tf.keras.layers.ConvLSTM2D throws error when backprop

Issue type
Bug
Have you reproduced the bug with TensorFlow Nightly?
No
Source
source
TensorFlow version
tf 2.14.0
Custom code
Yes
OS platform and distribution
windows colab
Mobile device
No response
Python version
3.10
Bazel version
No response
GCC/compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
No response
Current behavior?
API crashes in backprop.
Standalone code to reproduce the issue
filters = 2
kernel_size_0 = 4
kernel_size_1 = 2
kernel_size = [kernel_size_0,kernel_size_1,]
strides_0 = 1
strides_1 = 1
strides = [strides_0,strides_1,]
padding = "valid"
data_format = "channels_first"
dilation_rate_0 = 1
dilation_rate_1 = 1
dilation_rate = [dilation_rate_0,dilation_rate_1,]
activation = "tanh"
recurrent_activation = "hard_sigmoid"
use_bias = False
kernel_initializer = None
recurrent_initializer = None
bias_initializer = "zeros"
unit_forget_bias = True
kernel_regularizer = None
recurrent_regularizer = None
bias_regularizer = None
activity_regularizer = None
kernel_constraint = None
recurrent_constraint = None
bias_constraint = None
return_sequences = False
return_state = False
go_backwards = True
stateful = False
dropout = 0.0
recurrent_dropout = 0.0
__input___0_tensor = tf.random.uniform([2, 2, 2, 5, 1], minval=1.7518786460769893, maxval=2.8945805380363145, dtype=tf.float32)
__input___0 = tf.identity(__input___0_tensor)
ConvLSTM2D_class = tf.keras.layers.ConvLSTM2D(filters, kernel_size, strides=strides, padding=padding, data_format=data_format, dilation_rate=dilation_rate, activation=activation, recurrent_activation=recurrent_activation, use_bias=use_bias, kernel_initializer=kernel_initializer, recurrent_initializer=recurrent_initializer, bias_initializer=bias_initializer, unit_forget_bias=unit_forget_bias, kernel_regularizer=kernel_regularizer, recurrent_regularizer=recurrent_regularizer, bias_regularizer=bias_regularizer, activity_regularizer=activity_regularizer, kernel_constraint=kernel_constraint, recurrent_constraint=recurrent_constraint, bias_constraint=bias_constraint, return_sequences=return_sequences, return_state=return_state, go_backwards=go_backwards, stateful=stateful, dropout=dropout, recurrent_dropout=recurrent_dropout)

layer = ConvLSTM2D_class
inputs = __input___0

with tf.GradientTape() as g:
    g.watch(inputs)
    res = layer(inputs)
print(res.shape)
grad = g.jacobian(res, inputs)  # Error

Relevant log output
(2, 2, 2, 0)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-15-75a544b673ad> in <cell line: 57>()
     55     res = layer(inputs)
     56 print(res.shape)
---> 57 grad = g.jacobian(res, inputs)  # Error
     58 # print(grad)

1 frames
/usr/local/lib/python3.10/dist-packages/tensorflow/python/framework/ops.py in set_shape(self, shape)
    534   def set_shape(self, shape) -> None:
    535     if not self.shape.is_compatible_with(shape):
--> 536       raise ValueError(f"Tensor's shape {self.shape} is not compatible "
    537                        f"with supplied shape {shape}.")
    538

ValueError: Tensor's shape (2, 2, 2, 0, 1, 2, 2, 5, 1) is not compatible with supplied shape (2, 2, 2, 0, 2, 2, 2, 5, 1).

@sachinprasadhs
I was able to replicate the reported behaviour with TF2.13, TF2.14 and tf-nightly. Kindly find the gist for reference.

Hi @cheyennee,
The incorrect shape (2, 2, 2, 0) is due to mismatch between the input and padding, kernel size and strides. With 'valid' padding, the output of the ConvLSTM2D layer have a spatial dimension of 0. Instead of valid padding, use padding = "same"  and set return_sequences=True,  so that the output shape aligns with the expected shape for gradient calculation, even when processing the sequence in reverse order(go_backwards = True). Verified the code with these changes in TF 2.18.0 . Please refer to the following code.
print(tf.__version__)
filters = 2

kernel_size_0 = 4
kernel_size_1 = 2
kernel_size = [kernel_size_0, kernel_size_1]
strides_0 = 1
strides_1 = 1
strides = [strides_0, strides_1]
# Use 'same' padding ................
padding = "same"  # Changed from 'valid...............'
data_format = "channels_first"
dilation_rate_0 = 1
dilation_rate_1 = 1
dilation_rate = [dilation_rate_0, dilation_rate_1]
activation = "tanh"
recurrent_activation = "hard_sigmoid"
use_bias = False
kernel_initializer = None
recurrent_initializer = None
bias_initializer = "zeros"
unit_forget_bias = True
kernel_regularizer = None
recurrent_regularizer = None
bias_regularizer = None
activity_regularizer = None
kernel_constraint = None
recurrent_constraint = None
bias_constraint = None
return_sequences = True
return_state = False
go_backwards = True
stateful = False
dropout = 0.0
recurrent_dropout = 0.0
__input___0_tensor = tf.random.uniform([2, 2, 2, 5, 1], minval=1.7518786460769893, maxval=2.8945805380363145, dtype=tf.float32)
__input___0 = tf.identity(__input___0_tensor)
ConvLSTM2D_class = tf.keras.layers.ConvLSTM2D(filters, kernel_size, strides=strides, padding=padding, data_format=data_format, dilation_rate=dilation_rate, activation=activation, recurrent_activation=recurrent_activation, use_bias=use_bias, kernel_initializer=kernel_initializer, recurrent_initializer=recurrent_initializer, bias_initializer=bias_initializer, unit_forget_bias=unit_forget_bias, kernel_regularizer=kernel_regularizer, recurrent_regularizer=recurrent_regularizer, bias_regularizer=bias_regularizer, activity_regularizer=activity_regularizer, kernel_constraint=kernel_constraint, recurrent_constraint=recurrent_constraint, bias_constraint=bias_constraint, return_sequences=return_sequences, return_state=return_state, go_backwards=go_backwards, stateful=stateful, dropout=dropout, recurrent_dropout=recurrent_dropout)

layer = ConvLSTM2D_class
inputs = __input___0

with tf.GradientTape() as g:
    g.watch(inputs)
    res = layer(inputs)
print(res.shape)
grad = g.jacobian(res, inputs)

print(inputs.shape)
print(res.shape)
(2, 2, 2, 5, 1)
(2, 2, 2, 5, 1)

Thank You


WHEN I choose to view all departments

THEN I am presented with a formatted table showing department names and department ids

Done


how to load data picked

I just picked data, I want pick again. when picker show I want checkmark for my data picked.
Excuse me for translate.

Hi @xthaohg , I believe you can set - (NSArray *)selectedRows to indicate the selected rows. Refer to #10 for more information.


TODO in README

TODO: After extracting the plugin to a separate repo or publishing it to a artifact repository

Should there be a link to https://mvnrepository.com/artifact/com.wolt/ktor-idempotency?

yes, we should, I forgot to update that. thanks for noticing it 👍


Browser UI constantly freezes since last update

Operation System: macOS
Beaker version: 0.8.3
UI freezes as soon as I open a couple tabs. Menu bar continues to work, but no element in the browser window works anymore until I force quit the app.

I should add that the 0.8.3 version also didn't properly relaunch after installation. Menu bar showed up but main browser window didn't, until I killed it and restarted. The update apparently went through because the settings tab showed 0.8.3 after restarting the app.

Yes, I just solved this yesterday and will be putting together a patch release today. See: https://github.com/beakerbrowser/beaker/issues/1333
Sorry for the issue!


Typo in MP static content config documentation

The following doc page should use "path" instead of "classpath" in file example:
https://helidon.io/docs/latest/#/microprofile/04_static-content

Fixed by PR #634


Small fix of vertex map

What do these changes do?

When running the test of vertex map, I encountered a small problem with the script, see

Besides, some small code optimization of vertex map is submitted.
Related issue number

Fixes

Codecov Report

Merging #134 (91c9a57) into master (4aea35a) will decrease coverage by 0.03%.
The diff coverage is 100.00%.

Additional details and impacted files

@@            Coverage Diff             @@
##           master     #134      +/-   ##
==========================================
- Coverage   70.03%   70.00%   -0.04%
==========================================
  Files          64       64
  Lines        5726     5720       -6
==========================================
- Hits         4010     4004       -6
  Misses       1716     1716

Flag
Coverage Δ

app_tests
70.00% <100.00%> (-0.04%)
:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files
Coverage Δ

grape/vertex_map/global_vertex_map.h
62.60% <ø> (-0.31%)
:arrow_down:

grape/vertex_map/vertex_map_base.h
100.00% <ø> (ø)

tests/vertex_map_tests.cc
89.69% <ø> (-0.51%)
:arrow_down:

grape/vertex_map/local_vertex_map.h
60.48% <100.00%> (ø)

[AI Review] This comment is generated by an AI model (GPT-3.5-turbo).
Based on the provided patch, it seems that the changes are related to the VertexMap in the Grape library. The changes include modifying the way the vertices are mapped and converting the vertex ids with the help of mappings. Additionally, there are changes in the way the threads are created for sending and receiving messages and modifying the way the global and local vertex maps are built.
Without more context on the purpose of these changes, it is difficult to determine if they are correct or not. However, the changes seem to be consistent with the functionality of the Grape library. Therefore, it is recommended to review the purpose of these changes and test them thoroughly before merging the pull request.


Change exchange intention id to random number

Let's discard this storage item and use randomly generated hash so that this never overflows.
@orca84 is going to have a look at this.
https://github.com/galacticcouncil/hack.HydraDX-node/blob/694291f74180a4755904a6aa75a3ea4fbfb8ab0e/pallets/exchange/src/lib.rs#L48

Can we do this in a way it is easily mockable in tests ?
In exchange pallet there are ( or will be soon) tests of events, so it should be possible to determine a value for intention id easily.
So for example, instead of the hash,  it will be possible to change it in tests  so it will be generate sequential numbers like it does now.

@enthusiastmartin Do you have any proposal? Is it possible for you to get intention id hash from the first item event you receive?

@jak-pan although  we talked a possible way ( using a trait which would be implemented differently for tests ) - now that i am thinking about it- it wont be probably possible. Since the intention id is part of the event itself and it is defined as 'hash type' .
so, it wont be possible to change a type ( unless someone has another idea )
I will think about it again
but perhaps ,getting the hash from the last event is easier.

Intention Id itself could be a configurable trait in primitives/runtime like balance or accountId but that might be an overkill if it's only used for UI?


Added tests to increase coverage

[x] Related GitHub issue(s) linked in PR description
[x] Destination branch merged, built and tested with your changes
[x] Code formatted and follows best practices and patterns
[x] Code builds cleanly (no additional warnings or errors)
[x] Manually tested
[x] Automated tests are passing
[x] No decreases in automated test coverage
[x] Documentation updated (readme, docs, comments, etc.)
[x] Localization: No hard-coded error messages in code files (minimally in string constants)

Refactored some tests and added some more tests to improve code coverage.

@HeyKos @brandongregoryscott - The assertion is cleaned up if you would like to take another look. Thanks.

@wintondeshong I made the changes that you requested, thanks for catching those.

@SaidShah Just a reminder to link the related issue in the description with closing keywords next time 👍 Thanks for the contribution!


Suggested updates to periodic.py

Consolidates element information into a single tuple, update relative atomic mass/uncertainty values (current file is missing changes since 2016).
Also, alters the atomic_number function to accept lowercase atomic symbols.
References:

https://iupac.org/standard-atomic-weights-of-14-chemical-elements-revised/
https://iupac.org/standard-atomic-weight-of-lead-revised/

Edit: full disclusure, my Chemistry knowledge is middling to amateur at best, so the reasons for the failing tests are entirely opaque to me.

@cbporch thank you for these updates! Much appreciated. The test failures are actually due to overly tight tolerances (it doesn't make sense that I have tighter tolerances in those tests than the uncertainty associated with the average molar mass of the natural abundance of the isotopes of the element). I pushed a commit locking the mass used in those tests, if they pass I'll merge.
Thanks again!


Need a Code Review action for each PR

As a Developer
I need to suggest every PR should pass a code review
So that we can guaranteeing the reliability of our code
Details and Assumptions

We will do code review for each PR
after the code has been verified, we can merge it into our master branch

Acceptance Criteria
Given we submit our PR
When some one in our team approved that PR
Then the PR could merged into master branch

Duplicate of #47


Revert "#KYLIN-4044, upgrade curator dependency version"

This reverts commit<PHONE_NUMBER>11b285b78cfc3a63ac5025436ddb59.

Can one of the admins verify this patch?

Can one of the admins verify this patch?

Can one of the admins verify this patch?

Codecov Report

Merging #703 into master will increase coverage by 0.01%.
The diff coverage is n/a.

@@             Coverage Diff              @@
##             master     #703      +/-   ##
============================================
+ Coverage     25.71%   25.72%   +0.01%
+ Complexity     6013     6012       -1
============================================
  Files          1385     1385
  Lines         82424    82424
  Branches      11557    11557
============================================
+ Hits          21197    21207      +10
+ Misses        59179    59173       -6
+ Partials       2048     2044       -4

Impacted Files
Coverage Δ
Complexity Δ

...org/apache/kylin/rest/util/QueryRequestLimits.java
35.71% <0%> (-4.77%)
5% <0%> (-1%)

.../apache/kylin/cube/cuboid/TreeCuboidScheduler.java
66.15% <0%> (+2.3%)
0% <0%> (ø)
:arrow_down:

...rg/apache/kylin/cube/inmemcubing/MemDiskStore.java
69.3% <0%> (+2.73%)
7% <0%> (ø)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 9708990...958a3e8. Read the comment docs.

Pull Request Test Coverage Report for Build 4635

0 of 0   changed or added relevant lines in 0 files are covered.
5 unchanged lines in 2 files lost coverage.
Overall coverage increased (+0.007%) to 28.213%

Files with Coverage Reduction
New Missed Lines
%

server-base/src/main/java/org/apache/kylin/rest/util/QueryRequestLimits.java
1
47.62%

core-cube/src/main/java/org/apache/kylin/cube/inmemcubing/MemDiskStore.java
4
77.81%

Totals

Change from base Build 4633:
0.007%

Covered Lines:
23254

Relevant Lines:
82424

💛  - Coveralls


Is there a description on how methylation is called in MethylDackel

Hi @dpryan79,
Thank you for this software, it has been really useful in my research. Since there is no publication on MethylDackel, are there any description on how methylation is called from a BAM file?

Some day I hope to post something on bioarxiv, but in the interim here's a very brief description:
MethyDackel uses htslib (what powers samtools) to create a "pileup" of bases at each position in the genome. A "pileup" is a reference to the "samtools mpileup" command and can be visualized as a stack of bases covering a position with their corresponding Phred quality scores. MethylDackel then filters this pileup of bases according to base call quality and where they are in their reads (c.f. --OT and such). If the reference base at a given position is a C on either strand and that C is in one of the desired contexts then it's written to the output.
There are some additional details when one has a paired-end dataset. Namely, one doesn't want to extract the same methylation call from both mates if they overlap. Consequently, in such cases the base call quality of one of the mates is set to 0 so it will be filtered out.  Additionally, the base call quality of the remaining base is adjusted up or down depending on whether both mates agree on the base call or not (this is also how samtools mpileup works).
The mbias subfunction works in a similar manner. It notes when there's apparent methylation and save that as a function of position within each read.
If you need details about anything else related to this tool then feel free to ask. Also, sorry for any typos in this reply, I'm writing this on an iPad rather than a proper computer.

Thank you for the explanation. Looking forward to the paper!


Moved RPC related types to a dedicated package

What changed?
Moved RPC related stuff from config package to a dedicated rpc package, with minor renaming and splitting into files.

Why?
These types contain significant amount of RPC related logic, that IMO deserves their own place. Those are not very config related.
Also, this serves as a first refactoring step for further changes planned. Specifically unifying how dispatchers are created and used. This includes DispatcherProvider and all related stuff such as dnsDispatcherProvider, dnsUpdater, etc. Currently they lie under client package. In the end, these types will end up here as well.

How did you test it?
Existing tests.

Potential risks
None, only mechanical move.

Release notes

Documentation Changes

Pull Request Test Coverage Report for Build d2f8762a-9229-40b4-8a84-67df70d506d7

21 of 28 (75.0%)  changed or added relevant lines in 5 files are covered.
86 unchanged lines in 19 files lost coverage.
Overall coverage increased (+0.01%) to 56.431%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

cmd/server/cadence/server.go
0
1
0.0%

common/rpc/factory.go
0
6
0.0%

Files with Coverage Reduction
New Missed Lines
%

service/history/queue/timer_queue_processor_base.go
1
78.6%

client/history/client.go
2
40.74%

client/history/metricClient.go
2
45.94%

common/membership/rpServiceResolver.go
2
73.58%

common/task/fifoTaskScheduler.go
2
87.63%

common/task/weightedRoundRobinTaskScheduler.go
2
89.64%

service/history/handler.go
2
47.76%

service/matching/matcher.go
2
91.46%

service/matching/taskListManager.go
2
74.09%

common/persistence/nosql/nosqlplugin/cassandra/workflow.go
3
50.23%

Totals

Change from base Build 990de510-0305-41c9-a3c6-6d95cc8b4e3f:
0.01%

Covered Lines:
80141

Relevant Lines:
142016

💛  - Coveralls


OMF format: Added handling of ALIAS record type (Closes #4856)

See #4856
A better solution would be to simply skip GetRecordLength() bytes, but I didn't research if that is possible.

2 questions:
The unhandled record types:
BC - CEXTDEF, C2 - COMDAT, C4 - LINKSYM, C8 - NBKPAT, CA - LLNAMES Added for Microsoft C 7.0
CC - VERNUM, CE - VENDEXT TIS - Tool Interface Standard
could all be skipped the same way according to the format description, but I have no actual library that uses them, so can't test it.
Skipping them with a message, would allow for a file to pass, allowing people to do some work with the file even if these records aren't handled, rather than failing as it would now.
Should I add these while I am at it?
How should I log a message: Msg.Info?
Instead of OmfUnknownRecord I would do OmfSkipRecord, which I find a more correct and proper description of what is happening.

OmfUnknownRecord would be good if new cases can spring up over time and we aren't keeping pace with implementing them.  Since that isn't the case in this ancient format, OmfSkipRecord would be fine, assuming you add all the missing cases that you mentioned to the switch (which is a good idea to do).  The only downside I see to OmfSkipRecord is that it implies skipping them is how we prefer to handle them.  Really though, we are only skipping them because we haven't gotten around to fully implementing them yet and we are just looking for a way for them to not prevent the load.  I think OmfUnsupportedRecord conveys a better message.
For logging, you'll want to use the MessageLog that gets passed into OmfLoader.load().  This isn't currently passed in to the OmfRecord class, so you'd have to pass it into OmfFileHeader.parse(), and carry it through.  This MessageLog is what gets shown in the GUI popup that appears when the load completes.  The static Msg messages only end up in the application.log (and front-end GUI log viewer) file that is a bit more disconnected from the load process.
I wouldn't worry about testing all the missing cases.  It's pretty clear from the spec that all the records start with the type and length fields.  You can test by temporarily moving one of the less important records present in your binary to the unsupported/skip group in the switch.  On the off chance that one of these unsupported records is doing something weird with the first 2 fields and that causes it to blow up, we aren't any worse off than we currently are with these missing records.

I have updated to OmfUnsupportedRecord and added the missing record types.
Instead of parsing log down to OmfRecord, I do the logging in OmfFileHandler as the resulting handling of the records, the same as other records.
The message logs is in decimal but should it be in hex?
Found a library with a COMDAT (0xC3 - 32 bit) entry. So might have to do a proper implementation for that later.

The message logs is in decimal but should it be in hex?

Yea, I'd go with hex.  At least for the type since that's how they are specified in the spec.

This is now a 2 commit PR.
First commit is the implementation of the instanceof way.
Including a longer list of obselete record types.
The second commit makes an abstract handle function in OmfRecord and implemented in every type.
It makes the parse function even more simple and ensures that every record is handled or "documented" to not do anything.
lastDataBlock is moved to OmfFileHeader so it is tracked that way.
This change will obselete PR #4854 regardless of solution. :)
If second way is chosen I will of course merge the commits.
The code is untested, will test when I know what solution I should test. :)

Did a indentation fix on all files except OmfLoader.
Caused a "lot" of changes where a tab is being removed on empty lines.
Found that OmfLineNumRecord was created but not used in OmfFlieHeader, and contains no data of real use for Ghidra (linenumbers in source files).
So added a flag to OmfUnsupportedRecord to flag whether a message should be logged.
Could do a OmfUnusedRecord as the record type for this case.
Also marked all obselete record to not be logged.
As for the list of obselete record I have 2 sources:
OMF_v1.1.pdf - page 82 (reference on Wikipedia)
Include file for OMF format in Watcom compiler suite
Both OmfLibraryRecord and OmfFileHeader handles some part of the format.
OmfLibraryRecord isn't handled by OmfRecord at all. It is used as the container for each module where FileHeader is the first record.

Looks like we are almost there.  It really needs to be run through our eclipse formatter, and I see some other little design things that I think can be improved, but I'll address these things in a 2nd commit of my own to save some time.  Thanks!

Full fix is 1a36ad806e862de7f0bd9adfa16c112cdeb751ad


End to end example of remote data converter including tctl and ui

This branch is a testing ground for the new remote data converter support. It includes branch versions of: go-sdk, tctl and ui to tie all the changes together so they can be reviewed and tested.

SDK branch: https://github.com/temporalio/sdk-go/tree/rh-remote-encoder
tctl branch: https://github.com/temporalio/tctl/tree/rh-remote-encoder
UI branch: https://github.com/temporalio/ui/tree/rh-remote-encoder


Improve/walldelegate

@vadymmarkov what do you think about this approach ?

@zenangst Looks good. The only thing I don't really like it's that in WallDataSource we have methods like textTapped, it's kind of duplication, but it's also makes a sense because there we check for delegate and delegate method.

@vadymmarkov This is true, the current breadcrumb trail is pretty odd. I'll see if I can fix it :sunglasses:

@zenangst :cake:


Engineer/Intern Prompts

WHEN I select the engineer option
THEN I am prompted to enter the engineer’s name, ID, email, and GitHub username, and I am taken back to the menu

WHEN I select the intern option
THEN I am prompted to enter the intern’s name, ID, email, and school, and I am taken back to the menu


Missing 'iron-pureconfig' artifact

Describe the bug
Scala environment: JVM/Scala.JS/ScalaNative
Scala version: 3.4.1
Iron version: 2.6.0
Reproduction steps
The steps to reproduce the described issue
Add 'iron-pureconfig' dependency:
libraryDependencies += "io.github.iltotore" %% "iron-pureconfig" % "2.6.0"

Expected behavior
Artifact is available.
Current behavior
Artifact is not found.

Indeed it was not published. I'll check the cause once available and manually publish the missing version.

Found the "problem". Actually, the Pureconfig support was added after the release of 2.6.0. It will land in the next release, probably 3.0.0


Created Landing Page

Have you read the Contributing Guidelines on Pull Requests?
Yes
Description
Created landing page
Checklist

[x] I've read the contribution guidelines.
[x] This PR mets all the requirements like Clean Code, proper README and Documentation

Related Issues or Pull Requests
Fixes: #[123]

Screenshots (if any)
Original           | Updated

@devanshiv123 what is the [-------------url..... on the screenshot?
Also the page does not seem to be responsive, please do that too.

I think the url thing was in the PR template only. I have edited it. I will make it responsive.

Are you working on it @devanshiv123 ?

Are you working on it @devanshiv123 ?

@HarshCasper I have been working on it but I am not able to make it fully responsive. Please assign the issue to someone else if you want to, I dont think I will be able to do it in time. I am really sorry.


Right Click gives different UTM anwser than add-in pane

If you right click on a map and use the right click menu context to copy a UTM coordinate it is a different coordinate than what is on the coordinate view pane.
Example:
Coordinate Pane (This is also the coordinate ArcGIS Pro populates with the cursor on the point)
10S<PHONE_NUMBER>011
What is retrieved from the right click
10N<PHONE_NUMBER>026

@topowright Have you tested this in ArcMap? What version was this tested on in ArcGIS Pro?

Similar to #410

We need to give more clarity on this issue and issue #410


Project support, reorganize files, stdout output

Pass the project to executed rules in order to use the project path as context
Move functions around for clariry
make the checker Run function return the projects results

#sre


fix: handle encoded base paths

Description
supersedes and closes #16412
Due to the changes from https://github.com/vitejs/vite/pull/15311 (and tweaks thereafter) (Vite 5.2), I believe it broke most cases of base that contains encoded base paths, e.g. /foo%20bar/, which Vite encodes internally even if you pass /foo bar/.
I'm somewhat relieved that we didn't get a lot of reports of this, because base paths that look like this are hard 🥲

Because resolvedConfig.base is a URL-encoded string, when we merge it with some un-encoded strings, and encode the merged string, the base portion will get double encoded. The solution in this PR is to decode the base first.
In the future, maybe we can revisit if we want to have resolvedConfig.base be decoded only, or introduce a new resolvedConfig.decodedBase? Or we can say we don't support strange base paths.
NOTE: I also updated the code in plugin-legacy together as I noticed it while searching the codebase.

/ecosystem-ci run

Should we have a internal config._decodedBase to avoid all the new decodeURI calls?

/ecosystem-ci run analogjs

Should we have a internal config._decodedBase to avoid all the new decodeURI calls?

I was wondering that in the PR description too. I think I can refactor to that if we think it's cleaner.
Also, looks like I need to investigate the analog fail

When running the playground, I'm seeing two Pre-transform error. Are these expected?
$ pnpm -C playground/assets dev:encoded-base
...
  VITE v5.3.5  ready in 94 ms

  ➜  Local:   http://localhost:9524/foo%20bar/
  ➜  Network: use --host to expose
  ➜  press h + enter to show help
6:46:19 PM [vite] Pre-transform error: No matching HTML proxy module found from /foo bar/index.html?html-proxy&index=4.js
6:46:19 PM [vite] Pre-transform error: Failed to load url /foo bar/asset/main.js (resolved id: /foo bar/asset/main.js). Does the file exist?

I just pushed a fix to handle them. Looks like we were passing urls with decoded base, and then trying to strip with an encoded base, causing server.warmupRequest to not understand the path.
I'm not particularly happy with my fix as encoded and decoded urls/base are slightly more intertwined, but I think it's probably sufficient for now.

/ecosystem-ci run


⚠ Samsung has degraded performance

In 6874214, Samsung (https://samsung.com) experienced degraded performance:

HTTP code: 200
Response time: 2023 ms

Resolved: Samsung performance has improved in 37cc489.


Sidenav collapse menu item cannot be focused

Describe the bug
The sidenav collapsable nav menu titles are not focusable with keyboard.
How to reproduce
https://clarity.design/documentation/sidenav
Steps to reproduce the behavior:

Using the keyboard alone, try to tab to the  'Collapsible Nav' control and observe that you cannot

Expected behavior
It should be focusable.
Versions
App

Angular: [e.g. 6]
Node: [e.g. 8.10.0]
Clarity: [e.g. 0.12.5]

Device:

Type: [e.g. MacBook]
OS: [e.g. iOS]
Browser [e.g. chrome, safari]
Version [e.g. 22]

Additional notes
Use a button for this control, also use aria-expanded and aria-controls like an accordion, or simply use an accordion.

This should be resolved.

Collapsible Nav Element control now receives focus but cannot be activated using the keyboard. This control can only be used with a mouse . See. the Collapsible Nav Element example on https://clarity.design/documentation/sidenav.


Add scaffolding for request invite RPC

@chrisnojima Here's an early look at the functional request invite code, in case you want to pull it in.

:+1:

@keybase/react-hackers Added styling and RPC to this PR:
Zeplin:

GIF:

:+1: % c


ModuleNotFoundError: No module named 'object_detection'

When trying to run the notebook on google colab using Python 3 + GPU kernel, I get the error below. It looks like the correct folder has not been exported to the PATH
/root
Selecting previously unselected package libprotobuf10:amd64.
(Reading database ... 22298 files and directories currently installed.)
Preparing to unpack .../libprotobuf10_3.0.0-9.1ubuntu1_amd64.deb ...
Unpacking libprotobuf10:amd64 (3.0.0-9.1ubuntu1) ...
Selecting previously unselected package libprotoc10:amd64.
Preparing to unpack .../libprotoc10_3.0.0-9.1ubuntu1_amd64.deb ...
Unpacking libprotoc10:amd64 (3.0.0-9.1ubuntu1) ...
Selecting previously unselected package protobuf-compiler.
Preparing to unpack .../protobuf-compiler_3.0.0-9.1ubuntu1_amd64.deb ...
Unpacking protobuf-compiler (3.0.0-9.1ubuntu1) ...
Setting up libprotobuf10:amd64 (3.0.0-9.1ubuntu1) ...
Processing triggers for libc-bin (2.27-3ubuntu1) ...
Setting up libprotoc10:amd64 (3.0.0-9.1ubuntu1) ...
Setting up protobuf-compiler (3.0.0-9.1ubuntu1) ...
Processing triggers for libc-bin (2.27-3ubuntu1) ...
/root/models/research
Traceback (most recent call last):
File "object_detection/builders/model_builder_test.py", line 23, in
from object_detection.builders import model_builder
ModuleNotFoundError: No module named 'object_detection'

@dtrippas
Try this instead of os.environ:
%set_env PYTHONPATH=/root/models/research:/root/models/research/slim

Thanks @FoRomik
Solve my problem as well

Thanks @FoRomik That's solve my problem too :D


File upload issue

Files get uploaded but they don't get loaded into the model immediately. I have started working on a solution but it is not tested.

added file upload button, solves this issue


Compiled Versions Missing Required Module(s)

It appears that module(s) required for the LDAP protocol to run in the windows executable are not present.
Steps to reproduce the behavior:
Command: nxc.exe ldap <IP_ADDRESS>
Resulted in:

Expected behavior
The netexec LDAP protocol to function without error.
NetExec info

OS: Windows 10, Kali
Version of nxc: 1.0.0
Installed from: Executable

Hi, thanks for the report. This should already be fixed with #79.
I rerun the build-binary action for you so try the new binary:
https://github.com/Pennyw0rth/NetExec/suites/16742192422/artifacts/1004814088

Unfortunately, I am still seeing the error.

My bad, didn’t run the workflow properly. Can you try this one?
https://github.com/Pennyw0rth/NetExec/suites/17586142458/artifacts/1004886568

Looks all good on my end !!! Thanks !!


Sveltekit generated project using typescript has vite.config.js file instead of ts

Describe the bug
When generating a typescript project (skeleton) it gets me a vite.config.js file instead of .ts like it used to do in the past.
Playwright for example does has it's .ts file for it's config.
Reproduction
Generate a new typescript skeleton project, with all the options on yes (playwright, vitest, prettier and eslint).
Logs
No response
System Info
System:
    OS: macOS 12.6
    CPU: (10) arm64 Apple M1 Pro
    Memory: 2.98 GB / 32.00 GB
    Shell: 5.8.1 - /bin/zsh
  Binaries:
    Node: 16.17.1 - ~/Library/Caches/fnm_multishells/7782_1671956111960/bin/node
    npm: 8.15.0 - ~/Library/Caches/fnm_multishells/7782_1671956111960/bin/npm
  Browsers:
    Chrome: 108.0.5359.124
    Firefox Developer Edition: 106.0
    Safari: 16.0
  npmPackages:
    @sveltejs/adapter-auto: ^1.0.0 => 1.0.0
    @sveltejs/kit: ^1.0.0 => 1.0.1
    svelte: ^3.54.0 => 3.55.0
    vite: ^4.0.0 => 4.0.3

Severity
annoyance
Additional Information
No response

Is vite.config.ts even supported? I can't find reference to it in their docs.

yes it is, https://vitejs.dev/config/

Vite also directly supports TS config files. You can use vite.config.ts with the defineConfig helper as well.

So weird -- I even went to that page and Ctrl+F-ed for vite.config.ts! Thanks... 🙃

Doesn't #8258 implement this? Shouldn't it be closed?

Thank you for noticing, closing


Merging setup_wf and configure_arb_wf

Redundancy in two functions under drivers.instrument.py in class AWG where two functions serve the same purpose and could be merged for better usability.

fixed with latest commit. Now the _check_params works for both!


Complete re-write of two Xtend file to JAVA ( using modern JAVA

Description:

Link to tracking Issue:
Testing:
Documentation:

So Java has no extension methods concept. Have you considered how that fact will reflect on the remaining code?


Captive Network problem

Hi there,
Captive Network class is depreciated after IOS 9.. How did you handle it ?

That's true. For ios, plugin simply wraps the value of current connection in array of length 1 and sends it.

I want to learn, on ios how could I get wifi list like android ? Do you know or did you ever try this?


[chore] Update<EMAIL_ADDRESS>

Closes: #17
This PR updates rosetta-ethereum to<EMAIL_ADDRESS>Changes

[x] Update rosetta-sdk-go
[x] Update version

Pull Request Test Coverage Report for Build 211

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+5.7%) to 79.13%

Totals

Change from base Build 193:
5.7%

Covered Lines:
546

Relevant Lines:
690

💛  - Coveralls


tm_calendars_secs_from_bc aborts

Reported by Jonathan S Callahan on 11 Sep 2000 18:33 UTC
Using a dataset from WHOI I get the following:

jaguar callahan> ferret
NOAA/PMEL TMAP
Program FERRET
Version 5.22 - 07/27/00
11-Sep-00 11:29
yes?  use "http://www.wh.whoi.edu/cgi-bin/nph-nc/moor/gsc/mm1.cdf"
yes? show data
currently SET data sets:
1> http://www.wh.whoi.edu/cgi-bin/nph-nc/moor/gsc/mm1.cdf  (default)
name     title                             I         J         K         L
EAST     EAST_2                           1:1       1:1       1:1       1:4113
NORTH    NORTH_5                          1:1       1:1       1:1       1:4113
TEMPERATURE
TEMPERATURE_9                    1:1       1:1       1:1       1:4113
yes? plot/l=1:200 temperature
Subscript out of range on file tm_calendars_secs_from_bc.F, line 100, procedure
tm_calendars_secs_from_bc.
Subscript number 1 has value 0 in array days_before_month.
Abort
Migrated-From: http://dunkel.pmel.noaa.gov/trac/ferret/ticket/135

Comment by ansley.b.manke on 24 Jul 2010 00:01 UTC
Can't duplicate this bug.


Adding video upload support from ALAsset.

switching on ALAsset MIMEType via RegExp
buffered output for video type.

Very cool. Thanks!


add timestamp to printTrace

Andy,
See patch for adding timestamp to printTrace module. I really hoped to add timestamp to the same line as original log messages, but not sure how to do it.

Looks good to me. Thanks!


Add support for setting the VM admin password from vCloud

Add support for setting the VM admin password from vCloud
Description
These commits allow the user to establish the admin password of a virtual machine on its creation without having to connect to it. It uses the API provided by VMware and its VMware Tools.
Status
Done and ready for review.
Checklist (tick everything that applies)

[X] Code linting (required, can be done after the PR checks)
[x] Documentation
[X] Tests
[ ] ICLA (required for bigger changes)

Yes, you are right :)

thanks 👍


Add .env to .gitignore file generated in the starter code template

Description
When creating a new project running the npm create vite command, Vite generates a .gitignore file by default. However, the generated .gitignore file doesn't include the .env file paths as the files that should be untracked.
Since it is a common practice to keep .env files private and not commit them to a repository as they may contain private keys and given that Vite uses dotenv to load additional environment variables,  I think it would be a good idea to add .env files to the .gitignore.
Would there be any drawbacks to adding .env to the starter code .gitignore?
Suggested solution
Add .env files to the .gitignore generated by the create-vite tool.
Alternative
No response
Additional context
Content of the current default .gitignore file:
# Logs
logs
*.log
npm-debug.log*
yarn-debug.log*
yarn-error.log*
pnpm-debug.log*
lerna-debug.log*

node_modules
dist
dist-ssr
*.local

# Editor directories and files
.vscode/*
!.vscode/extensions.json
.idea
.DS_Store
*.suo
*.ntvs*
*.njsproj
*.sln
*.sw?

Validations

[X] Follow our Code of Conduct
[X] Read the Contributing Guidelines.
[X] Read the docs.
[X] Check that there isn't already an issue that request the same feature to avoid creating a duplicate.

.env files in Vite should not contain sensitive values by default, they should be in .env.local instead. As documented in https://vitejs.dev/guide/env-and-mode.html#env-files, *.local files are ignored by git.

@bluwy Thanks for taking the time to review the issue and for your prompt response.
Good point, but my concern is that the .env files are not being ignored by default. Ignoring *.local files won't necessarily prevent the accidental publishing of private or sensitive information contained in .env files. Therefore, it seems like a good idea to guard against this. I am curious to hear what other maintainers think about it. WDYT?
I have submitted a PR (#14383) with the changes, and I can also update the documentation if needed to reflect these changes. Thanks!


[#111760326] README: Add documentation about this fork.

NB: This is merging onto the gds branch of our fork.

Updated to match other PR.

LGTM


CentrifugeConnectEvent has not data property

Delegate.swift:
//...
public struct CentrifugeConnectEvent {
    public var client: String
}
//...

Specification Connect result fields:

Field
Type
Optional
Description

data
JSON
yes
a custom data to send to the client in connect command response.

In Java all is OK ;)
ConnectEvent.java
package io.github.centrifugal.centrifuge;

public class ConnectEvent {
    public String getClient() {
        return client;
    }

    void setClient(String client) {
        this.client = client;
    }

    public byte[] getData() {
        return data;
    }

    void setData(byte[] data) {
        this.data = data;
    }

    private String client;
    private byte[] data;
}

The same situation in dart library, but not in swift

Hello @shalom-aviv
Thanks, yeah, I noticed this and fixed while working on #58  (code). But that PR changes lots of things and will land a bit later (part of https://github.com/centrifugal/centrifugo/issues/500) – so for now we still need to support this field separately in current master.
Do you want to send PR supporting this? If not - I'll be able to add the missing field at some point (hopefully this week).

Please review my changes in pull request:
https://github.com/centrifugal/centrifuge-swift/pull/67
Thank you

Thanks! Just released 0.4.6

Awesome!
You are very speedy!
Thanks


.get() cannot return stored non-JSON values

I have tried to upgrade from version 0.15 to 0.2.1, but the latest version cannot read value stored with the previous one.
We store a token by using:
localStorageService.set('token', newToken); // newToken is just alphanumeric characters

And now the following code is crashing:
localStorageService.get('token'); // token is just alphanumeric characters

I had a look at the code and the issue is that now you always apply JSON.parse() while before you used to call fromJson() only when it made sense.
Is it possible to revert to the previous behavior? Why has this change been made?

I have the same problem.  I tracked it down to this code
0.2.0
    if (isUndefined(value)) {
        value = null;
  } else if (isObject(value) || isArray(value) || isNumber(+value || value)) {
        value = toJson(value);
      }

0.2.1
if (isUndefined(value)) {
        value = null;
      } else {
        value = toJson(value);
      }

Can you please provide some example @tbassetto ?
Please take a look on #225, #222, #214, etc.. if you want to get some point why this changes made for.
Thanks.

This sounds like a breaking change that needs to be noted in the changelog.
for example: these key value paris cause an error

@a8m please look at examples from previous comment

thanks @tbassetto for pointing out the root of the problem and agree with @btesser. while this change certainly makes sense, there should be alarm bells. it got deployed in production before we caught it and now i have to monkey wrench things back into shape with stuff like:
if (/^[a-zA-Z0-9]*$/.test(token)) {
    console.log('jsonifying token');
    localStorage['ls.token']=JSON.stringify(token);
  }

(of course that only handles the localStorage version, not the cookie based fallback.)

Fixed via v0.2.2.
Can you please validate that this issue has been resolved?

Doesn't matter for my use case, but if someone was storing quoted strings based on the old setter function, wouldn't this inadvertently remove them? I.e. imagine a "This is a famous quote" stored verbatim as as string.
Seems like a difficult problem to fully solve because there's no telling how people may have used (or abused?) the original verbatim string functionality.

Still not working for me, because the try-catch doesn't seem to work the way it should.
Debugged your code a bit and found following solution for me:
Your old code:
try {
   return JSON.parse(item);
} catch (e) {
   return item;
}

My fix:
try {
   a = JSON.parse(item);
   return a;
} catch (e) {
   return item;
}

Because of this the try-catch now seems to work!


add downstream polars test

Hey - just wanted to suggest this as a "sister PR" to https://github.com/pola-rs/polars/pull/13238
Then, we could be confident that the "Polars 🤝 hvPlot" compatibility stays stable?

Then, we could be confident that the "Polars 🤝 hvPlot" compatibility stays stable?

We'll 100% make sure of that!


Update Readme

Status
READY
Migrations
NO
Description
A few sentences describing the overall goals of the pull request's commits.
Updates readme for clarity, grammar
Deploy Notes
N/A

Impacted Areas in Application
List general components of the application that this PR will affect:

Updates Readme for clarity

Thanks for contribute.


Location of "Notes.db3"

Thanks for another great tutorial, sir!
I tried to find the location of "Notes.db3" so that I can try to modify the other way around to see the effect. (Modify from DB using "DB Browser (SQLite)", reflect the change in UI)
I tried to add
Console.WriteLine("Notes.db3 location: {0}", Environment.GetFolderPath(Environment.SpecialFolder.LocalApplicationData));
Got this location:
/data/user/0/com.companyname.Notes/files/.local/share
But when I looked into the phone's file structure, still can't find it ...
Am I missing some knowledge here, sir?

Hi @tpham210
Apologies for the delayed response.
The location is a private directory for your application, and so you won't be able to see the file using a file browser (unless it has root privileges). However, you can use add to inspect the file, or write code to copy it to a known public location on the device.
I suggest you take a look at:
https://forums.xamarin.com/discussion/87597/xamarin-extract-android-sqlite-to-a-local-folder-on-the-device
AND
https://forums.xamarin.com/discussion/129543/how-can-i-see-my-database
Hope this helps!


flutter inwebview not available

Hi, I am using things board pe flutter app.
I finally found the error part.
There seems to be a security issue with the flutter in webview. Is there anything else I need to set up?

Hello @yunamoon,
I will close this issue since a significant amount of time has passed since your initial query. However, if the issue is still relevant, please feel free to reopen it and provide additional information, such as the mobile app console output.
Thanks!


Evolution search in AutoFormer  embedding size mismatch

I  am trying to run the evolution search in AutoFormer with the following code:
CUDA_AVAILABLE_DEVICES=0 python3 -m evolutionNLP --gp --change_qk --relative_position --dist-eval --cfg ./experiments/supernet/supernet-S.yaml --resume  ./output_path/checkpoint.pth --min-param-limits 50 --param-limits 120
I keep getting the following error:
RuntimeError: Error(s) in loading state_dict for TransformerSuper:         size mismatch for blocks.0.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.0.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.0.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.0.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.1.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.1.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.1.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.1.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.2.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.2.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.2.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.2.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.3.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.3.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.3.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.3.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.4.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.4.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.4.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.4.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.5.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.5.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.5.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.5.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.6.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.6.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.6.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.6.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.7.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.7.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.7.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.7.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.8.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.8.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.8.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.8.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.9.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.9.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.9.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.9.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.10.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.10.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.10.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.10.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.11.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.11.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.11.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.11.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.12.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.12.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.12.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.12.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.13.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.13.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.13.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).         size mismatch for blocks.13.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).
I used the same yaml file for both supernet training and evolution. any idea what this could be?

I am trying to run the evolution search in AutoFormer with the following code:
CUDA_AVAILABLE_DEVICES=0 python3 -m evolutionNLP --gp --change_qk --relative_position --dist-eval --cfg ./experiments/supernet/supernet-S.yaml --resume ./output_path/checkpoint.pth --min-param-limits 50 --param-limits 120
I keep getting the following error: RuntimeError: Error(s) in loading state_dict for TransformerSuper: size mismatch for blocks.0.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.0.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.0.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.0.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.1.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.1.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.1.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.1.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.2.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.2.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.2.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.2.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.3.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.3.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.3.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.3.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.4.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.4.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.4.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.4.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.5.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.5.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.5.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.5.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.6.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.6.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.6.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.6.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.7.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.7.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.7.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.7.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.8.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.8.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.8.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.8.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.9.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.9.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.9.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.9.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.10.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.10.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.10.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.10.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.11.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.11.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.11.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.11.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.12.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.12.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.12.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.12.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.13.attn.rel_pos_embed_k.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.13.attn.rel_pos_embed_k.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.13.attn.rel_pos_embed_v.embeddings_table_v: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]). size mismatch for blocks.13.attn.rel_pos_embed_v.embeddings_table_h: copying a param with shape torch.Size([130, 64]) from checkpoint, the shape in current model is torch.Size([30, 64]).
I used the same yaml file for both supernet training and evolution. any idea what this could be?

Solved by changing the max relative position to match the one in the saved checkpoint


[8.x] Route group for same controller

Sometimes a controller that is responsible for a resource may use non-REST format, for example:

Deletion of user may be a GET request on /users/{id}/delete
Creation is a POST request on /users/{id}/store
The resource may have some additional actions.

In this cases the current 'resource' method is not flexible enough, but it still would be intuitive to group them based on the controller that processes these requests. The grouping also would reduce number of controller's class name repetitions.
I noticed this kind of grouping is very handy after using similar 'controller' method in Ruby on Rails.
Also, we already have a 'namespace' grouping option and controller grouping might work well in combination with it, or be an alternative in some places:
use Illuminate\Support\Facades\Route;
use App\Http\Controllers\UsersController;

// grouping with fully qualified class name
Route::group([ 'controller_class' => UsersController::class ], function () {
    // defining custom CRUD operations
    Route::get('/users', 'index');
    Route::post('/user-create', 'store');
    Route::post('/users/{id}/delete', 'destroy');
    // maybe some additional actions
    Route::get('/users/{id}/permissions', 'getPermissions');
});

// grouping with namespaces
Route::group([ 'namespace' => 'App\Http\Controllers' ], function () {
    Route::group([ 'controller_class' => 'UsersController' ], function () {
        Route::get('/users', 'index');
    });
});

// this will not work
Route::group([ 'namespace' => 'App\Http\Controllers' ], function () {
    Route::group([ 'controller_class' => UsersController::class ], function () {
        Route::get('/users', 'index');
    });
});

// using registrar interface
Route::controller(UsersController::class)->group(function () {
    Route::get('/users', 'index');
});

I had to name the key 'controller_class', since name 'controller' was already occupied in Route parameters for 'controller@method' string.
This feature is small and should not change any of the current behaviors and just add another option to users, so I decided it should belong to 8.x release. If not, I am sorry for picking the wrong branch.

Have you tested this with route caching?

@morloderex yes, php artisan route:cache works as expected

Thanks for your pull request to Laravel!
Unfortunately, I'm going to delay merging this code for now. To preserve our ability to adequately maintain the framework, we need to be very careful regarding the amount of code we include.
If possible, please consider releasing your code as a package so that the community can still take advantage of your contributions!
If you feel absolutely certain that this code corrects a bug in the framework, please "@" mention me in a follow-up comment with further explanation so that GitHub will send me a notification of your response.


AutoComplete unknown props validationError, validationErrors

Hi, this code produces the following error :

Warning: Unknown props validationError, validationErrors on  tag. Remove these props from the element. For details, see https://fb.me/react-unknown-prop
in input (created by TextField)
in div (created by TextField)
in TextField (created by AutoComplete)

<FormsyAutoComplete
	name='userId'
	floatingLabelText="How often do you?"
	dataSource={this.state.users}
	dataSourceConfig={sourceConfig}
/>

I tried with AutoComplete from material-ui, it works fine

Did you resolve it somehow? I have exactly the same issue ...

apparently #119 fixes it but still errors, let me know if you find a fix

@weits have you figured out a fix?

this issue should fix the issue. Please update formsy-react dependency to 0.18.1

I use just selects until it is fixed. My formsy-react is at version 0.18.1 so I doubt it will help.

any solution??

Was this a dup of #183? I think #184 fixes this.

Please re-try with latest v0.5.4

I have been evaluating (trying to get started with) formsy-material-ui, and hit this error simply trying to run the webpack example
I upgraded package.json with
"formsy-react": "^0.18.1",
"formsy-material-ui": "^0.5.4",

The example supplied by the project doesn't work. Doesn't make you feel very sure about choosing formsy-material-ui as your forms library, does it..

Any update on this ?


Remove out of date PSGallery kubectl install instructions

This PR removes out of date PSGallery kubectl installation instructions.
Fixes https://github.com/kubernetes/website/issues/26956.
Note for reviewer: This is my first website contribution (🥳 ). Not sure if the localized changes need to be against master or localized branches.

@sftim ahh thanks! Change made.
/assign @onlydole

/remove-language de
/remove-language es
/remove-language fr
/remove-language id
/remove-language ja
/remove-language ko
/remove-language ru
/remove-language vi
/remove-language zh

/kind cleanup
Page preview:
https://deploy-preview-27467--kubernetes-io-master-staging.netlify.app/docs/tasks/tools/install-kubectl-windows/

/lgtm
SIG Windows, we can review a PR to reinstate this if needed.


Fix the Required attribute description

Related to: https://github.com/aspnet/AspNetCore.Docs/pull/13988

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

@cnolewajka  Thanks!


Add roles and groups (Local Chapters)

Currently, we do not have defined any roles and groups. I would propose to add these asap because we need them in the next steps to be integrated with projects and organisations. I propose the following steps/tasks:

[ ] Add separate table for user_roles to normalize the schema
[ ] Introduce roles: Workspace Admin, Group Coordinator, Group Member
[ ] Add group table

@KonradUdoHannes @DatenBergwerker could you please add your thoughts and requirements?

I'm thinking of roughly the following.

Member:  Can see and edit projects they are invited to. Use case are project team members helping documenting the respective project.
Group Coordinator: Can view, create and edit projects for a specific group and can invite Members. Use case are LC core teams managing local projects.
Chief Coordinator: Can view, create and edit projects irrespective of their group. Can invite Members. Can invite Group Coordinators. Can create Groups. Use case are is the core team that supports projects in potentially any group.
Tech Admin: Can do everything a Chief  Coordinator can do and can additionally bypass normel project lifecycle restrictions to fix issues etc. Use case is tech support and dealing with unexpected issues.

I'm still not sure whether we need a Group Member, i.e. a low permission account associated with a group, in addition to a Member, i.e. a low permission account associated with one or multiple projects. Right now I cannot think of a good use case and it seems to me that working on one group project should not give access to other group projects by default, which in my view favors Member as opposed to Group Member.

@KonradUdoHannes Thank you for the detailed descriptions. We can also start without the Group Member and see later in the meeting with the Project Team if the role is needed at all.


warnings "relocation refers to discarded section" when using static boost libs

Thanks for providing these scripts, they help a lot.
When including the boost libs (built with Boost-for-Android) in an NDK shared lib project -- specifically, I need boost_system and boost_thread -- ndk-build is giving me the following warnings:
jni/../../../Boost-for-Android/build/lib/libboost_thread-gcc-mt-1_53.a(thread.o):thread.cpp:function non-virtual thunk to boost::exception_detail::bad_alloc_::~bad_alloc_(): warning: relocation refers to discarded section
jni/../../../Boost-for-Android/build/lib/libboost_thread-gcc-mt-1_53.a(thread.o):thread.cpp:function non-virtual thuntk to boost::exception_detail::bad_exception_::~bad_exception_(): warning: relocation refers to discarded section
jni/../../../Boost-for-Android/build/lib/libboost_thread-gcc-mt-1_53.a(thread.o):thread.cpp:function non-virtual thunk to boost::exception_detail::error_info_injector<boost::thread_resource_error>::~error_info_injector(): warning: relocation refers to discarded section
jni/../../../Boost-for-Android/build/lib/libboost_thread-gcc-mt-1_53.a(thread.o):thread.cpp:function non-virtual thunk to boost::exception_detail::error_info_injector<boost::lock_error>::~error_info_injector(): warning: relocation refers to discarded section
jni/../../../Boost-for-Android/build/lib/libboost_thread-gcc-mt-1_53.a(thread.o):thread.cpp:function non-virtual thunk to boost::exception_detail::error_info_injector<boost::condition_error>::~error_info_injector(): warning: relocation refers to discarded section

It's unclear to me if they have particular consequences -- the build suceeds, the app runs -- but I'm investigating some spurious issues (which MAY be completely unrelated, but threading issues are notoriously difficult...). I'd feel more comfortable fixing these warnings (or at least knowing that they can be ignored...).
Here are the relevant (I hope) sections of my Android.mk which uses boost:
LOCAL_PATH := $(call my-dir)
...

include $(CLEAR_VARS)
LOCAL_MODULE := boost_system-prebuilt
LOCAL_SRC_FILES = ../../../Boost-for-Android/build/lib/lib$(BOOST_LIB)-gcc-mt-1_53.a
include $(PREBUILT_STATIC_LIBRARY)

include $(CLEAR_VARS)
LOCAL_MODULE := boost_thread-prebuilt
LOCAL_SRC_FILES = ../../../Boost-for-Android/build/lib/lib$(BOOST_LIB)-gcc-mt-1_53.a
include $(PREBUILT_STATIC_LIBRARY)

...

include $(CLEAR_VARS)

LOCAL_MODULE := my_module

...

LOCAL_CFLAGS += -std=gnu++11

LOCAL_STATIC_LIBRARIES := \
    (other libs here, including OpenCV) \
    boost_thread-prebuilt boost_system-prebuilt \

LOCAL_SHARED_LIBRARIES := \
    (also some other libs here) \
...

(source files, etc)

LOCAL_C_INCLUDES := \
    (other paths) \
    $(LOCAL_PATH)/../../../Boost-for-Android/boost_1_53_0 \

LOCAL_ARM_MODE := arm

include $(BUILD_SHARED_LIBRARY)

The boost libs have been built with
./build-android.sh ~/android-devel/android-ndk-r10d/

...and the project is subsequently built with
~/android-devel/android-ndk-r10d/ndk-build -j4

Searching for the error message online suggests that warnings like this may occurr when using different compiler versions and such, but I haven't found anything that appeared to be applicable here; or better said: which I was able to apply here.
Any hints as to how to eliminate the warnings' cause or where I might find more information are appreciated :) Thanks!

Actually, here's an idea following up on the 'different compiler version' lead: you can specify the API version to be used when building an NDK project by specififying it in the jni/Application.mk as follows:
APP_PLATFORM := android-21
Is there an equivalent to that statement when building Boost-on-Android? Where would I specify that?


Consistently show bot icon after bot name #26831

Adding an is_bot property in input_pill's create method.
Fixes:
Showing bot icon after bot name in compose message - Link
Screenshots:
Tooling tips: https://zulip.readthedocs.io/en/latest/tutorials/screenshot-and-gif-software.html
Screenshots and screen captures:

Self-review checklist

[X ] Self-reviewed the changes for clarity and maintainability
(variable names, code reuse, readability, etc.).

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Add CosmoPower P(k,z)

Merging will close #84
Some things to think about so far:

Will build this out because I want to use it in a Likelihood (CrossCorrelationLikelihood) which needs a Pk (delta_tot, delta_tot) grid. It would be better to use the full machinery inhereted from BoltzmannBase.
CosmoPower networks do not contain metadata about valid parameter ranges. It would be good to think about a way of packaging them with it and then using them here to prevent sampling outside those ranges.
I don't know how to manage that different params are supported for Pk than tt, te, ee.

Superceded by #88


Do we need to train a seperate model for each dataset?

@wenwenyu Thanks for your greate work.
For different datasets, do we have to train a seperate model for different datasets? Or we can mix all the different types of datasets and train a single model with a large number of entities.

@etrigger If all the required entities are present in all the datasets and the datasets layout is similar then it's a good idea to train a single model.


Launching with no arguments should produce help text

It should not say "required command was not present" followed by help text.

It does now -- there's an error, followed by help text.


incremental improvements and documentation

Add jspsych plugins required by @CMonnin to runtime
Use jpeg for all images
On ourreach site, edirect to same page on language change if possible
Some structural changes and small additions to instrument docs
Add load testing package with k6

i'll need @jspsych/plugin-survey-html-form too at some stage

@jspsych/plugin-survey-html-form

Will come in next PR


[main] Merge from nightly for 1.18.1-1, 1.17.9-1 with linux-arm64

Auto-update infra updated the nightly branch with 1.18.1-1 and 1.17.9-1, so merge to get those changes. I double checked that they applied correctly by running dockerupdate -f ... again with the new build asset JSONs--no diff.
This merge also means we'll produce linux-arm64 images for this release.
This is a fast-forward merge, since I merged main into nightly recently.

(This PR contains changes to the FIPS images that shouldn't be built/released yet, because they're nightly updates. This is normal: the release process is to only build the non-FIPS images after merging this PR. Once the boring branch is updated, I'll be doing another main PR that updates to that FIPS build and then build the FIPS images.)

This is now up on MCR.


Add static build for jsoncpp

Provide a detailed description of the proposed feature
jsoncpp is only installed as a shared dylib. Could a static build be added a well?
What is the motivation for the feature?
From https://github.com/Homebrew/homebrew-core/issues/16441 - If someone requests them, or it's trivial to build both, we usually do.
How will the feature be relevant to at least 90% of Homebrew users?
Most of the brew formula will build static libs. And for such a small library, a shared lib does not make sense.
What alternatives to the feature have been considered?
brew edit jsoncpp
I added
  def install
  args = std_cmake_args
  args << "-DBUILD_SHARED_LIBS=OFF"

Then
brew reinstall jsoncpp
But still no static libs were installed.

We'll review a pull request that installs the static libraries in addition to the shared ones.
For future reference, this issue tracker is for issues regarding the brew command-line tool. Formula related issues should be addressed at https://github.com/Homebrew/homebrew-core. Note that we don't usually take feature requests there -- those should be made in the form of pull requests. Thanks!


Blacklist gulp-static-site-generator

I've written a project, https://github.com/straticjs, that will do the same thing but in an idiomatic gulp way (the project consists of many modules and a Yeoman generator). I'm reluctant to suggest it as a replacement in this blacklist entry for fear of being too opinionated, etc., but I'd be happy to change it if desired ;)

FYI @simbo

I don't see what your project has to do with blacklisting gulp-static-site-generator. (like the existence of any one of hundreds of static site generators out there would be a reason to deprecate another one...)
Regarding your described reason "does too much": this is exactly the reason why this plugin exists - because generating a static site with gulp plugins can be a complex and time-consuming approach. This plugin has everything wired together and in the end, it does one thing - generating a static site...

Creating something new doesn't mean you get to add everyone else to the blacklist.
Blacklist is for duplicates, broken modules, stuff that breaks the vinyl spec, etc.

@contra @simbo as I said earlier, admittedly buried in the diff, I didn't submit this to the blacklist because of my project, I submitted it because it "does too many things" - reasoning we've applied to many plugins already. https://github.com/gulpjs/gulp/blob/master/docs/writing-a-plugin/guidelines.md says, do one thing. The problem with this module is that it does many: it compiles Jade, it renders Markdown, parses frontmatter, etc.
Again, sorry for the confusion caused by mentioning my project - I wasn't saying that had anything to do with why I think this module should be blacklisted, just pointing out an alternative approach that solves the problems with this module. (IMHO, obviously.)

@strugee I think that you are right about not doing 1 thing but approaching it in a way that promotes your project is what got this closed.  I'll put this on my backlog to review in the future.

@phated right, totally understand - didn't mean to seem like I was promoting my project (that's why I didn't mention it in the actual diff). Do you want to reopen in the meantime?


Update DG issues

Pls ignore the commits for the changes to the test case (i accidentally pushed it to the wrong branch)

Codecov Report

Merging #217 (5b25601) into master (8fe53e0) will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master     #217   +/-   ##
=========================================
  Coverage     72.88%   72.88%
  Complexity      743      743
=========================================
  Files           108      108
  Lines          2423     2423
  Branches        280      280
=========================================
  Hits           1766     1766
  Misses          583      583
  Partials         74       74

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integration: Use wbitt/network-multitool for dns integration test.

Hi.
This PR changed the name of docker image used for DNS integration test because:
========================= IMPORTANT ==============================

# Press-release: `Praqma/Network-Multitool` is now `wbitt/Network-Multitool`

## 05 Jan 2022 - Important note about name/org change:
Few years ago, I created this tool with Henrik Høegh, as `praqma/network-multitool`. Praqma was bought by another company, and now the "Praqma" brand is being dismantled. This means the network-multitool's git and docker repositories must go. Since, I was the one maintaining the docker image for all these years, it was decided by the current representatives of the company to hand it over to me so I can continue maintaining it. So, apart from a small change in the repository name, nothing has changed.

The existing/old/previous container image `praqma/network-multitool` will continue to work and will remain available for **"some time"** - may be for a couple of months - not sure though.

- Kamran Azeem<EMAIL_ADDRESS>[https://github.com/KamranAzeem](https://github.com/KamranAzeem)

## Some important URLs:
* The new official github repository for this tool is: [https://github.com/wbitt/Network-MultiTool](https://github.com/wbitt/Network-MultiTool)
* The docker repository to pull this image is now: [https://hub.docker.com/r/wbitt/network-multitool](https://hub.docker.com/r/wbitt/network-multitool)

Best regards.

Thank you for the review!


Expose Users Identity/Refresh Tokens

Expected Behavior

I can get the users Identity token in raw format so I can retrieve the non-standard claims that are provided in the token.

I can retrieve the users Refresh token so I can choose exactly when I want to fetch a new access token inside of my application.

Actual Behavior
It's currently only possible to retrieve the users Access token. We should keep inline with all other IDM SDK's which expose every token to the developer.
Specifications

Core SDK Version: 0.0.1.SNAPSHOT
Relevant Service Modules: Auth

Integrated in https://github.com/aerogear/aerogear-android-sdk/pull/133


[Bug] Duplicates are created when importing twice

Duplicates are created when importing twice - there should be an option to corsscheck if the entry is already present - or (preferable) a tool which detects duplicates and gives the option to remove them.
-> It might be wise to add tags to transfered time entries

I started working on this but didn’t want it to hold up the initial release (which I was aiming for Monday). It’s going to require some complex logic to prevent duplicate entries. In the interim, I can add the delete functionality in pretty quickly. I already have some a script that deletes everything on Clockify (in the /scripts folder). I just need to port it over to TypeScript.


[Impeller] TextureSourceVK::SetLayout API is hard to use correctly.

If the new layout is the same as the old layout, the barrier is never inserted. This may cause issues if the transition is elided. And the caller may depend on the barrier being inserted. The method must return if a transition was actually performed.

We should probably just always insert the barrier?

Yeah, that would work but I am not sure about the performance implications. Likely minor. If there was an fml::Status where T was an enum, we could return a status that said the layout was already correct.


Should the Zstid CSRs be guarded by CRE

The description for CRE says:

Executing CSR instructions accessing any CSR added by Zcherihybrid (see Table 25) causes an illegal instruction exception

But this doesn't include the CSRs added by Zstid. Should they be included as well?
From @PRugg-Cap :

We need to make sure sneaky user-mode software can't stash values that are hidden from legacy OSs. That means either TID needs to be guarded on CRE, or more likely (but more annoyingly) we need to have another enable bit for the TIDs.

they definitely need an enable bit - so sharing CRE seems most sensible.
opinions?

If it’s a separate extension it needs its own enable. Even if it’s dependent on CHERI you could write software for CHERI without xtid, which will then be broken if you add xtid without its own enable.

I was worried you might say that...

I also think there this should not be gated by CRE, but instead using a state-enable bit. The capability extended versions should definitely be guarded by CRE though.

yeah - a state enable seems likely to be required


The Sheet component is missing from the package - @shopify/ui-extensions-react

Please list the package(s) involved in the issue, and include the version you are using

<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>
Describe the bug
Running the npm run dev command result in the following error message:
extensions/test-checkout-extension/src/Checkout.jsx:8:2: ERROR: No matching export in
<EMAIL_ADDRESS>for import "Sheet"
Steps to reproduce the behavior:

In order to test the Sheet component I created a new blank JavaScript React checkout extension
After that, I updated the @shopify, @shopify/ui-extensions-react, and @shopify/checkout-ui-extensions-react making sure that they are using the latest versions. The versions can be checked at the beginning of my issue description.
After that, I copied the example provided in the Sheet component's documentation and applied the code to my new checkout extension
Then I execute the npm run dev command which resulted in the error message i provided above.

Expected behavior
The Sheet component to be loaded successfully.
Screenshots
This is a video showcasing the version of the packages and the error - https://monosnap.com/file/w6IcdcoJBt3blvBmpRdfzxcL3CrtzO
Additional context

@AlexVasVas it's part of unstable and unstable often has releases that might not get picked up in your lockfile. If you find that you've installed unstable, re-creating your lockfile often does the trick.


Using with SystemJS

When using with SystemJS in browser, I get "rb" is not a function error.
Do have have any working examples with SystemJS?

we do not

Do you have any plans to support systemjs?
Sent from my iPhone

On Nov 29, 2016, at 9:26 PM, Roman Shtylman<EMAIL_ADDRESS>wrote:
we do not
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub, or mute the thread.

Nope

Guess I will have to drop this library from my project then
Sent from my iPhone

On Nov 29, 2016, at 9:55 PM, Roman Shtylman<EMAIL_ADDRESS>wrote:
Nope
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub, or mute the thread.

Your SystemJS setup is ignoring the browser field uuid provides indicate when to use rng.js vs. rng-browser.js.  See https://github.com/systemjs/systemjs/issues/860#issuecomment-149982732

Nope, still doesn't work... The only way I can get it to work is to modify rng-browser.js, and change the last line to
module.exports = { randomBytes: rng };

But still, I'm developing a library myself, and I need something that just works out of the box for the users of my library.

If you're getting rb is not a function, then you're still loading rng.js rather than rng-browser.js
kieffer@Roberts-MacBook-Pro$ grep -r --exclude-dir .git "\Wrb\W" .
./lib/rng.js:var rb = require('crypto').randomBytes;
./lib/rng.js:  return rb(16);

Nope, that was the first error, after patching in rng-browser.js is still does not work because it doesn't return an object with the same signature as the other one
Sent from my iPhone

On Nov 30, 2016, at 9:16 AM, Robert Kieffer<EMAIL_ADDRESS>wrote:
If you're getting rb is not a function, then you're still loading rng.js rather than rng-browser.js
kieffer@Roberts-MacBook-Pro$ grep -r --exclude-dir .git "\Wrb\W" .
./lib/rng.js:var rb = require('crypto').randomBytes;
./lib/rng.js:  return rb(16);
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You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub, or mute the thread.

Sorry, I don't know what to tell you at this point.  Let us know if you track this down to an actual issue with this module, I guess. :-/


Sample Added: Application Customizer to dynamic data with other Webparts

Q
A

Bug fix?
no

New feature?
no

New sample?
yes

What's in this Pull Request?
In this Pull Request I add an SPFX Extension of the Application Customizer type that can be a dynamic data source.  In order to check its correct functioning, a webpart is added in which a query is made to the search service

thx Ardian, appreciated. Let us know if you are interested on demonstrating this in on one of the upcoming SPFx community calls.


Page is incorrect state after successful purchase

After you successfully buy and nft the page you are on still says "For Sale" and the button "Buy Now".
Either the page should refresh or they should be redirected to the Collections page on success.
#121
@mycodecrafting

This is also true if you cancel an NFT sale. You wind up in a state where your NFT looks like its still available for sale.