrations/httpx_client/oauth2_client.py", line 120, in _fetch_token
[osso]     return self.parse_response_token(resp.json())
[osso]   File "/usr/local/lib/python3.7/site-packages/authlib/oauth2/client.py", line 348, in parse_response_token
[osso]     self.handle_error(error, description)
[osso]   File "/usr/local/lib/python3.7/site-packages/authlib/integrations/httpx_client/oauth2_client.py", line 76, in handle_error
[osso]     raise OAuthError(error_type, error_description)
[osso] authlib.common.errors.AuthlibBaseError: invalid_request: Missing parameter: redirect_uri

Expected behavior
A successful login via google oauth
Environment:

OS: python:3.7-slim docker image (alpine)
Authlib Version: 0.14.1

Thank you, ciao!

After digging a bit, I've found that this is a response we get from https://oauth2.googleapis.com/token, if I debug print in this function https://github.com/lepture/authlib/blob/7f4e2af155030afc6f7f1f44ebdadcaacf9a2ad5/authlib/integrations/httpx_client/oauth2_client.py#L104-L120 I can see:
CRITICAL: ENDPOINT: https://oauth2.googleapis.com/token
CRITICAL: url: https://oauth2.googleapis.com/token
CRITICAL: headers: {'Accept': 'application/json', 'Content-Type': 'application/x-www-form-urlencoded;charset=UTF-8'}
CRITICAL: auth: <authlib.integrations.httpx_client.oauth2_client.OAuth2ClientAuth object at 0x7f02282bc690>
CRITICAL: kw: {}

# this last one is the response we get from endpoint
CRITICAL: RESPJSON: {'error': 'invalid_request', 'error_description': 'Missing parameter: redirect_uri'}

So this seems to originate from google side. Analyzing the entire chat my browser did w/ google servers I can see that, where a redirect_uri is passed, there is always a correct value (ie. my.sub.domain.tld for a verified domain.tld).
Going further will be very difficult as I'll basically to understand a lot of codebase, which I'll do anyway. Any help would greatly appreciated tho.
Thanks in advance and have a nice day

Probably loook at https://github.com/lepture/authlib/blob/f754eff0c21a11c837a25bc6d4a49875de243c72/authlib/integrations/base_client/base_app.py#L146?

@phy25 could you please elaborate a bit? Unsure on what you mean w/ your comment...

@aogier This is where redirect_uri is being generated from fetch_access_token. You could print the value and see if it's the same as the one when you are being redirected to Google.

no redirect_uri in my session indeed, obv if I hardcode in the file
params['redirect_uri'] = my_redir_uri

this works.
Less luck if I set it in my endpoints' request.session. So I though my drop-in session replacement middleware could be the cause, but then again no luck using vanilla SessionMiddleware.
Honestly I don't have a clue, do you ? :) Anyway thank you a lot for pointing me out this one, I could start from it for a deeper dig...

Technically those session data should be saved here before you got redirected to Google:
https://github.com/lepture/authlib/blob/f754eff0c21a11c837a25bc6d4a49875de243c72/authlib/integrations/base_client/base_app.py#L153-L164
If needed I think you can just extend this class and write your own implementation against save_authorize_data().

I'm tracing set_session_data and get_session_data and I could see something is indeed setted during login execution:
CRITICAL: SET SESS DATA: redirect_uri -> https://...
CRITICAL: SET SESS DATA: state -> KD...
CRITICAL: SET SESS DATA: nonce -> loi...
INFO:     <IP_ADDRESS>:0 - "GET /login HTTP/1.1" 302 Found

But when I hit my redirect uri, everything is lost:
 CRITICAL: GET SESS DATA: state -> _google_authlib_state_ -> None
CRITICAL: GET SESS DATA: code_verifier -> _google_authlib_code_verifier_ -> None
CRITICAL: GET SESS DATA: redirect_uri -> _google_authlib_redirect_uri_ -> None

and session is btw empty so it's not persisting for dunno what reason...
I'd try to set them during my /login endpoint but I don't know state nonce et al...

This case you will have to check your session/cookie. nonce is intended to be random per request to prevent CSRF attacks.

I can see via devtools in my browser that the problem is I loose the session during the trip:

/login
accounts.google.com
/auth

So the superbasic workaround is to encode a session value in /auth start:
    request.session['_google_authlib_redirect_uri_'] = request.url_for('auth')

But there is something more to investigate on why session cookie that login correctly set gets then lost when we land back on pages... I'll investigate on this and let you know! Thank you!

I now found the culprit, that's was an error my side: session cookies w/ negative max-age that did not survived across auth flow :(((((( thank you, at least I'd learned a bit against authlib's internals and that's not bad at all! I'm sorry for the noise, ciao!

In case someone found this issue. There are posts to teach people set:
SECRET_KEY = os.urandom(16)

This is totally wrong. You can't set SECRET_KEY dynamically.
e.g. In production, there will be many workers, if you set SECRET_KEY dynamically, each worker will have its own secret key, workers won't share session at all.

@aogier We have a Google example for starlette: https://github.com/authlib/demo-oauth-client/tree/master/starlette-google-login
I didn't reproduce your problem. The starlette SessionMiddleware works well.


Understand concept of well-known DID configurations

https://identity.foundation/.well-known/resources/did-configuration/
https://learn.mattr.global/api-reference/v1.0.1#operation/wellKnownDidConfig

Why?

How to proof an entity controlling the origin and the Controller of the DID to be the same entity?


:lady_beetle: Invalid entrypoint in tool image Dockerfile fixed

Which issue(s) this PR fixes:
Fixes #56
See: https://stackoverflow.com/a/47643816/844449
/kind bug
/cc @kvmware
/cc @upodroid

I would like to see either the above mentioned stackoverflow link or a explanation in the file itself for the future. Wouldn't want someone to come and think they are cleaning it up and bring it back to the state it is in now. Other than that LGTM


Trying to compile several templates in a directory throws a TypeError

Running:
 twigjs templates/ --output out

Those are the details of the error
 forEachAsync(files, filesHandler).then(postFilesHandler);
          ^
TypeError: object is not a function
    at readFiles (node_modules/twig/node_modules/walk/walk.js:93:11)
    at readdirHandler (node_modules/twig/node_modules/walk/walk.js:98:9)
    at Object.oncomplete (fs.js:107:15)

It seems that forEachAsync which is used inside walk has been updated and the API has changed. The same is true for sequence.
At least for now you should consider use npm-shrinkwrap, a better solution will be to update to the latest dependency and use a specific version in your package.json not using >= anymore, which will break in case of API update of any dependency.

A lock file is now being used. I'm not sure if the original issue has been resolved in more recent versions, but please re-open if it needs to be revisited.


Move all generated binary targets to bin dir

Besides being more consistent, this improves the process of performing a clean make ("make clean") because all generated targets are in one place and can be removed more consistently.
The "make clean" target contines to refer to the old files in the stage1 directory so that executing "make clean" after picking up this change will correctly remove the old files.

Last thing, we should update Documentation/INSTALL.md

Done!


Doesn't work as it is in the wiki

When I tried to run the code, I do not see anything as it is in the wiki. which scene am I supposed to run? I tried all the possible scenes of the project.

There is only a single scene ArScene.unity in the Assets/Scenes folder. Use that scene.
Build and run that scene onto an eligible ARCore Android device.

when i build and run arscene.unity, it says that i have error in the script that i'm using Vectosity and its missing a reference. do i have to buy vectorosity or does the apk file run normally?

@usmanarif24 Vectrosity is included in the Assets folder and there is no need to buy the package from the Unity Store separately.
The apk file should have run normally.
You can try removing using Vectrosity; from the scripts and try building and running again.
Vectrosity wasn't used in the final build if I remember correctly.

I try to build and run arscene.unity. But I cannot put the arrow on the plane. What should I do?

@Wu712 I think it's just a post processed video... It doesn't work as it is in the video

Unity 2018.3.11f1 is the version which we had used to run the application and it worked exactly as shown in the wiki.

I'm using Readmi Note 8 which does support ARCore . But in Google Play Store, its showing it isn't compatible for your device.
Any solutions?

@hrm17 so how did you resolve the issue? Even now am getting the same error though my google arcore is in its latest  version.

hi,
i am not Aable to open the project in unity.It says project is invalid
any idea how to solve it?


Change the acr_values dynamically to pass a new tenant

I've been using this library with no issues, but I'm wondering how to change one of the read-only settings during the use of my app (ie, after the UserManager class is instantiated)?
When an admin user selects a customer from a list, I want to change the acr_values to the tenant selected so subsequent tokens will contain that tenant id.

??

I'm unsure what you're trying to do here, but you can easily update the configuration values using some state setup.

Closing this as stale. Please open a new issue or let me know you still have this issue in a comment 👍


Add support to SmartBCH

Website
https://smartbch.org/
ChainId
SmartBCH Mainnet: 10000
SmartBCH Amber Testnet: 10001
RPC
mainnet:
https://smartbch.fountainhead.cash/mainnet
amber:
http://<IP_ADDRESS>:8545

@rmeissner Hi! I can send you some smartbch & testnet coins if needed. Thank you

that would be really helpful (0.1 would be more than enough): 0x2dC63c83040669F0aDBa5F832F713152bA862c97

Sent 0.1 BCH https://www.smartscan.cash/transaction/0xd037e6f946f2a726e35136b6dece3a695b31e2a6da561479969b53bb1a14e78d (mainnet) and 0.1 BCHT https://www.smartscan.cash/transaction/0x6f39fb672af88757c75d658c04e1c55e7f93f77317e88829a52b21d7069ca7fc (amber)


Union of two unsorted array

💥 Proposal
To find the union of two unsorted arrays under others section.
Have you read the Contributing Guidelines on Pull Requests?
(Write your answer here.)
Yes
I am a GSSOC '21 participant. Please assign me this issue with relevant labels and level categories.

/assign

/assign

/assign

@Sapna2001 I am done with the code part but u closed ?

@jaimehta1912 you are not supposed to self-assign issues you have not created. Check discord.

@Sapna2001 read the statement again what you said and what it means .And don't create issue if you are doing just for points  .First learn how to get assign yourself


software_spec: fix handling of default non-host Cellar

[x] Have you followed the guidelines in our Contributing document?
[x] Have you checked to ensure there aren't other open Pull Requests for the same change?
[x] Have you added an explanation of what your changes do and why you'd like us to include them?
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[x] Have you successfully run brew typecheck with your changes locally?
[x] Have you successfully run brew tests with your changes locally?

https://github.com/Homebrew/brew/pull/11060#issuecomment-815350137

Review period skipped due to critical label.

Could you please add a summary of the problem and solution to the description of this PR? The linked comment https://github.com/Homebrew/brew/pull/11060#issuecomment-815350137 give some context but not a ton.

Yeah this PR got a bit sidetracked with refactoring. I've edited the description now.


triplet training did not converged

Hi, @davidsandberg
I just run two experiment:

facenet_train_classifier.py version, with around 2M images and  100 thousand person identity
facenet_train.py version, with around 10M images and  500 thousand person identity.

all the other parameters are same, bellow is the result:

I found that the triplet version (facenet_train.py) has some problems:

it did not converged, and the result is poor.
when run Validate-on-lfw use the model saved before, it failed.
I  found that the evaluation on lfw in facenet_train.py is complicated, there is no tensors named 'input'.

why did those happened? please help me. 3x

Hi,
For the first bullet I'm afraid I can't help you much. It looks similar to the performance that I used to get using facenet_train.py. Did you run inception-resnet-v1 in both cases?
For the second and third bullets those should be easy to solve by introducing an identity op as is done in facenet_train_classifier.py:
        eval_image_batch = tf.identity(eval_image_batch, name='input')

3x
your first question:
they both use inception-resnet-v1 model.
facenet_train.py use this config, which is same as facenet_train_classify.py except --center_loss_factor 2e-4:
--weight_decay 2e-4 --optimizer RMSPROP --learning_rate -1 --max_nrof_epochs 1500 --keep_probability 0.8 --random_crop --random_flip --learning_rate_schedule_file ../data/learning_rate_schedule_classifier_long.txt --gpu_memory_fraction 0.95
things changed after 65 epoch, the result became better, and the VAL is increased to 0.70 around.
I check the learning_rate_schedule, found that learning rate decreased after epoch 65, 77，etc..
This may be the reason why it converged.
Also, I check the google's facenet paper, they use initial learning rate 0.05 and adagrad, beside their dataset is very large, like 100M-200M picture.
So, my conclusion is,  triplet loss is suitable for large dataset, and we also should use ada/rms but not scheduler learning rate(maybe carefully design also works).
I also run a new training program according above configuration. we can compare the results tomorrow.
your second question:
Actually, I tried to change your code, but I did not know how to get the weights of this laryer:
pre_embeddings = slim.fully_connected(prelogits, args.embedding_size, activation_fn=None, scope='Embeddings', reuse=False)
I check the document of slim, find that reuse config is the key point, and I successfully changed your code.
Maybe you can fix this too for new users, LOL

Closing this. Reopen if needed.

Hi, @davidsandberg
I chose these parameters carefully, and run a new experiment (20 days).
The result is pretty good. Bellow is the val_rate curve:

the main parameter is:
--learning_rate_decay_factor  0.98 --learning_rate_decay_epochs 4 --people_per_batch 720 --images_per_person 5 --weight_decay 2e-4 --optimizer ADAGRAD --learning_rate 0.05
As your mentioned above, I think that, their are two key point:

set large people_per_batch when sampling triplet
learning rate should decay in several epochs

Thank you very much

Hi @mgy89!
This looks like an excellent result!! What is the resulting LFW accuracy?
If I understand it correctly from the image the training actually converges and achieves good performance.
If that is the case it would be really nice to update the wiki page about triplet loss training and maybe also supply a pretrained model based on that. Would you like to work with me on that?
I will try your parameters when I get some time. Did you have to modify the code anything?

Hi @davidsandberg
Yes, it achieves amazing result!
The accuracy is around 0.998, bellow is the accuracy curve:

The result above is based on my dataset(sorry for that I can not public it).
I only modify the evaluating part of your code, the main(training) code is remain the same.
So, I think that using that parameters, facescrub&casia dataset can improve performance too.
I am glad to work with you. what should I do?

@mgy89,
Incredible achievement! Congratulations.
Could you also tell us some properties of the dataset you used? Such as how many identities/images are in your dataset. Is the dataset clean or noisy? Thanks.

@mgy89
Could you plot your loss function values? I'm trying to reproduce your approach on a cleaned up version of VGG dataset (~650k images with 300 images per identity), my loss function values drop below 0.2 but the lfw/accuracy  stays under 94% and lfw/validation is below 55%.

Hi @mgy89,
It would be really nice to have a description of how to get decent performance when training using triplet loss. I have done some test, both training from scratch and starting from a pretrained model with the settings you proposed (people_per_batch=720 & images_per_person=5, Adagrad and your learning rate decay scheme) but I can't find a setting that gets even close to the ones trained as a classifier. If you can help out to find some settings that works well with e.g. casia that would be excellent.

@davidsandberg, when @mgy89 said "I chose these parameters carefully, and run a new experiment (20 days).", do you think s/he meant 20 days to train? Is it feasible to take this long to converge? Idk, I am just wondering.
In the first post, s/he meant 2M-10M datasets. Maybe triplet loss needs this much of data indeed. I also have a theory (just my thoughts) that noise has a severe impact on triplet loss, as selecting wrong triplets (the anchor and positive anchor example are different people, for example) would have severe negative impact preventing the training to converge.

@antoniosimunovic  would you please tell me how to get the cleaned up version of VGG dataset,thanks to the extreme!

@yekeping
First I've ran face detection on VGG images, after that I've projected the extracted faces to a feature space using a model provided by @davidsandberg . Then in that feature space I've used k-NN clustering to group similar faces, using only the ones in largest group.

Hi,
I have been struggling to get triplet loss for face verification running as well. I use a Resnet arch to train a classification problem (about 10000 ids)  first, which works fine. Afterwards I store the 256 dim feature vectors in an LMDB (in order to avoid the process of forwarding a huge net in each batch, of course I lose the option of updating the rest of the net before the embedding by this) and try to train a triplet embedding using this implementation:
https://github.com/luhaofang/tripletloss
The database I use for the triplet embedding training currently is VGG (as provided by the authors, not cleaned). I fix the anchor, randomly sample positives and negatives for each batch iteration. So far I see only lots of loss oscillation, the old (not embedded) features still work best...
There are many factors of uncertainty:

learning rate (started with 0.05, also tried 0.001,0.0001... nothing worked)
margin (fixed to 0.2 at the moment. Is this always a reasonable choice for an L2 normalized feature vector?)
solver (chose AdaGrad as suggested)
people per batch
images per person
triplet selection strategy
training from scratch/using pretrained classification model with SoftMax loss

My question: Lots of papers claim that their triplet loss is the "holy grail", but in my opinion the practical implementation problems are not covered enough in these research papers. I am also uncertain if the training method itself is responsible for the good results or the underlying database. I.e. does the triplet method trained on 2M images beat classification loss on 200M images?
Perhaps someone can elaborate on all of the issues and share more experiences. In particular I would be interested if someone has experiences with the above mentioned implementation or triplet loss in Caffe in general. I will also further comment on this if I should improve my training success.
Kind regards,
Christian

I am getting the missing tensor: input error. I understand that facenet_train.py can be modified as David said earlier by adding,
eval_image_batch = tf.identity(eval_image_batch, name='input')
But what do I do if I finished training already? Is there any way to salvage the trained model? I looked at the generated graph but the input name is not clear.

Hey guys, as mentioned https://arxiv.org/abs/1703.07737:

a stagnating loss curve by no means indicates stagnating progress. As the network learns to solve some hard cases, it will be presented with other hard cases and hence still keep a high loss. We recommend observing the fraction of active triplets in a batch, as well as the norms of the embeddings and all pairwise distances.

@davidsandberg really good work.
@mgy89 thank you very much for parameters.
I have followed procedure for triplet training using following parameters.
python src/train_tripletloss.py --logs_base_dir ~/workspace/logs/facenet/ --models_base_dir ~/workspace/models/facenet/ --data_dir ~/workspace/datasets/lfw/lfw_mtcnnpy_182 --image_size 182 --model_def models.inception_resnet_v1 --lfw_dir ~/workspace/datasets/lfw/lfw_mtcnnpy_182 --optimizer ADAGRAD --learning_rate 0.05 --learning_rate_decay_factor 0.98 --learning_rate_decay_epochs 4 --weight_decay 2e-4 --max_nrof_epochs 500 --people_per_batch 720 --images_per_person 5
and got following results as follows.

It seems that it is conversing.
Now I will tray on VGG images.

Hi @look4pritam,
Yes, it looks like it is converging. Interested to hear about your results...
It also looks like the training is collapsing a number of times, like at time step ~13k. Will be interesting to see if you get that also when training on VGG images. Maybe some tuning of the learning rate will be needed then.

Hi @davidsandberg
I am downloading VGG dataset and once VGG training is done I will let you know.
I can put LFW trained model on google drive, if you want it.
So that others can used it.

@look4pritam: i'm interested to hear about ur results afterwards. What is your accuracy on LFW datasetsets?

I am outside. Next week (27-05-2017) I will be there. On Wednesday 07-06-2017 LFW accuracy was 94-99%. It was fluctuating. Learning rate needs to be adjusted. I have kept it running on server. I will collect results on 27-05-2017 or may be before.

LFW accuracy

Model link is
https://drive.google.com/file/d/0B3E187MXEXQ6WjkzNlV4WFRnOU0/view?usp=sharing

Hi,@look4pritam
and how about the val rate on lfw please?

Hi @look4pritam  My network speed is too slow to download the VGGDataset, is it possible for you to upload the dataset and give me a link? Thanks!

Hi,@look4pritam:I have tested the model you released, I found that the input is 182x182,and I used the aligned LFW 182x182 images for the test , but I only got 0.77 accuracy and 0.09 validation rate, is there some wrong to use your model?

I have used 160x160 aligned images using mtcnn. I will check again for
aligned images size. I have uploaded the model just to indicate that it is
conversing and currently working on dataset derived from Ms 1m challenge.
On Oct 18, 2017 12:36, "Erdos001"<EMAIL_ADDRESS>wrote:

Hi,@look4pritam https://github.com/look4pritam:I have tested the model
you released, I found that the input is 182x182,and I used the aligned LFW
182x182 images for the test , but I only got 0.77 accuracy and 0.09
validation rate, is there some wrong to use your model?
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Hi @davidsandberg and @look4pritam.
It would be nice if you can provide an example of using the triplet loss pre-trained model in order to compare two photos.
Repo already contains a compare.py but this is suitable only for the classifier model.
Thank you.

@look4pritam I am having trouble recreating your model results on the VGG Faces2 dataset. Specifically, I am a bit confused how your model converges so incredibly quickly with only those given parameters. Did you start out with a pre-trained model, or did the model actually converge to 90% in less than 10k training steps?

Here batch size is the key. With larger batch size model converges fast.
Try to get larger batch size, depending upon your graphics card.
I have trained tensorflow slim models, there also batch size plays imp
role.
With larger batch size models get trained faster as well as they achieve
better accuracy.
But in case of tensorflow slim also I was not getting 90% in 10k iterations.
It may be because of centre loss for facenet. But I am not sure about it.
I have not tried centre loss in tensorflow slim. Once that is done, I can
comment.
On Mar 7, 2018 22:57, "Max Weinzierl"<EMAIL_ADDRESS>wrote:

@look4pritam https://github.com/look4pritam I am having trouble
recreating your model results on the VGG Faces2 dataset. Specifically, I am
a bit confused how your model converges so incredibly quickly with only
those given parameters. Did you start out with a pre-trained model, or did
the model actually converge to 90% in less than 10k training steps?
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@look4pritam thanks a lot for the insight!
@davidsandberg I think I might have a theory about why the training often seems to collapse. I was very interested in logging different training statistics, and after setting up some different metrics I noticed an interesting pattern:

I define active_triplet_percent as

triplet_loss = tf.maximum(pos_dist + margin - neg_dist, 0.0)
active_triplet_percent= tf.reduce_mean(tf.cast(tf.greater(triplet_loss, 0), tf.float32))

Even with the pos_dist_sqr + alpha > neg_dists_sqr triplet selection criteria (along with pos_dist_sqr < neg_dists_sqr for semi-hard) we see that there is consistently a decent percentage of inactive triplets.
Some of this I theorize can be attributed to batch normalization changing the batch statistics, but something interesting occurs where the model's accuracy and loss collapse at around iteration 12k. We see a massive spike of inactive triplets, down to only 13% of the minibatch triplets being used for that iteration.
For my training configuration, 12k is the exact iteration where new triplets are selected. It is not clear to me the direct cause, but it is clear that the problem arises from poor triplet selection. A few poor iterations can essentially torpedo the accuracy, and from this damage there are very few active triplets remaining within the batch. The model's recovery therefore takes some time, since it may suddenly be working with 10%-30% of the minibatch triplets. It seems like the damage was done at the tail end of the previous triplet selection (from 10.8k), and then the next triplet selection at 12k was based off this damaged state.
I would love to hear any other thoughts on this. I am specifically really interested in why my active triplet percent seems so low on average, considering the forward pass which is supposed to only select triplets which satisfy pos_dist_sqr + alpha > neg_dists_sqr. Is this entirely due to batch normalization statistics, or is something else going on here? I don't understand why there are so few active triplets on average (~50%). I could understand if it reduced through a batch and jumped back up at the start of the next batch, but this behavior confuses me.
I am going to continue to test with different batch sizes, and if I find a configuration which reduces this model collapse I will post it here.

Clean the dataset before training. It is also important. David has given
procedure for it. Basically it starts with dry run, train your model till
you get 50-70 % accuracy. Then remove top 10-20% images with more error.
Then train it again. It works, I am doing it for Microsoft 100K dataset.
On Mar 9, 2018 00:55, "Max Weinzierl"<EMAIL_ADDRESS>wrote:

@look4pritam https://github.com/look4pritam thanks a lot for the
insight!
@davidsandberg https://github.com/davidsandberg I think I might have a
theory about why the training often seems to collapse. I was very
interested in logging different training statistics, and after setting up
some different metrics I noticed an interesting pattern:
[image: g1]
https://user-images.githubusercontent.com/1005359/37170195-ccd4948e-22cf-11e8-9ae6-d4cb7c058b0d.PNG
[image: g2]
https://user-images.githubusercontent.com/1005359/37170200-cffa6f08-22cf-11e8-9b31-776778e27135.PNG
I define active_triplet_percent as
triplet_loss = tf.maximum(pos_dist + margin - neg_dist, 0.0)
active_triplet_percent= tf.reduce_mean(tf.cast(tf.greater(triplet_loss, 0), tf.float32))
Even with the pos_dist_sqr + alpha > neg_dists_sqr triplet selection
criteria (along with pos_dist_sqr < neg_dists_sqr for semi-hard) we see
that there is consistently a decent percentage of inactive triplets.
Some of this I theorize can be attributed to batch normalization changing
the batch statistics, but something interesting occurs where the model's
accuracy and loss collapse at around iteration 12k. We see a massive spike
of inactive triplets, down to only 13% of the minibatch triplets being used
for that iteration.
For my training configuration, 12k is the exact iteration where new
triplets are selected. It is not clear to me the direct cause, but it is
clear that the problem arises from poor triplet selection. A few poor
iterations can essentially torpedo the accuracy, and from this damage there
are very few active triplets remaining within the batch. The model's
recovery therefore takes some time, since it may suddenly be working with
10%-30% of the minibatch triplets. It seems like the damage was done at the
tail end of the previous triplet selection (from 10.8k), and then the next
triplet selection at 12k was based off this damaged state.
I would love to hear any other thoughts on this. I am specifically really
interested in why my active triplet percent seems so low on average,
considering the forward pass which is supposed to only select triplets
which satisfy pos_dist_sqr + alpha > neg_dists_sqr. Is this entirely due
to batch normalization statistics, or is something else going on here? I
don't understand why there are so few active triplets on average (~50%). I
could understand if it reduced through a batch and jumped back up at the
start of the next batch, but this behavior confuses me.
I am going to continue to test with different batch sizes, and if I find a
configuration which reduces this model collapse I will post it here.
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@look4pritam hi, how can I train a VGG dataset by using a triplet loss. Currently, I am using the
train_tripletloss.py --lfw_dir ./datasets/lfw --optimizer ADAGRAD --learning_rate 0.01 --weight_decay 1e-4 --max_nrof_epochs 150 --learning_rate_schedule_file_data/learning_rate_schedule_classifier_vggface2.txt --people_per_batch 720 --images_per_person 5
but the program is crashed when saving a checkpoint model.

Hi, can someone please tell me how to use a pretrained model for classifying unknown images using triplet loss? And where can I find the pretrained model for the same?


Fix keywords connect lhs

Turns out that just assuming any Stmt that begins with "reg" is a register declaration is a bad idea.
Added a bit of safety to visitStmt so that we actually check that the first child of a stmt is a TerminalNode before matching on a register or wire, or the like.
Also added some Parser tests I had been sitting on a while, as well as a check for the specific problem with keywords on lefthand side of connects.
I also noticed the tests were missing licenses, so might as well add that too.
Fixes ucb-bar/chisel3#87

lgtm


Add shortcut presets selection

Discussion started in #97 and moved here.

I think adding a minimal thing to begin with should be fine.
Probably having 2 options for now: linux and mac.
And maybe somehow to see which are the shortcuts could be nice too.

Mk.  Since I'm not on Linux all too often, what shortcuts that should be bound?

@mikesir87 linux shortcuts work fine as it is, so I guess we can start with a mac preset for the moment.

Sounds good!  Feel free to assign this to me if you want. I'll try to get something to you soon.

Closed by #99


Do not show wireless interface as ethernet

Describe the bug
nmstatectl show of a normal WiFi device shows type: ethernet
Nmstate version

Version 2.1.1 -  git describe --tags: v2.1.0-7-g4130865

NetworkManager version

Version 1.30.0

Platform

Platform: Ubuntu 21.04

How reproducible

100%

Steps to Reproduce
nmstatectl show wlp0s20f3

Nmstate output

Expected output:

   type: wireless # (or so...)

Current output:

[WARN  nmstate::nm::show] Failed to find applied NmConnection for interface wlp0s20f3 802-11-wireless
---
dns-resolver: {}
route-rules: {}
routes: {}
interfaces:
  - name: wlp0s20f3
    type: ethernet
    state: up
    ...

Additional context

@bernhardkaindl Sorrry, we have no plan to support WIFI device yet. But yes, we should not show it as ethernet

Considering we have https://github.com/rust-netlink/wl-nl80211/ , this task is doable.


[BUG] - Redux Store Resets on Every Route Change

NextUI Version
2.2.9
Describe the bug
After debugging this for quite a while, I've hopefully found some things to help you all.
Behaviour: The Redux store resets on every route change.

This occurs whether or not you use useRef or just pass configureStore response directly into the store prop.
The wrapping order in the root layout.tsx file doesn't seem to affect the behaviour.
When clicking the Navbar < NavbarItem < Links it works no problem.
When clicking the Navbar < Dropdown < DropdownItem.href the store resets.
When clicking the Tabs < Tab.href the store resets.

Your Example Website or App
No response
Steps to Reproduce the Bug or Issue
I put together a stackbliz that should have everything. However, there is an error stopping the env from working.
 ⚠ Disabling SWC Minifer will not be an option in the next major version. Please report any issues you may be experiencing to https://github.com/vercel/next.js/issues
 ⚠ Attempted to load @next/swc-linux-x64-gnu, but an error occurred: Cannot load native addon because loading addons is disabled<EMAIL_ADDRESS> ⚠ Attempted to load @next/swc-linux-x64-musl, but an error occurred: Cannot load native addon because loading addons is disabled<EMAIL_ADDRESS> ⨯ Failed to load SWC binary for linux/x64, see more info here: https://nextjs.org/docs/messages/failed-loading-swc

If your team has a working template that these files could be transfered (and offered for submitting new issues) that would be very helpful 🙏
https://stackblitz.com/edit/stackblitz-starters-zan1yb
Expected behavior
No redux state reset on route change.
Screenshots or Videos
Note the profile icon in the right corner. When it flashes is when redux store is reset.
https://github.com/nextui-org/nextui/assets/10913613/fa43d429-b9cf-463a-be6c-a15f4c393674
Operating System Version
macOS
Browser
Chrome

good afternoon, did you find a solution?


Remove LineWarpOutputStream

Wraping the line length to 1000 for SMTP is now not needed as
all emails are quoted-printable
quoted-printable has a maximum line length of 76 rfc 2045.
As this function is only called once to shorted it to 1000 characters length it is not needed.

This also means that issue #2209 is redundant

A point raised by @Valodim is that the headers can exceed this value. The current solution doesn't seem to work properly for long headers but that should probably be raised by another issue.

Where did is it written the 1000 char limit is no more?
I'm reading Tannenbaum, 2011, far later than that RFC, and he describes it as a requirement still.


Update German translation

Added the translation for the new settings

Thank you for contributing!
Would you mind updating the translations on Crowdin for the reason I stated in #96?

Sure, haven't read the other pr sorry. Should be translated on crowdin now.

Thank you so much!
cc9a01bfce69524a42705740a02bec6f7c38b2ee has been merged and I'll close this pull request now :)


Update to next 13

Hi, somebody found a way to make this work with next 13?

This works with Next 13 out of the box.
The only issue discovered whilst testing is there's a double anchor output in the HTML:

I'm guessing this will be because of the latest Link component changes and the legacyBehaviour prop needs to be passed at https://github.com/etchteam/next-pagination/blob/200c901f9083fbcc320a982c7fb908ac3f1045b2/src/index.tsx#L128

Thanks for the great lib, and thanks for fixing the Link issue with Next 13, as we just ran into this.


WXSDKInstance 中 onActivityResult 的resultCode 传错了

看了一下0.10.x的源码，还真是这样

This PR/issue doesn't received response since Weex migrated to Apache two years ago and this repository is no longer active yet.
Feel free to ask question in new repository and thanks for your contribution.

This issue is outdated for a long time and will be closed now. You can create a new one if you still have questions.


Make dashboard and discord logos white on badges

For readability the logos for the dashboard and discord badges are now white. This was supposed to be the PR linked below, but due to performance degradation from external services, the amended commit was not picked up.
Previous PR: https://github.com/systeminit/si/pull/2621

bors merge


Inconsistency of rendering column with buttons between Web and Android

Steps to Reproduce

Create Column with ElevatedButton-s (or OutlineButton-s, or TextButton-s)
Run on Web and Android (probably desk, iOS also)

render_issue.zip
Expected results:
Same render for web and mobile.
Actual results:

Code sample
  @override
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: Text(widget.title),
      ),
      body: Column(
          crossAxisAlignment: CrossAxisAlignment.stretch,
          children: <Widget>[
            ElevatedButton(onPressed: _incrementCounter, child: Text("1")),
            ElevatedButton(onPressed: _incrementCounter, child: Text("2")),
            ElevatedButton(onPressed: _incrementCounter, child: Text("3")),
            ElevatedButton(onPressed: _incrementCounter, child: Text("4")),
            ElevatedButton(onPressed: _incrementCounter, child: Text("5")),
          ],
      ),
    );
  }

 `flutter doctor -v`
[√] Flutter (Channel beta, 3.7.0-1.5.pre, on Microsoft Windows [Version 10.0.22621.1105], locale en-US)
    • Flutter version 3.7.0-1.5.pre on channel beta at ...
    • Upstream repository https://github.com/flutter/flutter.git
    • Framework revision 099b3f4bf1 (4 weeks ago), 2023-01-20 18:35:12 -0800
    • Engine revision 45c5586f2a
    • Dart version 2.19.0 (build 2.19.0-444.6.beta)
    • DevTools version 2.20.1

[√] Windows Version (Installed version of Windows is version 10 or higher)

[√] Android toolchain - develop for Android devices (Android SDK version 33.0.1)
    • Android SDK at ...
    • Platform android-33, build-tools 33.0.1
    • Java binary at: ...
    • Java version OpenJDK Runtime Environment (build 1.8.0_242-release-1644-b01)

[√] Connected device (4 available)
    • sdk gphone x86 arm (mobile) • emulator-5554 • android-x86    • Android 11 (API 30) (emulator)
    • Windows (desktop)           • windows       • windows-x64    • Microsoft Windows [Version 10.0.22621.1105]
    • Chrome (web)                • chrome        • web-javascript • Google Chrome 110.0.5481.77
    • Edge (web)                  • edge          • web-javascript • Microsoft Edge 110.0.1587.41

[√] HTTP Host Availability
    • All required HTTP hosts are available

• No issues found!

Try changing your ThemeData to use uniform
visualDensity: VisualDensity.standard,
materialTapTargetSize: MaterialTapTargetSize.shrinkWrap,

Hi @andrey-brill, as pointed out above you can achieve the desired effect by setting the visualDensity and the materialTapTargetSize.
See https://github.com/flutter/flutter/issues/85729#issuecomment-878640953 for more context.
Closing this as a duplicate of https://github.com/flutter/flutter/issues/85729.
Thank you


Fix Firefox issue: CanvasRenderingContext2D.createPattern: Passed-in canvas has width 0

Bug report:
I recently came to using html2canvas-pro and ran into the following issue when trying to create a PDF using html2canvas-pro and jsPDF:
DOMException: CanvasRenderingContext2D.createPattern: Passed-in canvas has width 0

Which seems to be an old issue from html2canvas (https://github.com/niklasvh/html2canvas/issues/2697)
There is also a potential fix mentioned in the above issue (https://github.com/Nexedi/erp5/commit/d4974e48408b823809757a2a5538fe43f6b71ea9)
For now I patched html2canvas-pro via patch-package to include the fix and so far I haven't notices any adverse effects, so I was wondering if the changes could just be included, removing the need for a manual patch and making it more compatible with Firefox.
I have prepared a little PR with the changes for your convenience #8
Specifications:

html2canvas-pro version tested with: 1.5.1
Browser & version: Firefox 127.0.2
Operating system: MacOS 14.5

hi, thx for your pr, fix for firefox has been merged in v1.5.3 of html2canvas-pro. If you encounter any issues with html2canvas-pro or have suggestions for new features, feel free to submit a PR. I'll address it as soon as possible.


Results are not shown and results container is all red

I followed all the instructions and run the app. I went to Linq Samples section and the first lesson in there called Restriction Operators
at this place I found this issue
https://localhost:56527/101-linq-samples/docs/restrictions.md#linq-query-structure

Hi team, same issue here.

Hi Team,
same issue on my machine.

Same! :(

I hit the same issue when i run it on Mac

I also get this issue, both in Chrome and Safari on MacOS 12.2 (Monterey).
On my laptop running MacOS 10.15 (Catalina) it doesn't start at all.

Same!

same issue

same here!

Same here!

I was curious about this project but I got same error and I can see this error in Console:
Uncaught (in promise) Error     at new t (tsMode.js:1:1)     at e.<anonymous> (tsMode.js:1:1)     at w (tsMode.js:1:1)     at Generator._invoke (tsMode.js:1:1)     at E.forEach.e.<computed> [as next] (tsMode.js:1:1)     at s (tsMode.js:1:1)

Hi, same here :(

I got the same problem. It would be great if this resource was working properly.

Same here :(

Same error

Same here :(

Same
when I run dotnet try verify I get the below error
Unhandled exception: System.AggregateException: One or more errors occurred. (Unsupported log file format. Latest supported version is 9, the log file has version 14.)
 ---> System.NotSupportedException: Unsupported log file format. Latest supported version is 9, the log file has version 14.
   at Microsoft.Build.Logging.StructuredLogger.BinLogReader.Replay(Stream stream) in C:\MSBuildStructuredLog\src\StructuredLogger\BinaryLogger\BinLogReader.cs:line 53
   at Microsoft.Build.Logging.StructuredLogger.BinLogReader.Replay(String sourceFilePath) in C:\MSBuildStructuredLog\src\StructuredLogger\BinaryLogger\BinLogReader.cs:line 37
   at Buildalyzer.AnalyzerManager.Analyze(String binLogPath, IEnumerable`1 buildLoggers)
   at WorkspaceServer.Packaging.Package.LoadDesignTimeBuildFromBuildLogFile(Package package, FileSystemInfo binLog) in D:\workspace\_work\1\s\WorkspaceServer\Packaging\Package.cs:line 138
   --- End of inner exception stack trace ---
   at System.Threading.Tasks.Task.ThrowIfExceptional(Boolean includeTaskCanceledExceptions)
   at System.Threading.Tasks.Task.Wait(Int32 millisecondsTimeout, CancellationToken cancellationToken)
   at System.Threading.Tasks.Task.Wait()
   at WorkspaceServer.Packaging.Package.TryLoadDesignTimeBuildFromBuildLog() in D:\workspace\_work\1\s\WorkspaceServer\Packaging\Package.cs:line 127
   at WorkspaceServer.Packaging.Package..ctor(String name, IPackageInitializer initializer, DirectoryInfo directory, IScheduler buildThrottleScheduler) in D:\workspace\_work\1\s\WorkspaceServer\Packaging\Package.cs:line 112
   at WorkspaceServer.Packaging.RebuildablePackage..ctor(String name, IPackageInitializer initializer, DirectoryInfo directory, IScheduler buildThrottleScheduler) in D:\workspace\_work\1\s\WorkspaceServer\Packaging\RebuildablePackage.cs:line 22
   at WorkspaceServer.Packaging.PackageBuilder.GetPackage(Budget budget) in D:\workspace\_work\1\s\WorkspaceServer\Packaging\PackageBuilder.cs:line 163
   at WorkspaceServer.PackageRegistry.<>c__DisplayClass10_0.<<GetPackageFromPackageBuilder>b__0>d.MoveNext() in D:\workspace\_work\1\s\WorkspaceServer\PackageRegistry.cs:line 139
--- End of stack trace from previous location where exception was thrown ---
   at WorkspaceServer.PackageRegistry.Get[T](String packageName, Budget budget) in D:\workspace\_work\1\s\WorkspaceServer\PackageRegistry.cs:line 92
   at WorkspaceServer.Servers.Roslyn.RoslynWorkspaceServer.CompileWorker(Workspace workspace, BufferId activeBufferId, Budget budget) in D:\workspace\_work\1\s\WorkspaceServer\Servers\Roslyn\RoslynWorkspaceServer.cs:line 412
   at WorkspaceServer.Servers.Roslyn.RoslynWorkspaceServer.Compile(WorkspaceRequest request, Budget budget) in D:\workspace\_work\1\s\WorkspaceServer\Servers\Roslyn\RoslynWorkspaceServer.cs:line 193
   at WorkspaceServer.Servers.WorkspaceServerMultiplexer.Compile(WorkspaceRequest request, Budget budget) in D:\workspace\_work\1\s\WorkspaceServer\Servers\WorkspaceServerMultiplexer.cs:line 26
   at MLS.Agent.CommandLine.VerifyCommand.Compile(Session session, MarkdownProcessingContext context) in D:\workspace\_work\1\s\MLS.Agent\CommandLine\VerifyCommand.cs:line 193
   at MLS.Agent.CommandLine.VerifyCommand.Do(VerifyOptions verifyOptions, IConsole console, StartupOptions startupOptions, MarkdownProcessingContext context) in D:\workspace\_work\1\s\MLS.Agent\CommandLine\VerifyCommand.cs:line 84
   at System.CommandLine.Invocation.CommandHandler.GetResultCodeAsync(Object value, InvocationContext context)
   at System.CommandLine.Invocation.ModelBindingCommandHandler.InvokeAsync(InvocationContext context)
   at System.CommandLine.Invocation.InvocationPipeline.<>c__DisplayClass4_0.<<BuildInvocationChain>b__0>d.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c.<<UseParseErrorReporting>b__20_0>d.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at MLS.Agent.CommandLine.CommandLineParser.<>c__DisplayClass7_0.<<Create>b__2>d.MoveNext() in D:\workspace\_work\1\s\MLS.Agent\CommandLine\CommandLineParser.cs:line 165
--- End of stack trace from previous location where exception was thrown ---
   at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c__DisplayClass15_0.<<UseHelp>b__0>d.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c__DisplayClass24_0.<<UseVersionOption>b__0>d.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c__DisplayClass22_0.<<UseTypoCorrections>b__0>d.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c.<<UseSuggestDirective>b__21_0>d.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c.<<UseParseDirective>b__19_0>d.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c.<<UseDebugDirective>b__11_0>d.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c.<<RegisterWithDotnetSuggest>b__10_0>d.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.CommandLine.Builder.CommandLineBuilderExtensions.<>c__DisplayClass13_0.<<UseExceptionHandler>b__0>d.MoveNext()

I tried the global.json fix suggested in similar raised issues but it didn't work

I was able to get this working with the SDK 3.1.424 installed alongside of 6.0.402. Had to add a global.json at the root of try-samples like this { "sdk": { "version": "3.1.424" } }
Removed references to the package 'System.CommandLine.Experimental' from all of the .csproj files. Removed the same references in .\try-samples\101-linq-samples\src\obj\project.assets.json Be sure to update any references to the latest SDK to refer to the 3.1.424, ie: in the project.assets.json... "runtimeIdentifierGraphPath": "C:\\Program Files\\dotnet\\sdk\\3.1.424\\RuntimeIdentifierGraph.json"
The first run will give an error but subsequent runs ran without issue.

Thank you, This Works !!!

This worked for me as well thank you

Thank you so much!

this should work:

check your sdk versions dotnet --list-sdks

3.0.103 [C:\Program Files\dotnet\sdk]
3.1.426 [C:\Program Files\dotnet\sdk] # <- try this one or any 3.x version
6.0.202 [C:\Program Files\dotnet\sdk]
6.0.203 [C:\Program Files\dotnet\sdk]
7.0.112 [C:\Program Files\dotnet\sdk]
8.0.100-preview.5.23303.2 [C:\Program Files\dotnet\sdk]
8.0.100-rc.2.23502.2 [C:\Program Files\dotnet\sdk]

set sdk version in your repo

dotnet new global.json

then use the version above. It then should be like this:
{
  "sdk": {
    "version": "3.1.426"
  }
}

install dotnet try tool

dotnet tool install --global "Microsoft.dotnet-try"

verify if any issues

dotnet try verify

If any, google it

enjoy it

dotnet try

this should work:

check your sdk versions dotnet --list-sdks

3.0.103 [C:\Program Files\dotnet\sdk]
3.1.426 [C:\Program Files\dotnet\sdk] # <- try this one or any 3.x version
6.0.202 [C:\Program Files\dotnet\sdk]
6.0.203 [C:\Program Files\dotnet\sdk]
7.0.112 [C:\Program Files\dotnet\sdk]
8.0.100-preview.5.23303.2 [C:\Program Files\dotnet\sdk]
8.0.100-rc.2.23502.2 [C:\Program Files\dotnet\sdk]

set sdk version in your repo

dotnet new global.json

then use the version above. It then should be like this:
{
  "sdk": {
    "version": "3.1.426"
  }
}

install dotnet try tool

dotnet tool install --global "Microsoft.dotnet-try"

verify if any issues

dotnet try verify

If any, google it

enjoy it

dotnet try

This works. Thanks!!!

I met the similar thing in my Computer too, the issue is solved with below steps:
The enviornment:
OS: Win 11
.NET SDKs: .NET Core 3.0 SDK, .NET Core 3.1 SDK, .NET 6.0 SDK, .NET 8.0 SDK installed.
1.Make sure you installed lastest version of "dotnet try" tool.
If you install it with the command "dotnet tool install -g dotnet-try", you need unistall it first with:
dotnet tool uninstall -g dotnet-try

If you install it with the command "dotnet tool install -g Microsoft.dotnet-try", you need unistall it first with:
dotnet tool uninstall -g Microsoft.dotnet-try

Then install the latest verion of "dotnet try" with below command:
dotnet tool install -g --add-source "https://pkgs.dev.azure.com/dnceng/public/_packaging/dotnet-tools/nuget/v3/index.json" Microsoft.dotnet-try

In Windows, recommand to run above commands in "cmd" with admin permission.
2.Make sure you installed .NET 3.0 and .NET 3.1 SDKs
You can run below command to check:
dotnet --list-sdks

If you did not install them, download from below links and install them.
https://dotnet.microsoft.com/en-us/download/dotnet/3.0
https://dotnet.microsoft.com/en-us/download/dotnet/3.1
Note: .NET core 3.1 SDK's version is "3.1.416" so far.
3.Clone code with below command using git shell
git clone https://github.com/dotnet/try-samples

4.Create global.json at the root of the folder "try-samples":
The content is below:
{
  "sdk": {
    "version": "3.1.416"
  }
}

Note: the version "3.1.416" here should be the same as in step 2.
5.Try to compile it with "dotnet try verify" command
cd try-samples/
dotnet try verify

If no exceptions happened, jump to next step below.
Else try to remove references to the package 'System.CommandLine.Experimental' from all of the .csproj files.
6.Run "dotnet try" command to open the web in browser:
dotnet try ".\101-linq-samples"

7.Try the examples from Web.
May it be helpful for you.

References:
https://github.com/dotnet/try/blob/main/DotNetTryLocal.md
https://github.com/dotnet/try/issues/938#issuecomment-1023604536
This anwer first publish in:
https://stackoverflow.com/a/78534041/6075331


Update scalatest to 3.2.8

Updates org.scalatest:scalatest from 3.2.2 to 3.2.8.
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

Ignore future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "org.scalatest", artifactId = "scalatest" } ]

labels: test-library-update, semver-patch

Superseded by #60.


regex of named parameters doen't match route

I have a router on which I mounted the following route (created thanks to the relative doc):
router.get( '/:article([0-9]+-.*)', function(req, res, next){
  console.log("Article matched");
  next();
});
app.use('/mountpath', router);

I want this route to match /mountpath/1-a (req.path inside the router: /1-a), but it doesn't.
I also tried with /:article(.+) and /:article, only the last match.
However, the (nice) tool provided by @ForbesLindesay said me that I have correctly written the 2 previous path.
Am I doing something wrong? Or maybe it is linked to the version of path-to-regexp in express package.json?

I have to look when I get to a computer, but I believe that the version we use in Express 4 does not support using * in the regular express. Can you try this:
'/:article([0-9]+-.{0,})'

@dougwilson It looks your regex doesn't match the path too.

K. You can definitely achieve what you're trying to do in Express 4, I just don't remember the path-to-regexp module's syntax off hand. I'll check it out when I eventually get to a computer.
It's possible you may also have to use {1,} instead of +

Ah, I see, it's that path-to-regexp that we use does not allow you to use . in the regular expression group. The following path is what you want to use:
router.get( '/:article([0-9]+-[\\S\\s]{0,})', function(req, res, next){

i.e you have to use something in place of . like [\\s\\S] or [\\w\\W] or you can just specify a more restricted thing that "any character".

Nice! I think I'll find a more restricive character matching pattern than '.'.
Is there a reason why Express doesn't use the last path-to-regexp version?
Shouldn't the allowed pattern and other rules be documented in Express, as the current path-to-regexp documentation doesn't match the Express version (the module can use '.')?

I'm glad we got it working :)

Is there a reason why Express doesn't use the last  path-to-regexp  version?

All versions higher than the one we are using is not backwards compatible, so we cannot upgrade without breaking everyone's apps due to changed route syntax. We will upgrade, but it has to wait until 5.0, which is only a few months out.

Shouldn't the allowed pattern and other rules be documented in Express, as the current  path-to-regexp  documentation doesn't match the Express version (the module can use '.')?

Yes, they should. Please open an issue over at https://github.com/strongloop/expressjs.com :)


quartata: Blacklist techtweek.com

quartata requests the blacklist of the website techtweek.com. See the Metasmoke search here

plus one more they didn't properly link

!!/approve


pact-stub-server running with HTTPS

Hi,
I'm trying to make our infrastructure more secure and so decided to use HTTPS. I successfully did that for Pact Broker, however now I'm having issues with pact-stub-server now.
Can pact-stub-server run in Docker and use https?
Thanks for the whole framework, it turned to be extremely helpful in our environment!
Martin

It can run in Docker and use HTTPS. It just needs to be updated to allow the self-signed certificate to be trusted.

Just to clarify what you are asking (as you changed the issue title), do you need to fetch pacts from a server using a self-signed cert, or are you asking about running the stub server using TLS and a self-signed cert?

I've updated the title, because while writing the description of my query, I've realized couple of things that made it easier :) So what you did - the flag, was what I was asking about.
In AWS environment I was able to run the pact-stub in docker container with nginx as reverse proxy similar way as pact-broker, using very similar headers. And since pact-stub reaches to pact-broker via Load Balancer, the self-signed cert is not an issue in our "production" environment. The Flag to ignore the self-signed cert warnings is very handy in local dev environment though. Thanks a lot!


Some of functions are not supported

Using of eval, call, foreach functions break everything including code highlighting.
Probably, they can be parsed in grammar, even if not proceed by plugin.
Full list of functions can be found here:
https://www.gnu.org/software/make/manual/html_node/Functions.html
I can do it myself in couple weeks. What format of pull requesting you like?

Here is an example commit which added support for some other functions: c3cb4db14921dd0aa2909feb5840933b79ba513e
If you want to contribute you'll need to update parser and lexer, regenerate them (see README.md) and add a test.

I have started some work here https://github.com/kunyavskiy/intellij-makefile/commits/fixes.
But I noticed a big problem. which will probably need big parsing rewriting to fix.
For example code like this which is quite usefull can't be parsed by current lexer even if support foreach and call functions.
$(foreach file, ${FILE_LIST}, $(call MyMacro, ${file}))

To fix this one will need get rid of FUNCTION state in lexer, because otherwise he will need to check balanced brackets sequence using automaton, which is impossible.
Probably, it can be done, because this state is quite useless anyway, but it is bigger work than I thought first.
Also this will help to parse something like ${C_FILES_LIST:%.c=${OBJECTS_DIR}/%.o}
which is not parsed either now.

Yeah, I see. Current lexer impl is a bit hacky and dirty. Seems it's time to rewrite it.
Parsing function calls and variables correctly will also allow to implement completion in appropriate places.


TS-4909: Throttling based on resident memory usage

FreeBSD build successful! See https://ci.trafficserver.apache.org/job/Github-FreeBSD/900/ for details.

Linux build successful! See https://ci.trafficserver.apache.org/job/Github-Linux/795/ for details.

Linux build failed! See https://ci.trafficserver.apache.org/job/Github-Linux/912/ for details.

FreeBSD build successful! See https://ci.trafficserver.apache.org/job/Github-FreeBSD/1019/ for details.

Linux build successful! See https://ci.trafficserver.apache.org/job/Github-Linux/911/ for details.


Add test for the reason TimeNode broke from 4.1.0 -> 4.2.0

@Kuzirashi discovered that the TimeNode doesn't work on version 4.2.0 while integrating with the DApp. We need to add a test once we find the bug in  order to make sure future changes do not break functionality.

Resolved by @Bagaric


Gjoranv/vagrant gui switch

Please note the <TODO>s for the environment vars to specify box and box url with GUI. Feel free to commit to this branch or specify what the section should say in a comment.
FYI: @bjorncs

@geirst Updated according to your comments. PTAL


[DocDB] Is checkName valid?

Hi @dmakwana
Testing chackNameExists leads an error in Python:
msrestazure.azure_exceptions.CloudError: 401 Client Error: Unauthorized for url: https://management.azure.com/subscriptions/XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXX/providers/Microsoft.DocumentDB/databaseAccountNames/mypydocdbe7ce0d93?api-version=2015-04-08

Could you take a look at the Swagger file and confirm this seems to be valid? If yes, have you an idea of why it fails?
Thanks,

I looked at the Swagger file and it seems to be valid. Which subscription ID are you testing with? Make sure the calls you make are authorized for that subscription ID.

@dmakwana I was waiting more testing before answering. I was able to do create/list/list_keys/regenerate, etc. with this subscription but still the same error on "checkName". So I guess my subscription is OK (I don't think I can be able to create an account, but not check a name no?)

HTTP query:
interactions:
- request:
    body: null
    headers:
      Accept: [application/json]
      Accept-Encoding: ['gzip, deflate']
      Connection: [keep-alive]
      Content-Type: [application/json; charset=utf-8]
      User-Agent: [python/3.5.1 (Windows-10-10.0.14393-SP0) requests/2.11.1 msrest/0.4.4
          msrest_azure/0.4.3 documentdb/0.1.0 Azure-SDK-For-Python]
      accept-language: [en-US]
      x-ms-client-request-id: [028bc236-a550-11e6-861c-ecb1d756380e]
    method: HEAD
    uri: https:/management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/providers/Microsoft.DocumentDB/databaseAccountNames/mypyddbtestf5d40e06?api-version=2015-04-08
  response:
    body: {string: ''}
    headers:
      Cache-Control: [no-cache]
      Connection: [close]
      Content-Length: ['0']
      Content-Type: [application/json]
      Date: ['Tue, 08 Nov 2016 01:09:33 GMT']
      Expires: ['-1']
      Pragma: [no-cache]
      Server: [Microsoft-HTTPAPI/2.0]
      Strict-Transport-Security: [max-age=31536000; includeSubDomains]
      x-ms-activity-id: [73139e54-abe6-4c14-a3b0-fac9bd0066db]
      x-ms-correlation-request-id: [d39fa77b-5e3e-4dc3-b0ed-133cdff6219f]
      x-ms-ratelimit-remaining-subscription-reads: ['14972']
      x-ms-request-id: [d39fa77b-5e3e-4dc3-b0ed-133cdff6219f]
      x-ms-routing-request-id: ['NORTHCENTRALUS:20161108T010934Z:d39fa77b-5e3e-4dc3-b0ed-133cdff6219f']
    status: {code: 401, message: Unauthorized}
version: 1

(subscription replaced for security)

@lmazuel  Thanks! I've discovered the error, the subscription Id is supposed to be omitted from the path for that request. I've removed it in the PR: #697

PR merged, thanks!


_onWillPop() callback always gets vetoed

I believe I found an odd behaviour when the _onWillPop() callback always vetoes an attempt to pop the screen no matter if it returns true or false;
Future<bool> _onWillPop() async {
    return true;
  }

It is the same code provided with the package example (minus the styling and decoration to keep the question concise).
 @override
  Widget build(BuildContext context) {
    return ConditionalWillPopScope(
      onWillPop: _onWillPop,
      shouldAddCallback: _hasChanges,
      child: Scaffold(
        appBar: AppBar(title: Text('Second Screen')),
        body: Center(
          child: Container(
            child: SwitchListTile(
              onChanged: _updateChanges,
              title: Text('Disable back navigation'),
              value: _hasChanges,
            ),
          ),
        ),
      ),
    );
  }

I've double-checked that the custom transition builder is also set correctly, as per:
@override
  Widget build(BuildContext context) {
    return MaterialApp(
      title: 'Flutter Demo',
      theme:
          primarySwatch: Colors.blue,
          pageTransitionsTheme: PageTransitionsTheme(builders: {
            TargetPlatform.iOS: CupertinoWillPopScopePageTransionsBuilder()
          })),
      home: const MyHomePage(title: 'Flutter Demo Home Page'),
    );
  }

The issue is reproducible in a brand-new project to make sure it doesn't conflict with any other packages. Also relates to this issue which seems to be stale.
Any idea what might be wrong?

Same here. The _onWillPop is always called - even with the iOs back swipe. But the screen is only popping when the default BackButton of the AppBar is used. When using the back swipe, pop is always canceled (despite _onWillPop returning true).


Unable to load lingoes on CentOS when using PyInstaller

The so loading doesn't work when running inside PyInstaller even though PyInstaller correctly adds libgeos to the build.
Operating system
CentOS 6.4 and most likely newer versions
Shapely version and provenance
1.6b4 installed via whl

There is special code in geometry.py to handle anaconda, but not frozen.


Need warning before unsubscribing from a private stream.

I am Really happy after testing out zulip the last couple days. I'm excited to use it to help coordinate a distributed team. You are doing great work.
I had one issue when I accidentally clicked the "checkmark" in the stream list and removed myself from a private stream. I didn't get any warning this would cause me to be unsubscribed. Then, as organization admin, I wasn't able to find a way to subscribe to any private stream which I created but am no longer a member of—locked out of my own stream!
To resolve it, I deleted and made a new stream with the same name. There wasn't any conversation yet, so no harm done.
I'll try to be more careful but it would be really nice if there was a modal asking if I really want to leave and that I won't be able to get back in without an invitation, especially for private streams.
Also, please consider allowing an organization admin to add people (including themselves) to private streams even if they are not a member.
Thanks, —AJ

Let's make 2 milestones for this.

Modal for unsubscription from a stream.

Admins have right to add themselves to a private stream.

@zulipbot label "needs review"

@zulipbot remove "needs review"


Very Slow Processing Time

Hi,
It takes more than 1 minute to process 1 image.
I ran the bash scripts/dense_cap_demo.sh ./output/ckpt ./output/ckpt/vocabulary.txt  command.
I wonder if I am doing anything wrong.   I am using an aws p2.xlarge gpu.  Is this normal ?
Or do have to do another configuration I am not aware of.  Please any help is appreciated.
Thanks

Hi,
I tested once, K80 is slower than gtx 10xx. You may change the config TEST.USE_BEAM_SEARCH in scripts/dense_cap_demo.sh to be False and it will be faster.
best,

Hi,
Thanks I did change it and it was a lot faster.  Good job on the code !   Thanks

Glad to help.
I will close the issue, but feel free to reopen it if you have further question.
best


research

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Recommend using a cluster name that meets the requirements, i.e., with only alphanumeric characters

I recommend providing the requirements for cluster names, i.e., it can only include characters that are alphanumeric.
When running the az kusto cluster create --cluster-name $clustername ... command, if a cluster name is used the violates the cluster name requirements, the following, obscure, error is received:
The command failed with an unexpected error. Here is the traceback:
local variable 'deserialized' referenced before assignment
Traceback (most recent call last):
  File "/opt/az/lib/python3.6/site-packages/knack/cli.py", line 231, in invoke
    cmd_result = self.invocation.execute(args)
  File "/opt/az/lib/python3.6/site-packages/azure/cli/core/commands/__init__.py", line 657, in execute
    raise ex
  File "/opt/az/lib/python3.6/site-packages/azure/cli/core/commands/__init__.py", line 720, in _run_jobs_serially
    results.append(self._run_job(expanded_arg, cmd_copy))
  File "/opt/az/lib/python3.6/site-packages/azure/cli/core/commands/__init__.py", line 691, in _run_job
    result = cmd_copy(params)
  File "/opt/az/lib/python3.6/site-packages/azure/cli/core/commands/__init__.py", line 328, in __call__
    return self.handler(*args, **kwargs)
  File "/opt/az/lib/python3.6/site-packages/azure/cli/core/commands/command_operation.py", line 121, in handler
    return op(**command_args)
  File "/home/name/.azure/cliextensions/kusto/azext_kusto/generated/custom.py", line 122, in kusto_cluster_create
    parameters=parameters)
  File "/opt/az/lib/python3.6/site-packages/azure/cli/core/util.py", line 646, in sdk_no_wait
    return func(*args, **kwargs)
  File "/home/name/.azure/cliextensions/kusto/azext_kusto/vendored_sdks/kusto/operations/_clusters_operations.py", line 226, in begin_create_or_update
    **kwargs
  File "/home/name/.azure/cliextensions/kusto/azext_kusto/vendored_sdks/kusto/operations/_clusters_operations.py", line 171, in _create_or_update_initial
    return cls(pipeline_response, deserialized, {})
UnboundLocalError: local variable 'deserialized' referenced before assignment

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

ID: 33701166-a22b-03c6-3d9b-9ec4aa4b6abf
Version Independent ID: be982211-68ff-1896-c59b-3ab3820887ca
Content: Quickstart - Export data from Azure IoT Central
Content Source: articles/iot-central/core/quick-export-data.md
Service: iot-central
GitHub Login: @dominicbetts
Microsoft Alias: dobett

@petertuton Thanks for the feedback! We are currently investigating and will update you shortly.

@dominicbetts Please review the feedback and update the doc accordingly.
These feedbacks are related to single doc: https://docs.microsoft.com/en-us/azure/iot-central/core/quick-export-data
https://github.com/MicrosoftDocs/azure-docs/issues/84617
https://github.com/MicrosoftDocs/azure-docs/issues/84618

Hi @petertuton - thanks for reporting this - I've added some notes to the quickstart about the acceptable characters to use in the cluster name. I'll publish an updated version of this quickstart later today.

I'll close this issue now, but feel free to reopen if you have any follow-up comments. Thanks!
#please-close


non-pandas DataFrame equality checks don't pass when getting the df variable name

fixed in https://github.com/noteable-io/dx/pull/193


Editor: Update Text Presets to Latest Designs

I think this just involves updating line height and bg text mode for the presets. Updates here:
https://www.figma.com/file/NHHMwIfxMnz39NxqkrFb7R/Stories---Post-Stable

The highlight background for the paragraph default extends beyond blue border
Also, shouldn't I be seeing values for padding (according to figma H=8px V=4px)?

The highlight background for the paragraph default extends beyond blue border
Also, shouldn't I be seeing values for padding (according to figma H=8px V=4px)?

@csossi the padding extending beyond the border box is an existing bug that's not related to this update. we can try to increase it's width so that it gets mitigated a little bit, but its a known unrelated bug
Also the padding value there is correct. Sam requested a hidden padding that shows up on the element but isn't seen in the inspector. So at the displayed values on the element this is what should show up in the inspector:
element on canvas : input showed to user
8x4.                          : 0x0
12x8                         : 4x4
28x14.                      : 20x10

@csossi the padding extending beyond the border box is an existing bug that's not related to this update. we can try to increase it's width so that it gets mitigated a little bit, but its a known unrelated bug
Also the padding value there is correct. Sam requested a hidden padding that shows up on the element but isn't seen in the inspector. So at the displayed values on the element this is what should show up in the inspector:
element on canvas : input showed to user
8x4.                          : 0x0
12x8                         : 4x4
28x14.                      : 20x10

Ah, ok - thanks so much for clarifying @littlemilkstudio
Verified in QA

Ah, ok - thanks so much for clarifying @littlemilkstudio
Verified in QA


[ARCTIC-985] remove the useless expiration process of table_transaction_meta

Why are the changes needed?

table_transaction_meta in sysdb is useless now, its expiration process should be removed
Brief change log

remove the useless expiration process of table_transaction_meta
catch all exceptions of RuntimeDataExpireService and add some error log

How was this patch tested?

[ ] Add some test cases that check the changes thoroughly including negative and positive cases if possible

[ ] Add screenshots for manual tests if appropriate

[x] Run test locally before making a pull request

Documentation

Does this pull request introduces a new feature? (yes / no)
If yes, how is the feature documented? (not applicable / docs / JavaDocs / not documented)

table_transaction_meta could be removed from sysdb after ams upgrade to 0.4.1.
However, it should be removed in the upgrade-0.4.0-to-0.4.1.sql, since these sqls are run before the upgrade.


feat: support changing the import package name

This adds support to change the package name from which we import css. e.g.
litcss({importPackage: 'lit'})
will result in
import {css as cssTag} from 'lit';
NOTE: this is based on #41, so there are other files changed in the diff

@umbopepato could you please publish the updated version to npm with the latest PRs merged.
Thanks a lot! 🙏

Sorry for the delay @VitaliiK91, I was having some trouble with GH Actions.
Anyway, published it yesterday (1.1.0) 😊


added one question relating binary and linear search

Checklist:

[x] I have read freeCodeCamp's contribution guidelines.
[x] My pull request has a descriptive title (not a vague title like Update index.md)

Closes #XXXXX

I am closing this PR because it looks like you have open another one.
But in the future, you don't need to open a new PR if you need to make changes.
You can push up your changes to the original PR instead 👍


[DOC] Update README.rst

As title

Job PR-884/1 is complete.
Docs are uploaded to http://gluon-nlp-staging.s3-accelerate.dualstack.amazonaws.com/PR-884/1/index.html


SSO Email Assignment (Old 331)

In gitlab by @A-Lawrence on Aug 31, 2015, 01:07
#WEB-174730
It seems that members who've stored multiple SSO assignments over time experience an offset error when they try to login via SSO.

In gitlab by @A-Lawrence on Dec 31, 2015, 03:04
This was resolved in an earlier version it seems.  Now unable to recreate.

In gitlab by @NFarrington on Dec 31, 2015, 15:35
Was resolved in e7b0160d4ba1cb22beb77b126fa93457904bed26

In gitlab by @A-Lawrence on Jan 12, 2016, 18:53
Milestone removed


Feature: CORS mode opt-in

Summary
This PR resolves #11 by adding a crossorigin prop that can be used to opt-in to CORS mode for the cross-origin image requests.
Example:
<clazy-load src="https://other-domain.com" crossorigin="anonymous">

    Loading message

</clazy-load>

This allows the lazily-loaded images to make cross-origin requests with CORS mode allowing them to be properly cached using a Workbox Service Worker cacheFirst strategy.
Other
I was sure if I needed to or not, but I ran npm run build and generated new files in the dist/ directory as well.
Any feedback is greatly appreciated, thank you! 😉

Thank you for this PR! Really appreciate it. And yes, npm run build is needed. I'll merge this and tomorrow release a new version with a bunch of other fixes.


Add ability to assign project to pull request

As we could assign milestone to pull-request using -M flag, it would be great if I would be able to assign projects to PRs while creating them.
Also if someone could guide me, I can also try to contribute this feature.

Duplicate of https://github.com/github/hub/issues/1858
You're welcome to try making this change! The existing code in commands/pull_request.go related to assignees/reviewers should guide you.


use full width images in posts

https://infrastructure.sparcopen.org/landscape-analysis/elsevier

Do you want people to be able to click on the images, or for the images to appear, inline, in full-size? It will bleed & overlap with the right-side content, unless we make the right-side content not sticky.

erm, I want them the full width of the text (so, the RHS column would be clear)

Ah okay, then it’s not a CSS issue. Do you just need to crop the images then?

Joseph McArthur
Assistant Director: Right to Research Coalition ( http://righttoresearch.org )
Director / Founder: Open Access Button ( http://openaccessbutton.org )
Twitter: @Mcarthur_Joe ( https://twitter.com/Mcarthur_Joe )
Skype: joseph_mcarthur
On Mon, Jun 22, 2020 at 5:49 PM, Sophy <<EMAIL_ADDRESS>> wrote:

Ah okay, then it’s not a CSS issue. Do you just need to crop the images
then?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub (
https://github.com/sparcopen/infrastructure/issues/80#issuecomment-647642291
) , or unsubscribe (
https://github.com/notifications/unsubscribe-auth/ABFZMZ23LPTL4H7PI7NW2RTRX6DRHANCNFSM4ODIHECQ
).

Yep!

Ah, if it's fast for you to crop them then that would be great... but if it isn't let me know and I deal with it.

Sure, but shouldn’t you have the source material instead of the PNGs? Probably easier to export from there -- if not, no problem, I can do that too...

Should do, let me hunt down.
Joseph McArthur
Assistant Director: Right to Research Coalition ( http://righttoresearch.org )
Director / Founder: Open Access Button ( http://openaccessbutton.org )
Twitter: @Mcarthur_Joe ( https://twitter.com/Mcarthur_Joe )
Skype: joseph_mcarthur
On Mon, Jun 22, 2020 at 6:31 PM, Sophy <<EMAIL_ADDRESS>> wrote:

Sure, but shouldn’t you have the source material instead of the PNGs?
Probably easier to export from there -- if not, no problem, I can do that
too...
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I've cropped them


[sram_ctrl/dv] Verify the MEM.READBACK feature

Description
PR #23212 introduced the readback mode to the SRAM controller. However, currently, we do not test, whether this feature can mitigate bit flips introduced by FI.

This issue is about creating a sec_cm DV test for the readback feature. It would be nice to have but it will only cover a list of pre-defined signals fed into the test. What really counts for this feature is doing some kind of formal analysis, RTL simulation with automated FI or real FI on a chip / FPGA. All this seems out of scope for M5. I am thus assigning a lower priority to this one for now.

Just discussed: We have high confidence in this feature, and this CM test would just check that the alerts are properly connected, which is also being checked in the netlist. --> M7

I have manually tested that the readback mechanism successfully detects a mismatch and triggers a fatal alert.
More specifically, I have changed this comparison:
https://github.com/lowRISC/opentitan/blob/1b56f197b49d5f597867561d0a153d2e7a985909/hw/ip/tlul/rtl/tlul_sram_byte.sv#L156
to:
assign rdback_chk_ok_unbuf = (rdback_data_exp_q == ~tl_sram_i.d_data);

When starting the SRAM smoketest with:
./util/dvsim/dvsim.py hw/ip/sram_ctrl/dv/sram_ctrl_main_sim_cfg.hjson -i sram_ctrl_smoke --fixed-seed 1234 -t xcelium

I get:
UVM_ERROR @ 578601207 ps: (cip_base_scoreboard.sv:242) [uvm_test_top.env.scoreboard] Check failed expected_alert[alert_name].expected == 1 (0 [0x0] vs 1 [0x1]) alert fatal_error triggered unexpectedly

Which is the expected behavior.


Support for proxy

Is there a way to use this library over a proxy?

I see. So there is support for the RTU but not for Modbus TCP, right? I'm looking for a way of using the library over Socks5 proxy.


performance of multiple iSCSI LUNs in one session

@mikechristie @dillaman @lxbsz
LIO will start tx/rx thread per session, session means a link between an initiator with a target.
Suppose I have an SCSI I-T nexus, If the initiator have 20 RBD image to be exported as iSCSI LUNs under a single target, they will share the same tx/rx thread, will it bottleneck the LUN performance?
Or if I create 20 target, with only one LUN under a target，which means  LIO will create a pair of tx/rx threads for each LUN, will it be a better choice?
By the way, for now, gwcli only support one target, is there any technical consideration?
/> /iscsi-target create target_iqn=iqn.2003-01.com.redhat.iscsi-gw1
Only ONE iscsi target image is supported

It might be a bottleneck, but we have not seen that be an issue on the target side. When you run your test get some perf/profiling data on the target side so we can check things like if locks are a hotspot.
On the initiator side there are issues in Linux at least. I think because there are some session wide locks they become bottlenecks when doing multiple lun testing. However for ceph iscsi, we have not been able to really stress the iscsi session level limits yet, because we have hit perf issues on the runner/rbd side first :)
There are no technical limits. Gluster actually does a target per LUN.
For ceph iscsi we just thought it would be easier for the user to manage and did not see any perf issues.
I am open to patches to support multiple targets in the ceph-iscsi-* code.
A target/session per LUN is actually better for the ceph iscsi timeout handling because only one image/lun might have an issue but we bring down all sessions due to disabling the tpg.

Thanks for your detailed explanation, Mike. Very helpful. I will do some perf analysis on target side.

Multiple iSCSI Targets would allow for strict seperation of iSCSI Targets in different network segments (VLAN, interfaces). Each Target would have it's own Target Portal Groups and Portals. A "per tenant" Target configuration would be possible, exposing only those targets in a specific network to iSCSI clients: similar to what is being done for Ceph based NFS Ganesha.
Use cases:

Support migration from traditional enterprise SAN boxes where network segmentation is used.
PCI DSS compliance. Being able to segmentate the network would make passing PCI DSS audits easier. Otherwise you pretty much have to encrypt all the traffic (IPSEC).

Closing. Multiple targets is supported in ceph-iscsi 3.x.


Fix TO update_status to exclude ADMIN_DOWN

Specifically, changed to only include ONLINE and REPORTED, and thus
also exclude PREPROD and any other similar future states.
Fixes #3687
Still WIP, haven't tested.

What does this PR (Pull Request) do?

[ ] This PR fixes #REPLACE_ME OR is not related to any Issue

Which Traffic Control components are affected by this PR?

CDN in a Box
Documentation
Grove
Traffic Control Client
Traffic Monitor
Traffic Ops
Traffic Ops ORT
Traffic Portal
Traffic Router
Traffic Stats
Traffic Vault

What is the best way to verify this PR?

If this is a bug fix, what versions of Traffic Ops are affected?

The following criteria are ALL met by this PR

[ ] This PR includes tests OR I have explained why tests are unnecessary
[ ] This PR includes documentation OR I have explained why documentation is unnecessary
[ ] This PR includes an update to CHANGELOG.md OR such an update is not necessary
[ ] This PR includes any and all required license headers
[ ] This PR ensures that database migration sequence is correct OR this PR does not include a database migration
[ ] This PR DOES NOT FIX A SERIOUS SECURITY VULNERABILITY (see the Apache Software Foundation's security guidelines for details)

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/trafficcontrol-PR/3883/
Test PASSed.


Install MOFED instead of rdma-core in rocky accelerator preview images

/assign @jjerger
/hold
Waiting for my local Rocky 8 build to succeed before removing the hold, but I'm confident it will and this is ready for review.

/unhold

/hold Having some Rocky 9 problems

/unhold

/lgtm


feat: handle plugin/loader ValidationErrors

What kind of change does this PR introduce?

[x] Feature

Did you add tests for your changes?

[ ]

Summary
Explain the motivation for making this change. What existing problem does the pull request solve?
Consistency between schema-utils and webpack Core
Does this PR introduce a breaking change?

[x] No

Other information
#5892

The failure is to be expected atm, due to schema-utils (#14)

I found a better solution (to handle it directly in schema-utils instead).
This PR contains only a small refactor  to error handling now. I will leave it open, but feel free to close :)

Thanks


Store internal error file and line number information in error wrappers

Motivation
When generating errors, we want Error wrapper objects to store the file and the line number that the error originated from. This will greatly simplify debugging of the runtime failures.
Modification

Extended BoringSSLInternalError to store file path and line number along with the BoringSSL error code.
Extended errorMessage to append filepath:line to the message string
Now calling CNIOBoringSSL_ERR_get_error_line instead of CNIOBoringSSL_ERR_get_error to extract the necessary info

Result
Printing a BoringSSL error now shows the file path and the line number

@swift-nio-bot add to allowlist


Improvements

I've attempted to make this a proper python package and optimize your original codebase using Cython. To get the persistence from a dataset, the workflow is also now more sklearn-like:
import numpy as np
from tda import PersistentHomology

data = np.array([[1,4],[1,1],[6,1],[6,4]])

ph = PersistentHomology(epsilon=7.)
persist = ph.fit_transform(data)

which takes just over a millisecond to compute.
For the figure 8 example (w/ jitter added), the code now clocks in around ~120 milliseconds.
In [8]: ph = PersistentHomology(epsilon=0.2)
In [9]: %timeit ph.fit_transform(data)
10 loops, best of 3: 126 ms per loop

I'll try to add docstrings and such later.
Thanks for all your original hard work!

This is very neat! I will merge it. I will add a /legacy/ folder with the original code because this was originally meant to be associated with my blog's tutorial, so I want blog readers to still be able to follow along with the original code.
I'm also planning to add the Mapper algorithm to this project. I know the original Mapper is a Python project but it's not as usable as I would like.

I found an alternative implementation of the mapper algorithm here in pure Python, in case you're interested.

That project hasn't been updated in 4 months despite saying it's in "active development."
If we add Mapper to this project, we can have a complete open-source TDA library with both major tools, PH and Mapper. We could pull code form that other project so we don't need to build it from scratch, however.
If you're interested in contributing, then we can make this into a useful performant TDA library for Python.


refactor: remove @fromdeno/test peer dependency

We should develop out Deno.test within the shim itself so we don't require a peer dependency. It's not very user friendly to have to include a peer depedency... especially when Deno.test is not being used. For now, I propose this be a no-op and then we can develop it out more later.

How do you want to implement the cli/runner?
Potentially having deno.ns expose a bin that allows running deno.ns test might be nice. It'd be great DevEx too.
I could pull the impl from fromdeno/test and PR if you'd like this

npm 7 installs peerDependencies implicitly.

But yarn and pnpm do not. I don't think we should depend on npm's implicit behaviour like that.

I haven't seen questions from users of other package managers.

I don't understand, there are currently not many users of either deno.ns or @fromdeno/test, so there are no questions yet. Do you actively want to make it difficult for users of yarn/pnpm?

deno.ns is simply too big for it to depend on.

deno.ns shouldn't have to make decisions to accommodate @fromdeno/test. Plus, it doesn't need to depend on deno.ns. It can continue to have its own test implementation and be a standalone minimal testrunner. We simply need a way for it to pick up deno.ns tests.

test result: ok. 0 passed; 0 failed; 0 ignored; 0 filtered out


Fixing namespace 'InputSystem' does not exist in namespace 'CoreServices' when using Assembly Definition and Unity 2020.3.11f

Describe the problem
using Microsoft.MixedReality.Toolkit;
using Microsoft.MixedReality.Toolkit.Input;
using UnityEngine;

public class GetMRTKScoreServiceInputSystem : MonoBehaviour
{
    private void Start()
    {
        IMixedRealityInputSystem inputSystem = CoreServices.InputSystem;
    }
}

The code above causes the following error
Assets\CoreServiceTest\GetMRTKScoreServiceInputSystem.cs(11,48): error CS0234: The type or namespace name 'InputSystem' does not exist in the namespace 'CoreServices' (are you missing an assembly reference?)

Create a new project in Unity 2020.3.11f1
Import MRTK
Create the script like the one above
Add an Assembly Definition to the directory with the script
Add MRTK.Core as an Assembly Definition Reference and Apply
Observe the error from above.

Unity added a namespace called CoreServices that's now conflicting with MRTK CoreServices.
Describe the solution you'd like
Consider changing the name to CoreServices that is less ambiguous or provide documentation on best practices when using Assembly Definitions.
Describe alternatives you've considered
Using the full path to Microsoft.MixedReality.Toolkit.CoreServices fixes the issue, but not ideal.
An Alias is much nicer.
using MRTKCoreServices = Microsoft.MixedReality.Toolkit.CoreServices;

//

IMixedRealityInputSystem inputSystem = MRTKCoreServices.InputSystem;

Additional context
Assembly Definition References

@killerantz This is unfortunately a bug with Unity's Version Control / Collab package. They're accidentally including some Xamarin types. Last I heard, they've acknowledged the issue and are looking into a fix.
Another workaround until then is to uninstall that package if you aren't using it.

Closing this as fixed in the 1.13.5 release of Unity's Version Control package<EMAIL_ADDRESS>


Add google oauth docs

@prachidamle added a section on service account and why it's needed

@mrajashree make a new clean PR off of staging to add your single commit.

Closing in favor of https://github.com/rancher/docs/pull/1784
will address the pr review comments in this one in the other pr


[npo] added npo3 support

Before submitting a pull request make sure you have:

[x] At least skimmed through adding new extractor tutorial and youtube-dl coding conventions sections
[x] Searched the bugtracker for similar pull requests

In order to be accepted and merged into youtube-dl each piece of code must be in public domain or released under Unlicense. Check one of the following options:

[x] I am the original author of this code and I am willing to release it under Unlicense
[ ] I am not the original author of this code but it is in public domain or released under Unlicense (provide reliable evidence)

What is the purpose of your pull request?

[ ] Bug fix
[ ] Improvement
[ ] New extractor
[x] New feature

Description of your pull request and other information
Some NPO videos are also available at npo3.nl, I've added support for that URL and wrote a test for it. The videos at npo3.nl can be downloaded exactly the same way as on npo.nl, so I only had to add a regex. npo3.nl is an official site of NPO.

What do you mean with embedded?


[#8300] Fix for Tooltips remaining open despite option data-click-ope…

Before submitting a pull request, make sure it's targeting the right branch:

For documentation fixes, use master.
For bug fixes, use develop.
For new features, use the branch for the next minor version, which will be formatted v6.x.

If you're fixing a JavaScript issue, it would help to create a new test case under the folder test/visual/ that recreates the issue and show's that it's been fixed. Run npm test to compile the testing folder.
Happy coding! :)
…n is set to false.

Thanks! Need to do some testing before we can pull this in.

@kintesh can you write a testcase for the visual regression tests that reproduced the bug prior to the fix, and lets us quickly verify the fix across various environments?
Thanks

Can you delete this PR and I will take a look at this issue again.


thanos store: No store matched for this query

thanos version: 0.6.0
thanos query web: No store matched for this query
thanos sotre log：
read meta.json: invalid character '\u008b' looking for beginning of value"
level=warn ts=2020-03-26T09:28:36.522935346Z caller=bucket.go:325 msg="error parsing block range" block=01E2Z1FVA38NDR15DY9FKT6YR1 err="read meta.json: invalid character 'ø' looking for beginning of value"
level=warn ts=2020-03-26T09:28:36.522989196Z caller=bucket.go:325 msg="error parsing block range" block=01E2ZF76DR26D6BAXY0PNQE8ER err="read meta.json: invalid character '<' looking for beginning of value"
level=warn ts=2020-03-26T09:28:36.523013321Z caller=bucket.go:325 msg="error parsing block range" block=01E2ZF79XSFX6KHBVPFJ6DV625 err="read meta.json: invalid character 'ø' looking for beginning of value"
level=warn ts=2020-03-26T09:28:36.523063309Z caller=bucket.go:325 msg="error parsing block range" block=01E2ZP318B5P2YGERASTEQZPYJ err="read meta.json: invalid character '{' after object key:value pair"
receive series from Addr: thanos-store1.srv.daling.com:10905 LabelSets: Mint:<PHONE_NUMBER>000 Maxt:<PHONE_NUMBER>000: rpc error: code = Aborted desc = fetch series for block 01E321KYDHEQN9KRXFV6FBYFG0: add chunk preload: reference sequence 0 out of rangereceive series from Addr: thanos-store2.srv.daling.com:10905 LabelSets: Mint:<PHONE_NUMBER>000 Maxt:<PHONE_NUMBER>000: rpc error: code = Aborted desc = fetch series for block 01E321KYDHEQN9KRXFV6FBYFG0: add chunk preload: reference sequence 0 out of range
help me. thanks.

HI, it seems that the block files in object store are malformed. Could you provide the Object Store provider?

I`m sorry so later.
the Object Store provider is minio.