Fix double logger adding

I moved adding of our custom logger to "session" fixture, so there shouldn't be any more problems with duplicated logs. I tested it with command:
pytest -k FetchUnit_0 -s --log-level=debug

Resolves #675
Based on #573

I can, but both edits the same part of code, so there will be conflict between them if this review will be based on master.

This seems to be a straightforward change, and it also fixes a very annoying bug, so it could be merged very quickly. Meanwhile #573 has now around 500 lines of code and a number of features besides the main one (the CAM), so I expect that PR to be reviewed after some time.

Ok, I will prepare a separate change, but this would be probably in Sunday.

I have created a version which is based on master. Please see #694


Fix a linker error: undefined kMaxSmallSize

When building with a recent version of xt-clang and -std=c++11, the linker errs on missing definition of a static constexpr class member. In C++11, static class members still had to be defined in a C++11 file and TFLM code is expected to be compatible with C++11.
BUG=323856831

@rascani @shlmregev
This PR needs to be submitted in the Tensorflow repository.  The reason is that the file being changed is currently being synched daily from TensorFlow Lite.
FYI, the list of TFLite synched files is here.

Per our OOB conversation, this definition can be defined in runtime_shape.cc, as it is from the runtime_shape.h header. The runtime_shape.h header is not synced from TFLite.


Added cron example to readme

Resolves https://github.com/niqdev/packtpub-crawler/issues/8

That's fine, just before merge the request, does this work to you? Remember that yesterday I explain my issue and c&p the logs

Can you try changing the working directory first?
# m h  dom mon dow   command 00 09 * * * cd PATH/packtpub-crawler && /usr/bin/python PATH/packtpub-crawler/script/spider.py --config PATH/packtpub-crawler/config/prod.cfg --claimOnly --notify join >> /tmp/packtpub.log 2>&1
There seem to be issues with relative paths in python and cron.
Also, please pipe the output to a file so we can see what's happening in the script.

I think there are some errors, the script doesn't work anymore now
[-] <type 'exceptions.AttributeError'> 'NoneType' object has no attribute 'select' | spider.py@90
Traceback (most recent call last):
  File "script/spider.py", line 90, in main
    run(packpub, args, config)
  File "script/spider.py", line 19, in run
    packpub.run()
  File "XXX/packtpub-crawler/script/packtpub.py", line 115, in run
    self.__POST_login()
  File "XXX/packtpub-crawler/script/packtpub.py", line 75, in __POST_login
    title = div_target.select('div.dotd-title > h2')[0].text.strip()
AttributeError: 'NoneType' object has no attribute 'select'

The cron with this work anyway
*/2 * * * * cd XXX/packtpub-crawler && /usr/bin/python script/spider.py --config config/prod.cfg >> /tmp/packtpub.log 2>&1

I opened an issue about this today. There simply is no free book today but
some subscription offer instead. Hope this happens rarely but we should add
a better error message
niqdev<EMAIL_ADDRESS>schrieb am Do., 15. Dez. 2016, 21:35:

I think there are some errors, the script doesn't work anymore now
[-] <type 'exceptions.AttributeError'> 'NoneType' object has no attribute 'select' | spider.py@90
Traceback (most recent call last):
File "script/spider.py", line 90, in main
run(packpub, args, config)
File "script/spider.py", line 19, in run
packpub.run()
File "XXX/packtpub-crawler/script/packtpub.py", line 115, in run
self.__POST_login()
File "XXX/packtpub-crawler/script/packtpub.py", line 75, in __POST_login
title = div_target.select('div.dotd-title > h2')[0].text.strip()
AttributeError: 'NoneType' object has no attribute 'select'
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Win7 - IP leak while connected

SoftEther version: 4.24, Buils 9651 and 5.01, 9665 (i.e. tested on both)
Component: Client
Operating system: Windows 7
Architecture: 64 bit (x86_x64)
Processor: Intel(R) Core(TM) i5-3320M CPU @ 2.60GHz
Description
after a successful connection to server everything just works and ipaddress.com does show the IP of the server, However after a while if we refresh the site ipaddress.com we see that our original IP is restored while the connection is still established.
Expected behavior:
It should keep routing the traffic to our companies SE-server until we press disconnect or at least until there is an error
Actual behavior:
We do lose servers IP address and our original IP gets visible while there is no single error with the connection
Steps to reproduce

Install SoftEther-Client, run, connect to any SE-Server (ensure it works), disconnect
Run ipconfig /release and ipconfig /renew commands to refresh all Network-Adapters
Open ipaddress.com in Chrome (to make at least one use from real-adapter)
Connect to any SE-Server
Refresh the site ipaddress.com (to make at least one use from vpn-adapter, ensure it works)
First disconnect from SE-Server
Then Hibernate the system (without even closing the browser)
Power-on again
Refresh the site ipaddress.com (to again use the real-adapter at least once)
Connect to any SE-Server again (the IP should be changed in this point)
Start any download in your Internet-Download manager
(just to increase bandwidth usage, mine is limited by 512 Kilo-Bit)
Keep refreshing the site ipaddress.com about 7 times (wait each time until fully loaded)
After some point we notice that the server IP is lost and the original is visible again

If we Disconnect and repeat above steps only the number of times we need to refresh does change
Update:
After running the commands ipconfig /release and ipconfig /renew it did become really hard to reproduce this issue;
and it is really stable, only after long time playing around with connect and disconnect it did happen again (without any hibernate).

below is the route print command result (where <IP_ADDRESS> and metrics 2 and 257 belong to VPN Client Adapter):
===========================================================================
Interface List
 35...00 ac 57 34 84 38 ......VPN Client Adapter - VPN
 42...84 3a 4b 40 e8 6d ......Microsoft Virtual WiFi Miniport Adapter #25
 16...00 21 cc d8 fe 4a ......Intel(R) 82579LM Gigabit Network Connection
 14...f4 b7 e2 f6 db ac ......Bluetooth Device (Personal Area Network)
 11...84 3a 4b 40 e8 6c ......Intel(R) Centrino(R) Advanced-N 6205
  1...........................Software Loopback Interface 1
 68...00 00 00 00 00 00 00 e0 Microsoft ISATAP Adapter
 73...00 00 00 00 00 00 00 e0 Microsoft ISATAP Adapter #2
 43...00 00 00 00 00 00 00 e0 Microsoft ISATAP Adapter #3
 37...00 00 00 00 00 00 00 e0 Microsoft ISATAP Adapter #4
 45...00 00 00 00 00 00 00 e0 Microsoft ISATAP Adapter #6
 64...00 00 00 00 00 00 00 e0 Microsoft ISATAP Adapter #7
===========================================================================

IPv4 Route Table
===========================================================================
Active Routes:
Network Destination        Netmask          Gateway       Interface  Metric
          <IP_ADDRESS>          <IP_ADDRESS>   <IP_ADDRESS>    <IP_ADDRESS>     25
          <IP_ADDRESS>          <IP_ADDRESS>     <IP_ADDRESS>    <IP_ADDRESS>      2
        <IP_ADDRESS>        <IP_ADDRESS>         On-link         <IP_ADDRESS>    306
        <IP_ADDRESS>  <IP_ADDRESS>         On-link         <IP_ADDRESS>    306
  <IP_ADDRESS>  <IP_ADDRESS>         On-link         <IP_ADDRESS>    306
     <IP_ADDRESS>    <IP_ADDRESS>         On-link     <IP_ADDRESS>    281
    <IP_ADDRESS>  <IP_ADDRESS>         On-link     <IP_ADDRESS>    281
   <IP_ADDRESS>  <IP_ADDRESS>         On-link     <IP_ADDRESS>    281
     <IP_ADDRESS>    <IP_ADDRESS>         On-link     <IP_ADDRESS>    257
    <IP_ADDRESS>  <IP_ADDRESS>         On-link     <IP_ADDRESS>    257
   <IP_ADDRESS>  <IP_ADDRESS>         On-link     <IP_ADDRESS>    257
        <IP_ADDRESS>        <IP_ADDRESS>         On-link         <IP_ADDRESS>    306
        <IP_ADDRESS>        <IP_ADDRESS>         On-link     <IP_ADDRESS>    281
        <IP_ADDRESS>        <IP_ADDRESS>         On-link     <IP_ADDRESS>    257
  <IP_ADDRESS>  <IP_ADDRESS>         On-link         <IP_ADDRESS>    306
  <IP_ADDRESS>  <IP_ADDRESS>         On-link     <IP_ADDRESS>    281
  <IP_ADDRESS>  <IP_ADDRESS>         On-link     <IP_ADDRESS>    257
===========================================================================
Persistent Routes:
  None

IPv6 Route Table
===========================================================================
Active Routes:
 If Metric Network Destination      Gateway
  1    306 ::1/128                  On-link
 11    281 fe80::/64                On-link
 35    276 fe80::/64                On-link
 11    281 fe80::8438:32e4:4257:a00a/128
                                    On-link
 35    276 fe80::c52b:1bc6:9a60:156b/128
                                    On-link
  1    306 ff00::/8                 On-link
 11    281 ff00::/8                 On-link
 35    276 ff00::/8                 On-link
===========================================================================
Persistent Routes:
  None

Could you please attack the "Advanced Settings" dialog box of your connection settings as the following?

We did ask the server provider for the screenshot, but I do not think it is related to the server;
since WireShark does not show any traffic being sent to the VPN Adapter once the issue happens.
we are sure this is related to the client or adapter

After setting No Adjustments of Routing Table to off was never again able to reproduce this issue (no wonder since SoftEther-Client now does ensure there is only one <IP_ADDRESS> in route table)
so will close this issue, but feel free to open this issue if No Adjustments of Routing Table is meant to be on by default (when SoftEther-Client is installed the first time)


Model load_from_checkpoint

Describe the bug
When loading a model directly from a checkpoint I get an error "OSError: Checkpoint does not contain hyperparameters. Are your model hyperparameters storedin self.hparams?"
But my model clearly has the hparams.
To Reproduce
Just create a model save a checkpoint and try to load it like explained in the documentation:
pretrained_model = MyLightningModule.load_from_checkpoint(
    checkpoint_path='/path/to/pytorch_checkpoint.ckpt'
)

Possible reason
I found that code in the trainer_io.py class line 301:
 try:
     torch.save(checkpoint, filepath)
except AttributeError:
     if 'hparams' in checkpoint:
     del checkpoint['hparams']
     torch.save(checkpoint, filepath)

Obviously if the code to save the checkpoint deletes de hparams the load checkpoint function will not find that...
Expected behavior
A more concise way to easily load a checkpoint without the need for the load_from_metrics function.

IIRC, that was a hack to workaround an edge case where the hparams weren't pickleable. Seems like the original ticket #433 is still open. @williamFalcon do we still need this hack?

Maybe the problem is about saving an object with a lamba function. I see this line in the issue log:
File "/private/home/falc/.local/lib/python3.7/site-packages/torch/serialization.py", line 224, in save
return _with_file_like(f, "wb", lambda f: _save(obj, f, pickle_module, pickle_protocol))

Pickle doesn't allow lambda functions to be saved but if it's this the reason, it's an easy fix I believe.
https://stackoverflow.com/questions/25348532/can-python-pickle-lambda-functions

I'm also having the same issue but I'm not using any lambda

in general lambda function is not serializable, so all these items should be removed before saving
@wakandan @ricardorei @neggert interested in sending PR?

I've encountered the same problem. Looks like the culprit is this line: https://github.com/williamFalcon/pytorch-lightning/blob/6666ca5af39aa2d3e5a483da3d7f6bb76514cc9f/pytorch_lightning/trainer/trainer_io.py#L321
After a bit of debugging I've figured out that the return of vars actually contains all of the bound methods of hparams! This seems to produce a pickling error. In my case it goes like this:
AttributeError: Can't pickle local object 'ArgumentParser.__init__.<locals>.identity'

This exception in its turn gets handled in https://github.com/williamFalcon/pytorch-lightning/blob/6666ca5af39aa2d3e5a483da3d7f6bb76514cc9f/pytorch_lightning/trainer/trainer_io.py#L264
by removing the hparams altogether.
Do we need this vars call at all? The TTNamespace that is normally used here in perfectly picklable on its own.

Ahh, good catch. So this works with an argparse.Namespace, but will fail with a TTNamespace? Want to send a PR that changes it to just pickle the Namespace directly and removes the hacky exception handling?

I just encountered the same issue - does this mean I can't load the models I trained in the past couple of days or is there some workaround until this is fixed?

I faced the same issue, thanks @expectopatronum for the workaround, it helps me a lot.

Here's a solution that doesn't require modifying your model (from #599).
model = MyModel(whatever, args, you, want)
checkpoint = torch.load(checkpoint_path, map_location=lambda storage, loc: storage)
model.load_state_dict(checkpoint['state_dict'])

Hi guys.. it seems that in my case the load_from_checkpoint function didn't load the params for me..
I had to use the code posted above by @neggert instead. ( manually load_state_dict)

solved in 0.7.1
if not, we can reopen

@williamFalcon
Based on the documentation I found  (this seemed most relevant)  I'm not totally sure best practices for how saving / loading is supposed to work:
I initialized a trainer as follows (disabled tensorboard because it was erring due to TF dep):
trainer = pl.Trainer(gpus=1, val_check_interval=0.25, use_amp=True, logger=False)

Then observed that the models were saved in ./checkpoints/ by default and thus assumed when I restarted training for same dir it would load the weights. But that was not the case (it seemed), instead I got this message:
/opt/conda/lib/python3.7/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:82: UserWarning: Checkpoint directory ~/answerbot/accuracy/checkpoints exists and is not empty with save_top_k != 0.All files in this directory will be deleted when a checkpoint is saved!

What is best practice for loading/ saving model with no logger? is this possible? Thank you in advance.

@pertschuk As i remember that auto loading is disabled in latest master, can you check your lightning version?

@Ir1d 0.7.1

@pertschuk I believe that auto restoring is removed, and you should load the weights on your own. The doc you linked is not updated yet.

@Ir1d Is there a callback or function to override to integrate weight loading / saving with PL?

@pertschuk sorry, I dont understand transformer model. You see, PL checkpoints is a wrap of a lot of things.YOu can get this by calling dict.keys(). And you'll find that model.load_state_dict(dict['state_dict']) is exactly the weight loading for pure pytorch. Hope this helps. Also, the above script by @neggert works perfectly for me .
`

@Ir1d Is there a callback or function to override to integrate weight loading / saving with PL checkpointing?
For example I'm training a huggingface/transformers model and want to save checkpoints in that format.

I also have been using lightning with pytorch transformers. I save checkpoints normally without changing anything in lightning.
If for some reason I need to resume training from a given checkpoint I just use the resume_from_checkpoing Trainer attribute.
If I just want to load weights from a pretrained model I use the load_weightsflag and call the function load_weights_from_checkpoint that is implemented in my "base" model.
parser = HyperOptArgumentParser(strategy="random_search",  add_help=False)
parser.add_argument(
        "--resume_from_checkpoint",
        default=None,
        type=str,
        help=(
            "To resume training from a specific checkpoint pass in the path here."
            "(e.g. 'some/path/to/my_checkpoint.ckpt')"
        ),
)
parser.add_argument(
        "--load_weights",
        default=None,
        type=str,
        help=(
            "Loads the model weights from a given checkpoint while resume_from_checkpoint "
            "resumes the entire training session (model/optimizer/scheduler etc..). "
            "If architectures are different this will load only the common module parts."
        ),
)

.....

trainer = Trainer(
        logger=setup_testube_logger(),
        checkpoint_callback=True,
        early_stop_callback=early_stop_callback,
        default_save_path="experiments/",
        gradient_clip_val=hparams.gradient_clip_val,
        gpus=hparams.gpus,
        show_progress_bar=False,
        overfit_pct=hparams.overfit_pct,
        check_val_every_n_epoch=hparams.check_val_every_n_epoch,
        fast_dev_run=False,
        accumulate_grad_batches=hparams.accumulate_grad_batches,
        max_epochs=hparams.max_epochs,
        min_epochs=hparams.min_epochs,
        train_percent_check=hparams.train_percent_check,
        val_percent_check=hparams.val_percent_check,
        val_check_interval=hparams.val_check_interval,
        log_save_interval=hparams.log_save_interval,
        row_log_interval=hparams.row_log_interval,
        distributed_backend=hparams.distributed_backend,
        precision=hparams.precision,
        weights_summary=hparams.weights_summary,
        resume_from_checkpoint=hparams.resume_from_checkpoint,
        profiler=hparams.profiler,
        log_gpu_memory="all",
    )

model = build_model(hparams)
if hparams.load_weights:
    model.load_weights_from_checkpoint(hparams.load_weights)

log.info(f"{model.__class__.__name__} train starting:")
trainer.fit(model)

My load_weights_from_checkpoint function:
def load_weights_from_checkpoint(self, checkpoint: str) -> None:
        """ Function that loads the weights from a given checkpoint file.
        Note:
            If the checkpoint model architecture is different then `self`, only
            the common parts will be loaded.

        :param checkpoint: Path to the checkpoint containing the weights to be loaded.
        """
        log.info(f"loading model weights from {checkpoint}.")
        checkpoint = torch.load(checkpoint, map_location=lambda storage, loc: storage,)
        pretrained_dict = checkpoint["state_dict"]
        model_dict = self.state_dict()

        # 1. filter out unnecessary keys
        pretrained_dict = {k: v for k, v in pretrained_dict.items() if k in model_dict}
        # 2. overwrite entries in the existing state dict
        model_dict.update(pretrained_dict)
        # 3. load the new state dict
        self.load_state_dict(pretrained_dict)

Does this solve your problem of loading pre-trained weights and resuming training sessions?

PS: The initial purpose of this issue was solved some versions ago and it's now working.

@ricardorei yes it does, thank you

Okay sorry to keep posting here but have run into VERY confusing issue and would appreciate any ideas for guidance. I am trying to export the models to save in huggingface/transformers format for reuse and the saved model appears to have identical state_dict to the model wrapped in a Pytorch Lightning module, but the results of passing the same inputs through are not the same?
import os
os.makedirs('./test-1', exist_ok=True)
# model is PytorchLightning Module and model.model = Transformers model
model.model.save_pretrained('./test-1')
loaded_model = AlbertForSequenceClassification.from_pretrained('./test-1')
loaded_model.cuda()

for k, v in loaded_model.state_dict().items():
    assert torch.all(model.model.state_dict()[k].eq(v)) # this assert works

correct = 0
total = 0

def call_model(inputs, model):
    return model(inputs['input_ids'].cuda(),
                 token_type_ids=inputs['token_type_ids'].cuda(),
                 attention_mask=inputs['attention_mask'].cuda())[0]

for ex in get_data():
    label = 0 if ex['is_impossible'] else 1
    inputs = tokenizer.encode_plus(ex['question'],
                                   ex['context'],
                                   add_special_tokens=True,
                                   max_length=256,
                                   return_tensors='pt')

    lightning_logits = call_model(inputs, model.model)
    transformers_logits = call_model(inputs, loaded_model)

    assert torch.all(lightning_logits.eq(transformers_logits)) # this assert fails ???

@pertschuk you should check how big is the difference. I noticed some small differences when using big transformer models. I actually have an issue in lightning regarding the subject and in Fairseq.
https://github.com/pytorch/fairseq/issues/1605
https://github.com/PyTorchLightning/pytorch-lightning/issues/669
If the difference is really small this should not affect your results and is basically a precision issue.

@ricardorei unfortunately it was a very large error but I fixed by disabling mixed precision training if anyone else finds this thread.

For those that have the issue of not being able to load the model using the load_from_checkpoint method, I tried using the workaround here. After playing around, I noticed that there is a problem with the way the state_dict is being loaded. After using the code snippet from a post on PyTorch's forum, I managed to solve the problem.
To be more specific, the weights were being loaded into the model but there was no error message.
@williamFalcon Please take note of this.

For those that have the issue of not being able to load the model using the load_from_checkpoint method, I tried using the workaround here. After playing around, I noticed that there is a problem with the way the state_dict is being loaded. After using the code snippet from a post on PyTorch's forum, I managed to solve the problem.
To be more specific, the weights were being loaded into the model but there was no error message.
@williamFalcon Please take note of this.

I checked: The problem arises when we are using a self.model value to define our forward pass and also our parameters.

I encountered the same issue when passing self.model

For those that have the issue of not being able to load the model using the load_from_checkpoint method, I tried using the workaround here. After playing around, I noticed that there is a problem with the way the state_dict is being loaded. After using the code snippet from a post on PyTorch's forum, I managed to solve the problem.
To be more specific, the weights were being loaded into the model but there was no error message.
@williamFalcon Please take note of this.

I checked: The problem arises when we are using a self.model value to define our forward pass and also our parameters.


Allow actions to run for first time contributors

Currently we have to manually allow running actions from new contributors and wait for it to finish, which is a bit time consuming.
I propose to allow workflow runs for first time contributors whenever a PR is opened, as per this setting:

Done :)


Q / Periodically, showed the first frame during the playing animation.

Hi, all.
I want to loading Animation. so I found the issues&example code.
but It is have a little problem.
Periodically, showed the first frame during the playing animation.
Sorry for my English is not good.
Could you check my code please ?
My project
I want to show this Image

From trying your app I can see that the frames are not animated in the right sequence. The files from the zip archive are not processed in the expected order. Without code changes renaming Frame0, Frame1, .., Frame9 to Frame00, Frame01, .., Frame09 should do the trick. Attaching the updated archive:
loading.zip.

@liaxim
Thank you for your comment.
I solved the issues. :-)


[Feature Request] Provide rollback feature

some time real-time application scenario after release if we need to rollback to previous running instance e.g. "app-name-old". currently we need to all this steps manually. it will be great helpful to provide rollback from "app-name" to makr as "app-name-failed" and "app-name-old" to "app-name".

Rollback would be a great feature.


Fix JIT test failures on ROCm

Close #4997. Detail to follow.

Jenkins, test this please

Jenkins CI test (for commit b34b1ae86aaecd6907faedfa412123ac568c5284, target branch master) failed with status FAILURE.

I think that you are including a header with unicode, and py 3.6 has an issue when plain reading these files.
we have to open them using open(file, encoding='utf-8'

I have no idea what's going on.  How can that be? Note that in the one stack up (in cupy/cublas.py) the local variables look totally fine...

@emcastillo btw since all failing tests are from tests/cupy_tests/test_cublas.py, which is the first test file being run, I built a py36 env locally to test it, but all tests passed...

Let me run the CI again and see if it's reproducible
Jenkins, test this please

Still reproducible... https://jenkins.preferred.jp/job/chainer/job/cupy_pr/3484/TEST=cupy-py36,label=mn1-p100/

@emcastillo You're right. It's a unicode issue, fixed in 717ccea. I forgot to check headers included in the previous PRs, and probably my env was too dirty to reproduce.
Jenkins, test this please

Jenkins CI test (for commit 717cceaba4d62a5549adb090f9c344c8abe3d4c6, target branch master) succeeded!

Sorry to reply late.
Instead of changing the header file, can we change the code that reads the headers and set the encoding on it?

Instead of changing the header file, can we change the code that reads the headers and set the encoding on it?

@emcastillo If the concern is to preserve the original header, note that that header has already been altered when it's bundled in #4890, so if you compare it with, say, /usr/local/cuda-11.2/include/thrust/tuple.h the diff is not empty.

Jenkins, test this please

Jenkins CI test (for commit 717cceaba4d62a5549adb090f9c344c8abe3d4c6, target branch master) succeeded!

Jenkins, test this please

Jenkins CI test (for commit 717cceaba4d62a5549adb090f9c344c8abe3d4c6, target branch master) succeeded!


[Bug]: Python 3.12 not supported for many integrations and packs

Bug Description
I noticed there was an issue with Python 3.12 in the core regarding pyproject.toml with [tool.poetry.dependencies] requiring python = ">=3.8.1,<3.12". This was fixed here but it hasn't cascaded down to the other integrations or packs.
Is this intentional? Should we use Python <3.12 for the integrations and packs?
If it's not intentional, and [tool.poetry.dependencies] should have python = ">=3.8.1,<4.0" then I am happy to go through all of the pyproject.toml files, update accordingly, and submit a PR.
Cheers
Version
0.10.9
Steps to Reproduce
Create a python environment with Python 3.12.1 and then try pip install llama-index-vector-stores-qdrant and you will see the following error:
ERROR: Ignored the following versions that require a different python version: 0.0.1 Requires-Python >=3.8.1,<3.12; 0.1.0 Requires-Python >=3.8.1,<3.12; 0.1.1 Requires-Python >=3.8.1,<3.12; 0.1.2 Requires-Python >=3.8.1,<3.12
ERROR: Could not find a version that satisfies the requirement llama-index-vector-stores-qdrant (from versions: none)
ERROR: No matching distribution found for llama-index-vector-stores-qdrant

Relevant Logs/Tracbacks
No response

We know 😢 It takes time to update and publish every package (assuming every package+their dependencies supports 3.12)
Will probably tackle this sometime in the next few days

I'm happy to help with updating the packages if needed!


Using Stream to do asynchrone and parallele job

Is there a way to use stream?
I'm using jimp in a node-webkit app and each time i resize and crop a file the app freeze during the job. I wrapped everything in a promise but nothing seem to change, it's still synchrone and freeze my app.

Node is single threaded environment. This means that while your application is doing one thing (e.g. resizing an image) it cannot do other things (e.g. responding to mouse clicks).
This is a "by design" characteristic of Node and has nothing to do with Jimp or any other module.
However, Node is an asynchronous environment. This means that it can call other processes (e.g. run an external script that resizes an image) and do other things while it waits for the response.
The easiest way to do this is to write a small command-line script that resizes images using Jimp (it could take an arguments, such as the desired size and a path to a file). Call this script as a child process from your main app and it won't block your application.
See documentation on child processed here: https://nodejs.org/api/child_process.html

I was looking this direction but not sure about it.
Thanks for your reply.
Le 30 juin 2015 21:51, "Oliver Moran"<EMAIL_ADDRESS>a écrit :

Node is single threaded environment. This means that while your
application is doing one thing (e.g. resizing an image) it cannot do other
things (e.g. responding to mouse clicks).
This is a "by design" characteristic of Node and has nothing to do with
Jimp or any other module.
However, Node is an asynchronous environment. This means that it can call
other processes (e.g. run an external script that resizes an image) and do
other things while it waits for the response.
The easiest way to do this is to write a small command-line script that
resizes images using Jimp (it could take an arguments, such as the desired
size and a path to a file). Call this script as a child process from your
main app and it won't block your application.
See documentation on child processed here:
https://nodejs.org/api/child_process.html
—
Reply to this email directly or view it on GitHub
https://github.com/oliver-moran/jimp/issues/24#issuecomment-117319110.


[Feature request] Many-to-many ANI comparisons

I want to try replacing FastANI with Skani in my workflow.  However, I need easy access to the many vs. many utility.  For example, in FastANI I would do the following: fastANI --ql [QUERY_LIST] --rl [REFERENCE_LIST] -o [OUTPUT_FILE]
Can you add this functionality to Skani?

Hi @jolespin,
skani has this capability: try skani dist --ql QUERY_LIST --rl REF_LIST -o OUTPUT.
Also, you can try skani dist -q gn1.fa gn2.fa -r gn3.fa gn4.fa too.
Let me know if I've misunderstood something,
Jim

No, that's definitely what I was trying to do. Amazing!
A few follow ups:

Do you have an example of the output in what it looks like?
How is the memory usage compared to FastANI (apologies if you discussed this in the paper)

It's about 10x less than fastani, although it depends on the exact parameters and settings. For genome level ani calculations, should be interchangeable with fastani.

The preset only determines -c and overrides it.

Got it implemented.  Thanks!


Warning against updating to Android 8.0 Oreo

http://ankulua.boards.net/post/11234/thread
In android 8.0 turning usb debugging off will turn off the daemon, rending AnkuLua completely unable to work on FGO. Not something that can be fixed here, but thought I'd drop a warning and hopefully save others the confusion.

Added text in the beginning of readme.md.


Address typo in command identifier for installMissingDependencies

The command is currently registered with the identifier workbench.extensions.installMissingDepenencies.
Changes introduced in this PR

Updates the command identifier installMissingDepenencies to installMissingDependencies

This PR fixes https://github.com/microsoft/vscode/issues/84055

Thanks @sandy081


adds basic ragas eval

This PR introduces Rubric-based evaluation through Ragas using the default with-reference rubric that they provide.
The current evaluation supports the two following modes:

Being given a dataset contains records which hold user_input (question), reference (golden answer), and response (model answer)
Being given a dataset with the user_input and reference, and additionally a ModelConfiguration of a model which will be used to generate the response for each question. This can be any model running on an OpenAI-compatible endpoint

Signed-off-by: Oleg S<EMAIL_ADDRESS>

@RobotSail let me know once you are done with testing the code. Other than that LGTM.

@abhi1092 I've updated the code to have unit tests, please let me know if there was anything I missed.


Publish 2.x as webpack@next

Would help a lot for installing the latest beta (e.g. npm install webpack@next) and package.json dependencies (e.g. { "webpack": "webpack@next" ))
The command to do so is:
npm publish --tag next, this command should be ran whenever there is a new release

We already publish it with a beta tag (npm publish --tag beta). You can do npm install<EMAIL_ADDRESS>and it will follow new beta versions.

👍 sorry, didn't see that on npm


Allow x-vss-e2eid response header to be logged in AzurePipelinesCredential for diagnostics.

For any responses coming from the OIDC endpoint as part of getting the token from AzurePipelinesCredential, we allow logging the x-vss-e2eid response header so that the service team can use that info for diagnostics and troubleshooting.
Fixes https://github.com/Azure/azure-sdk-for-cpp/issues/5992
The value of the activityid and x-vss-e2eid are identical, so it doesn't seem necessary to log both. Also, even though we aren't enabling the header to be logged globally, it is worth noting that activityid seems to be used by other management plan services, unlike x-vss-e2eid which seems to only be used by Azure Pipelines and the azure devops cli/extension.
@manolerazvan, @geekzter, @kboom - please take a look and confirm this header is useful (and safe) to log along with any other headers that you'd find useful for the SDK customers to provide when filing issues.

/azp run cpp - identity

/azp run cpp - identity

/azp run cpp - identity


Add Support for Gitlab Diff endpoints

Add support for these endpoints:

https://docs.gitlab.com/ee/api/merge_requests.html#get-mr-diff-versions
https://docs.gitlab.com/ee/api/merge_requests.html#get-a-single-mr-diff-version

Thank you.


Refactoring account collector

Issue #, if available:
Description of changes:
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

I do not see a need for deployment in payer if none of chosen modules require that.


FCOS structure

@yinghdb Which FCOS structure are you using ?

What is the meaning of 'FCOS structure' ?

@yinghdb I saw that in FCOS implementation, they used deformable convolutions in some config files, so I have a question that in your EmbedMask, did you train with deformable convolutions or not ?

I have not used deformable convolutions. In fact, for the configuration to the detection part of EmbedMask,  I use the settings from the 'fcos_imprv_R_50_FPN_1x.yaml' as default.


Reduce the number of Spark jobs.

Addressing https://github.com/databricks/koalas/pull/1159#discussion_r364100375.

cc @HyukjinKwon @itholic

Codecov Report

Merging #1174 into master will decrease coverage by 1.6%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master    #1174      +/-   ##
==========================================
- Coverage   95.28%   93.68%   -1.61%
==========================================
  Files          35       35
  Lines        7084     7089       +5
==========================================
- Hits         6750     6641     -109
- Misses        334      448     +114

Impacted Files
Coverage Δ

databricks/koalas/base.py
96.39% <100%> (+0.04%)
:arrow_up:

databricks/koalas/indexing.py
96.01% <100%> (+0.02%)
:arrow_up:

databricks/koalas/usage_logging/__init__.py
24.32% <0%> (-72.98%)
:arrow_down:

databricks/koalas/usage_logging/usage_logger.py
50% <0%> (-50%)
:arrow_down:

databricks/koalas/__init__.py
76.59% <0%> (-8.52%)
:arrow_down:

databricks/conftest.py
92% <0%> (-6%)
:arrow_down:

databricks/koalas/frame.py
96.44% <0%> (-0.57%)
:arrow_down:

databricks/koalas/generic.py
95.85% <0%> (-0.42%)
:arrow_down:

databricks/koalas/indexes.py
96.42% <0%> (-0.33%)
:arrow_down:

databricks/koalas/plot.py
94.04% <0%> (-0.24%)
:arrow_down:

... and 1 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update c8c2214...b4da219. Read the comment docs.


Images are missing for docs/home/12c-ocm/data-and-performance-management/create-sql-plan-baselines.html

All image links are broken in docs/home/12c-ocm/data-and-performance-management/create-sql-plan-baselines.html. Images are available on New Google Sites.

The resolution of issue #74 fixed this issue.


Use now available link name "signal" instead of "bsd_signal"

On android, the bsd_signal is gone, the signal is available.
While this is the most obvious solution, I am not sure of a few things:

How are we going to keep compatibility with older NDKs where signal does not exist;
Was something dependent on this being different on android and thus would break (for example, the rust compiler uses this function, so it may break somewhere).

Fixes #236.

Thanks for the pull request, and welcome! The Rust team is excited to review your changes, and you should hear from @alexcrichton (or someone else) soon.
If any changes to this PR are deemed necessary, please add them as extra commits. This ensures that the reviewer can see what has changed since they last reviewed the code. Due to the way GitHub handles out-of-date commits, this should also make it reasonably obvious what issues have or haven't been addressed. Large or tricky changes may require several passes of review and changes.
Please see the contribution instructions for more information.

Thanks for the PR! Let's continue the discussion on https://github.com/rust-lang/libc/issues/236 for now until we reach a conclusion, but this definitely seems like one plausible course of action we could take!

cc https://github.com/rust-lang/rust/pull/32415 (I think we'll also want to accept this one though)

@alexcrichton Maybe I should add feature bsd_signal so libc users can toggle old link symbol if needed?

Hm for now let's hold off on new features. I suspect that those which want to support these old versions of Android are pretty small, in which case this can be done on a case-by-case basis (like the standard library) if needed.

Ok now that https://github.com/rust-lang/rust/pull/32415 has landed I think that we're ready to land this as well. Could you also remove this exception so we can check this looking into the future?

@alexcrichton done :8ball:

@bors: r+ 0b7ccdd11917810fb9d514a55ab20ea8cb44eb8e

:hourglass: Testing commit 0b7ccdd with merge 60f90cf...

:sunny: Test successful - status-appveyor, travis


hello

What you were trying to do
What actually happened
How to reproduce

Step 1
Step 2
Step 3

Log details and game version
Computer details

Hello there.
Issues should only be for either bug reporting, feature suggestion/discussion and a few other cases.
If you want to chat to us then feel free to use our forum or discord. Links to both can be found on our website terasology.org


Split compilation of large files automatically

As an alternative to https://github.com/ginkgo-project/ginkgo/pull/1375, here I automatically generate files that instantiate a subset of the templates in a source file each. Due to the format of the instantiation source file, it can be included both in its original form and split into different files.

To put some number on these changes: time ninja ginkgo gives the following output (256 threads)

rocm45 before
real    2m44.885s
user    34m59.771s
sys     10m28.850s

rocm45 after
real    1m48.505s
user    18m8.664s
sys     2m23.337s

rocm502 before
real    3m55.766s
user    19m59.029s
sys     2m21.003s

rocm502 after
real    2m37.208s
user    49m14.886s
sys     11m57.626s

NVHPC23 before
real    4m24.576s
user    119m53.211s
sys     24m25.492s

NVHPC23 after
real    3m22.483s
user    8m36.878s
sys     2m18.913s

I added a switch to enable and disable the split: GINKGO_SPLIT_TEMPLATE_INSTANTIATIONS


Alternative/Fix for CXF handlers to inject request scoped object without CDI issue/Null issue

We are trying to call CXF SOAP client from REST endpoint and we are trying to set a value from SOAP response in REST HTTP response headers but we are unable to do it because we are unable to inject any request scoped object in CXF SOAP handlers due to CDI.
Kindly let us know if any alternative/fix is available.

@sreekar12 Injecting a request scoped bean in a SOAP handler seems to work fine for me.
Did you mark your SOAPHandler as @ApplicationScoped?

Yes @shumonsharif . Can you please share the example.

I don't have an example project handy - and I likely won't have the time to put one together this week.  I tested the CDI injection on one of my existing projects.
You're welcome to put together a simple reproducer and I can try to help with that.

@shumonsharif We are trying like below.
We are unable to inject HeaderImpl in SoapHandler class. it is giving object as null. Can you please help us on this.
Created 3 classes RequestScoped, RestService and SOAPHandler
**@RequestScoped
class HeaderImpl{
private String corrId;
// setter and getters
}
Rest service : class A{
@Inject
HeaderImpl impl;
@Path("/hi")
public Response m1(@RestHeader("correlationId") String correlationID){
impl.setCorrId(correlationID);
}
}
SoapHandler:
@ApplicationScoped
class A implements SOAPHandler  {
{
@Inject
HeaderImpl impl;
public boolean handleMessage(SOAPMessageContext context) {
System.out.println(impl.getCorrelId);
}
}**

@sreekar12 In case you need to put together a reproducer in the future, you can follow the steps below ... even though it only takes a few minutes, it helps a lot because making the time to be doing it on your behalf, can become challenging for us.

Go to https://code.quarkus.io/
Search for quarkus-cxf and select the checkbox
Download the generated project zip file
Add the classes that you pasted in your comment above into the project
Share the project as a reproducer that demonstrates the issue you are having

Having said all that, I tried to mimic your code in the attached code-with-quarkus.zip project; injecting the request scoped bean is working as expected.
If you still have an issue with this, and need further help, kindly take the time to help us help you by updating the attached project and demonstrating the issue you are having.  If it addresses your issue, let us know, hope this all is helpful.

Thanks @shumonsharif. It is working now


WASM - f32.convert_u/i32

Implement operator f32.convert_u/i32

This is mostly done in term of feature.
Please refer to #1967 for known bugs


Input inactive

Whenever I open a converted NES rom, it will not respond to the control input. I am using bsnes to emulate the converted rom.

As far as i do know bsnes and Zsnes cannot  yet run patched nes games because or it lacks 8MB or sram support or both,BUT i can assure you that snes9x does work with patched nes games,so i will highly suggest you to try snes9x😁

What games have you tested on bsnes?

What games have you tested on bsnes?

Duck Hunt, Donkey Kong, and Super Mario Bros.

Donkey Kong and Super Mario Bros work for sure. Duck Hunt won't work with Super Scope.
Are inputs working for regular SNES games on your bsnes?
Do you have the latest version of bsnes?

For some reason, they work now. I'm not sure what was causing the controls to not respond before. Apologies


[Integration][SonarQube] Added _target='blank' attribute to spec links

Update the description content and the attribute target="_blank" to anchor tags in descriptions to open a new browser tab instead of the current browser.

[ ] Documentation (added/updated documentation)

Nit change

@phalbert can you please elaborate here


List dependencies and instructions for installing them

I notice on the CLI page for example, the npm and git commands are entered, which assumes that the user has these installed already. It would be worth noting at the beginning of the documentation what dependencies are required to go through the documentation (including the minimum version required) and how to install the dependency.

Perhaps related to #77, and maybe we could generalize it to be a starting help page for all OSes?

That'd be good too, since the instructions may vary for different OSes.

Maybe for git we can mention you'll need it in environment setup and then link this section in the aragonCLI introduction

More installation prerequisites were added to https://hack.aragon.org/docs/cli-intro#installation-pre-requisites.


put all test files to single folder and delete it on exit

Clean files created during tests. Close https://github.com/ergoplatform/ergo/issues/707

Coverage remained the same at 47.185% when pulling 4f29198b39592ff0023b9f18c5acd54219c4a2eb on test-files into e699882d3e4a7c388e0ed753f983fb710e2d8ea3 on master.


⚠ T:Riza Api has degraded performance

In 8b1d4c2, T:Riza Api (https://api.triza.dev) experienced degraded performance:

HTTP code: 200
Response time: 20903 ms

Resolved: T:Riza Api performance has improved in e577e07.


Create "controlled page" layout

Description
Sometimes (#15) it would be nice to have a static page have the same controls posts do (i.e. BibTex, Translate, Related, etc.).
Tasks

[x] Extract controls into their own file (under _includes)
[x] Create a controlled_page layout with these controls

Closed by 697aba1.


zooming camera applies twice (i.e. zoom value is quadratic) on tilemaps

Version

Phaser Version:
3.12.0
Operating system:
Windows 7
Browser:
Firefox and Chrome

Description
Zooming camera applies twice on tilemaps. I.e. zoom(n) will work as zoom(n*n) on tilemaps
Example Test Code
scene.cameras.main.setZoom(2)

Want to back this issue? Post a bounty on it! We accept bounties via Bountysource.

If you can provide a code example demonstrating this bug I can re-open it and investigate, but as is, there's not enough information and it doesn't manifest in a simple test.


Allow JS properties to contain special chars, using bracket notation

What
I added the ability for JS to handle special chars in identifiers. I noticed this specifically in keys for colors, but really this could happen anywhere. We may still want to restrict the names of things from the LS perspective, but this will allow a little more flexibility for props.

@mathieudutour brought up that swift offers something similar to JS's bracket notation that would fix the swift generated code in this example. I can back out the generated code changes in this PR if we're uncomfortable with having swift code like this until someone can change the swift compiler to do the same. Let me know what you think Devin

Since the Swift generation is normally working and usable, I don't think we should leave it in a broken state.
For the Swift case I think we should strip out any - in identifiers, rather than doing the backtick notation (or whatever) since it's not idiomatic for this kind of thing.

So yeah, I guess just take out that color for now and the rest of the PR is fine

Ok, test and generated code changes have been reverted


Cursor shaking in oh-my-zsh

Environment
Windows build number: [Microsoft Windows NT 10.0.19042.0]
Windows Terminal version (if applicable): 1.4.3243.0

Any other software?
MSYS2  oh-my-zsh  zsh-syntax-highlighting

Steps to reproduce
install and config msys2 in Terminal, install zsh and oh-my-zsh, install and enable  zsh-syntax-highlighting plugin. open MSYS2 tab in Terminal, input any letters.
Expected behavior

The cursor should be steadily alone with the inputted letters.
Actual behavior

In the first few letters of any lines,(I guess the plugin is trying to scan whether the command is valid), the cursor will change position to 3 letters front, then change back.
https://user-images.githubusercontent.com/45709656/103154549-f2f85f80-47d2-11eb-9e3e-69cddbcfdd1a.mp4
https://user-images.githubusercontent.com/45709656/103154551-f4c22300-47d2-11eb-80d4-0cb6f381f80e.mp4
close the plugin OR directly use MYSL2 will not reproduce.

What version of the MSYS2 runtime are you using?

/dup #6217
Sorry for the radio silence for so long. We're duplicating this with an earlier issue. This is a new issue.

This is not a duplicate of the #6217. This issue happen only when zsh-syntax-highlighting enabled. I'm still getting the issue despite of having the latest version Window Terminal.

The issue is still occurring in the latest version of Windows Terminal (1.21.2911.0). I agree that it only happens when zsh-syntax-highlighting is enabled. By the way, the cursor doesn't seem to shake in the VSCode terminal.


:effect/spawn

Blocking player movement
Needs AI for following player or moving towards nearest enemy
Check position valid for spawning - what if during action-time is blocked? (or make instant/block location while casting?)
effect/spawn is effect/target-position?

; spawning on player both without error ?! => not valid position checked
; also what if someone moves on the target posi ? find nearby valid cell ?
; BLOCKING PLAYER MOVEMENT ! (summons no-clip with player ?)
; check not blocked position // line of sight. (part of target-position make)
; limit max. spawns
; animation/sound
; proper icon (grayscaled ?)
; keep in player movement range priority ( follow player if too far, otherwise going for enemies)
; => so they follow you around
; not try-spawn, but check valid-params & then spawn !
; new UI -> show creature body & then place
; >> but what if it is blocked the area during action-time ?? <<


[Fix]: The images are not showing

Current Behavior

when I am heading to integrations tab in meshery I am unable to see the images on the box elements
Expected Behavior

I should be able to see the images on the box elements
Screenshots/Logs

you can see in the above one the white box elements do not have images
Environment

Host OS: Mac Linux Windows
Platform: Docker or Kubernetes
Meshery Server Version: stable-v
Meshery Client Version: stable-v

Contributor Guides and Handbook

🛠 Meshery Build & Release Strategy
📚 Instructions for contributing to documentation

Meshery documentation site and source

🎨 Wireframes and designs for Meshery UI in Figma (open invite)
🙋🏾🙋🏼 Questions: Discussion Forum and Community Slack

can you assign me this issue I would like to work on this

Thanks for reporting the @kanugurajesh  , assigning to you .

fixed by : https://github.com/meshery/meshery.io/pull/1640


Support sending relay mappings used at runtime over CAN

Piclib would surely need to be updated to support sending it all. New message types needed too.

Looking at the dataaheet it seems that long messages are not supported. Worst case just split the data into multiple messages.


Validation for cobbler and custom iso

Is your feature request related to a problem? Please describe.
Validation for Cobbler and Custom Iso.
Describe the solution you'd like
Validation scripts for Cobbler and Custom Iso.

The code was merged  for the PR raised '1286'.


False positive on Enabled()

Hello,
I am getting this:
zerologlinter: must be dispatched by Msg or Send method (zerologlint)
                                        if logger.Info().Enabled() {

I believe this is false positive, or am I missing something in here? Thanks.

Sure, this is useful when you want to do expensive code and avoid it when level is not set. Example is right in the project README:
https://github.com/rs/zerolog#setting-global-log-level
    if e := log.Debug(); e.Enabled() {
        // Compute log output only if enabled.
        value := "bar"
        e.Str("foo", value).Msg("some debug message")
    }

I think this should be fixed and I think I can work on this by the end of this year but right now not possible because of too many other things to work on.
So in the meantime, let me put help wanted tag so that someone could potentially work on this.

@lzap
I cannot reproduce this at least with this example below. Can you try the latest version? If it persists after trying the latest version, please give me the specific example.
package main

import (
	"github.com/rs/zerolog/log"
)

func main() {
	if e := log.Debug(); e.Enabled() {
		// Compute log output only if enabled.
		value := "bar"
		e.Str("foo", value).Msg("some debug message")
	}
}

Sure, if you re-enable the linter on one of our projects it will error out:
https://github.com/RHEnVision/provisioning-backend/blob/main/.golangci.yml#L25

Let me run it:
[lzap@nuc provisioning-backend]$ make fmt
/home/lzap/go/bin/go1.20.10 fmt ./...
/home/lzap/work/provisioning-backend/bin/gofumpt -l -w .
/home/lzap/work/provisioning-backend/bin/goimports -w .
GOROOT=/home/lzap/sdk/go1.20.10 PATH=/home/lzap/sdk/go1.20.10/bin:/home/lzap/.rbenv/shims:/home/lzap/.rbenv/bin:~/Mutt:/home/lzap/.local/bin:/home/lzap/bin:/home/lzap/bin/public:/home/lzap/.npm/bin:/home/lzap/go/bin:/usr/local/bin:/usr/bin:/usr/local/sbin:/usr/sbin:/home/lzap/.fzf/bin:~/work/foreman-bats GOCACHE=/home/lzap/.cache/go-build /home/lzap/work/provisioning-backend/bin/golangci-lint run --path-prefix /home/lzap/work/provisioning-backend
/home/lzap/work/provisioning-backend/internal/telemetry/zerolog_exporter.go:32:22: zerologlinter: must be dispatched by Msg or Send method (zerologlint)
                t := e.logger.Trace().
                                   ^
/home/lzap/work/provisioning-backend/cmd/pbackend/statuser.go:210:20: zerologlinter: must be dispatched by Msg or Send method (zerologlint)
                                        if logger.Info().Enabled() {
                                                      ^
/home/lzap/work/provisioning-backend/internal/kafka/kafka.go:293:18: zerologlinter: must be dispatched by Msg or Send method (zerologlint)
                if logger.Trace().Enabled() {
                               ^

Thank you for sharing. Confirmed the situation.
So minimum reproducible example is below.
func falsePositiveOnEnabled() {
	if log.Info().Enabled() {
		log.Info().Str("foo", "bar").Send()
	}
}

However, I am not sure if this can be fixed because if we permit the log.Info().Enabled(), then below won't be reported based on what I've considered now.
func main() {
	if e := log.Debug(); e.Enabled() {
		value := "bar"
		e.Str("foo", value) // <- this should be reported
	}
}

Also it might be a good idea to rewrite your code with this style because then you only have to create zerolog.Event once which leads to better performance. What do you think?
Additionally, found another false positive from the repository you provided. This definitely can be and should be fixed. Thanks.
https://github.com/ykadowak/zerologlint/issues/13

Thanks for the analysis, I am not going to spend time on this premature optimalization tho. All three cases are in the initialization code which is only called once. We are good, closing cheers!

I'm also hitting this when experimenting with zerologlint in a large private project.
Wouldn't a good solution be to not warn if the *zerolog.Event is assigned to a variable? So a statement like
e := log.Debug()

would never cause a linter warning.


Update rich-text-editor-control.md

Fixed formatting of JSON configuration provided and expanded example JSON to add property outside of "defaultSupportedProps".
Very minor change but makes a big difference to readability of the JSON examples provided.

@microsoft-github-policy-service agree company="Y365"