fix(native-filters): Show incompatible native filters indicator

SUMMARY

The aim of this PR was to add Incompatible section to filter indicator. ⚠Incompatible filters are created using datasets & fields which are incompatible with a given chart.
I have also added simple mocks for native filters: mockStore and mockNativeFilters to test displaying filter indicators for native filters.
I have also slightly changed structure of Filter Badge tests in FiltersBadge_spec.tsx - I have divided them into 'for dashboard filters' and 'for native filters'. Section 'for dashboard filters' is the same as on master, I have only added analogical tests for native filters.

Fixes #12568
Closes #12568
BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF
Before incompatible section for native filters was missing.
Now different configurations:
With some correct native filters applied and one incompatible:

With trying to apply two incompatible native filters from two different datasets:

With one dashboard filter applied and one incompatible native filter:

With incompatible dashboard filters (without native filters):

TEST PLAN
Enable native filters: go to config.py and set "DASHBOARD_NATIVE_FILTERS": True,
Go to dashboards and create native filters. One one them should be created with incompatible dataset, which cannot be applied to this dashboard.
ADDITIONAL INFORMATION

[x] Has associated issue: #12568
[ ] Changes UI
[ ] Requires DB Migration.
[ ] Confirm DB Migration upgrade and downgrade tested.
[ ] Introduces new feature or API
[ ] Removes existing feature or API

cc @junlincc @rusackas @villebro @suddjian
@adam-stasiak could you test?

Codecov Report

Merging #12687 (bfdd97b) into master (734fb75) will decrease coverage by 3.53%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master   #12687      +/-   ##
==========================================
- Coverage   66.85%   63.32%   -3.54%
==========================================
  Files        1018      486     -532
  Lines       49776    29970   -19806
  Branches     4869        0    -4869
==========================================
- Hits        33278    18978   -14300
+ Misses      16375    10992    -5383
+ Partials      123        0     -123

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javascript
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python
63.32% <ø> (-0.69%)
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Impacted Files
Coverage Δ

superset/db_engines/hive.py
0.00% <0.00%> (-85.72%)
:arrow_down:

superset/databases/commands/create.py
32.65% <0.00%> (-59.19%)
:arrow_down:

superset/sql_validators/postgres.py
50.00% <0.00%> (-50.00%)
:arrow_down:

superset/db_engine_specs/hive.py
54.61% <0.00%> (-29.24%)
:arrow_down:

superset/views/database/mixins.py
59.64% <0.00%> (-22.81%)
:arrow_down:

superset/databases/commands/update.py
85.71% <0.00%> (-8.17%)
:arrow_down:

superset/databases/schemas.py
93.40% <0.00%> (-6.05%)
:arrow_down:

superset/databases/dao.py
94.11% <0.00%> (-5.89%)
:arrow_down:

superset/databases/api.py
86.55% <0.00%> (-5.47%)
:arrow_down:

superset/views/database/validators.py
78.94% <0.00%> (-5.27%)
:arrow_down:

... and 552 more

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Codecov Report

Merging #12687 (bfdd97b) into master (734fb75) will decrease coverage by 3.53%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master   #12687      +/-   ##
==========================================
- Coverage   66.85%   63.32%   -3.54%
==========================================
  Files        1018      486     -532
  Lines       49776    29970   -19806
  Branches     4869        0    -4869
==========================================
- Hits        33278    18978   -14300
+ Misses      16375    10992    -5383
+ Partials      123        0     -123

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Coverage Δ

cypress
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javascript
?

python
63.32% <ø> (-0.69%)
:arrow_down:

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Impacted Files
Coverage Δ

superset/db_engines/hive.py
0.00% <0.00%> (-85.72%)
:arrow_down:

superset/databases/commands/create.py
32.65% <0.00%> (-59.19%)
:arrow_down:

superset/sql_validators/postgres.py
50.00% <0.00%> (-50.00%)
:arrow_down:

superset/db_engine_specs/hive.py
54.61% <0.00%> (-29.24%)
:arrow_down:

superset/views/database/mixins.py
59.64% <0.00%> (-22.81%)
:arrow_down:

superset/databases/commands/update.py
85.71% <0.00%> (-8.17%)
:arrow_down:

superset/databases/schemas.py
93.40% <0.00%> (-6.05%)
:arrow_down:

superset/databases/dao.py
94.11% <0.00%> (-5.89%)
:arrow_down:

superset/databases/api.py
86.55% <0.00%> (-5.47%)
:arrow_down:

superset/views/database/validators.py
78.94% <0.00%> (-5.27%)
:arrow_down:

... and 552 more

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Scenario:
Set 3 native filters (1 valid for this dashboard)
Enable all filters
Apply change
Check chart filters
Disable one of incorrect native filters and apply change
Observed: I see disabled filter in section Incompatible Filters
Expected: I would see this filter under Unset section.
https://user-images.githubusercontent.com/25153919/105514912-568f8300-5cd4-11eb-9224-480f209e61ba.mov

Scenario:
Set 3 native filters (1 valid for this dashboard)
Enable all filters
Apply change
Check chart filters
Disable one of incorrect native filters and apply change
Observed: I see disabled filter in section Incompatible Filters
Expected: I would see this filter under Unset section.
https://user-images.githubusercontent.com/25153919/105514912-568f8300-5cd4-11eb-9224-480f209e61ba.mov

Retested again and consulted with Agata. It looks like my issue was caused by performance on my machine (on video you can see how long everything takes).
I double checked that after computer restart and saw that it was for a moment in yellow zone without value but after a second it was moved to unset 🆗 .
So no issue there.

Retested again and consulted with Agata. It looks like my issue was caused by performance on my machine (on video you can see how long everything takes).
I double checked that after computer restart and saw that it was for a moment in yellow zone without value but after a second it was moved to unset 🆗 .
So no issue there.

Oh apologies Adam, I didn't see your comment when I left my review. Glad it's working!

Oh apologies Adam, I didn't see your comment when I left my review. Glad it's working!

LGTM, thank you for fixing it! ♥ @agatapst  we are very close to demo-able stage.

LGTM, thank you for fixing it! ♥ @agatapst  we are very close to demo-able stage.


Fixed whole blog page

@PriyaGhosal @samarth-6 please review and merge it

@AsifQamar BuddyTrail theme is sky blue .... Why did you choose black ... Sorry but this doesn't look good and I need to close your PR .Find another issue or feature to contribute to. Thank you!


ur_sim_moveit.launch.py launches two rviz instances

Affected ROS Driver version(s)
847d052b7c9154905386b6633aaf39e182887740
Used ROS distribution.
Humble
What combination of platform is the ROS driver running on.
Linux without realtime patch
How did you install the UR ROS driver
Build the driver from source and using the UR Client Library from binary
What robot platform are the driver connected to.
URSim in linux
Robot SW / URSim version(s)
N/A, running in Gazebo (not an option above)
How are you using the ROS driver
Others
Issue details
Summery
Running ros2 launch ur_simulation_ignition ur_sim_moveit.launch.py causes two instances of rviz to launch, when only one should.
Issue details
ur_sim_moveit.launch.py includes ur_sim_control.launch.py with "launch_rviz": "false", and ur_moveit.launch.py with "launch_rviz": "true",. However, two RViz instances are started.
From experimenting, it appears that the ur_moveit.launch.py launch_rviz argument is somehow leaking into ur_sim_control.launch.py. Setting it to false causes no instances of rviz to launch. Also, when it is true, commenting out delay_rviz_after_joint_state_broadcaster_spawner from ur_sim_control.launch.py results in the expected behavior of only the MoveIt RViz being started.
Steps to Reproduce
Run ros2 launch ur_simulation_ignition ur_sim_moveit.launch.py
Expected Behavior
One RViz launching
Actual Behavior
Two RViz's
Workaround Suggestion
Comment out delay_rviz_after_joint_state_broadcaster_spawner in ur_sim_control.launch.py
Relevant log output
No response
Accept Public visibility

[X] I agree to make this context public

Same as in https://github.com/UniversalRobots/Universal_Robots_ROS2_Gazebo_Simulation/issues/17


Can't use GetName

Attempting to use GetName results in bot.go:46: undefined: irc.GetName
I also can't find any other way to get my current nickname

irc.GetNick()

./madbot.go:69: undefined: irc.GetNick
That original was me copying the wrong thing from when I was just pretty much acting randomly out of sleep deprivation trying to make this work. GetNick is not working, and I've got a whole bot implemented otherwise with multiple network support and all that jazz so the library itself is working

Can i see the code in question? GetNick() is a function:
// Determine nick currently used with the connection.
func (irc *Connection) GetNick() string {
return irc.nickcurrent
}

https://gist.github.com/witheld9/a85dc5cfcc40c042d8bb here's an example where I try to use it in the function join

You're not using it correctly. GetNick is a method on the Connection object, but you're trying to call it as a method of the irc package, and that doesn't exist.
It looks like what you want to do is call either:
func join(event *irc.Event) {
nicktest := event.Connection.GetNick()
}

or
func join(event *irc.Event) {
nicktest := event.Nick
}

depending on what it is you actually want to achieve (the first, getting the nick of the bot, the second getting the nick of the instigator of the event)

That was it


Studio update images

Update outdated screenshots in the explore-ml-experiments page.
Update some of the text in this page to better fit the updated screenshots.

Completes https://github.com/iterative/dvc.org/issues/4679 and https://github.com/iterative/studio/issues/4770
Required png and gif files have been updated in the static repo in this commit.

@omesser Thanks for your review. I've replied to your comments - ptal.

@tapadipti what is the status of this?

@tapadipti what is the status of this?

@shcheklein I'll review the last comments by Oded and then merge this.

@omesser Thanks for your suggested text for the nested branches and commits on branch filter. I think it makes that section much clearer. I'll merge this PR now. But feel free to open a new issue if you think it needs some more revision.

The formatting check is failing for this PR. But it's complaining about a file that this PR does not touch (content/docs/user-guide/integrations/sagemaker.md). Can I ignore this? Who can suggest - is it @yathomasi?

@tapadipti Could you please run yarn fix-all and see if it fixes the file and commit and push the change would help ?

@yathomasi I ran yarn fix-all and now all these files have changes.
content/docs/user-guide/integrations/sagemaker.md
<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>src/components/Community/Section/styles.module.css
src/components/DownloadButton/styles.module.css
src/components/Home/LandingHero/styles.module.css
src/components/Home/LogosSlider/styles.module.css
src/components/Home/WhatsNewModal/styles.module.css
src/components/PromoSection/styles.module.css
src/components/Support/Popover/styles.module.css
src/components/Support/styles.module.css

Should I push just content/docs/user-guide/integrations/sagemaker.md?

It should be okay to commit and push them all

@yathomasi I couldn't commit all - it failed with stylelint --fix [FAILED]. So I just committed the sagemaker.md file. But now I've reverted even that, coz it's causing the following code block

to appear as

I could add \ in that command, but if it's been fine so far, I think it'll be ok now as well.


Can't open data viewer on a particular variable

Bug: Notebook Editor, Interactive Window, Editor cells

Steps to cause the bug to occur
Add the following:
#%%
import numpy as np
x = np.linspace(0, 20, 100)

And attempt to view the data table for the variable x.
Actual behavior
No buttons or clear way to open the data viewer appear, nor does double-clicking the variable work. Am also unable to sort the columns.

Expected behavior
There is a button shown that, when pressed, opens the data viewer:

(from docs)

Your Jupyter and/or Python environment
Please provide as much info as you readily know

Jupyter server running:                       Local
Extension version:                               2020.02.62710
VS Code version:                                1.42.0
Setting python.jediEnabled:               true
Python and/or Anaconda version:     3.7.6
OS:                                                     Mac
Virtual environment:                          N/A

Developer Tools Console Output
[Extension Host] Starting WebSocket: ws://localhost:8888/api/kernels/d695212e-f2d1-4b27-b1b3-e7d1fa42139b
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:19: Waiting for idle on (kernel): d695212e-f2d1-4b27-b1b3-e7d1fa42139b -> unknown
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:19: Initial setup complete for history://ec155b3b-dc18-49dc-9e99-9a948aa2f27b
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:19: restartKernel - initialSetup completed
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:19: Adding sys info for f696f14b-fb27-43a2-abe2-5ace774a50fd 1
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:19: Sys info for f696f14b-fb27-43a2-abe2-5ace774a50fd 1 complete
workbench.desktop.main.js:sourcemap:259 [Extension Host] Kernel: connected (d695212e-f2d1-4b27-b1b3-e7d1fa42139b)
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:19: Finished waiting for idle on (kernel): d695212e-f2d1-4b27-b1b3-e7d1fa42139b -> idle
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:30: Attempting to start a server because of preload conditions ...
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:30: Cached data exists getEnvironmentVariables, /path/to/test.py
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:36: Loading web panel. Panel is set
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:36: Wait for sys info for f696f14b-fb27-43a2-abe2-5ace774a50fd 0
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:36: Submitting code for f696f14b-fb27-43a2-abe2-5ace774a50fd
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:36: Loading web panel. Panel is set
2workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:36: Wait for sys info for f696f14b-fb27-43a2-abe2-5ace774a50fd 0
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:36: Adding hash for 1 = c6091b1a78db with 2 lines
workbench.desktop.main.js:sourcemap:259 [Extension Host] Info Python Extension: 2020-02-13 01:30:36: Finished execution for e08e5d3f-1ddf-43e8-af01-f0767e636ddd

Thanks for the bug. Numpy.ndarray is not currently supported. If you convert it to a list, it should work:
import numpy as np
x = np.linspace(0, 20, 100)
v = x.tolist()

Oh wait this used to work. Must be a typo somewhere.

Validated. Shows and can be opened in the data viewer for ndarray types.

Validated


Failed to import - Ink

Failing module

GitHub: https://github.com/vadimdemedes/ink
npm: https://www.npmjs.com/package/ink

import {render, Text} from<EMAIL_ADDRESS>
Error message
After running deno run I get this:
Uncaught TypeError: error sending request for url (https://cdn.esm.shchalk/): error trying to connect: dns error: No such host is known. (os error 11001)
    at https://cdn.esm.sh/v58/ink@3.2.0/build/components/Text.d.ts:2:33
    at async <anonymous>:2:28

Additional info

esm.sh version: v55
Deno version: 1.17.0

Problem Solved, Thanks 🙏🏻💡


Fixing error logging in indicies

Just a small typo I noticed when trying the es command for the first time.

Sorry for the long delay. This little utility is somewhat deprecated. It only works against ES 1.x, not 2.0 or later. Also, it should have been rewritten to use elastic under the covers, which it only does in some areas. However, I'm not able to find any spare time for a rewrite. Sorry.

@olivere thanks for merging this. Do you like the direction I'm taking here:
https://github.com/olivere/es/compare/master...proletariatgames:use_lib

TBH I'd like the es tool abandoned in favor of a new command-line tool completely based on/directly integrated into Elastic (e.g. with a main.go in the github.com/olivere/elastic/cmd/es directory). The es tool pre-dates Elastic, its /_cat endpoints, curator etc. es still doesn't use Elastic for all commands. I'd also like es to be independent of the ES version (1.x, 2.x, 5.x). But I really don't have the time to do that ATM.


Missing requirements

There were some additional requirements not mentioned in the README (or a requirements file). That might be because of an assumption that the user has Anaconda instead of a vanilla pip environment. In any case, this also requires sklearn and scipy, which you don't get from merely pip installing pytorch.

Oh. You are absolutely right. Thank you for your kind reminder 😄


doc: use travis badge

Types of changes

[ ] Bug fix (a non-breaking change which fixes an issue)
[ ] New feature (a non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Description

Checklist:

[ ] My change requires a change to the documentation.
[ ] I have updated the documentation accordingly. (PR: #)
[ ] I have added tests to cover my changes (if not applicable, please state why)
[ ] All new and existing tests are passing.

Codecov Report

Merging #4169 into dev will not change coverage.
The diff coverage is n/a.

@@          Coverage Diff          @@
##             dev   #4169   +/-   ##
=====================================
  Coverage   81.8%   81.8%
=====================================
  Files         29      29
  Lines       1561    1561
  Branches     409     409
=====================================
  Hits        1277    1277
  Misses       224     224
  Partials      60      60

Continue to review full report at Codecov.

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@clarkdo

Close this pr since #4190


fixed 64 bit variables on 32 bit machine

this fixes u64/s64 read/write functions on 32 bit builds.
see https://github.com/CANopenNode/CANopenSocket/issues/8

I still get a load of compile warnings from co_trace.c about non fitting printf arguments, but I don't really care about those...


Argument Types for Validation Rules

I created the following rule:
public function not_blocked(int $mebn_seq): bool   {     return !(new MebnDb())->isBlocked($mebn_seq);   }
It errored because $mebn_seq is declared as an int. I had to declare it as  'string' and cast my argument using (int):
return !(new MebnDb())->isBlocked((int)$mebn_seq);
I don't believe I should have to do this.

Hello!
We are using GitHub for tracking bugs and issues related to CI 3 itself. Please use our forums if you need help with your project.


runAsGroup is referenced on explanation but is missing from code example

This is a...

[ ] Feature Request
[x] Bug Report

Problem:
security-context.md references a runAsGroup parameter which was supposed to exist on the security-context.yaml code example. However the code does not include the parameter.
Proposed Solution:
Update security-context.yaml code example to include the runAsGroup parameter.
Page to Update:
https://kubernetes.io/docs/tasks/configure-pod-container/security-context/#set-the-security-context-for-a-pod

/assign

Thanks @rjmco for this bug report, I was wondering If I should create a bug for this ? :+1:

@doog33k I'm not sure if I will be able to answer your question, but from my point of view I thought this issue was considered already a bug report on the website's content. If on the other hand you mean a bug report on Kubernetes' codebase then I don't think that is required.
Finally, I've already created PR #13538 where I've submitted a possible fix to this issue/bug on the website's content.
Let me know if I have clarified your question or I misunderstood it completely.

Closed by #13538.


docker 执行 docker-compose up 报错

=============================DEBUG ASSISTANCE=============================
  If you are seeing a compilation error please try the following steps to
  successfully install cryptography:
  1) Upgrade to the latest pip and try again. This will fix errors for most
     users. See: https://pip.pypa.io/en/stable/installing/#upgrading-pip
  2) Read https://cryptography.io/en/latest/installation.html for specific
     instructions for your platform.
  3) Check our frequently asked questions for more information:
     https://cryptography.io/en/latest/faq.html
  4) Ensure you have a recent Rust toolchain installed:
     https://cryptography.io/en/latest/installation.html#rust
  5) If you are experiencing issues with Rust for *this release only* you may
     set the environment variable `CRYPTOGRAPHY_DONT_BUILD_RUST=1`.
  =============================DEBUG ASSISTANCE=============================

error: Can not find Rust compiler
ERROR: Failed building wheel for cryptography
ERROR: Could not build wheels for cryptography which use PEP 517 and cannot be installed directly
是不是pip版本太老了

加上
ENV CRYPTOGRAPHY_DONT_BUILD_RUST=1


RackResponse includes the reason phrase

Someone double check this, I'm multi-tasking and don't trust myself right now.

@JoshCheek everything looks good. Thank you!


[SPARK-11649] Properly set Akka frame size in SparkListenerSuite test

SparkListenerSuite's "onTaskGettingResult() called when result fetched remotely" test was extremely slow (1 to 4 minutes to run) and recently became extremely flaky, frequently failing with OutOfMemoryError.
The root cause was the fact that this was using System.setProperty to set the Akka frame size, which was not actually modifying the frame size. As a result, this test would allocate much more data than necessary. The fix here is to simply use SparkConf in order to configure the frame size.

Test build #46264 has started for PR 9822 at commit 1ae1391.

It already passed the test. Merging into master 1.6.

Test build #46264 has finished for PR 9822 at commit 1ae1391.

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

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/46264/
Test PASSed.


Reverse for 'my_test_app_view' not found

I installed Django-CMS via installer some time ago but think I have since not used the installed. Still getting
reverse('my_test_app_view'): Reverse for 'my_test_app_view' with arguments '()' and keyword arguments '{}' not found. 0 pattern(s) tried: []
I can't find any reference in my repo. Where does this come from and how do I get rid of this?

@maltebeckmann
Hi there, the code responsible for this is in https://github.com/divio/django-cms/blob/develop/cms/utils/apphook_reload.py#L96. This is called by the apphook reload middleware.
As you can see, it will only show up if DEBUG = True.
That said, I think this (as most of the times prints are used) is a great case for logging..

Thanks!

@czpython So what does this message tries to say a user who has just installed django-cms using the installer wizard and expecting that there will be no warnings there on this stage? I don't see any references of 'my_test_app_view' in django-cms except in this file.
And how to get rid of it? I need DEBUG=True for other things, it is not an option for me to turn it off.

Why is this closed when it is still present there?

user who has just installed django-cms using the installer wizard and expecting that there will be no warnings there on this stage? I don't see any references of 'my_test_app_view' in django-cms except in this file.????

Why is this closed? I have the same issue, and it makes no sense to see a warning unless there is something to fix.

The original question was solved. I've created a ticket to track the issue https://github.com/divio/django-cms/issues/5448


[functionapp] add support for runtime versions

Fixes  https://github.com/Azure/azure-cli/issues/10766 (https://github.com/Azure/Azure-Functions/issues/1355)
Fixes https://github.com/Azure/azure-cli/issues/10549 (https://github.com/Azure/Azure-Functions/issues/1341)
cc: @Hazhzeng @divyagandhii

This checklist is used to make sure that common guidelines for a pull request are followed.

[x] The PR has modified HISTORY.rst describing any customer-facing, functional changes. Note that this does not include changes only to help content. (see Modifying change log).

[x] I adhere to the Command Guidelines.

Please fix errors in CI.
Be careful with runtime, runtime.lower(), runtime.upper().
Thanks.

CI is stuck, closing and re-openening

@qwordy please help with this PR.


How convert darknet model to onnx?

Hi,
Can someone give me instructions how convert my custom darknet model (yolov2-tiny) to ONNX? I know I should convert my darknet model to tensorflow, then to onnx, but I struggle with this for several days.
What I've tried:
Convert darknet model (weights + cfg) to tensorflow using darkflow -> I got .pb file (SUCCESS)
Then I wanted to convert pb file to onnx:

Tried to convert pb file to onnx using mmconvert:
mmconvert -sf tensorflow -iw path_to_my_pb_file -df onnx -om yolotfonnx --inNodeName input --dstNodeName output
error:
TypeError: can only concatenate list (not "NoneType") to list
Tried to convert using tf2onnx:
python3 -m tf2onnx.convert --graphdef path_to_my_pb_file --output yolov2-tiny.onnx --inputs input:0 --outputs output:0
error:
AssertionError: output is not in graph

this also doesn't work:
python3 -m tf2onnx.convert --saved-model path_to_my_pb_file --output yolov2-tiny.onnx
error:
RuntimeError: MetaGraphDef associated with tags 'serve' could not be found in SavedModel. To inspect available tag-sets in the SavedModel, please use the SavedModel CLI: `saved_model_cli`
available_tags: []

Tried to convert using onnx-tf:
onnx-tf convert -i path_to_my_pb_file -o path_for_output_onnx_file
error:
ValidationError: The model does not have an ir_version set properly.

I think darkflow can be not compatible with yolov2-tiny. I also tried to convert original darknet yolov2 model and have same problems after conversion with darkflow.

Hi @michalek-marcin ,
Did you freeze the tf graph to convert model parameters into constants? You may need tf weights (.ckpt, you can get it here: DW2TF) and the tf graph (.pb). Somthing like this:
python3 -m tensorflow.python.tools.freeze_graph --input_graph=./checkpoint_dir/yolov2-tiny.pb --input_binary=true --output_node_names=yolov2-tiny/convolutional9/BiasAdd --input_checkpoint=./checkpoint_dir/yolov2-tiny.ckpt --output_graph=./checkpoint_dir/yolov2-tiny-freeze.pb
I then convert the frozen graph to onnx through:
python3 -m tf2onnx.convert --graphdef ./yolov2-tiny-freeze.pb --output yolov2-tiny.onnx --inputs yolov2-tiny/net1:0 --outputs yolov2-tiny/convolutional9/BiasAdd:0
Make sure you use the correct graph inputs and outputs.

Hi @derenlei ,
I found different solution.

Convert darknet weights and cfg to keras
Convert keras to coreml
Convert coreml to onnx

Tools which I used:
https://github.com/hollance/YOLO-CoreML-MPSNNGraph
https://github.com/onnx/onnxmltools
I got onnx file and it looks good, but when i paste my model and change DetectorYolo2 component on scene it doesn't work:

Here is my onnx file:
https://drive.google.com/file/d/110foE_F0fDRtKByt-dFjyHb8EeVqDkOu/view?usp=sharing

Ok, I tried your method @derenlei and I have new Onnx file, but I think I did something wrong. Maybe I wrote wrong output node name? I need to understand how read neural network graph in Netron.
What I did:

https://github.com/jinyu121/DW2TF
python3 main.py --cfg 'tiny/yolov2-tiny-custom.cfg' --weights 'tiny/yolov2-tiny-custom_final.weights' --output 'data/' --prefix 'yolov2-tiny/' --gpu 0

Freeze graph
python3 -m tensorflow.python.tools.freeze_graph --input_graph='/home/ubuntu/Downloads/DW2TF-master/data/yolov2-tiny-custom.pb' --input_binary=true --output_node_names=yolov2-tiny/convolutional22/BiasAdd --input_checkpoint='/home/ubuntu/Downloads/DW2TF-master/data/yolov2-tiny-custom.ckpt' --output_graph='/home/ubuntu/Downloads/DW2TF-master/data/yolov2-tiny-custom_freeze.pb'

https://github.com/onnx/tensorflow-onnx
python3 -m tf2onnx.convert --graphdef '/home/ubuntu/Documents/yolo/yolov2-tiny-custom_freeze.pb' --output yolov2-tiny.onnx --inputs yolov2-tiny/net1:0 --outputs yolov2-tiny/convolutional9/BiasAdd:0

Here are my files (cfg, weights and onnx):
https://drive.google.com/drive/folders/1GXXe2ej5w8pKkM4XNPDrPArxFUTHa3YD?usp=sharing
My classes:
emiratestower-left
emiratestower-right
emiratestower-back

Hi,
I tried your 'yolov2-tiny_freeze' model and I think it works well. Set the INPUT_NAME to yolov2-tiny/net1 and OUTPUT_NAME to yolov2-tiny/convolutional9/BiasAdd. Also, we use different scripts for yolov2 and v3 so make sure the Selected_detector under Camera Image is yolov2.

@derenlei's first answer worked for me. Though for a noob like me it was quite difficult to figure out the parameters and tech stack versions I needed to use in order to get it working.
I summarized all the steps I did in my Jupyter Notebook that I uploaded here: https://github.com/DaphiFluffi/Yolov3-To-Onnx-Unity. It converts a Darknet-trained yolov3-tiny model into a Tensorflow model, then into a frozen Tensorflow Graph and then into the Barracuda format. You can open it in Google Colab.
Feel free to use it. I tried to describe everything as noob-friendly as I could. I hope it helps ✌

Hello, I'm having a hard time converting the darknet yolov2 model to onnx.
It has been converted but does not detect anything when running Barracuda.
I want to know in detail how you did it, is it possible?
https://github.com/derenlei/Unity_Detection2AR/issues/39
Here's what I tried.

I remember that my converted model also didn't detect anything in Unity. Somebody wrote this under the repository I posted. Maybe it helps:
_

For others coming here from Derenley's repo, i used @Kanyade 's answer from this issue https://github.com/derenlei/Unity_Detection2AR/issues/29 and my model is working now

_

Hello @jjeongmin0308 @DaphiFluffi
This was the final colab snippet with which I converted the model successfully which can also be found at the end of the issue linked by Daphi:
https://gist.github.com/Kanyade/c8ee3b7eca6f6e470e418b018ea02e83
Please note that there may be redundant parts as I just copied it from a project of mine to share.
Also note that the project the snippet is based on (https://github.com/jkjung-avt/tensorrt_demos) had been updated since then so it may or may not work with its latest version but you can always switch back to an earlier version.


chore: Added LitmusCon Event Details

@hrishavjha is attempting to deploy a commit to the Harness Chaos Team Team on Vercel.
A member of the Team first needs to authorize it.

Deployment Failed at first due to dev.to API getting timed-out.


Add explainer for Run on OS Login

For those who wonder what happened with this PR. We'll post a new one and merge the explainer soon.


VoID file changes might not take into account changes in data by uploading the void file it self.

We have code in the virtuoso side that takes this into account. I need to test that this works for the standard sparql update.
Distinct object/subject counts are at risk (especially for the total endpoint.)

I think that this situation may not always have a solution.
For example, consider the following very simple dataset:
ex:idA ex:prop1 1.
ex:idB ex:prop2 3.

This dataset contains two distinct objects. If we add this information to the dataset, then the dataset will contain three distinct objects:
ex:idA ex:prop1  "1"^^xsd:long .
ex:idB ex:prop2  "3"^^xsd:long .
[] void:distinctObjects "2"^^xsd:long .

If we try to update this value, then the dataset will contain only two distinct objects:
ex:idA ex:prop1  "1"^^xsd:long .
ex:idB ex:prop2  "3"^^xsd:long .
[] void:distinctObjects "3"^^xsd:long .

Thus, there are situations when it is not possible to store the correct number of distinct objects in the database.

I noticed that the VoID standard contains the following sentence:

As a general rule, statistics in VoID can always be provided as approximate numbers.

So I think that this issue can be closed.


Debbit v.2.1 thread error

Running into this thread error using debbit 2.1
I have two Amazon reloads. The first one goes through but not the second one.
Thanks in advance!

Can you post your config.txt? Remove your username, password, and card number of course. I have a feeling that your amount_min and amount_max are the same and Windows is handling this situation weird.

Here it is:

I found out why, the amount_min/max for one of the payment has decimals, should have been in integers of cents.


let listener command print at a certain rate

As discussed with @bkueng
It would be really great if the listener command supported printing at a less than maximum rate,
something like
listener ekf2_innovations 60 -f 1

to print 60 ekf2_innovation messages at 1 Hz

Hey, this issue has been closed because the label status/STALE is set and there were no updates for 30 days. Feel free to reopen this issue if you deem it appropriate.
(This is an automated comment from GitMate.io.)


Cannot load the config file

It doesn't load my config file and falls back to the default config.
I just changed the proxy listen_mode from "loopback_only" to "all_interfaces" in my new config file, and run it using the following command:
$ java -jar burp-rest-api/build/libs/burp-rest-api-1.0.0.jar --config-file=/tmp/project-options.json
Log:
2017-08-01 06:59:16.239  INFO 28104 --- [           main] c.vmware.burp.extension.BurpApplication  : Starting BurpApplication v1.0.0 with PID 28104 (burp-rest-api/build/libs/burp-rest-api-1.0.0.jar started by ec2-user in /tmp/burp)
2017-08-01 06:59:16.265  INFO 28104 --- [           main] c.vmware.burp.extension.BurpApplication  : No active profile set, falling back to default profiles: default
2017-08-01 06:59:16.457  INFO 28104 --- [           main] ationConfigEmbeddedWebApplicationContext : Refreshing org.springframework.boot.context.embedded.AnnotationConfigEmbeddedWebApplicationContext@36f8f43d: startup date [Tue Aug 01 06:59:16 UTC 2017]; root of context hierarchy
...
2017-08-01 06:59:21.025  INFO 28104 --- [           main] c.v.burp.extension.service.BurpService   : Launching the Burp suite (pro edition) in headless mode...
2017-08-01 06:59:21.033  INFO 28104 --- [           main] c.v.burp.extension.service.BurpService   : Launching the Burp suite with options: [--project-file=temp-project.burp, --config-file=/tmp/project-options8553372049623231948.json, --config-file=/tmp/user-options2287475060260215367.json]
Proxy: Proxy service started on <IP_ADDRESS>:8080

Same even after providing --config-file path, the the default config getting set.

This is a bug. There's no code to handle situations when there's a user-supplied config file but no project data file. I will push a new PR with the fix for this.

I believe I am running into this issue on 1.0.2 still.

Great - I am happy! @gangelino we can close this one - one more done!

Thanks guys :)


cob_android: 0.1.7-2 in 'kinetic/distribution.yaml' [bloom]

Increasing version of package(s) in repository cob_android to 0.1.7-2:

upstream repository: https://github.com/ipa320/cob_android.git
release repository: https://github.com/ipa320/cob_android-release.git
distro file: kinetic/distribution.yaml
bloom version: 0.9.3
previous version for package: 0.1.6-1

cob_android

No changes

cob_android_msgs
* Merge pull request #38 <https://github.com/ipa320/cob_android/issues/38> from fmessmer/ci_updates
  [travis] ci updates
* catkin_lint fixes
* Contributors: Felix Messmer, fmessmer

cob_android_resource_server
* Merge pull request #39 <https://github.com/ipa320/cob_android/issues/39> from fmessmer/feature/python3_compatibility
  [ci_updates] pylint + Python3 compatibility
* fix pylint errors
* python3 compatibility via 2to3
* Contributors: Felix Messmer, fmessmer

cob_android_script_server
* Merge pull request #39 <https://github.com/ipa320/cob_android/issues/39> from fmessmer/feature/python3_compatibility
  [ci_updates] pylint + Python3 compatibility
* fix pylint errors
* python3 compatibility via 2to3
* Contributors: Felix Messmer, fmessmer

cob_android_settings

No changes

I think travis just needs a restart....?

I think travis just needs a restart....?

Yeah, I'll close and reopen to kick travis again.

Holding for sync


Translate video titles

Currently video titles do not translate within Vimeo embed. This could be accomplished via a Vimeo feature (will enquire) or via markdown.

This is achievable using the title parameter for the Verto video tag. Moving this out of the 3.0 milestone as it's not critical for release, and part of our ongoing translation work. Subtitles for the videos are more important (and generally contain the title anyway).


Funny compiler bug

ExampleVGMPlay - Archive  [Date 2023.01.30  Time 00.48].zip
Apparently setting _CLKFREQ from a subobject constant is busted in 2.9.2. The changelog alleges that such an issue has been fixed, but I guess this is an edge case?

Are you getting a compiler error, or a runtime error of some sort?  I compiled your example starting from "ExampltVGMPlay.spin2" and it compiled successfully.

Oh yes, it's a run-time problem. Connect audio to appropriate pins and marvel at the difference between the given _clkfreq expression and setting it to 320_000_000 (or anything else, really)

Maybe I'm missing something somewhere, but what I see is exactly what it should be:
The subobject's OPN_SAMPLE_RATE value is 55555 (which is 8,000,000 / (646))
and 55555 * 256 * 23 is 327,107,840 which is exactly what Propeller Tool shows the _CLKFREQ constant was set to:

Yep, it shows the correct value, but is broken at runtime

Clock settings are going to be computed for each object, according to any clock-setting symbols present. Only the top file's setting will be used, in the end. Child objects should be checking the runtime variable "clkfreq" to get the actual clock frequency. Any child object that relies on its own compile-time clock settings can wind up out of tune with the top file's setting which was used on application start-up. Am I not understanding something, though, Wuerfel21?

No, the problem is setting the top-level clkfreq to an expression involving a constant from a sub-object. Just download the the archive in OP and see it for yourself. Surely you got one of those DAC boards around.

That should be fixed in v38 of PNut.
On Fri, Feb 3, 2023 at 12:34 PM Wuerfel21 @.***> wrote:

No, the problem is setting the top-level clkfreq to an expression
involving a constant from a sub-object. Just download the the archive in OP
and see it for yourself. Surely you got one of those DAC boards around.
—
Reply to this email directly, view it on GitHub
https://github.com/parallaxinc/Propeller-Tool/issues/176#issuecomment-1416373228,
or unsubscribe
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Cannot read property 'setNativeProps' of undefined

I have
TabNavigator({
user: {
screen: StackNavigator ({
userSetting: { screen: UserSetting }
})
},
shop: {
screen: StackNavigator ({
shopScreen: { screen: Shop}
}, {
navigationOptions: {
tabBarVisible: false,
}
})
},
support: {
screen: StackNavigator ({
supportScreen: { screen: Support}
})
}
So I set tabBarVisible false on shop child element...but I cant navigate on support it crashes withCannot read property 'setNativeProps' of undefined

I'm having the same problem with a similar setup.
Anybody got a solution to this?

+1
Works on Android but not iOS

@josephrstraub how did you get it to work on android?

I have the same issue with the similar setup: it occurs on switching between tabs, when one of the tab has tabBarVisible: false. And I'm also having this error only in iOS.

It seems like an error is not thrown when the screen you are navigating too also has the tab bar hidden.

👍  Encountered this issue too. Commenting out the tabBarVisible: false fixes the issue. Using iOS simulator and<EMAIL_ADDRESS>(though I still need to figure out a workaround to hide the tab bar)

I also encountered this issue and resolved it with taking away the tabBarVisible: false
Though I might add this issue came up when I both set route config dynamically AND statically

Can confirm issue is happening as described, and removing tabBarVisible "resolves" the issue

+1 If it's intended behavior will be nice to have noted in docs

Have same problems with master branch
For me unstable workaround is to add setTimeout in componentDidUpdate in TabViewPagerPan in node_modules/react-navigation/node_modules/react-native-tab-view to
  componentDidUpdate(prevProps: Props<T>) {
    if (prevProps.navigationState.index !== this.props.navigationState.index) {
      setTimeout(this._transitionTo, 0, this.props.navigationState.index);
    }
  }

I think this is what happening: TabBar from react-navigation and TabViewPagerPan are both children of TabViewAnimated and they share animated value for nav index (TabViewAnimated.state.position). However, when nav state changes, it is not TabViewAnimated who starts animated transition, but  TabViewPagerPan. It does so in its own componentDidUpdate, but because TabBar is not its child, it is not mounted yet.
I also would like to know, if it is intended behavior (i.e. react-native-tab-view assumes that footer/header doesn't get mounted and unmounted). If it is so, the correct workaround is to manage TabBar visibility from inside your own custom TabBar wrapper.

I am getting the same error when switching between a tab that hides the tabBar and another that shows the tabBar. Everything works fine if both tabs use the same tabBarVisible value.
Can't read property 'setNativeProps' of undefined

Running into the same issue right now. @doomsower, can you give an example of the TabBar wrapper that you mentioned? Maybe we can reset the tabBarVisible option to true right before we navigate?

I need this behavior in different tab views, so I wrote this.
const styles = StyleSheet.create({
  hidden: {
    height: 0,
    opacity: 0,
  },
});

const TabBarFactory = (ignoreIndices: number[] = []) => {

  const TabBar: React.StatelessComponent<Props> = (props) => {
    const { navigationState } = props;
    const hidden = ignoreIndices.includes(navigationState.index);
    const style = hidden ? styles.hidden : undefined;
    return (
      <View collapsable={false} style={style}>
        <TabBarBottom {...props} />
      </View>
    );
  };

  return TabBar;

};

I also use TabBarBottom on both platforms.

This worked a charm for me:
import { Animated } from 'react-native';
import { TabView, TabBarBottom } from 'react-navigation';

const TAB_BAR_OFFSET = -60;

export default class MyTabBar extends Component {
  constructor(props) {
    super(props);
    this.state = {
      offset: new Animated.Value(0),
    };
  }

  componentWillReceiveProps(props) {
  const newState = props.navigation.state;
  const newRoute = newState.routes[newState.index];

  if (newRoute.key === 'Home') {
    // Animated.timing(this.state.offset, { toValue: TAB_BAR_OFFSET, duration: 200 }).start();
    this.state.offset.setValue(TAB_BAR_OFFSET);
  } else {
    // Animated.timing(this.state.offset, { toValue: 0, duration: 200 }).start();
    this.state.offset.setValue(0);
  }
}

  render() {
    return (
      <TabView.TabBarBottom
        {...this.props}
        jumpToIndex={index => {
          const { dispatch, state } = props.navigation

          if (state.index === index) {
            const stackRouteName = ['Tab1', 'Tab2', 'Tab3', 'Tab1'][index]

            dispatch(NavigationActions.reset({
              index: 0,
              actions: [NavigationActions.navigate({ routeName: stackRouteName })],
            }))
          } else {
            jumpToIndex(index)
          }
        }}
        style={[styles.container, { bottom: this.state.offset }]}
        />
        // <TabBarBottom {...this.props} style={[styles.container, { bottom: this.state.offset }]}/>
    );
  }
}

const styles = {
  container: {
    overflow: 'hidden',
    position: 'absolute',
    bottom: 0,
    left: 0,
    right: 0,
    backgroundColor: 'white',
    elevation: 8,
  },
};

Based on @doomsower idea, I made a PR  #2101 . It would great to have some feedback and more testing, branch: https://github.com/gusgard/react-navigation.git#patch-1
@veljkomatic @mcampsall @EslamNasser

I get the same issue as the OP (Cannot read property 'setNativeProps' of undefined) when rapidly changing the items in the tab bar (this currently happens during login in my app; the tabs all go away while loading user profile, then new tabs appear soon after).
Interestingly, setting animationEnabled: true prevents the error 👍. The PR #2101 didn't change anything for me, but I have a different cause than most other commenters here; it would be good if someone else could test out that PR.

Here's my workaround (very simple change to add a 10ms delay) and associated update to react-navigation if anyone wants to use it in their app. It's not PR-worthy since it's just a hacky workaround, but at least it works.

mark

This bug will fixed when I set animationEnabled = false for TabNavigator

I'm getting this error only when I build the app on release mode, the screens that I'm testing are not using TabNavigator:
this._component.setNativeProps is not a function. (In 'this._component.setNativeProps(e)', 'this._component.setNativeProps' is undefined)
2017-11-06 12:05:55.048 [fatal][tid:com.facebook.react.ExceptionsManagerQueue] Unhandled JS Exception: this._component.setNativeProps is not a function. (In 'this._component.setNativeProps(e)', 'this._component.setNativeProps' is undefined)
libc++abi.dylib: terminating with uncaught exception of type NSException

I found out that the error is coming from https://github.com/react-community/react-navigation/blob/d1c434b54c73b6ed17b1642acd6646fbca92c92e/src/views/CardStack/PointerEventsContainer.js#L86 commenting out that same line gets rid of it.

if someone wants to dig in and submit a PR for a fix that would be great. even sharing a full working example would be good.

@brentvatne Could you review this PR https://github.com/react-navigation/react-navigation/pull/2101 ? Is working with version 1.0

Anyone know whats the solution for this? I'm using 1.5.9.
In earlier version i could enable animation and overwrite configureTransition with 10 ms duration, but with new its not working now.

For now instead of setting tabBarVisible false, I am setting style of tabbar absolute.
{
    position: 'absolute',
    bottom: -100
}

this solves the issue for now.


fix: fixed testset columns naming conventions

Description
Fixed the test set colums naming conventions by making it lowercase.
Screenshot

Issue
Closes #1737

The primary issue is with the ag-grid-react library used to generate the test set tables. This library does not allow styling of the column header names.The library, by default, uses CamelCase format for column headers.

To fix this issue, I am using the column names that are coming from the database, rather than the names provided by the library.
Code Changes:

Using the inputValues as header name which is comming from the database insead of displayName which is provided by the ag-grid-react library.
Implemented a setTimeout function to prevent the glitch associated with name changing. The glitch is between previous name and the new name.

I don't understand the changes that you have made and why you have made them..
The way I would tackle this is the following: Somewhere in the code we are transforming the input made by the user and uppercasing the first letter (unless this is the default behavior in ant.design which is very likely), you need to find that part and remove it. That's it.

The code is fine, the uppercase formatting is a characteristic of the ag-grid-react library that are used to create the testset tables. This library by default CamelCase column headers.
ag-grid-react library doc: https://www.ag-grid.com/react-data-grid/column-headers/#header-name

The primary issue is with the ag-grid-react library used to generate the test set tables. This library does not allow styling of the column header names.The library, by default, uses CamelCase format for column headers.

To fix this issue, I am using the column names that are coming from the database, rather than the names provided by the library.
Code Changes:

Using the inputValues as header name which is comming from the database insead of displayName which is provided by the ag-grid-react library.
Implemented a setTimeout function to prevent the glitch associated with name changing. The glitch is between previous name and the new name.

Thanks for the explanation and for sharing the link to the documentation. I think you misunderstood the documentation. See the example that they provide, if the user specifies field they would use a camel case, if the user provides a headerName they use it as is. I think we just need to use headerName and that would resolve the issue, no?

I apologize for everything @mmabrouk, I misunderstood the documentation. Also, thank you @bekossy, for the direction.

Awesome work @ashrafchowdury however we also need to do the same when we add a new column

@all-contributors please add @ashrafchowdury for bug fix and code


Proxy support

This is untested as, for some reason, the compiled Electron app produced by ./deploy.sh refuses to run on my laptop. No idea why! That is a problem for another day.
There's the potential for a race condition here if the app attempts to communicate before the resolveProxy calls return. They should complete pretty quickly, however, and any errors will hopefully be ironed out by the retry logic. If there's a more intelligent place to move the calls to to ensure they execute before any network traffic is attempted, by all means do so.
Ref #3

hey why don't you add these things yourself. sent invitation. the more the merrier. :D

I see you have foiled my sneaky plan to get you to test this for me. Well played!
Worked around the segfault. Logged the issue with Electron here: https://github.com/atom/electron/issues/2050
All of this appears to be functioning correctly. The only way I have to test this is by using Charles to proxy my connection locally. This technique has served me well in the past, however there is some serious Wild West stuff going on with proxies in educational and corporate environments. Alls I'm saying is we shouldn't be shocked to see edge cases from users.

I'll merge this in as soon as I've got a :+1: from an existing contributor that we're happy with the code style, etc  (4 space indentation? You monsters!).

how worried are we about that race condition? I mean if we have the slightest concern, it's pretty darn easy to ensure there's no network activity too early.
the entire hangupsjs starting point is this row:
    # first connect
    reconnect().then ->

but if we're not worried then lgtm
+1

Ah! Yes. If it's that straightforward then yes, absolutely makes sense to delay starting the network activity until the proxy stuff is done.
I'll make the changes.

Sweet! +1


Drag & Drop

Hi there!
I know you mention drag & drop in your TODO section. Is this in the works? Would it be very hard to implement? I'm trying to determine if I can use re-com for an upcoming project and drag & drop is a key feature.
:smile:

We've certainly done drag and drop interfaces, and they work :-)
Most  issues you run into will be around using the HTML5 DnD API  (which is a pig).
The other issue that puzzled us for a while were reagent-related ones  ... we attached drag-end type event handlers to elements and then we'd remove those elements (because stuff was happening in response to the drag), and then wonder why we weren't getting drag-end events.   Given the HTML DnD API is so distractingly bad to deal with,  this issue took us a while to figure out.
So, I guess I'm saying that there are no issues for re-com around drag-drop.  Your challenges will be elsewhere.   :-)

Thanks for the input!
Trying to sort out our requirements now - I'm hoping to be able to use this :+1:


Missing HTML executor

Type: Feature Request
unable to execute HTML files
VS Code version: Code 1.91.1 (Universal) (f1e16e1e6214d7c44d078b1f0607b2388f29d729, 2024-07-09T22:07:54.982Z)
OS version: Darwin arm64 24.1.0
Modes:

/needsMoreInfo
what do you mean - execute html files?
You should be able to open file in browser or create run/debug configuration that would open it


how to change calendar style

how to hide calendar border style,i have delete the style in style.styl or add new style to cover,
but it is no effect.
.vdp-datepicker__calendar{
border: none !important;
}

how to hide calendar border style,i have delete the style in style.styl or add new style to cover,
but it is no effect.
.vdp-datepicker__calendar{
border: none !important;
}

I've tested your sample, it works just fine, probably you are using scoped component styles, that's why it doesn't work

Does styling the calendar require an !important declaration on every CSS property you wish to override?

Does styling the calendar require an !important declaration on every CSS property you wish to override?

You should use !important keyword only for existed properties, take a look in inspect tool and you can add new property without !important

i just tested his issue and it should works even without !important flag

i just tested his issue and it should works even without !important flag

It depends on your architectural stack, for example, how do you import calendar style, anyway I'm sure that it works with !important, if it works without overriding property I'm glad...

how to hide calendar border style,i have delete the style in style.styl or add new style to cover,
but it is no effect.
.vdp-datepicker__calendar{
border: none !important;
}

I've tested your sample, it works just fine, probably you are using scoped component styles, that's why it doesn't work

Scoped... thank you good sir for mentioning this.


vscode terminal with canvas renderer mode don't handle resize event

Does this issue occur when all extensions are disabled?: Yes

VS Code Version: 1.73.1
OS Version: Ubuntu 20.04, Ubuntu 22.04

Steps to Reproduce:

change Terminal > Integrated: Gpu Acceleration to canvas
open a terminal, run top, then resize that terminal.

working for me
I believe this is already fixed, can you see if you can reproduce in the Insiders build?
/label info-needed


Apply SimOTA on FCOS with Centerness instead of IoU

Prerequisite

[X] I have searched the existing and past issues but cannot get the expected help.
[X] I have read the FAQ documentation but cannot get the expected help.
[X] The bug has not been fixed in the latest version.

🐞 Describe the bug
Using SimOTA on FCOS with centerness will produce wrong target bounding box for centerness target.
@HEADS.register_module()
class MyHead(FCOSHead):
    """ FCOS Head with simOTA Assigner """
    def __init__(self,
                 num_classes,
                 in_channels,
                 loss_lqe=dict(
                     type='CrossEntropyLoss',
                     use_sigmoid=True,
                     loss_weight=1.0
                 ),
                 **kwargs):
        super(MyHead, self).__init__(
            num_classes,
            in_channels,
            **kwargs
        )
        self.loss_lqe = build_loss(loss_lqe)
        assigner_cfg = dict(type='SimOTAAssigner',
                            center_radius=2.5,
                            candidate_topk=10)
        self.assigner = build_assigner(assigner_cfg)
        sampler_cfg = dict(type='PseudoSampler')
        self.sampler = build_sampler(sampler_cfg, context=self)

    def _bbox_decode(self, priors, bbox_preds):
        """ Convert [l, t, r, b] bbox format to [x1, y1, x2, y2] bbox format """
        x1 = priors[..., 0] - bbox_preds[..., 0]
        y1 = priors[..., 1] - bbox_preds[..., 1]
        x2 = priors[..., 0] + bbox_preds[..., 2]
        y2 = priors[..., 1] + bbox_preds[..., 3]
        return torch.stack([x1, y1, x2, y2], dim=-1)

    def _bbox_encode(self, priors, bbox_targets):
        """ Convert [x1, y1, x2, y2] bbox format to [l, t, r, b] bbox format """
        left = priors[..., 0] - bbox_targets[..., 0]
        top = priors[..., 1] - bbox_targets[..., 1]
        right = bbox_targets[..., 2] - priors[..., 0]
        bottom = bbox_targets[..., 3] - priors[..., 1]
        return torch.stack([left, top, right, bottom], dim=-1)

    def centerness_target(self, pos_bbox_targets):
        """Compute centerness targets.

        Args:
            pos_bbox_targets (Tensor): BBox targets of positive bboxes in shape
                (num_pos, 4)

        Returns:
            Tensor: Centerness target.
        """
        # only calculate pos centerness targets, otherwise there may be nan
        left_right = pos_bbox_targets[:, [0, 2]]
        top_bottom = pos_bbox_targets[:, [1, 3]]
        if len(left_right) == 0:
            centerness_targets = left_right[..., 0]
        else:
            centerness_targets = (
                left_right.min(dim=-1)[0] / left_right.max(dim=-1)[0]) * (
                    top_bottom.min(dim=-1)[0] / top_bottom.max(dim=-1)[0])
        return torch.sqrt(centerness_targets)

    @force_fp32(apply_to=('cls_scores', 'bbox_preds', 'objectnesses'))
    def loss(self,
             cls_scores,
             bbox_preds,
             lqe_preds,
             gt_bboxes,
             gt_labels,
             img_metas,
             gt_bboxes_ignore=None):
        """Compute loss of the head.
        Args:
            cls_scores (list[Tensor]): Box scores for each scale level,
                each is a 4D-tensor, the channel number is
                num_priors * num_classes.
            bbox_preds (list[Tensor]): Box energies / deltas for each scale
                level, each is a 4D-tensor, the channel number is
                num_priors * 4.
            lqe_preds (list[Tensor], Optional): Score factor for
                all scale level, each is a 4D-tensor, has shape
                (batch_size, 1, H, W).
            gt_bboxes (list[Tensor]): Ground truth bboxes for each image with
                shape (num_gts, 4) in [tl_x, tl_y, br_x, br_y] format.
            gt_labels (list[Tensor]): class indices corresponding to each box
            img_metas (list[dict]): Meta information of each image, e.g.,
                image size, scaling factor, etc.
            gt_bboxes_ignore (None | list[Tensor]): specify which bounding
                boxes can be ignored when computing the loss.
        """
        num_imgs = len(img_metas)
        featmap_sizes = [cls_score.shape[2:] for cls_score in cls_scores]
        mlvl_priors = self.prior_generator.grid_priors(
            featmap_sizes,
            dtype=cls_scores[0].dtype,
            device=cls_scores[0].device,
            with_stride=True)

        flatten_cls_preds = [
            cls_pred.permute(0, 2, 3, 1).reshape(num_imgs, -1,
                                                 self.cls_out_channels)
            for cls_pred in cls_scores
        ]
        flatten_bbox_preds = [
            bbox_pred.permute(0, 2, 3, 1).reshape(num_imgs, -1, 4)
            for bbox_pred in bbox_preds
        ]
        flatten_lqe_preds = [
            lqe_pred.permute(0, 2, 3, 1).reshape(num_imgs, -1)
            for lqe_pred in lqe_preds
        ]

        flatten_cls_preds = torch.cat(flatten_cls_preds, dim=1)
        flatten_bbox_preds = torch.cat(flatten_bbox_preds, dim=1)
        flatten_lqe_preds = torch.cat(flatten_lqe_preds, dim=1)

        flatten_priors = torch.cat(mlvl_priors)
        flatten_priors = flatten_priors.unsqueeze(0).repeat(num_imgs, 1, 1)
        flatten_bboxes = self._bbox_decode(flatten_priors, flatten_bbox_preds)

        (pos_masks, cls_targets, lqe_targets, bbox_targets,
         num_fg_imgs) = multi_apply(
             self._get_target_single, flatten_cls_preds.detach(),
             flatten_lqe_preds.detach(),
             flatten_priors,
             flatten_bboxes.detach(), gt_bboxes, gt_labels)

        # The experimental results show that ‘reduce_mean’ can improve
        # performance on the COCO dataset.
        num_pos = torch.tensor(
            sum(num_fg_imgs),
            dtype=torch.float,
            device=flatten_cls_preds.device)
        num_total_samples = max(reduce_mean(num_pos), 1.0)

        pos_masks = torch.cat(pos_masks, 0)
        cls_targets = torch.cat(cls_targets, 0)
        lqe_targets = torch.cat(lqe_targets, 0)
        bbox_targets = torch.cat(bbox_targets, 0)

        # centerness weighted iou loss
        centerness_denorm = max(
            reduce_mean(lqe_targets.sum().detach()), 1e-6)
        loss_bbox = self.loss_bbox(
            flatten_bboxes.view(-1, 4)[pos_masks],
            bbox_targets,
            avg_factor=centerness_denorm)
        loss_lqe = self.loss_lqe(flatten_lqe_preds.view(-1, 1)[pos_masks],
                                 lqe_targets.unsqueeze(-1),
                                 avg_factor=num_total_samples)
        loss_cls = self.loss_cls(
            flatten_cls_preds.view(-1, self.num_classes)[pos_masks],
            cls_targets,
            avg_factor=num_total_samples)

        loss_dict = dict(
            loss_cls=loss_cls, loss_bbox=loss_bbox, loss_lqe=loss_lqe)

        return loss_dict

    @torch.no_grad()
    def _get_target_single(self, cls_preds, lqe_preds, priors, decoded_bboxes,
                           gt_bboxes, gt_labels):
        """Compute classification, regression, and objectness targets for
        priors in a single image.
        Args:
            cls_preds (Tensor): Classification predictions of one image,
                a 2D-Tensor with shape [num_priors, num_classes]
            lqe_preds (Tensor): Objectness predictions of one image,
                a 1D-Tensor with shape [num_priors]
            priors (Tensor): All priors of one image, a 2D-Tensor with shape
                [num_priors, 4] in [cx, xy, stride_w, stride_y] format.
            decoded_bboxes (Tensor): Decoded bboxes predictions of one image,
                a 2D-Tensor with shape [num_priors, 4] in [tl_x, tl_y,
                br_x, br_y] format.
            gt_bboxes (Tensor): Ground truth bboxes of one image, a 2D-Tensor
                with shape [num_gts, 4] in [tl_x, tl_y, br_x, br_y] format.
            gt_labels (Tensor): Ground truth labels of one image, a Tensor
                with shape [num_gts].
        """

        num_priors = priors.size(0)
        num_gts = gt_labels.size(0)
        gt_bboxes = gt_bboxes.to(decoded_bboxes.dtype)
        # No target
        if num_gts == 0:
            cls_target = cls_preds.new_zeros((0, self.num_classes))
            bbox_target = cls_preds.new_zeros((0, 4))
            l1_target = cls_preds.new_zeros((0, 4))
            lqe_target = cls_preds.new_zeros((num_priors, 1))
            foreground_mask = cls_preds.new_zeros(num_priors).bool()
            return (foreground_mask, cls_target, lqe_target, bbox_target,
                    l1_target, 0)

        assign_result = self.assigner.assign(
            cls_preds.sigmoid() * lqe_preds.unsqueeze(1).sigmoid(),
            priors, decoded_bboxes, gt_bboxes, gt_labels)

        sampling_result = self.sampler.sample(assign_result, priors, gt_bboxes)
        pos_inds = sampling_result.pos_inds
        num_pos_per_img = pos_inds.size(0)

        cls_target = sampling_result.pos_gt_labels
        # cls_target = F.one_hot(sampling_result.pos_gt_labels,
        #                        self.num_classes)
        bbox_target = sampling_result.pos_gt_bboxes
        pos_priors = priors[pos_inds]
        encoded_bbox_target = self._bbox_encode(pos_priors, bbox_target)
        lqe_target = self.centerness_target(encoded_bbox_target)
        foreground_mask = torch.zeros_like(lqe_preds).to(torch.bool)
        foreground_mask[pos_inds] = 1
        return (foreground_mask, cls_target, lqe_target, bbox_target, num_pos_per_img)

When converting pos bbox_target from [tl_x, tl_y, br_x, br_y] to [l, t, r, b] using self._bbox_encode, it will sometimes produce a negative values on one of the 4 value for [l, t, r, b]. I think this is because pos_inds will sample the anchor point outside ground truth bounding box region (but still in the center region of radius 2.5 from SimOTA). Therefore, perform conversion on pos bbox_target to get centerness target will result in a nan lqe_target
Is there a way to fix this?
Environment
sys.platform: linux
Python: 3.9.12 (main, Jun  1 2022, 11:38:51) [GCC 7.5.0]
CUDA available: False
GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
PyTorch: 1.10.0+cpu
PyTorch compiling details: PyTorch built with:

GCC 7.3
C++ Version: 201402
Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
Intel(R) MKL-DNN v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740)
OpenMP 201511 (a.k.a. OpenMP 4.5)
LAPACK is enabled (usually provided by MKL)
NNPACK is enabled
CPU capability usage: AVX2
Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.10.0, USE_CUDA=0, USE_CUDNN=OFF, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=ON, USE_OPENMP=ON,

TorchVision: 0.11.0+cpu
OpenCV: 4.5.1
MMCV: 1.5.3
MMCV Compiler: GCC 7.3
MMCV CUDA Compiler: not available
MMDetection: 2.25.1+8f66fe3
Additional information
No response

@iumyx2612 The easiest way is to truncate the centerness target. There might be a better way.

@iumyx2612 duplicate with https://github.com/open-mmlab/mmdetection/issues/9138


Interpreting FFT symmetry

Hello,
The image below is the FFT plot of my data and it is showing symmetry (I did not change the values printed on the x axis to reflect the frequency of the original time domain, but the shown FFT plot below is assuredly of transformed data).  Would you please tell me if such symmetry is indicative of raw data that is too noisy or lacking of any discernible constituent sinusoids (my raw data does actually have a nice bandwidth - fixed y max and fixed x max - throughout the collected data oscillations)?  I've been looking at FFT plots of a more "textbook" like quality and those plots give nice and discernible/distinct peaks that don't have symmetry in their profile and those ideal peaks shoot up from the x axis as opposed to my profile which looks like raw data itself (such idealized "textbook" data tends to be of the waveform from a guitar or violin string just to point out what I've been looking at).  Thanks for any direction or tips you can provide.
LM

Could you share the code you used to generate this?

The specific code I used to invoke the FFT is
_Fourier ft = new FastFourier(XArray);         ft.transform();         boolean onlyPositive = false; double[] xOut = ft.getMagnitude(onlyPositive);
The code for making the plot is:
width = 600;         height = 500;         title = "Angle Transform"; x_axis = "Frequency";         y_axis = "Don't Know";         Plotting xFrequencies = new Plotting(width, height, title, x_axis, y_axis);         xFrequencies.initialisePlot(); xFrequencies.addSignal("Angle Transform", xOut, false); xFrequencies.saveAsPNG("AngleFrequencies.png");
Thanks.
LM

@LobsterMan123
FFTs of real signals are always mirrored. The reason why this happens is very well explained in this post. And his is where the parameter onlyPositive comes into play. onlyPositive returns the value of only the positive frequency components (for complex signals, the negative frequency components are also returned). If you plot this, you will see the length is half of what you have now and the mirroring effect does not occur.
The fact that there are multiple peaks, implies there may be some harmonic components. But the overall signal is fairly noisy determined from how jagged the FFT profile looks overall.

Thanks for the explanation and the post.  This is starting to make sense.
My follow-up question is: is it advisable then to carry out a filtration of the original signal with something like Butterworth and then execute the transform on the filtered data (my plotted raw data and its Butterworth filtration is seen in the figure below - raw data in blue and filtered signal in green)?  Is transforming a filtered signal physically or mathematically meaningful and/or feasible?  Thanks.
LM

In continuation to my previous question, I went and transformed (FFT) the filtered (Butterworth) signal just to see how it looks should it mean anything physically or mathematically.  The image is below.  Thanks.

For the first part, whether it should be done or not is entirely problem-dependant. If you think that applying a filter can be helpful to your end goal, it can definitely be done. In terms of meaningfulness, it can indeed be done. Filtering fundamentally removes signals from a specific frequency; so applying an FFT on the filtered signal would lead to those specific frequency bins to be empty.
For the second part, it appears you have used a high-pass filter on the signal before transforming. Other than that, I cannot particularly comment about anything because again, interpretation of a plot is problem-dependant. FFT ad filters are simply tools to help you achieve certain tasks; the usage,utility and the interpretation of results is still on the user.

The current version of JDSP (v1.0.0) does not include the functionality to get the frequency bins based on the FFT. It has been added in the upcoming release with the getFFTFreq() function.
Currently, to compute the frequencies for the data, you need to generate the bins yourself. Please refer to the function from this commit file on a guide to compute the same.

Ok, I went ahead and tried using the commit file with my code but three things happened:

I needed to delete "implements _Fourier" from line 30 in order for it to compile and work with my code

I needed to delete the "if" block (lines 58-60) beginning with "if (this.output == null)" in order for the code to compile since the array named "output" is always null/doesn't change its value.

Executing the above changes results in the "results" array being populated with nothing but zeros.  I also provided various different sampling frequencies but when I print out the length of the "results" array the length is always the same number (65 for me).

I also set the "onlyPositive" parameter in the "getFFTFreq" method to "true" since I am working with only the positive values of the DFT.
Should I be doing other changes to the code instead?  Thanks.
LM

Right. So I don't think this is the right forum to discuss about potential coding problems; especially since the relevant code will be deployed in a future release.
However, the expectation was not to modify the library itself, but to write a separate function derived from the referred function getFFTFreq() to compute the FFT frequency bins separately. This can be done independently of the FFT and has no dependency on the actual transform. All that is needed to compute the FFT Frequency bins is the signal length and the sampling frequency.
Hope this helps.

Got it.  Since the signal length and sampling frequency is all I need, I'll take a look then at the maths for calculating the bins in light if what you also have in the commit file.
Yes, I've starred the project as it's proving to be extremely useful for my own work (it's showing up as having gone up to 97 stars with my contribution).
LM

Also, is there a general timeline when the next release with the feature of calculating the bins will come out (a few months, next year, etc...)?  Thanks.

The potential release date for v2.0.0 which includes some speech-processing tools is the middle of the fourth quarter of 2022.
Given the issues that have been reported for v1.0.0, I might be inclined to make an intermediary release with the minor feature updates. This will be done once the peak detection time issues are resolved - so potentially in July.
However, if you want to use the development version of the code, please refer to the README file where you can find reference to a tool called JitPack which allows users to work with development versions of the codebase. Please make sure you are building from the dev branch.

Wonderful, I'll keep an eye out then for the new release even if it is the intermediary version for the short term.  Will the new maven summons code for the pom file be found on https://jdsp.dev/get_started.html whenever the new release(s) come(s) out?  Thanks.
LM

For any new release, the website will be updated with the latest summons and the latest API usage example.


How to setup on Linux?

Hello, I'm unable to get this working on Fedora Core 28. I have installed xclip from the default repo, but still get the error of

You need to install xclip command first.

The same result happens regardless of how I paste it

Take screenshot, copy that to clipboard, attempt to paste
Take screenshot, save to file, copy file, attempt to paste

$ uname -a
Linux desktop 4.16.13-300.fc28.x86_64 #1 SMP Wed May 30 14:31:00 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux
$
$ xclip -version
xclip version 0.13
Copyright (C) 2001-2008 Kim Saunders et al.
Distributed under the terms of the GNU GPL
$

I tested xclip and it works fine within the terminal
$ uptime | xclip
$
$  19:42:01 up 8 min,  2 users,  load average: 0.42, 0.49, 0.29
bash: 19:42:01: command not found...
$
$ echo "test" | xclip
$ test

Am I missing something, do I need to add an extra step?

Hi !
Same error here on Manjaro...
~ >>> command -v xclip
/usr/bin/xclip
~ >>> echo $?
0
Thank you for help !

Greetings Linux folks.  Perhaps like me, vscode isn't a toolchain mainstay and you weren't mindful of the fact that you're running vscode from within a container, isolated from xclip. You may want check if this is the case by running the above recommended verification commands from within the vscode terminal. This simple act lit a candle in my moment of darkness.
Don't get me wrong, I don't yet know what to do. I mean... it IS just a candle and the moment continues. However, I can now say that the darkness is less of an encumberance.
Take Care,
An I-love-the-vscode-markdown-flow-with-Mushan's-extension vim user
In a non-sandboxed terminal:
toor@seclab:~$ xclip -version xclip version 0.13 toor@seclab:~$ hostname seclab
Inside this bubble-wrapped vscode terminal:
sh-5.2$ xclip -version sh: xclip: command not found sh-5.2$ hostname seclab
Thanks Mushan!


Please turn on -Wmissing-import-lists

I am using versions from CHaP, using the build plan specified by cardano-node - produced as a result of running:
nix build github:input-output-hk/cardano-node/master#project.x86_64-linux.plan-nix.json -o plan.json

relevant versions are here, which are the ones that I am using:
"cardano-ledger-binary-<IP_ADDRESS>-4dfc7b45882c15932e1b21e8ca21a140c225a8b30407267b8e602e6bff3681ed",
"cardano-ledger-byron-<IP_ADDRESS>-54be2730b8b028afc7e153fae3fc3793f0e58e30cbecf9086dcab8e78441d279",

I get build errors like this:
cardano-ledger-byron> src/Cardano/Chain/Update/Proposal.hs:188:18: error:
cardano-ledger-byron>     Ambiguous occurrence ‘annotation’
cardano-ledger-byron>     It could refer to
cardano-ledger-byron>        either the field ‘annotation’ of record ‘Annotated’,
cardano-ledger-byron>               imported from ‘Cardano.Ledger.Binary’ at src/Cardano/Chain/Update/Proposal.hs:62:3-16
cardano-ledger-byron>               (and originally defined in ‘cardano-ledger-binary-<IP_ADDRESS>:Cardano.Ledger.Binary.Decoding.Annotated’)
cardano-ledger-byron>            or the field ‘annotation’ of record ‘AProposal’,
cardano-ledger-byron>               defined at src/Cardano/Chain/Update/Proposal.hs:95:5
cardano-ledger-byron>     |
cardano-ledger-byron> 188 |   recoverBytes = annotation
cardano-ledger-byron>     |                  ^^^^^^^^^^

This is confusing, but would be far easier to diagnose if we would just keep explicit import lists.

It is pretty easy to diagnose the problem, the error message tells you exactly what's wrong.
I appreciate your suggestion, but we will not be turning on -Wmissing-import-lists everywhere in the codebase. That being said if you feel like submitting a PR with this warning and explicit imports for the whole of byron codebase (eras/byron/*), I'll be happy to merge it.
Note, that you are trying to build the project with a newer ghc version that is not yet officially supported. This issue will be fixed in #3437


iOS 14 broke reverb and vibrato

What I know
Since iOS 14, adding vibrato or reverb no longer works on my iPhone XS.
An error suggests something to do with panWaveShareNode.inputs, something I can’t find in the Tone.js repository.
What I have
To keep my project alive I isolated my synth setup with a try/catch.
I couldn’t make a JSFiddle work, but the repo is here, and playable here.
This is the error:

TypeError: undefined is not an object (evaluating 'panWaveShaperNode.inputs[0]')
  connectGraph — native-stereo-panner-node-faker-factory.js:109
  whenConnected — native-stereo-panner-node-faker-factory.js:240
  (anonymous function) — monitor-connections.js:13
  [native code]
  (anonymous function) — wrap-audio-node-disconnect-method.js:7
  connectNativeAudioNodeToNativeAudioNode — connect-native-audio-node-to-native-audio-node.js:8
  connect — audio-node-constructor.js:323
  CrossFade — CrossFade.js:77
  Effect — Effect.js:17
  Reverb — Reverb.js:24
  _callee2$ — SynthKeys.vue:133
  tryCatch — runtime.js:63
  invoke — runtime.js:293
  asyncGeneratorStep — asyncToGenerator.js:3
  _next — asyncToGenerator.js:25
  (anonymous function) — asyncToGenerator.js:32
  Promise
  (anonymous function) — asyncToGenerator.js:21
  setupSynth
  _callee$ — SynthKeys.vue:71
  tryCatch — runtime.js:63
  invoke — runtime.js:293
  asyncGeneratorStep — asyncToGenerator.js:3
  _next — asyncToGenerator.js:25
  promiseReactionJob

As @TaoJinjin-Thomas said the error comes from inside standardized-audio-context. However I think it's a good sign. Currently a bug is used to detect Safari and to apply a workaround. It looks as if this bug is fixed in the current preview of Safari. Although this was not mentioned in the release notes.
Do you have an idea when Safari v14 is going to be released?

It does seem positive. Major iOS updates have been released around 18th September for the last few years.

I am seeing this also, on macOS Safari 14, released today.

https://github.com/chrisguttandin/standardized-audio-context/blob/c7565cf469ade950832a773c7bdd24dcd0453717/src/factories/native-stereo-panner-node-faker-factory.ts#L49

Thanks for the heads up. A fix for standardized-audio-context is on it's way.

@tambien would be great to get a release with the above fix in ☝

I don't mean to nag, is there be a new release planned for this fix?

<EMAIL_ADDRESS>includes that fix

Thanks @tambien, I missed that because it's not listed on https://github.com/Tonejs/Tone.js/releases

Hi, I have the same issue but with FeedbackDelay, I am on @14.7.58.


Unable to post Gets Error message

Describe the bug
Unable to post Gets Error message

Steps to reproduce
post something in highlights
Affected services
insights.opensauced.pizza
Platforms
No response
Browsers
No response
Environment
No response
Additional context
No response
Code of Conduct

[X] I agree to follow this project's Code of Conduct

Contributing Docs

[X] I agree to follow this project's Contribution Docs

@parmishh thanks for opening this. Can you also share the error message in the console?

@bdougie This is the error message from console.

@parmishh what's the error in the network request? A 400 means something incorrect was provided as POST data

@TAKANOME-DEV Sure, Can you describe little more how it should look like.
What I understand is we need to show the message in console to frontend.

What I understand is we need to show the message in console to frontend.

Yeah, replace an error occurred with the error message

.take

can anyone review?

can anyone review?

@parmishh this is not necessary. The whole team gets notified and Discord gets notified when a PR is opened.


Extending @playwright/test 1.12

@playwright/test 1.12 is self-contained and basically re-exports playwright.
This breaks extending as all the objects and types are now from the @playwright/test package and not the playwright package.

Hi @denovodavid, thanks for reporting this. I just recently became aware of @playwright/test. We've had some recent issues with jest-playwright (see #140) that touches on some of these same issues. I'm really trying to find the time to get back in here and move CI into GitHub actions and add support for @playwright/test soon. Please feel free to open up a PR in the meantime, otherwise I will keep you posted.

Ah, one more thing: if you do plan on working on a PR let me know and I'll make sure to at least get CI sorted for you.

Is it just extend that breaks with @playwright/test or also the standalone queries?

I think the main issue here is the way that Playwright distributes the different "flavors" of the library as I described here: https://github.com/hoverinc/playwright-testing-library/pull/295#issuecomment-924421199

Actually, maybe this could be implemented as a selector engine?

There's no maybe about it: https://github.com/hoverinc/playwright-testing-library/pull/330

@playwright/test is now officially supported in 4.0.1 under the name @playwright-testing-library/test via #315.
Note: unfortunately I messed up and published a 4.0.0 on the next distribution channel while I was sorting the CI process, hence 4.0.1 ... 🤦🏼♂ .
I'm going to close this and let's continue the selector engine discussion in #330 or a new issue.


Add default reviewers to PR create service revision produces

As a developer I would like people listed in the maintainers.yaml file to be default reviewers when spk service create-revision is called
Describe the solution you'd like:
The command spk service create-revision creates a pull request. It should utilize the people in the maintainers.yaml file and add them to the code review. This way maintainers are notified of changes.
Describe alternatives you've considered:
Manually adding people to the PR
Does this require updates to documentation?:
Yes

Thoughts? @mtarng @bnookala

@andrebriggs seems fine, and I imagine it's fairly straightforward - is this a high priority item?

@bnookala not high priority but I'll put it in the groomed bucket


I Have a question

When the operation order was changed from cw > hc > hw to hw > cw > hc, performance improved in certain models. Calculations are performed independently of each other. Do you know why this is?
thank you.

Ideally that shouldn't be the case since all the three operations are computed in parallel and independently. Can you provide a reproducible experiment where we can observe that? Further are you sure, the seeds were the same between the two runs and there is no randomness?

I'm honored for your response.
The code below is the code I modified.
When tested on existing code and custom data, the modified code showed a slight improvement. I wonder if there is a cause that I don't know about.
class ZPool(nn.Module):
def forward(self, x):
return torch.cat(
(torch.max(x, 1)[0].unsqueeze(1), torch.mean(x, 1).unsqueeze(1)), dim=1
)
class AttentionGate(nn.Module):
def init(self):
super(AttentionGate, self).init()
kernel_size = 7
self.compress = ZPool()
self.conv = Conv(
2, 1, k=kernel_size, s=1, p=(kernel_size - 1) // 2, act=False
)
def forward(self, x):
x_compress = self.compress(x)
x_out = self.conv(x_compress)
scale = torch.sigmoid(x_out)
return x * scale
class TripletAttention(nn.Module):
def init(self, no_spatial=False):
super(TripletAttention, self).init()
self.cw = AttentionGate()
self.hc = AttentionGate()
self.hw = AttentionGate()
def forward(self, x):
x_hw = self.hw(x)
x_hc = self.hc(x.permute(0, 3, 2, 1).contiguous()).permute(0, 3, 2, 1).contiguous()
x_cw = self.cw(x.permute(0, 2, 1, 3).contiguous()).permute(0, 2, 1, 3).contiguous()
x_out = 1/3 * (x_hw + x_hc + x_cw)
return x_out

@byunsunghun Sorry for my late response, from your snippet I don't see anything obvious that would explain such improvement as you mentioned. However, as I stated if the seeds were not fixed between the two experiments or any other source of randomness can cause variance in performance. It would be best to run multi-seed runs and benchmark the average and variance in the performance of the two settings.

Thank you for the reply. The two seeds were always fixed, and we will investigate separately whether the performance difference occurred due to the combination of other codes.
Happy new year!

Keep me posted, happy new year to you too!

Hi! Sorry for my late response, now responding after 7 months.
The seeds in both experiments were always fixed, but as you mentioned earlier, other sources of randomness resulted in performance differences.
The question has been resolved.
Please continue to do good research!
thank you


Performance/Memory consumption issue

Hey, appreciate the effort creating such an amazing library, I just have one issue, I've noticed that using MotiView with the simplest form of animations (for example; using it in a button) is adding around 5MB of memory per reusable component, I've replaced it with a normal View and the same component is consuming around 1MB of memory per reusable component, MotiView is not triggering any kind of animations on-mount or exit, it's just changing the opacity on press or on flag change, so the animations are inactive unless the user interacted with the component, this is creating a very heavy memory usage when used in lists (around >200MB every list render/open), I've spent a whole day debugging and enhancing the list which was having this issue but eventually found out that it's a MotiView issue. my component looks like this:
 <Pressable disabled={disabled} onPress={onPress} style={style}>
    <MotiView
        transition={{type: 'timing', duration: 300, delay: loading ? 0 : 300}}
        from={{opacity: 1}}
        animate={{opacity: loading ? 0 : 1}}>
          <Text style={[props.titleStyle, styles.title]}>text</Text>
      </MotiView>
</Pressable>

any ideas how can I possibly overcome this issue?
Thank you.
react-native version: 0.64.2
react-native-reanimated version: 2.2.0
moti version: 0.11.0
platform: iOS and Android

Oh man, that's really bad. Could you try replacing MotiView with a custom Animated.View that uses a useAnimatedStyle from Reanimated? This may be related to https://github.com/software-mansion/react-native-reanimated/issues/1499

Does taking the MotiView props out of render change anything? Just a guess

@nandorojo  So I've done some tests with/out MotiView,

this is when using MotiView with the props

when list page has just been presented:

after around 2 minutes, same view, no interactions have been made to the:

ps: it's not stable, still going up and down at a consistent pace.

this is when using MotiView without the props:

when list page has just been presented:

also after around 2 minutes:

when using normal view

when list page has just been presented:

after 2 minutes:

when using Animated.View

when list page has just been presented:

after 2 minutes:

as you can see the curve is very stable by the time the list got fully rendered/cached

until this get fixed, I guess will use reanimated to recreate these animations, appreciate if you can estimate the time to get this fixed so I can wait, if it takes a lot of time I guess I will recreate these animations using rn-reanimated

Hmm that's quite bizarre, since Moti is just a thin wrapper around Reanimated. The only other thing I can think of is the user of framer-motion.
Could you try importing that, and put the usePresence hook in your component alongside the Reanimated component?

When you say "without the props", you mean without initial and animate? Those alone cause this?

When you say "without the props", you mean without initial and animate? Those alone cause this?

yea exactly.

Could you try importing that, and put the usePresence hook in your component alongside the Reanimated component?
so I've just added

usePresence()

at the top of my component while still using Animated.View and it seems very stable at 219MB after 2 minutes.

What if you use useAnimationState with the state prop?
https://github.com/nandorojo/moti/api/use-animation-state
Or useDynamicAnimation?
https://github.com/nandorojo/moti/releases/tag/v0.7.3

@nandorojo  useAnimationState stable at 257MB, not changing the state just hooking it up to my MotiView state prop, which is also a lot, when considering that the button is being used all over the app.

This is definitely interesting. I'm also using MotiView in very long lists for the BeatGig iOS app, so I can see if I experience something similar. What are you using to benchmark this stuff?

@nandorojo running the app from Xcode directly into my physical iOS device, then I just keep monitoring the profiler in Xcode (https://developer.apple.com/documentation/xcode/gathering-information-about-memory-use)

What if you pass empty dictionaries as the props, and keep them outside of render?

@nandorojo I've reimplemented all the animations using reanimted already so it's really hard to rollback to test this case, anyways,the point of moti is the clean minimal implementation of it's components so this bug really should be fixed, any work around or a tweak when using it will just make it pointless, really appreciate your help 🙏🏻

My suggestions are meant to narrow down the issue you're facing. It's hard for me to track down a bug without a reproduction. I agree the bug should be fixed. I'm open to a PR if you make headway.

@nandorojo I will try to send you a full example reproducing this issue ASAP, thank you

Cool thanks


The mapped network driver does not show up fully in the list.

After I have mapped my network drive (NAS) using Microsoft's File Manager, if I disconnect, when I click the icon again, it tries to reconnect. But in this file manager, the icon will just disappear. Also, this file manager doesn't use the mapped network drive feature and to reconnect I have to open the file manager that comes with the system, which causes me a lot of trouble.
我使用微软的文件管理器对我的网络硬盘（NAS）做了映射之后，如果断开了连接，当我再次点击图标时，会尝试重新连接。但是在此文件管理器中，图标会直接消失。并且，此文件管理器没用映射网络驱动器功能，要想重新连接，我不得不打开系统自带的文件管理器，这对我造成了很大的困扰。
system info：win10 Home 1909 /18363

@Czile-create Is this still an issue in v1.3?


DocLinkChecker: Support for %20 in links

Add basic support for %20 in url. See #60 for details.
Was hoping for a more elegant implementation. But this works.
Fixes #60

@mtirionMSFT can you have a look as well?


Unable to get workflow to work with -app-port option in my daprd command

In what area(s)?
/area runtime
What version of Dapr?
1.11.0
Expected Behavior
Sidecar should be up and running and I should be able to execute a workflow
Actual Behavior
The sidecar and the app are running but the app isn't able to locate the sidecar
Steps to Reproduce the Problem
Spin up the app and the side car using docker compose file. Add the -app-port option in the daprd command

@hitekshu Please can you share your complete compose file? I ask because what you're describing works fine for me. Thanks.


Pedestrian alignment

Did you have tried Pedestrian alignment to preprocess those datasets？i don't know wether it is helpful to use Pedestrian alignment methods improving adaptability in practical application scenarios.

Actually, I don't try pedestrian alignment to preprocess the datasets. The reasons are below:

I need to perform pose estimation to get the keypoints and then do the alignment when training and testing. It will bring extra overhead.
When detector is bad, you need to align the pedestrian, but in my situation, the detector is very good. So I don't need to consider the alignment problem.

thanks for your incere answer. The reason why i have asked this question is that i had tested our models in  some small space scene in door where the angle that camera is installed may causes distortion of pedestrian.


Add server API

#2  👈
main

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Join @higgsboz-beam and the rest of your teammates on  Graphite

Merge activity

May 20, 1:55 PM EDT: @higgsboz-beam started a stack merge that includes this pull request via Graphite.


Add one item to the "Prerequisites” section

Can you add the following information to the "Prerequisites” section?
It is a mandatory requirement to support BGP 4-byte ASN to establish connectivity between AVS and On-premise.

Azure VMware Solution uses 4-byte Public ASN to advertise routes. Make sure that all routers including your ExpressRourte Provider's service support 4byte ASN.

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

ID: b5e365a3-e2f9-0fed-e8cc-8a6cad6224ef
Version Independent ID: 8204c126-3976-8a5b-8c4a-58935d05464f
Content: Tutorial - Peer on-premises environments to a private cloud - Azure VMware Solution
Content Source: articles/azure-vmware/tutorial-expressroute-global-reach-private-cloud.md
Service: azure-vmware
GitHub Login: @shortpatti
Microsoft Alias: v-patsho

@tamaejim
Thanks for the feedback! I have assigned the issue to content author to check and update the document as appropriate.

@tamaejim
Thanks for the feedback! I have assigned the issue to content author to check and update the document as appropriate.

@shortpatti
Can you please check and add your comments on this doc update request as applicable.

@shortpatti
Can you please check and add your comments on this doc update request as applicable.

@shortpatti
Can you please check and add your comments on this doc update request as applicable.

I'll work with the engineering team to clarify this more :)

@shortpatti
Can you please check and add your comments on this doc update request as applicable.

I'll work with the engineering team to clarify this more :)

Updated content.
#please-close

Updated content.
#please-close


chore: simulate work to validate CI changes

Dummy commit in dependent_targets.bxl to run all CI targets

bors merge


Transaction management

How do you manage transaction for each service in the framework? Are there any examples ？Thank you.

There are two areas that we need to cover. How to connect to two different databases from one service and ensure consistency. Take a look at this lib https://www.atomikos.com/Main/TransactionsEssentials
For distributed transactions between services, light-eventuate-4j and light-saga-4j are designed for it.
https://doc.networknt.com/architecture/transaction/