Features and suggestion

I usually just post something when an actual issue arises but, in this case, after using your software for some time and liking it very much, I feel confident that some suggestions could be appreciated.
First of all, even on a pc without a touch screen (with the help of some simple scripts) your software is great and very usable.
Let me say that I use pc with ubuntu or debian, chromebooks and windows devices.
When I use my chromebook, I actually don't need scrcpy, because my android apps are already there. I mainly use scrcpy on my lenovo thinkpad t430 (no touch) and the only missing feature is the chance of making phone calls, when at my desk, and using the laptop as a speaker.
So I googled ad bit and I was able to install Dell Mobile Connect, which can do all the things that scrcpy can do and lets me make phone call too... But there is a caveat, it works like a charm when both the pc and the phone are connected to a wifi spot  but, when I am sharing the phone's hotspot with my pc, such software looses the mirroring part! That's because it uses the wifi direct connection for mirroring and obviously, when the hotspot is on, the phone wifi direct is not available.
So, I keep on using  Dell Mobile Connect mainly for phone calls and scrcpy for the mirroring feature.
Well, I know, more or less, the limitations of adb but being able to make phone calls with the speaker of my pc would let me ditch Dell Mobile Phone in no time, because I appreciate how light your software is.
So I definitely wonder if you could add some bluetooth magic in order to route the call to the microphone and the speaker of the pc. May be something different from the jar that's being pushed to the phone, even one apk to install apart.
Thanks

hmmmm ... interesting feature ... good to have such an option ...

Can you please rename this issue as "Forward audio from PC to android"?
Call on PC requires 1. audio from PC to be forwarded to android and 2. audio from android to be forwarded to PC. 2 is being worked at #14 so let's make this issue to address 1.

Other use cases of this feature would be to use assistant apps. Google Assistant, Alexa etc.


feat(dropdown): added support for multi-level dropdown menus

fixes https://github.com/patternfly/patternfly-next/issues/2635

PatternFly-Next preview: https://patternfly-next-pr-2666.surge.sh

@mcarrano hmmm, I don't see anything different about the mockups. The shadow on the sub-menu is the same as the shadow on the main menu - the only thing that is different is its positioning.
If you'd like me to make a change so you can see what it looks like another way, let me know and I'll update the example in the PE.

Looks good to me, thanks @mcoker @mcarrano The shadow thing doesn't bother me too much, and maybe makes more sense since the expanded menu is now the "top" interest of the user as they've intently activated it.

Marking this on hold since we're going to revisit after sorting out the mobile design.


Prepare for Gradle plugin release 4.0.2

#286  👈
main

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Rustic compilation buffers are always killed ahead of a new compilation

Hi,
Not sure if this is intentional or not but in rustic-save-some-buffers you seem to kill the builtin *rustic-compilation* buffer among others.  Is this necessary?

Ah, nevermind, this is because I tried to combine all the different buffer names together and you explicitly kill the rustfmt buffer.


ng-sortable events

sometimes on the callback you want to know about data of the events let say remove css class you appended on setData option so it will be just excellent to send also the event to the callback

Create a example on jsbin.com


Action points after sprint closing

[ ] @KristellP write email to Anke about dialog overview
[ ] @Milonvv decide on real final date for virtual coach
[ ] @KristellP & @Milonvv talk to Anke, Eline, Veronica, Winnie making time content development how to approach it?
[ ] @KristellP & @Milonvv write a draft content development planning, @svenvanderburg will check it. (@svenvanderburg will resend a link to software development planning)
[ ] @KristellP run future self activity by Veronica & Winnie
[ ] @svenvanderburg will make sure to implement dialog 1 in the virtual coach

In software development planning should go:

[ ] When is a dialog done? When final dialog. I.e. definition of done
[ ] What are true must have dialogs?
[ ] Who does what and in which form?

Extra notes for planning: Make milestones (general issues that need to be solved; must-have dialogs etc.) and link issues. Plan an new sprint?

Here is the link to the software development planning document.


Rename contact_group to contact_groups

This commit renames the contact_group field in the contact schema to contact_groups and the type to identifiers to reflect the fact that there can be more than one contact group. The value of the field is an array of slugs.
Trello: https://trello.com/c/wD10DEXt/260-migrate-the-hmrc-contacts-page-to-a-finder

This seems to make sense to me.
👍

Note that we can rename this so easily because there's no data in the contact_group field currently. Otherwise we would've had to arrange a migration.


pip requirements.txt

Would you mind implementing a requirements.txt file for subradar, which lists all of the external pip libraries required?  You can mention how to use it in your README.md.  It looks like this is mainly mpmath and scipy.  numpy follows automatically from scipy.
This would help systematically track what version of scipy and mpmath you need, and also we will use it as part of the installation procedure for the svv code (by telling people to install the requirements for subradar) AND svv, since subradar is a submodule.  Then if you need to update the requirements for subradar, this can happen systematically.
https://pip.pypa.io/en/stable/user_guide/#requirements-files
You probably want to change the output of pip freeze to be >= rather than ==

I can work on that, yes. Another option would be to make a distribution package that can be installed through pip (https://packaging.python.org/tutorials/packaging-projects/). It might take a bit more time to implement, but the installation for other projects would be seamless.

Yes, that would be a good option, too.  Actually formalizing a release process would be very nice for our development process, if you did it for this and for rsr.
I can leave that to you, I don't know how long it takes, but it would be nice.  If you think you'll do that on some fixed timeline (doesn't have to be too soon), then no need to do the requirements.txt as an intermediate.

You might need to think about package naming for rsr: https://pypi.org/project/pyrsr/

Hi Greg,
You can now install subradar and rsr through pip
pip install rsr subradar
I let you make the necessary modifications in the sds hierarchy to
handle these packages through pip. Let me know when this is done so
that I could test.
On Mon, Nov 2, 2020 at 06:43, gregoryng<EMAIL_ADDRESS>wrote:

You might need to think about package naming for rsr:
https://pypi.org/project/pyrsr/
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Hi Greg,
You can now install subradar and rsr through pip
pip install rsr subradar
I let you make the necessary modifications in the sds hierarchy to
handle these packages through pip. Let me know when this is done so
that I could test.
On Mon, Nov 2, 2020 at 06:43, gregoryng<EMAIL_ADDRESS>wrote:

You might need to think about package naming for rsr:
https://pypi.org/project/pyrsr/
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Fix Spotless Build failure

🎯 Goal
Describe the big picture of your changes here to communicate to the maintainers why we should accept this pull request. If it fixes a bug or resolves a feature request, be sure to link to that issue.
🛠 Implementation details
Describe the implementation details for this Pull Request.
Addressed issue https://github.com/skydoves/pokedex-compose/issues/15 this PR resolves the reported issue and improves codebase formatting.
✍ Explain examples
Explain examples with code for this updates.
this
Preparing a pull request for review
Ensure your change is properly formatted by running:
$ ./gradlew spotlessApply

Please correct any failures before requesting a review.

@skydoves change list is long because i ran./gradlew spotlessApply


fix(catppuccin): Integration with navic.

If custom_bg was not set then we could get a strange-looking white background or no highlight.

@Jint-lzxy I also moved bufferline to respect the author's guidelines, please update it too!
More info here: https://github.com/catppuccin/nvim/issues/260#issuecomment-1229178598


mssql - missing extended properties

Maybe this is not a bug, but a feature request
System information:

Operating system (distribution) and version: Windows 10
DBeaver Version <IP_ADDRESS>104181339
Additional extensions

Connection specification:

Database name and version: SQL Server 2017, 2019
Driver name
Do you use tunnels or proxies (SSH, SOCKS, etc)?

Describe the problem you're observing:
Missing support for extended properties in dbeaver
Steps to reproduce, if exist:
Create a table (or view or other objects) containing extended properties

for the object
for columns

Create Table [dbo].[zzz](
	[aaa] [Int] Null
) On [PRIMARY]
Go

Exec sys.sp_addextendedproperty @name=N'RepoObjectColumn_guid', @value=N'8198f068-ca9d-eb11-84f6-a81e8446d5b0' , @level0type=N'SCHEMA',@level0name=N'dbo', @level1type=N'TABLE',@level1name=N'zzz', @level2type=N'COLUMN',@level2name=N'aaa'
Go

Exec sys.sp_addextendedproperty @name=N'RepoObject_guid', @value=N'8098f068-ca9d-eb11-84f6-a81e8446d5b0' , @level0type=N'SCHEMA',@level0name=N'dbo', @level1type=N'TABLE',@level1name=N'zzz'
Go

check the object in dbeaver DDL
-- Drop table

-- DROP TABLE dhw_self.dbo.zzz;

CREATE TABLE dhw_self.dbo.zzz (
	aaa int NULL
);

extended properties are missing

Implemented (for tables and their columns only):

Verified


Don't load the pixel, cell, and neighborhood FOVs in batches for mask generation

What is the purpose of this PR?
Closes #815. Resolves an issue with variable-sized images using the legacy batch loading technique for mask generation.
How did you implement your changes
Implement a for loop to generate these instead of using one load_imgs_from_dir call.

@ngreenwald


#foreach @blog.navigation does return wrong URLs (IMHO)

Hello.
Sorry to bother you. I'm not exactly 100% sure this is a bug, but yesterday I wanted to put a list of my navigation links in the footer of my website, so I wrote this into partials/footer.hbs:
{{#foreach @blog.navigation}}

        {{label}}

{{/foreach}}

And this code is correctly displaying all the links I have created under Design -> Navigation, but the {{url}} property for each of these links is not correct: instead of pointing to the correct URL, it is instead pointing to the root URL of my website. I don't know if I have explained this concept properly, however just to make an example, instead of having a URL like this:
https://www.cesco.it/my-products
The returned URL value is just:
https://www.cesco.it/
If you want to see this in action, just pay a visit to my website on https://www.cesco.it and scroll down to the end and try any link in the section "Link rapidi" (that's would be the italian translation of "quick links", I'm still not sure about that translation...)
Technical details:

Ghost Version: 2.15.0
Node Version: 8.15.0
Browser/OS: Chrome 72.0.3626.109 on macOS 10.14
Database: MySQL

I'm also attaching the complete partials/footer.hbs file for completeness.
footer.hbs.zip

Never mind, I just saw that using just {{url}} instead of `{{url absolute='true'}} works as expected.

Duplicate of https://github.com/TryGhost/Ghost/issues/5162.


Best way to debug 'Invalid Resource' exceptions?

I'm running into the following error when saving a SalesEntry and I'm wondering what the easiest way to debug these kind of problems is since the gem isn't returning helpful information on what went wrong.
E, [2017-01-13T19:17:46.569754 #79564] ERROR -- : Invalid Resource Elmas::SalesEntry, attributes: {:journal=>"60", :sales_entry_lines=>[#<Elmas::SalesEntryLine:0x007fdbc583f218 @attributes={:amount_FC=>129, :description=>"Expedited Review for Submission #44192", :entry_id=>"aff6e4e3-77d6-4c25-b81d-46b6e09f58f9", :GL_account=>"1fcbed3f-52d8-439a-a2aa-eb970bc50090", :VAT_code=>8}, @filters=[], @query=[], @valid_attributes=[:serial_number, :asset, :cost_center, :cost_unit, :description, :notes, :project, :quantity, :serial_number, :subscription, :tracking_number, :VAT_amount_FC, :VAT_base_amount_DC, :VAT_base_amount_FC, :VAT_code, :VAT_percentage, :account, :amount_FC, :GL_account, :entry_ID]>], :customer=>"78140b87-c202-4a64-8a93-ca421762ea49", :description=>"Expedited Review for Submission #44192", :entry_date=>"2016-12-28", :payment_reference=>"ch_9p2ou3fSefFEwP", :currency=>"USD", :rate=>1.0678807947019868}
E, [2017-01-13T19:17:46.572996 #79564] ERROR -- : There was an error parsing the response
E, [2017-01-13T19:17:46.573496 #79564] ERROR -- : JSON::ParserError: 784: unexpected token at 'Invalid Request'
E, [2017-01-13T19:17:46.573644 #79564] ERROR -- : An error occured, the response had status 400. The content of the error was: JSON::ParserError: 784: unexpected token at 'Invalid Request'
E, [2017-01-13T19:17:46.573816 #79564] ERROR -- : There was an error parsing the response
E, [2017-01-13T19:17:46.573914 #79564] ERROR -- : JSON::ParserError: 784: unexpected token at 'Invalid Request'

Perhaps there's a way to see the raw POST request that's being made to the API?

Invalid request usually means that you have provided wrong attributes. Log level of faraday is currently not editable trough config. Will see if we can add that.

There's a PR in progress that validates input better,  #14,  it also might be an issue we recently fixed with a hardcoded base url. You could try your thing again with version2.4.1. Otherwise i suggest you open a PR where you make it possible to debug the request output, it's a log level in Faraday.

Hi @marckohlbrugge
I'm actually going to build some better debugging functions, so stay tuned.


tf.keras.layers.Embedding causes memory leak

System information

Have I written custom code: yes
OS Platform and Distribution: Linux Mint 19.1
TensorFlow installed from: binary (using pip)
TensorFlow version: 2.0.0-beta1 (v2.0.0-beta0-16-g1d91213fe7)
Python version: 3.6.8
CUDA/cuDNN version: 10.0 / 7.5
GPU model and memory: Nvidia Quadro P1000 - 4 GB GDDR5

Describe the current behavior
A GPU (edit: CPU as well, see addendum below) memory leak (rapidly) emerges from using (high-dimensional) tf.keras.layers.Embedding layers.
To be more precise, I am working on Transformer networks, and found out that when I try to fit one, e.g. on the portuguese-to-english translation task presented in this official tutorial, a GPU memory leak emerges after a few iterations. Based on this StackOverflow post, I rapidly came to suspect that the issue comes from the (learnable) embedding layers at the base of both the encoder and decoder parts of the network.
To further assess the issue and its source, I implemented a pseudo-Transformer network (see code linked below) that is stripped of most technical components the actual model embarks (e.g. I removed positional encoding, residual connections, masking mechanisms, etc.) - the rationale being to provide a more condense (and faster-run) code to document this issue, but also to confirm that the leak does not come from custom layers or any "complex" data processing mechanism.
The provided code includes a data pre-processing pipeline entirely based on the aforementioned tutorial, a model-construction function that makes use of the keras functional API, and a main function to call the former and start the fitting process. On my computer, everything runs fine and I can see the first few fitting iterations pass, until an ugly stack of allocation error messages show up (see full log linked below), whose informative part seems to be W tensorflow/core/framework/op_kernel.cc:1546] OP_REQUIRES failed at cwise_ops_common.cc:70 : Resource exhausted: OOM when allocating tensor
Addendum: I re-ran the provided code disabling access to the GPU, and it turns out there also is a high memory usage when running on CPU. During the first epoch (and mostly during its first half), memory usage goes up multiple GB (in my case, from 2 to 10 GB, with an increase from 2 to 7 within the first 60 train steps out of 704), and keeps slowly increasing throughout the following epochs (with minor decreases between increases, thus displaying local plateaux which I would guess are related to the loading / discarding of data batches). Although it is a bit less of a problem than with GPU since it is relatively common to have quite some RAM available (plus some swap space, on linux), it still does not feel right that fitting the fake model on a dataset which can be fully loaded in memory (creating a list of Eager Tensors from the tf.data.Dataset object containing the batched, padded training set results in a marginal usage of around 100 MB of RAM) would end up using 16GB or RAM. I would also like to note that calling gc.collect after training does not empty the used RAM, which is only freed (instantly) when ending the python process.
Describe the expected behavior
The fitting process should go one fine, and the memory should not get saturated (I would expect some tensors to be de-allocated as iterations pass).
Code to reproduce the issue
The script I wrote to illustrate the issue is publicly accessible as a gist here.
Other info / logs
The full error stack (with GPU enabled) is publicly accessible as a gist here

@pandrey-fr Hi Paul,
this is not related to your problem. However, I am stuck at one step before you, since you have helped me earlier so I thought maybe you can give me some suggestions.
I am training my tf.keras model on multiple GPUs (2 exactly) and following TF2.0's example for doing that. I am adding these two lines
mirrored_strategy = tf.distribute.MirroredStrategy()
with mirrored_strategy.scope():
before the model's definition and compilations as also shown in the link. Now, I am receiving errors. My question from you is if there is anything else that has to be added in order to train it on multiple GPUs?  I have my own tf.data.Dataset separates into train and test sets after padding and batching.
Thank you for your helpful reply. I already opened an issue on TF but haven't gotten any response.

After additional testing, I found out the high memory usage is not exclusive to the GPU, and update the initial post accordingly.

@rishabhsahrawat Hi, I unfortunately have no experience with GPU distribution strategies, and only have 1-GPU machines at my current disposal, hence I would not know how to help you... Sorry :/

I could reproduce the reported issue on Colab with Tensorflow version 2.0.0.beta1. Please take a look at gist of colab. Thanks!

Additional information: since this aforementioned post recommends taking the embedding lookup out of the training loop, I ran a modified version of the code where the embedding layers are declared outside of the instantiated keras Model (which now takes pre-embedded Tensors as inputs) and applied to the datasets at the time of their reshaping (in the reformat_inputs function).
This does not resolve the issue, and the GPU runs out of memory just as fast. However, if I try to load the entire training set in (non-GPU) memory (e.g. data = list(iter(trainset))), it works, but the memory used (which is greater than when loading the non-embedded data, which makes sense) is not freed upon deletion. I.e. it appears that every time the data is loaded, memory is allocated that cannot be de-allocated - and apparently, more data loading occurs when fitting the model than I would expect (since the increase (with GPU disabled) is far greater when running model.fit than when listing the contents of the trainset object).

With some effort, I found a way to export and reload the datasets after their creation (which requires Eager execution), so that I was able to run setup_dataset, dump the results, restart python, tf.compat.v1.disable_eager_execution, reload the datasets, setup_model and fit it without Eager.
Long story short, it turns out the issue does not show up when Eager is disabled (and the fitting goes slightly faster - on CPU, 250s / epoch instead of 280s ; and obviously enabling GPU use makes for a great runtime gain, with less than 80s /epoch).
So, Eager execution messes things up badly... Why does that seem to be the endpoint of each and every issue I encounter these days? Anyway, I hope someone can find out where things go wrong with Eager enabled, and how to fix this (because disabling Eager is not exactly a fix, just a workaround for the times being - and an option I would personally like to keep in the future, outside of the compat sub-module, but that is another question).
Code to reproduce (not including the functions defined in the aforeshared gist)
First session - Eager execution is enabled.
# Use aforeshared code to define setup_dataset
import numpy as np

train, valid, inp_voc_size, tar_voc_size = setup_dataset()
np.save('train.npy', [(x.numpy(), y.numpy()) for x, y in train])
np.save('valid.npy', [(x.numpy(), y.numpy()) for x, y in valid])

# I also ran commands to get the constants and note them somewhere.
# In the second run, I therefore hard-code them for simplicity.
# input vocab size is 8443, target vocab size is 8356
# train set comprises 704 batches, validation set has 17

Second session
import tensorflow as tf
import numpy as np

tf.compat.v1.disable_eager_execution()

def reload_dataset(path):
   """Reload a dumped dataset and finish formatting it."""
    data = np.load(path, allow_pickle=True).tolist()
    def generator():
        for inputs, target in data:
            yield ((inputs, target[:, :-1]), target[:, 1:])
    types = ((tf.int64, tf.int64), tf.int64)
    shape = (((None, None), (None, None)), (None, None))
    dataset = tf.data.Dataset.from_generator(generator, types, shape)
    return dataset

# use aforeshared code to define setup_model

def main():
    train = reload_dataset('train.npy')
    valid = reload_dataset('valid.npy')
    model = setup_model(3443, 8356)
    model.fit(
        epochs=10, x=trainset.repeat(), steps_per_epoch=704,
        validation_data=validset.repeat(), validation_steps=17,
    )

if __name__ == '__main__':
    main()

Oh, and for the sake of it: I tried fitting a model with Eager enabled after reloading the data from the .npy dumps, and the memory issue is still there (i.e. it is not caused by the use of dataset transformations in setup_dataset).

As I am still hoping that someone will pick up this issue, I conducted (yet) additional testing, namely replacing tf.keras.layers.Embedding with a subclass that overrides the call method in order to use one-hot-encoding and dot-product to retrieve embeddings instead of tf.nn.lookup (see code below). This does not fix the issue, which therefore seems to be a general input tensors non-discarding issue in Eager execution (regardless of how they are created).
The class I used to replace tf.keras.layers.Embedding inside the setup_pseudo_model function:
class OneHotEmbedding(tf.keras.layers.Embedding):
    "Embedding layer with one-hot dot-product retrieval mechanism."""

    def call(self, inputs):
        """Embed some inputs."""
        one_hot = tf.one_hot(inputs, depth=self.input_dim, dtype=tf.float32)
        return tf.keras.backend.dot(one_hot, self.embeddings)

Again, disabling Eager has everything run as smoothly as I want...

I am happy to see some activity popping (@robieta, you seem to be quite the expert on this kind of issue!), however I see the type:bug tag was removed which in my humble opinion is incorrect; this is not just a performance issue (as is the case, e.g. in #30561), this is a bug, in the sense that training is not just slower, it is made altogether impossible on some configurations (namely when a GPU is visible or the amount of RAM is under 16 GB, which it really should not given the size of the model and dataset).

Hi,
Thanks for the report and the reproduction script.
I am not able to reproduce the memory leak with the beta1 release on CPU, with the script provided. I will try GPU next.
The tutorial script itself does not seem to feature a memory leak either on CPU or GPU.
Please try your reproduction script with your local configuration with the TF2.0 nightly build: https://pypi.org/project/tf-nightly-2.0-preview/

I cannot reproduce the memory leak on Colab on either GPU or CPU: https://colab.research.google.com/drive/19CrtGEtAQQNSzwbCA1GL-NypPBucxuyF
Memory usage is flat within epochs and across epochs. The only bumpy is at the start of training (which is expected), and it is a very small bump.
It appears that the issue is specific to your configuration. As such, I would recommend reinstalling TF 2.0 (nightly) as well as the latest version of every dependency, and check if the issue is still there.

It seems that updating the TF version from beta1 to the latest nightly fixes the issue for me. Could you check if the update works for you as well?
pip install tf-nightly-gpu-2.0-preview

Hey, I just want to say that I experienced the same problems with memory leaks (very high memory usage during first epoch) and installing the nightly version instead of beta1 fixed it for me.

Hi,
Thank you for the follow-up on this. I currently am on the move and will only have access to the machine I ran those tests on next week, but hopefully the nightly build comes with the rightful fixes indeed. I will post the results (and hopefully close this issue) next week.

@fchollet
As suggested, I installed the lastest gpu-enabled 2.0 nightly build (from binary, using pip) and ran the test script again (without the line disabling Eager execution), both with and without GPU; unfortunately, I still encounter the same issue.
When using the GPU, I get the following error after the first 38 training steps:
ResourceExhaustedError: 2 root error(s) found.
  (0) Resource exhausted:  OOM when allocating tensor with shape[64,37,8356] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
	 [[node loss/dense_2_loss/clip_by_value/Minimum (defined at /home/pandrey/Documents/tfnightly/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:1686) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

	 [[training/Adam/gradients/gradients/embedding_1/embedding_lookup_grad/Reshape/_34]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

  (1) Resource exhausted:  OOM when allocating tensor with shape[64,37,8356] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
	 [[node loss/dense_2_loss/clip_by_value/Minimum (defined at /home/pandrey/Documents/tfnightly/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:1686) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

0 successful operations.
0 derived errors ignored. [Op:__inference_keras_scratch_graph_1551]

Function call stack:
keras_scratch_graph -> keras_scratch_graph

When running solely on CPU, the training runs but the RAM usage goes up as before, i.e. very much during the first steps, and more slowly but still up as further steps are run (at the end of the first epoch, I reached nearly 12 GB of RAM usage).

I also re-ran the tests adding the tf.compat.v1.disable_eager_execution() line, which again avoids triggering the issue. On CPU, RAM usage fluctuates between 2 and 2.4 GB, and on GPU the available 4GB of dedicated memory are not exhausted (and training goes way faster than the first steps run with both GPU and Eager enabled).

@pandrey-fr This was resolved in 2.0.0rc0 and was tested internally. Can you check and let us know whether it resolved for you when you use !pip install tensorflow==2.0.0rc0. Thanks!

Awesome! I will test on my custom model tomorrow, but as for the example case I initially shared, it is indeed running just fine with 2.0.0rc0. Many thanks and congratulations on the work already achieved towards the 2.0 release :-)

As a conclusive note:
I ran my actual model with 2.0 rc0, comparing performances with and without disabling Eager execution. Most importantly, I am happy to report that leaving Eager enabled no longer causes memory issues. Regarding fitting runtimes, disabling Eager still yields a slight gain (122 seconds per epoch, versus 145 for the first and 135 for the following ones when Eager is left enabled - so, around 10 % runtime difference), but this is a relatively small gap compared to what I encountered in 2.0b1.
On the overall, Eager now seems much more stable than a couple of months ago - an impressive progress which must have taken a lot of hard work from all people involved, so many thanks and congrats for that!


ci: Test with the 4 latest major versions of scikit-learn

Not sure skore is critical to the point of making our CI run 4 times slower

Oldest versions of scikit-learn are only tested on ubuntu-latest python 3.12.


460 ts connect definition

see https://github.com/rofrischmann/fela/issues/460

Oh yeah, thanks for the typings!
The proposed API change also looks fine to me, I will test it later and merge it =)

My colleague found an error in my typing. This happened because I did not properly test the typing. The project does not yet have a suitable infrastructure for verifying typing. Let's roll back the commit of merge, will I fix the error and additionally prepare a separate plug-and-play module?

Sorry

A TypeScript example would be great! Looking forward to see it. No worries, didn’t release it anyways :)

ready, see https://github.com/rofrischmann/fela/pull/463


Fix for gitignore getting written every time we run a build

Fixed issue related to gitignore

LGTM - let's await if this fix solves the issues of the reporter, before we do the merge.

LGTM (original reporter).


Fix- when saving offline, instead of project name the object was showing

Fixes #2000
Screenshots of the changes (If any) -
Before

After

Coverage decreased (-0.1%) to 84.389% when pulling a742adc91c5f593374a1054a5f7aa7670b8d112c on dipanshparmar:fix/project-name into 3d065506a4edf5d8bdb9752aeb49fb165234a73b on CircuitVerse:master.

@dipanshparmar can u check #2026

@dipanshparmar can u check #2026

Sure @satu0king


Question: How to handle failed payments.

Can anyone confirm the following:
When a payment fails, my application gets informed trough the webhook.
I can listen in my application for the events: OrderPaymentFailed and OrderPaymentFailedDueToInvalidMandate.
Inform my users their payment has failed and they need to update their payment method.
When payment method is updated, retry the payment.
Thanks in advance.

I think I found something, can anyone confirm this?
When a payment fails, my application gets informed trough the webhook.
I can listen in my application for the events: OrderPaymentFailed and OrderPaymentFailedDueToInvalidMandate.
Inform my users their payment has failed and they need to update their payment method.
When payment method is updated, retry the payment.

Hi @Juleshendriks,
that's exactly right. You can then use the Order's id from the events to find the specific order and retry them after the user has updated the payment method.
$order->retryNow();

s. https://www.cashiermollie.com/14-retry.html#subscriptions-and-failed-payments for further details.


[4.4] docs: improve description for Factories BC

Description
See https://forum.codeigniter.com/showthread.php?tid=87335&pid=411906#pid411906
Checklist:

[x] Securely signed commits
[] Component(s) with PHPDoc blocks, only if necessary or adds value
[] Unit testing, with >80% coverage
[x] User guide updated
[] Conforms to style guide

Updated!


New rule: jsx-no-trailing-semicolon

We had a case in our code where a semicolon was accidentally used at the end of a line of a tsx statement. Since this is almost always unintended, it makes sense to have a lint rule to warn against it. The rule would warn against code like the following:
<div>
  <SomeComponent/>;
</div>

(haven't thought about the rule name that much, so take the title with a grain of salt)

I was just looking for something like this. Maybe no-errant-characters? Is there an actual use-case for having characters not wrapped in an element in a JSX statement? For RN there is not.

Closing due to deprecation timeline #210, let's focus on getting support in eslint


software bug: kubean supported k8s version list is not match to the kubespray k8s version in helm manifest.cr.yaml

Describe the version
version about:

kubean: v0.5.3
kubespray
kubenetes
what CNI and itsversion

Describe the bug
the lowest k8s version  supported by kubean is 1.24.0
https://github.com/kubean-io/kubean-helm-chart/blob/main/charts/kubean/templates/manifest.cr.yaml#LL118C14-L118C14
the  lowest k8s version  supported by kubespray is 1.25.0
https://github.com/kubernetes-sigs/kubespray/blob/master/roles/download/defaults/main.yml#L233

/kind bug

kubesprayVersion: "f264426"


Push opam converter to Yunxing's npm-opam

We can make npm-opam support both forms until esy becomes the standard.
https://github.com/yunxing/opam-npm
We should also consider having better documentation for how people can convert their own packages.

Currently at https://github.com/esy-ocaml/esy-opam
There are a couple of changes:

We publish packages to a custom registry (rather than to GitHub repos and npm proxy packages within the package scope, like @opam-alpha).
We specify concrete versions of OPAM packages which we need to convert (rather than the number of latest releases).

We publish packages to a custom registry (rather than to GitHub repos and npm proxy packages within the package scope, like @opam-alpha).

Is there a reason why this is better than a git repo? I did not find a significant performance difference.

We specify concrete versions of OPAM packages which we need to convert (rather than the number of latest releases).

Great!

Closing this as we integrated opam packages installation into esy install command.


JavaScript group capstone: Kanban Board Set-up

JavaScript group capstone: Kanban Board Set-up
In this Issue, our team prepared a Kanban board with a GitHub project.  We prepared a very detailed kanban from the templates and the steps was carefully followed to assign all the project to the necessary team member.
The team is made up of two members and the assignment of task are as follows,

No of Team Members in a Group -

2 members - @uisendy  and @SurafelGetachewT
StudentA - @uisendy
StudentB -  @SurafelGetachewT

Click the link to see the project - Javascript Capstone Project

Status: Approved :green_circle:

Hey @uisendy, @SurafelGetachewT  :wave:
Great work on implementing the requirements. Your project is complete. :blush:
There is nothing else to say about your project. :+1:
Highlights :1st_place_medal:
:heavy_check_mark: Using Github issues page
:heavy_check_mark: Following requirements
:heavy_check_mark: Using Github project feature
Optional
All the changes with optional tags are not crucial enough to prevent you from getting the approval but we highly recommend to students that they should take these changes into consideration.
Cheers and Happy coding! :clap: :clap: :clap:
Feel free to leave any questions or comments in the PR thread if something is not 100% clear. Please, remember to tag me in your question so I can receive the notification.
Please, do not open a new Pull Request for re-reviews. You should use the same Pull Request submitted for the first review, either valid or invalid unless it is requested otherwise.

As described in the Code reviews limits policy you have a limited number of reviews per project (check the exact number in your Dashboard). If you think that the code review was not fair, you can request a second opinion using this form.


Parameter handling

We need to support the following parameter conventions:
global (every node and edge sees all parameters)
local (every edge sees only parameters with the right index)
partially missing (edges might have no parameters, while vertices have either global or local ps)
At the moment global is the standard and local can be achieved by passing a tuple: https://fhell.github.io/NetworkDynamics.jl/dev/directed_and_weighted_graphs/#Parameter-handling-1
The problem with the tuple syntax is that it doesn't play nicely with Flux and MTK. An array-based solution would be desirable and could be based on: https://github.com/SciML/RecursiveArrayTools.jl
Note however, that there seem to remain some problems with MTK & ArrayPartitions combined https://github.com/SciML/ModelingToolkit.jl/issues/341.
The strategy for tackling this will be to modify p_e_idx. Once this is resolved, it should be tested in the relevant environments and the documentation should be expanded.

maybe define a new struct and add a dispatch
@inline function p_e_idx(p::T, i, dim_v) where {T <: AbstractArray}
p[i + dim_v]
end

The state of my thoughts on the problem
How we handle parameters at the moment

Structs, Arrays, Dicts, ... are global, i.e. visible for all nodes and edges

A tuple of (vertexpara, edgepara) is local, i.e. each component sees only its ps

Global parameters are not very useful in heterogeneous systems

Hetereogeneous callable structs are used in PowerDynamics but unintuitive to construct. Besides they don't allow for parameter optimization. How about performance? Should PD migrate to the tuple syntax?

Ideally parameters would be attached to the network components (for efficiency) and stored in a flat array (for compatibility). Offsets and pre-allocated views into the parameter array would be stored in the graph structure. We would need to provide an API for conveniently specifying parameters.

Compatibility with DiffEqFlux
The problem doesn't originate at the level of DiffEqFlux but rather at DiffEqSensitivity.jl, ReverseDiff.jl, ForwardDiff.jl and Zygote.jl.
All of these (seem to) work ideally with flat Arrays.
The adjoint methods (ReverseDiff) of DiffEqSensitivity will accept a masked version of the tuple synax, such as
function nd_wrapper!(dx, x, p, t)
  nd!(dx, x, ([p; para_fixed], nothing), t)
end

This comes with a reasonable computational overhead. At the moment this is the recommended way for utilizing DiffEqSensitivity, since the performance is okay and we don't have to rewrite our library.
Tracker.jl is a very robust package and has no problems differentiating the tuple syntax. However it seems to be faster for large problems and for out-of-place problems. The DiffEqSensitivity manual doesn't recommend its usage with inplace problem such as we provide. At the moment, Tracker is the only option for tackling SDEs but this branch of DiffEqSensitivity is under development.
ForwardDiffSensitivity should be fastest for small problems [<100paras], but ForwardDiff.jl needs AbstractArrays to pass along dual numbers. Wrapping the tuple in a function such as above does not work. Modifying p_e_idx straighforwardly to pass p[:,i] leads to different issues.(In a test problem I was optimizing  a subset of the parameters. However, when i wrote a wrapper to do that, it complained about alignment issues. Optimizing over all parameters wasn't feasible in the test problem. So this appraoch should be investigated further. [#keepsomeparametersfixed])
Zygote isn't compatible with DiffEqSensitivity yet, but that's under development. Still Zygote seems to be used internally for calculating vector jacobian products (vjps). This might cause some of the errors we are seeing.  DiffEqSensitivity provids an option for specifying  other algorithms for the vjp calculations. We could experiment with that.
Parallelization with @Threads causes problems at the moment. This will take a while to fix.
Compatibility with ModelingToolkit
MTK does not like the tuple Syntax. Ideally parameters should be in an array (does the array have to be flat? it seems yes). Wrapping doesn't help either. To use modelingtoolkitize use global parameters or rewrite p_e_idx (in the right way, though, since p[:,i] leads to complaints about undefined references)
Policy
Without a concrete problem at hand we have these guidelines.

In general: use tuple syntax since it is convenient and fast
For SciML use adjoint methods and function wrappers
If that doesn't work and you have enough computational resources, use TrackerAdjoint
For MTK use global parameters [or modify p_e_idx and use flat parameter arrays, if you come up with a good design make a pull request]

For a concrete application it might make sense to rewrite ND, such that parameter dimensions are specified at VertexFunction level. This will take a while, though.

Issue about types of parameters in DiffEqFLux: https://github.com/SciML/DiffEqFlux.jl/issues/178

It's in the docs: https://fhell.github.io/NetworkDynamics.jl/dev/parameters/

Hi,
I think the issue I'm facing is related to how ND handles parameters.
The parameters are passed onto the ODEproblem as a tuple. The first element getting passed to the nodes is an array of 4 structs corresponding to the number of nodes, the lines have no parameters:
parameters = (Vector{myStruct} with 4 elements, nothing)
The issue is that I'm using a PeriodicCallback (every hour) to modify each of the four parameters passed to the nodes. For this, I'm using a loop to iterate over integrator.p[1][j].a.b (with a being a field of the parameter struct and b being a field of a) and assign it to integrator.u[4*j]:
for j = 1:4
    integrator.p[1][j].a.b = integrator.u[4*j]
end

However, this code line seems to be updating all four .a.b fields to the value of u[4*j]. When existing the loop, all .a.b fields have the value of integrator.u[16], which is not the required behavior.
Any thoughts on why this occurs?

Hmm... sounds strange. Could you post a minimal example where this problem occurs?
I am not sure how this has to do with NetworkDynamics, since in the moment that the callback is applied ND shouldn't be doing anything.


Pre-built .apk with offline bootstrap?

How do I get pre-built .apk with bootstrap included? I need it in the case of no internet connection.
I run on marshmallow 6.0.1 and latest termux is only for nougat v7+.
The legacy repository has bootstrap included as termux-v0.79-offline-bootstraps.apk
https://archive.org/download/termux-repositories-legacy
Could I have something like com.termux.nix_188031-offline-bootstrap-release-22.11.apk?

You might get away with specifying a local URL / path to the bootstrap dialog, but the problem is, our bootstrap itself needs network. All in all, Nix package manager isn't exactly offline-friendly either.


CB-14091 Implement retry for FreeIPA

flow retry related code has been moved to flow module
endpoint and controller code introduced in FMS
flows has been adjusted to be restartable in FMS
default failure payload has been fixed in several cases

See detailed description in the commit message.

Thanks for trying. I see now, the failure handler has no failureEvent
registered, so it will not send a new event - I overlooked it.
https://github.com/hortonworks/cloudbreak/blob/16067565792b2db2d6f80e7098753b7ed3625523/flow/src/main/java/com/sequenceiq/flow/core/AbstractAction.java#L107
On Fri, Sep 17, 2021 at 12:03 PM Mihaly Laszlo Molnar <
@.***> wrote:

@.**** commented on this pull request.
In
freeipa/src/main/java/com/sequenceiq/freeipa/flow/freeipa/downscale/action/FreeIpaDownscaleActions.java
https://github.com/hortonworks/cloudbreak/pull/11416#discussion_r710925778
:

@@ -432,11 +431,6 @@ protected StackContext createFlowContext(FlowParameters flowParameters, StateCon
return super.createFlowContext(flowParameters, stateContext, payload);
}

       @Override

I have tested with 2 different flows and there is no loop. It would fail
with the following, and the flow would stop:
021-09-17 12:01:33,985 [reactorDispatcher-10] lambda$reactor$1:145 ERROR c.s.f.r.c.EventBusConfig - [type:STACK] [crn:crn:cdp:freeipa:us-west-1:cloudera:freeipa:e28e9559-e222-40de-b033-ebdacb44e866] [name:mmolnar-awsenv2-freeipa] [flow:1f1a91e2-7c8f-46bd-ad1b-2b79983549ca] [requestid:c480ed03-a041-4d71-bacf-a606dadf113c] [tenant:cloudera] @.*** [environment:crn:cdp:environments:us-west-1:cloudera:environment:6ce22431-6f79-4b4d-981f-07ba899db7ad] [traceId:0465a361c0ec7006] [spanId:38ce7e0130802f45] [operationId:] Exception happened in dispatcher
com.sequenceiq.cloudbreak.common.exception.CloudbreakServiceException: Missing error handling for com.sequenceiq.freeipa.flow.freeipa.salt.update.action.SaltUpdateFailureAction
at com.sequenceiq.flow.core.AbstractAction.lambda$execute$0(AbstractAction.java:111)
at com.sequenceiq.cloudbreak.auth.ThreadBasedUserCrnProvider.doAs(ThreadBasedUserCrnProvider.java:113)
at com.sequenceiq.flow.core.AbstractAction.execute(AbstractAction.java:78)
If there is no failure payload for that action it would cause a
nullpointer, so I think this is way better
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Refactor navigation drawer and support/add various navigation items

https://github.com/Crystal-Creations-GbR/crystal-components/compare/5d1f458625f0c79aad12a6b2377ea2935134aa4a..d29ad43ecfa1e0ed3eba5f8d84d73a26dc9e2de7
Made it smaller and the text not bold

https://github.com/Crystal-Creations-GbR/crystal-components/compare/d29ad43ecfa1e0ed3eba5f8d84d73a26dc9e2de7..84b60a417144297bb0d11b356d5a779457503b37


How to match .gitignore files using PhysicalFileProvider.Watch?

The PhysicalFileProvider is not watching the pattern  /**/.gitignore
I think it may be a bug, but I want to confirm if I'm not doing something wrong.
The globbing pattern provided by this class seems to lack some common glob pattern features.
Try creating/change a ".gitignore" file in the folder of the application bellow. It doesn't detect any change:
class Program
    {
        static void Main(string[] args)
        {
            var fileProvider = new PhysicalFileProvider(Directory.GetCurrentDirectory());
            var changeToken = fileProvider.Watch($"/**/.gitignore");
            changeToken.RegisterChangeCallback((o) => Console.WriteLine("Change detected!"), null);

            Console.Read();
        }
    }

Removing the "." from the filename works.

You'll need to set up a PhysicalFileProvider with an ExclusionFilters setting that allows folders with dot prefix. The default is to exclude these files.


Error when running tests

I'm running Node 6.2.1 on Windows 10. When running npm test on a fresh repo, I get the following error:
$ npm test

><EMAIL_ADDRESS>test C:\Users\weeseng\Documents\GitHub\prettier
> jest

TypeError: string.replace is not a function
    at string (C:\Users\weeseng\Documents\GitHub\prettier\node_modules\jest-util\build\index.js:45:19)
    at p (C:\Users\weeseng\Documents\GitHub\prettier\node_modules\jest\node_modules\jest-cli\build\SearchSource.js:65:26)
    at new SearchSource (C:\Users\weeseng\Documents\GitHub\prettier\node_modules\jest\node_modules\jest-cli\build\SearchSource.js:101:34)
    at Runtime.createHasteContext.then.hasteMap (C:\Users\weeseng\Documents\GitHub\prettier\node_modules\jest\node_modules\jest-cli\build\jest.js:191:20)
    at process._tickCallback (internal/process/next_tick.js:103:7)
npm ERR! Test failed.  See above for more details.

Not too familiar with Jest, so I can't really help debug :(

Hm, thanks for the report! I will look into it later today. I just cloned a fresh repo and it worked locally.

I've tried it out, and have a fix locally. Will send a PR soon!


Using AutoSizer/CellMeasurer with dangerouslySetInnerHTML

Hi there,
First of all, thanks for the awesome library! <3 Amazing job.
Now onto my problem:
When the content of my rows is generated using dangerouslySetInnerHTML the AutoSizer gets confused and behaviour of the scrolling goes crazy, most likely caused by the fact that dangerouslySetInnerHTML is somewhat rendered asynchronously.
Now I found that react-virtualized offers CellMeasurer, but where am I supposed to put the measure callback in my dangerouslySetInnerHTML-hydrated component?

Same issue here. Have you figured out how to deal with it?

Nah, left the project. Sorry.


fix(macos): fix notraytool's apple-id option name, close #7917

What kind of change does this PR introduce?

[x] Bugfix
[ ] Feature
[ ] Docs
[ ] New Binding issue #___
[ ] Code style update
[ ] Refactor
[ ] Build-related changes
[ ] Other, please describe:

Does this PR introduce a breaking change?

[ ] Yes, and the changes were approved in issue #___
[x] No

Checklist

[x] When resolving issues, they are referenced in the PR's title (e.g fix: remove a typo, closes #___, #___)
[x] A change file is added if any packages will require a version bump due to this PR per the instructions in the readme.
[ ] I have added a convincing reason for adding this feature, if necessary

Other information
Issue: #7917
OVERVIEW: Submit an archive to the Notary service

USAGE: notarytool submit [<options>] <file-path>

ARGUMENTS:
  <file-path>             Path to the archive

OPTIONS:
  -v, --verbose
  -k, --key <key>         App Store Connect API key. File system path to the private key.
  -d, --key-id <key-id>   App Store Connect API Key ID. Usually 10 alphanumeric characters.
  -i, --issuer <issuer>   App Store Connect API Issuer ID. UUID format.
  --apple-id <apple-id>   Developer Apple ID.
  --password <password>   App-specific password for your Apple ID. You will be given a secure prompt on the command line if Apple ID and Team ID are provided and '--password' option is
                          not specified.
  --team-id <team-id>     Developer Team ID.
  -p, --keychain-profile <keychain-profile>
                          Authenticate with credentials stored in the Keychain. Use the profile name you provided in the "store-credentials" command.
  --keychain <keychain>   Pass the path to a keychain file to use for reading the keychain item. If the specified keychain is locked, you'll be prompted to unlock it.
  -f, --output-format <output-format>
                          Desired output format. Note that 'json' and 'plist' are incompatible with '--progress'; a single update will be output at the end of the operation. Choices:
                          ["normal", "json", "plist"] (default: normal)
  --progress/--no-progress
                          Display progress indicators. Only compatible with normal output format (default) and will be otherwise suppressed. (default: true)
  --webhook <webhook>     Designate a public webhook URL to receive HTTP notifications on.
  --wait/--no-wait        Wait until processing is complete. Optionally set a '--timeout' if waiting. (default: false)
  --timeout <duration>    Optional time limit for 'wait'. notarytool will exit after polling for <duration>. The Notary service will continue processing even if the timeout is reached.
        'duration' is an integer followed by an optional suffix: seconds 's' (default), minutes 'm', hours 'h'. Examples: '3600', '60m', '1h'
  --s3-acceleration/--no-s3-acceleration
                          Use S3 Transfer Acceleration for uploads. (default: true)
  --force                 Upload the file even if pre-flight validation or other problems are encountered.
  --version               Show the version.
  -h, --help              Show help information.

Not seeing the --username option in the notarytool's manual, I guess it might be a typo?
After changing it back to --apple-id, it signed successfully.

This PR introduce new error

This PR introduce new error
Must provide all app-specific password authentication arguments (--apple-id, --password, --team-id). You may leave '--password' unspecified on initial invocation to receive a secure prompt.

       Error [tauri_cli_node] failed to bundle project: failed to upload app to Apple's notarization servers.
 ELIFECYCLE  Command failed with exit code 1.

Hmm, Did you set your APPLE_TEAM_ID to the environment when bundling? This is a new environment variable in 1.5 and seems required by the new notarytools

We left it as an option because the apple docs made it sound like it was optional. A pr to make it required was already opened.

To be clear, their docs make it sound like it's optional when it's not. It is required by notarytool and not just best practice. We'll adapt the tauri cli to also require it as mentioned above in this PR: https://github.com/tauri-apps/tauri/pull/7972


Thank you for the library!

@ywilkof
Just want to say thank you for this library! We have used it in production for 4 years!  It works well. Thank you :)

Welcome ;)
If you have updates or forks of it and would like to push into the main branch, please feel free. I haven't maintained if for some time myself.


MathML mathjax fallback stumbles over links (<a> tags).

Issue Summary
I am using latexml to convert exercise sheets to html.
In particular the result typsets mathematical formulas in mathml which means that a fallback to mathjax for browsers other than firefox is currently neccessary.
Now if you open the site "https://mannheim-probability.github.io/Probability-Theory/exercises/sheet_7.html"
in any browser other than firefox you will find a "Math input error" in Exercise 5(iv).
The reason is "unknown node type "a"". In firefox the end result looks like this:

i.e. there are links to previous equations over some equalities. These use the tag <a> which seems to be what mathjax is having issues with.
Steps to Reproduce:
Open up the linked page in any non-Gecko browser such as Chrome or Safari.
Technical details:

MathJax Version: The fallback script includes https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js?config=MML_HTMLorMML

The MathML in your equation includes an HTML <a> element within an <mtext> element.  That is allowed in HTML5's MathML, but it is not required by the MathML specification, and MathJax doesn't currently implement it.  There is a pull request pending that implements it, but that is not scheduled to be included until the next feature release later this summer.
The link would be better handled via an href attribute on the <mtext> element, and indeed that <mtext> does have one, so I'm not sure why the need for the HTML <a>.  Perhaps there is an option to write "pure" MathML without embedded HTML?  If not, then one could probably write a MathML input jax pre-filter to remove the anchors.

PS, the ?config=MML_HTMLorMML is not needed (and does nothing) in your call to MathJax, and should be removed for version 3.

@dpvc thank you for the information. The MathML is autogenerated by latexml and I do not want to modify it at the moment. I created an issue in the latexml repo (see above).

The MathJax pre-filter is one that would run in the browser as part of MathJax's processing of the page, so that may still be an option for you that doesn't require modifying the actual MathML that is generated and included in the HTML.

The MathJax input processors each have lists of functions that get called before or after the input is processed, so that you can do pre- and post-filtering on the input (for just such situations like this).  In the MathML input processor, there is a filter list that is called on the intermediate MathML (before it is turned into internal MathJax MathML nodes).  Here is one that will remove the <a> tags and replace them with the text content (i.e., the equation numbers that are the text of the link).  Since the <mtext> elements already have href attributes, there is no need for these <a> elements, as MathJax will create anchors based on the href itself.
<script>
MathJax = {
  startup: {
    ready() {
      MathJax.startup.defaultReady();
      MathJax.startup.input[0].mmlFilters.add(({math, document, data}) => {
        const tags = Array.from(data.querySelectorAll('a'));
        tags.forEach(tag => {
          tag.parentNode.innerHTML = tag.innerText;
        });
      });
    }
  }
}
</script>
<script<EMAIL_ADDRESS>defer></script>

Note that this uses version 3 of MathJax, as your original post indicates; but the page you link to uses version 2.7.0, a very old version.  You don't seem to need anything specific to version 2, so I'd recommend moving to version 3.  If you must stay at v2, then at least move up to the current version, which is 2.7.9, which has a number of improvements and bug fixes over version 2.7.0.  Something similar could be done for v2, but the API is a bit different, so if you must stay with v2, this will need to be adjusted a bit.

@dpvc thank you for the example - I think the reason for the version mismatch might be that, that the github action environment uses an older version of latexml and the maybe mathjax script is automatically added by that. I can change that easily though.


batchAll example

Showing off use of Utility.batchAll. Perhaps to only transfer from Bob to Charlie if an initial transfer from Alice to Bob succeeds?

Ah, we're already using batchAll... I thought it was using batch. Perhaps we should colocate the two examples, and ensure that the batchAll example showcases the desire for sequential execution (or reversion).

colocate as in in the same file?


iSCSI VM size

Hi,
Regarding the following part:

Deploy new SLES 12 SP1 or higher virtual machines and connect to them via ssh. The machines don't need to be large. A virtual machine size like Standard_E2s_v3 or Standard_D2s_v3 is sufficient. Make sure to use Premium storage the OS disk.

I noticed that you advise using Standard_E2s_v3 or Standard_D2s_v3 VM sizes to create iSCSI target VM.
As the document was clear to ensure that iSCSI target has a premium OS disk, would it be possible to use another VM size that has Premium disk support like B1ms or B1s in case of small implementations?
Best regards,
Abdelrahman Mohamed
Alliance Solutions Architect
<EMAIL_ADDRESS>
Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: a20453e6-5273-2119-69f7-85b5108a8f7d
Version Independent ID: 4ac93e53-6969-4c8d-5b5c-0db47a8976ce
Content: Setting up Pacemaker on SUSE Linux Enterprise Server in Azure
Content Source: articles/virtual-machines/workloads/sap/high-availability-guide-suse-pacemaker.md
Service: virtual-machines-windows
GitHub Login: @MSSedusch
Microsoft Alias: sedusch

@ab-mohamed Thank you for sharing the query. I am assigning this issue to the document author for addressing this query.

@MSSedusch Can you please confirm if the other size VM's can be used.

adding @rdeltcheva
I would not recommend using burstable VMs for hosting iSCSI devices for production workload. For test purposes you can certainly use burstable VMs (B series)

adding @rdeltcheva
I would not recommend using burstable VMs for hosting iSCSI devices for production workload. For test purposes you can certainly use burstable VMs (B series)

Thanks, @MSSedusch for your reply.
So if I understood your reply correctly, In production environments,  B series VMs may have insufficient bandwidth quota utilized by SBD disks.
Please correct me if I am mistaken. :)
Best regards,
Ab

We are currently closing out long standing backlog in order to better determine which issues are still valid and which have been addressed. If you are still seeing a specific problem with this document please open a new issue so we can properly assign the feedback to the correct author and get it addressed ASAP.
#please-close

@ab-mohamed sorry for missing you question.
I was referring to the burst feature of the CPU which means that you would need to test if during a peak load of all attached SBD disks, the base CPU performance would be enough. For example, if you use a Standard_B1ls, you would have to test if 5% CPU performance is enough to handle a peak SBD load.
In addition to that, you are correct. The B series have very limited IO performance, especially the smaller sizes.
Hope that helps.

@MSSedusch: Than you for the confirmation and elaboration. :)


schedule send dashboard failed about screen capture

davinci-assembly_3.0.1-0.3.1-SNAPSHOT-dist-beta.9.zip
Exception message：

config/application.yml

Try chrome instead.

Try chrome instead.

But replace it with chrome  error message appears in the log file '/logs/sys/davinci.2020-09-18.log' ，The error The error message :

The above is not a schedule exception, please check whether the configuration is correct

Ooh , thanks.. , Can you tell me which module caused this error ,  i think the file 'application.yml' configuration is right.
give me a hand,looking forward to your reply soon。
------------------ 原始邮件 ------------------
发件人:                                                                                "edp963/davinci"<EMAIL_ADDRESS>发送时间: 2020年9月18日(星期五) 下午5:33
收件人<EMAIL_ADDRESS>抄送: "陈元浩"<44323733<EMAIL_ADDRESS>主题: Re: [edp963/davinci] schedule send dashboard failed about screen capture (#1952)
The above is not a schedule exception, please check whether the configuration is correct
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub, or unsubscribe.

Sorry, can't reproduce your scenario. Please provide more information if need help.

Sorry, can't reproduce your scenario. Please provide more information if need help.

`#  <<
Davinci
==
Copyright (C) 2016 - 2019 EDP
==
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
>>
server:
protocol: http
address: <IP_ADDRESS>
port: 8080
servlet:
context-path: /
Userd for mail and download services, can be empty, careful configuration
By default, 'server.address' and 'server.port' is used as the string value.
access:
address: <IP_ADDRESS>
port: 8081
jwt is one of the important configuration of the application
jwt config cannot be null or empty
jwtToken:
secret: secret
timeout: 1800000
algorithm: HS512
##your datasouce config
source:
initial-size: 2
min-idle: 1
max-wait: 6000
max-active: 10
break-after-acquire-failure: true
connection-error-retry-attempts: 0
query-timeout: 600000
validationQueryTimeout: 30000
enable-query-log: false
result-limit: 1000000
spring:
mvc:
async:
request-timeout: 30s
davinci datasouce config
datasource:
url: jdbc:mysql://<IP_ADDRESS>:3306/davinci
username: root
password: 123456
driver-class-name: com.mysql.jdbc.Driver
initial-size: 2
min-idle: 1
max-wait: 60000
max-active: 10
redis config
please choose either of the two ways
redis:
isEnable: false
standalone config
host: <IP_ADDRESS>
port: 6379

cluster config
cluster:
nodes:
password:
database: 0
timeout: 1000
jedis:
  pool:
    max-active: 8
    max-wait: 1
    max-idle: 8
    min-idle: 0

mail is one of the important configuration of the application
mail config cannot be null or empty
some mailboxes need to be set separately password for the SMTP service)
mail:
host: smtp.163.com
port: 465
username: a
fromAddress: aac
password: xxdxxd
nickname: sfdsfg
properties:
  smtp:
    starttls:
      enable: true
      required: true
    auth: true
  mail:
    smtp:
      ssl:
        enable: true

ldap:
urls:
username:
password:
base:
domainName:    # domainName 指<EMAIL_ADDRESS>这里值为<EMAIL_ADDRESS>security:
oauth2:
enable: false
client:
registration:
cas:
provider: cas
client-id: "xxxxx"
client-name: "Sign in with XXX"
client-secret: "xxxxx"
authorization-grant-type: authorization_code
client-authentication-method: post
redirect-uri-template: "{baseUrl}/login/oauth2/code/{registrationId}"
scope: userinfo
provider:
cas:
authorization-uri: https://cas.xxxxx.cn/cas/oauth2.0/authorize
token-uri: https://cas.xxxxx.cn/cas/oauth2.0/accessToken
user-info-uri: https://cas.xxxxx.cn/cas/oauth2.0/profile
user-name-attribute: id
userMapping:
email: "attributes.Email"
name: "attributes.CnName1"
avatar: "attributes.Avatar"
screenshot:
#default_browser: PHANTOMJS
default_browser: CHROME
timeout_second: 600
#phantomjs_path: /opt/phantomjs/bin/phantomjs
chromedriver_path: /usr/bin/chromedriver
data-auth-center:
channels:
- name:
base-url:
auth-code:
statistic:
enable: false
You can use external elasticsearch storage [<IP_ADDRESS>:9300]
elastic_urls:
elastic_user:
elastic_index_prefix:
You can also use external mysql storage
mysql_url:
mysql_username:
mysql_password:
You can also use external kafka
kafka.bootstrap.servers:
kafka.topic:
java.security.krb5.conf:
java.security.keytab:
java.security.principal:
`


Minimal port to Tensorflow 2

The changes in this PR are the absolute minimum needed to get this project to
work with Tensorflow 2.
I am a ML and TF novice, so I probably missed something, but these changes
allowed me to use attention-ocr to train a new model and produce predictions
for new inputs, using only TF2.

That's awesome work, thank you for this. Merging :)


Add [your name] Markdown

Project Request

Proejct Request to Add [your name] markdown file and route

Field
Description

Name
Nanda-Kumar-T

Email
<EMAIL_ADDRESS>

Github
NandaKumar060504

What do you what to contribute to:

[ ] HackFest GDSC Contributor
[ ] Hacktober Fest Contributor

please add your name in the issue name


libnbd: cve-2024-7383 (mariner 2.0)

Merge Checklist

All boxes should be checked before merging the PR (just tick any boxes which don't apply to this PR)

[x] The toolchain has been rebuilt successfully (or no changes were made to it)
[x] The toolchain/worker package manifests are up-to-date
[x] Any updated packages successfully build (or no packages were changed)
[x] Packages depending on static components modified in this PR (Golang, *-static subpackages, etc.) have had their Release tag incremented.
[x] Package tests (%check section) have been verified with RUN_CHECK=y for existing SPEC files, or added to new SPEC files
[x] All package sources are available
[x] cgmanifest files are up-to-date and sorted (./cgmanifest.json, ./toolkit/scripts/toolchain/cgmanifest.json, .github/workflows/cgmanifest.json)
[x] LICENSE-MAP files are up-to-date (./LICENSES-AND-NOTICES/SPECS/data/licenses.json, ./LICENSES-AND-NOTICES/SPECS/LICENSES-MAP.md, ./LICENSES-AND-NOTICES/SPECS/LICENSE-EXCEPTIONS.PHOTON)
[x] All source files have up-to-date hashes in the *.signatures.json files
[x] sudo make go-tidy-all and sudo make go-test-coverage pass
[x] Documentation has been updated to match any changes to the build system
[x] Ready to merge

Summary
Create patches to fix libnbd CVE-2024-7383
Change Log

Create 3 patch files
Update spec version

Does this affect the toolchain?
NO
Associated issues
Links to CVEs

https://nvd.nist.gov/vuln/detail/CVE-2024-7383

Test Methodology

https://dev.azure.com/mariner-org/mariner/_build/results?buildId=624653&view=results
with single combined patch: https://dev.azure.com/mariner-org/mariner/_build/results?buildId=625051&view=results
fasttrack/2.0: https://dev.azure.com/mariner-org/mariner/_build/results?buildId=633963&view=results

Ignoring the Go test coverage test - it's failing due to GitHub's policy check, not the changes in the PR.
The single ptest failure comes from nbdkit, which is a known issue and not a regression.

Auto cherry-pick results:

main :white_check_mark: -> https://github.com/microsoft/azurelinux/pull/10343

Auto cherry-pick pipeline run -> https://dev.azure.com/mariner-org/mariner/_build/results?buildId=634027&view=results


Avisynth lang definition.

I will not be offended if you recoil in disgust from this PR when you see the corpus that has been programmed into it. AviSynth is a scripting language that acts as a video frame server, so that you can programmatically edit video.

Homepage
The full AviSynth grammar
This PR in action, using the (in)famously complex QTGMC deinterlacer script: https://zinfidel.github.io

Why are there that many words?
AviSynth poses an interesting challenge for syntax highlighting, as it can be argued that its built-in functions and filters represent the core of its functionality. The very goal of the language itself, which is to edit video, is achieved by these built-in filters. Indeed, many AviSynth scripts (maybe even most?) are just a small collection of its included filters, such as Trim, AddBorders, etc.
This is the reason why I decided early on to include the full list of internal functions/filters as highlighted elements in this definition. Without considering the internal functions/filters as part of the core language features, there is actually very little to highlight overall. Whether this choice was the right one, I do not truly know.
Questions to Answer

Internal functions/filters/properties use the builtin token, which in the default theme is the same color as strings. This seems... wrong, especially since many of these functions take string arguments. Is the builtin token really the wrong token for these? Perhaps it should be function instead?
I have also included highlighting for user-defined functions, and external filters using the function token. It may be the case that the internal functions/filters/properties should be using this token instead. If that is the case, though, then user-defined/external filters probably don't have an appropriate token and will remain unhighlighted.
I made a really contentious choice to highlight some predefined, special constants as they appear in strings. You can see a couple at the top of my linked github.io example. AviSynth has very few constants, and these string constants only ever appear in those exact functions to enable special (but common) functionality. This isn't a must have.
This definition becomes unusably slow for editing for large scripts. The QTGMC script takes nearly a full second to update for each entered character, for example.
The last variable is quite special in AviSynth, and I have assigned it the variable token. However, it can show up a LOT in scripts, and may contribute to a "color soup" problem as a result. Highlighting this word as the only variable type may be a mistake.

@RunDevelopment

lol. Don't worry, Avisynth isn't the worst by far.

Oh wow, I had no idea...
I have moved all of the internal stuff over to 'builtin-function' as suggested. Unfortunately, @vadosnaprimer revealed to me last night that functions that take no arguments (or rather, take only the implicit first clip argument) do not actually need the parentheses to qualify as a statement. So,
KillAudio == KillAudio() == last.KillAudio == last.KillAudio()

This means that external/user-functions are indistinguishable from variables in some cases without semantic(?) parsing. I could still try to catch them by looking for identifiers that proceed a . OR precede a ( but it would only guarantee partial coverage of all the cases. I see three possible moves here:

Remove highlighting of user/external functions
Ignore this yucky use case
Regex for the above mentioned pattern and only match user/external functions that can be guaranteed

I'm not sure if partial matching is acceptable at all. If the highlighting is removed, function definitions could still get hightlighted at least.

I have a suggestion for a new token: argument-label.

I really like it! That helps the QTGMC script immensely and looks natural to me, so I'm pretty sure I've seen this type of styling elsewhere. Punctuation does seem iffy, but I think that punctuation is probably universally styled to be downplayed in themes, which is the intent here so I think it works.

That makes things more difficult... I say we still try to highlight functions. A few false negatives here and there are acceptable.

I did some testing, and discovered that clip properties are actually no different from other functions and filters (including being useable without parenthesis) and so I was able to collapse the definition for all of these tokens down into one area.
Unfortunately, that led me to the discovery of yet another problem: AviSynth allows variable shadowing. This means that you can define variables with the same name as built-in functions/filters/properties and it's valid. I noticed it in a script that I personally use quite a bit. Here's a few more test cases:

encode.avs
functions.avsi

You'll notice in encode.avs, there is a string variable called time that gets defined, which shadows the internal function time. This causes it to get highlighted as a function. I added a negative lookahead for the pattern identifier = identifier so that when the name is on the left-hand side this ambiguity is resolved, but right-hand side situations remains highlighted.
So now, this leads to a case with occasional false negatives and occasional false positives. The fact that those scripts have variables named this way is probably a bad thing and should be corrected, and I don't think those of who worked on it had any idea the shadowing was occurring.

Highlighting terms that are reused for variables helps the user to know they are actually internal functions/variables and to stop using them. Does it still work fine in avs if you use the internal filter and also a variable that has its name in the same script?

I tested this abomination:
int = 5
bool = yes
string = "test"
float = 0.5
# global = 10 # error

ColorBars()
Subtitle(string(float))

global time = "not the time"

function test(clip c, float float, int "global") {
    c = c.Subtitle(string(float), align=1)
    c = c.Subtitle(string(global), align=9)
    c = c.Subtitle(time, align=5)
    return c.Subtitle(string(time("%X")), align=3)
}

test(0.5, global=int)

SwapUV = "don't do this"

#SwapUV # <--- returns a string
SwapUV()

... and it works. 😥 The int, bool, string, and float variables all get subtitled "correctly" in that function. The arguments with type/keyword names work too. In the QTGMC script I actually noticed this - the MAnalyze function uses a "global" optional parameter. It looks like filters that are shadowed by variables will resolve to the variables unless followed by parenthesis, which then gets the function instead.
@vadosnaprimer As you can see, you can mix your variables and filters all in the same script. I agree with you that consistently highlighting the internal functions/filters/properties is a good way to let users know that something is amiss, and I think @RunDevelopment agrees that consistency is the way to go here even if it means more false positives.

 I can understand shadowing built-in functions and variables but keywords? Damn.

test(0.5, global=int)

Beautiful.

Yeah, I think we can all kinda agree that using keywords/types as identifiers is a bad idea. I don't think we need to support this because the overwhelming majority of people won't do this. Highlighting 98% of inputs correctly is good enough.

Yeah, I think we can all kinda agree that using keywords/types as identifiers is a bad idea. I don't think we need to support this because the overwhelming majority of people won't do this. Highlighting 98% of inputs correctly is good enough.

Agreed. I think "incorrectly" highlighting instances of keywords where they are used as variables/parameters probably has the benefit of indicating to users that they are doing something they really should not be doing anyway.
I was more concerned with handling edge cases initially because I didn't realize just how badly you could abuse the language before the testing I've done now.

Thank you for contributing @Zinfidel!

And thank you for all of the help improving the definition @RunDevelopment !


Arguments with a - do not get parsed properly

I was testing the shortcode feature in OrchardCore and passing an Argument with a - does not parse properly.
For example, [col offset-md='5'] the first argument is offset-md='5'

By default the identifier doesn't - as a valid char.
But it should read quoted strings for argument names, i.e. [col 'offset-md'='5']
That being said, I wouldn't be against the identifier accepting - as a valid char, we've already had the same problem reported in Orchard Core (fixed by validating the input for naming shortcodes), where they can't be named with a -, only _ is valid.

But it should read quoted strings for argument names, i.e. [col 'offset-md'='5']

Just tried this (with the OrchardCore ShortcodeTemplate feature) and the first arguments comes out as offset-md when quoted :(

@sebastienros is there any reason why - is not a valid char for an identifier in parlot ?

Javascript/C# don't support it, and that would break a lot of grammars. For instance "a-b", I would expected to read it as "a - b".
This is more like and html attribute name. Maybe that could be added in a specific category of parsers when common language identifiers are defined. Also I don't think no having it in the default identifier is a big issue since you can pass custom extra chars already in the Identifier() method.


Append to Spine URL for resources

I would like to be able to fetch resources like so (default way):
/resources
but, I would also like to be able to add a function that can fetch resources with a different path, like so:
/resources/available
I have tried to set the baseURL in a separate initializer to /resources/available, however this results in the URL for fetch calling to /resources/available/resources which is not what I want.
Is there a specific way of appending to the Spine URL for a single function?
e.g.
fetchAllResources() -> /resources
fetchAllAvailableResources() -> /resources/available

I have another question regarding error handling.
Whenever I catch an error in the error block for my save function, I am not able to get any of the details from the error.
dump(error) responds with:
Spine.SpineError.serverError
  ▿ serverError: (2 elements)
    - .0: 422
    ▿ .1: Optional([Spine.APIError(id: nil, status: nil, code: nil, title: nil, detail: Optional("Unavailable resource provided"), sourcePointer: Optional("/data/attributes/resources"), sourceParameter: nil, meta: nil)])
      ▿ some: 1 element
        ▿ Spine.APIError
          - id: nil
          - status: nil
          - code: nil
          - title: nil
          ▿ detail: Optional("Unavailable resource provided")
            - some: "Unavailable resource provided"
          ▿ sourcePointer: Optional("/data/attributes/resources")
            - some: "/data/attributes/resources"
          - sourceParameter: nil
          - meta: nil

However I would like to be able to access the error detail and the error status code to determine what to do with the resulting error.
I have tried casting the error to NSError as well as multiple SpineError types but none have given me the information I need.
My save function looks like this:
  func saveResource(resource: ResourceModel) {
    spine.registerResource(EventModel.self)
    spine.registerResource(ResourceModel.self)
    spine.registerResource(ReservationModel.self)

    spine.save(resource)
      .onSuccess { _ in
        print("Save Resource Successful")
      }
      .onFailure { error in
        print("Error: \(error)")
    }
  }

and I am calling it like this:
      resourceApiHelper.saveResource(resource: newResource,
        successBlock: { _ in
          self.performSegue(withIdentifier: "unwindToPreviousView", sender: self)
        },
        errorBlock: { error in
          dump(error)
        }
      )

I think for default endpoints you can use a custom Query as follows:
let query = Query(url: URL(string: "http://example.com/resources/available"))
spine.find(query)

For the error handling the ServerError contains the HTTP status code, and an array of errors returned by your api. You should be able to get them as follows:
switch error {
  // Handle other errors here.
  case SpineError.serverError(let statusCode, let apiErrors):
    // Do something with statusCode and apiErrors
  default: ()
}


some other cleaning

What does this PR do?

Fixes # (issue)
Before submitting

[ ] Was this discussed/approved via a Github issue? (no need for typos and docs improvements)
[x] Did you read the contributor guideline, Pull Request section?
[x] Did you make sure your PR does only one thing, instead of bundling different changes together?
[x] Did you make sure to update the documentation with your changes?
[x] Did you write any new necessary tests? [not needed for typos/docs]
[ ] Did you verify new and existing tests pass locally with your changes?
[ ] If you made a notable change (that affects users), did you update the CHANGELOG?

PR review

[x] Is this pull request ready for review? (if not, please submit in draft mode)

Anyone in the community is free to review the PR once the tests have passed.
If we didn't discuss your PR in Github issues there's a high chance it will not be merged.
Did you have fun?
Make sure you had fun coding 🙃

Interestingly, lut.add_label takes a name, value, color as parameters: http://www.open3d.org/docs/release/python_api/open3d.ml.tf.vis.LabelLUT.html#open3d.ml.tf.vis.LabelLUT.add_label.
From examples:
lut = ml3d.vis.LabelLUT()
lut.add_label('one', 1)
lut.add_label('two', 2)
lut.add_label('three', 3, [0,0,1]) # use blue for label 'three'

And the color map we get from a dataset, only has an ID and the color: see here. So we need to get the name from: labels in the yml file (labels using get_label_to_names function)
Let's do this in a separate PR since this PR is about cleaning stuff, what do you think? @Borda @ethanwharris
For this PR, I suggested to just use str(id_color), id_color, color.

Let's do this in a separate PR since this PR is about cleaning stuff, what do you think? @Borda @ethanwharris
For this PR, I suggested to just use str(id_color), id_color, color.

yep, agree

@ethanwharris mind check it is fine to land? :rabbit:

@ethanwharris mind review? :rabbit:


Add multiple subtitles

Hello,
I am trying to add multiple subtitles,
When I only add one subtitle, this is working:
const subtitles = [
  {
    default: true,
    kind: 'subtitles',
    srclang: 'ja-JP',
    label: '日文',
    src: 'https://MyDomain/JP.txt'
  }
]
player.subtitles().load(subtitles);

But when I try to add multiple subtitles, like this:
const subtitles = [
  {
    default: true,
    kind: 'subtitles',
    srclang: 'ja-JP',
    label: '日文',
    src: 'https://MyDomain/JP.txt'
  },
  {
    default: false,
    kind: 'subtitles',
    srclang: 'zh-TW',
    label: '中文（繁體）',
    src: 'https://MyDomain/TC.txt'
  }
]
player.subtitles().load(subtitles);

It can be loaded normally,
But the subtitle option in the menu is no longer valid, Can't close or switch subtitles,
The preset subtitles must be pressed once to work properly.
No output from the console.
Effect demo:

which version do you using?

This is the project I created yesterday,
include:
videojs: 7.6.6
videojs-contrib-quality-levels.js: 2.0.9
videojs-plus.umd.js: <Yesterday downloaded from github/Pong420>
quality-hls/index.js: <Yesterday downloaded from github/Pong420>
audio-track/index.js: <Yesterday downloaded from github/Pong420>
hotkeys/videojs.hotkeys.js: <Yesterday downloaded from github/ctd1500>
subtitles/index.js: <Yesterday downloaded from github/Pong420>
live/index.js: <Yesterday downloaded from github/Pong420>
videojs-vtt-thumbnails.js: <Yesterday downloaded from github/chrisboustead>
...<css omitted below>...

Are up to date.
My setting:
<script>
    const log = (event, data) => console.log(event.type, data);
    var player = videojs('movie-player', {
        title: 'test',
        aspectRatio: '16:9'
    });
    player.vttThumbnails({
        src: 'https://myurl/thumbnails.vtt'
    });
    player.src([{
        type: "application/x-mpegURL",
        src: "https://myurl/index.m3u8"
    }]);
    const subtitles = [
        {
            default: true,
            kind: 'subtitles',
            srclang: 'zh-TW',
            label: '中文（繁體）',
            src: 'https://myurl/test.TC.txt'
        },
        {
            default: true,
            kind: 'subtitles',
            srclang: 'ja-JP',
            label: '日文',
            src: 'https://myurl/test.JP.txt'
        },
        {
            default: true,
            kind: 'subtitles',
            srclang: 'en-US',
            label: '英文',
            src: 'https://myurl/test.EN.txt'
        }
    ];
    player.subtitles().load(subtitles);
</script>

Actually this problem already existed a year ago,But I didn't have a github account a year ago.

The scripts included in examples properly not up to date.
Please install from npm or clone the gh-pages branch
git clone https://github.com/Pong420/videojs-plus.git --branch gh-pages --depth=1

This is the full demo I just built at 6 am, All files are downloaded using npm,
Unfortunately, the problem remains.
https://github.com/Ami-OS/videojs-plus-demo

Thank you for your demo.
Please try the new release 1.5.9

thx, this is work!


Fixes 4223: Ensure modals do not cause redirect on close

Summary

Fixes an issue where modals were redirecting on close, causing a rerender of the root node > clearing filters and component state.

Testing steps

Set a filter on the repositories page, open and close any modal, the filter should remain.

/retest


Can I do some validation before submit?

E.g. I have a form with 4 inputs.I hope the 1st & 2nd inputs validated when I click the "Get cell phone verification code" and the 3rd and 4th still pristine.
Can I make this through?

Yes, just don't create any validation functions for the 3rd and 4th inputs. I don't think it's possible to keep certain inputs of a form pristine when you call handleSubmit. If you really need that functionality, you can try separating the 4 inputs into 2 separate forms.

@brotzky Thanks for your reply.
My example includes "Get cell phone verification code"button and "submit"button.I just want the 1st & 2nd inputs validated when I click the former one and the whole 4 inputs validated when I click the latter one, i.e., the submit button.
I want to keep them in one form. Is there any possibilities?

Hm, not that I'm aware, sorry.

Thank you.I create a submit function func() and do mapStateToProps.Then I call it in parent container by this.refs.xxx.stateProps.func().Not the best solution,but meets what I need.


add R.pair

Closes #1310

:+1: What about adding a @see to fromPairs as well?

:herb:

What about adding a @see to fromPairs as well?

:zap:


test: temp diable kong EE and upload diag

What this PR does / why we need it:
upload diagnostics of running Kong 3.0 compatibility tests, and temporarily disable tests against Kong EE for #2891.

Which issue this PR fixes:

Special notes for your reviewer:

PR Readiness Checklist:
Complete these before marking the PR as ready to review:

[ ] the CHANGELOG.md release notes have been updated to reflect any significant (and particularly user-facing) changes introduced by this PR

@randmonkey Can you add a link of a failing job to this PR's description so that we can see what the problem is?

@randmonkey Can you add a link of a failing job to this PR's description so that we can see what the problem is?

A link to the failure is pasted, and also in #2891.


Remove references to config change issues

Since all operations can be affected by config changes (depending on the implementation) it makes no sense to call it out in the specification.

Pull requests:

https://github.com/Senzing/senzing-rest-api/pull/21


Configure the acl interface path in the authInterceptor

What is the purpose of the change
Configure the dlq message interface path in the authInterceptor.
Brief changelog
XX
Verifying this change
XXXX
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[x] Format the pull request title like [ISSUE #123] Fix UnknownException when host config not exist. Each commit in the pull request should have a meaningful subject line and body.
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Codecov Report

Merging #77 (edb926b) into master (6de5d51) will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master      #77   +/-   ##
=========================================
  Coverage     76.88%   76.88%
  Complexity      820      820
=========================================
  Files            91       91
  Lines          2838     2838
  Branches        281      281
=========================================
  Hits           2182     2182
  Misses          500      500
  Partials        156      156

Impacted Files
Coverage Δ

.../dashboard/config/AuthWebMVCConfigurerAdapter.java
57.14% <ø> (ø)

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fixes replication documentation

also this reduces the time for a doctest run by 30sec

Codecov Report

:exclamation: No coverage uploaded for pull request base (master@8c7a474). Click here to learn what that means.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master    #6012   +/-   ##
=========================================
  Coverage          ?   83.12%
  Complexity        ?    12410
=========================================
  Files             ?     1434
  Lines             ?    46928
  Branches          ?     5769
=========================================
  Hits              ?    39009
  Misses            ?     5236
  Partials          ?     2683

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has anyone got this working on an esp-8285?

I got the led example working on a esp-8266 but unable to get it working on a esp-8285. Everything seems to go fine and i've tried different flashing params but still no good... got some csum error in serial monitor after flashing.

Ok now I was aable to flash it almost correctly by using dout -mode ... now it's failing to write the accessory key etc. to it's memory... any ideas with what mem address params I should use to flash it with? (or is the problem something else?)

0x7A000 is a safe bet

it seems that the "make -C examples/led flash" command still writes to wrong mem address even though I have used export HOMEKIT_SPI_FALSH_BASE_ADDR=0x7a000=
esptool.py v2.8
Serial port /dev/tty.wchusbserial1440
Connecting....
Detecting chip type... ESP8266
Chip is ESP8285
Features: WiFi, Embedded Flash
Crystal is 26MHz
MAC: 60:01:94:9b:c5:90
Uploading stub...
Running stub...
Stub running...
Configuring flash size...
Flash params set to 0x0020
Compressed 3104 bytes to 2169...
Wrote 3104 bytes (2169 compressed) at 0x00000000 in 0.2 seconds (effective 114.3 kbit/s)...
Hash of data verified.
Compressed 2048 bytes to 23...
Wrote 2048 bytes (23 compressed) at 0x00001000 in 0.0 seconds (effective 585.6 kbit/s)...
Hash of data verified.
Compressed 432544 bytes to 311120...
Wrote 432544 bytes (311120 compressed) at 0x00002000 in 27.9 seconds (effective 124.2 kbit/s)...
Hash of data verified.

With this command-set I'm the closest to get it done and working but get the failing to save
esptool.py -p /dev/tty.wchusbserial1440 --baud 57600 write_flash -fs 1MB -fm dout -ff 26m 0x0 xxx/homekit_esp/esp-open-rtos/bootloader/firmware_prebuilt/rboot.bin &&
esptool.py -p /dev/tty.wchusbserial1440 --baud 57600 write_flash -fs 1MB -fm dout -ff 26m 0x1000 xxx/homekit_esp/esp-open-rtos/bootloader/firmware_prebuilt/blank_config.bin &&
esptool.py -p /dev/tty.wchusbserial1440 --baud 57600 write_flash -fs 1MB -fm dout -ff 26m 0x2000vxxx/homekit_esp/esp-homekit-demo/examples/led/firmware/led.bin
SO basically I'm flashing the parts one by one so is some of them wrong? Tried flashing the led.bin to 0x7a00 with less success

I have also tried to rebuild the app, clearing the flash and so on...

If you're building it inside docker container like I do, environment variables are not automatically propagated into container. You have several options: pass environment variable to docker explicitly (with -e MY_ENV_VAR)
export HOMEKIT_SPI_FLASH_BASE_ADDR=0x7A000
docker run -it --rm -v `pwd`:/project -w /project esp-rtos -e HOMEKIT_SPI_FLASH_BASE_ADDR make -C examples/led all

or pass it as make argument:
docker run -it --rm -v `pwd`:/project -w /project esp-rtos make -C examples/led HOMEKIT_SPI_FLASH_BASE_ADDR=0x7a000 all

or just edit examples/led/Makefile and add this line before include $(SDK_PATH)/common.mk:
HOMEKIT_SPI_FLASH_BASE_ADDR ?= 0x7A000

Thanks @maximkulkin ! Just figured it out myself too and seems to work :D