Numpy/Astropy PyObject RuntimeWarning not ignored when testing a single file with Python 3.10

When running pytest on a single file with Python 3.10, I get the following warning: RuntimeWarning: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 96 from PyObject. I seems to be ignored by pyproject.toml, but is not ignored when running a single module (e.g. pytest amical/tests/test_cli.py`). In Python 3.9 everything seems to work as expected.

Oh maybe the pyproject.toml is ignored when running 1 specific module? @neutrinoceros is our expert here 🙂

For context this warning comes (very likely) from a mistake in astropy's compilation, which is not in our control, hence we (try to) ignore it. When you compare a Python 3.10 and a Python 3.9 env, you're actually using different wheels for astropy, and it's possible that only the 3.10 one is broken in that sense.
Now, I don't know why pytest seems to ignore to read the configuration file
here's what I tried
cd /tmp
git clone git@github.com:neutrinoceros/AMICAL.git
python3.10 -m venv .env
source .env/bin/activate
pip install ".[dev]"
pytest amical/tests/test_io.py

And indeed I reproduce the problem you're reporting
  Pytest log
========================================== test session starts ===========================================
platform darwin -- Python 3.10.1, pytest-7.0.0, pluggy-1.0.0
rootdir: /private/tmp/AMICAL, configfile: pyproject.toml
plugins: cov-3.0.0
collected 0 items / 1 error
================================================= ERRORS =================================================
________________________________ ERROR collecting amical/tests/test_io.py ________________________________
amical/tests/test_io.py:7: in
import amical
.env/lib/python3.10/site-packages/amical/init.py:6: in
from .analysis.fitting import fits2obs
.env/lib/python3.10/site-packages/amical/analysis/fitting.py:11: in
from amical.analysis import models
.env/lib/python3.10/site-packages/amical/analysis/models.py:4: in
from amical.tools import mas2rad
.env/lib/python3.10/site-packages/amical/tools.py:18: in
from astropy.nddata import Cutout2D
.env/lib/python3.10/site-packages/astropy/nddata/init.py:11: in
from .nddata import *
.env/lib/python3.10/site-packages/astropy/nddata/nddata.py:13: in
from astropy.wcs.wcsapi import (BaseLowLevelWCS, BaseHighLevelWCS,
.env/lib/python3.10/site-packages/astropy/wcs/init.py:26: in
from .wcs import *
.env/lib/python3.10/site-packages/astropy/wcs/wcs.py:56: in
from .wcsapi.fitswcs import FITSWCSAPIMixin, SlicedFITSWCS
.env/lib/python3.10/site-packages/astropy/wcs/wcsapi/fitswcs.py:11: in
from astropy.coordinates import SpectralCoord, Galactic, ICRS
.env/lib/python3.10/site-packages/astropy/coordinates/init.py:16: in
from .builtin_frames import *
.env/lib/python3.10/site-packages/astropy/coordinates/builtin_frames/init.py:29: in
from .fk5 import FK5
.env/lib/python3.10/site-packages/astropy/coordinates/builtin_frames/fk5.py:11: in
from .utils import EQUINOX_J2000
.env/lib/python3.10/site-packages/astropy/coordinates/builtin_frames/utils.py:16: in
from astropy.utils import iers
.env/lib/python3.10/site-packages/astropy/utils/iers/init.py:2: in
from .iers import *
.env/lib/python3.10/site-packages/astropy/utils/iers/iers.py:23: in
from astropy.table import QTable, MaskedColumn
.env/lib/python3.10/site-packages/astropy/table/init.py:4: in
from .column import Column, MaskedColumn, StringTruncateWarning, ColumnInfo
.env/lib/python3.10/site-packages/astropy/table/column.py:22: in
from ._column_mixins import _ColumnGetitemShim, _MaskedColumnGetitemShim
astropy/table/_column_mixins.pyx:1: in init astropy.table._column_mixins
???
E   RuntimeWarning: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 96 from PyObject
======================================== short test summary info =========================================
ERROR amical/tests/test_io.py - RuntimeWarning: numpy.ndarray size changed, may indicate binary incompa...
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
=========================================== 1 error in 21.34s ============================================

I can also confirm that pytest runs smoothly with a simple invoke.
I thought this could be a regression in pytest 7.0 which just came out a couple days ago so I also tried
pip install "pytest < 7"
pytest amical/tests/test_io.py

but the issue persisted.
Still, this looks like a pytest bug to me, so the next step is to try and reproduce this situation in a much smaller env.

the next step is to try and reproduce this situation in a much smaller env.

So I did just that, but couldn't reproduce.
Now after taking a closer look to the report I note that the error we're seeing now is
Expected 88 from C header, got 96 from PyObject
while in pytest's configuration we're only ignoring
Expected 80 from C header, got 96 from PyObject
And indeed, generalizing this string (which is really just a regexp) solves the issue. I'll open a PR.


👉 Filter on Active WELLS

👉 Is your feature request related to a problem? Please describe.
This task is related to User Story #177
Users should be able to filter on Active Wells to more easily work only on active WELLS / WELLBORES.
Describe the solution you'd like
A filter option or check box similar to what is seen in the picture.
When the filter is applied, only Active Wells are displayed.
Using a similar approach to what exists in current solutions makes it easier for users of WITSML Explorer to recognise the functionality.

Describe alternatives you've considered
Currently no alternatives, but open to suggestions
Additional context
The relevant WITSML data comes from the isActive tag.
<wellbores version="<IP_ADDRESS>" xmlns="http://www.witsml.org/schemas/1series">
	<wellbore uidWell=" uid=">
		<nameWell />
		<name />
		<isActive>true</isActive>
	</wellbore>
</wellbores>

Will discuss with UI designer asap. Will notify you.


ZenjectIntegrationTestFixture:CurrentTestHasAttribute minor bug fix

This should be just a quick little fix for you: In the CurrentTestHasAttribute<T> method, you get the method name by taking the full name, stripping off everything before the last dot & then removing the parens at the end (if they exist). However, if you're using parameterized tests which have doubles (as I am), the full name of the test will have a dot within the parens, e.g. Parameterized_Double_Test(1.653442234d). The fix is simple: just strip the parens before getting everything after the last dot.
Let me know if you want a pull request.

A pull request would be great  :)

I've not done this before so apologies if I'm getting it wrong, but I don't think I can yet because I don't have permission to push the branch I've created with the changes. If you want to add that permission for me, I pledge to use it wisely. (Or if there's a better way, just let me know.)

Github has a built-in way to submit fixes to other repositories without needing direct access to it.  See here: https://opensource.guide/how-to-contribute/#opening-a-pull-request

Okay, I think it's done. Let me know if you need more & thanks for letting me learn pull requests on your project. :)

No problem - thanks for contributing!


Is it valid? Test it at https://html5.validator.nu/

I tested and got errors(attached as a photo)

The cause was that I added spaces to the CSS path. I fixed it and it became validated! Thank you!


Updated URLs

Fixes issue #<issue_number>
#605
Brief summary of changes
Updated URLs
Testing I've completed
None since I can't build locally
CHANGELOG.md (choose one)

no need to update because it is not a new feature.

Thanks @jimmyDunne Please test on next build when it comes out.


Launching the complied version on ChromeOS - Code: E_HID_CONNECTION

Chrome unable to detect Medtronic 670G after plugged into the device.
Code: E_HID_CONNECTION.

Hi Todd,
We don't yet support the Uploader on ChromeOS, but I'm curious how you managed to install it?


devcontainer: "extensions" has been removed and replaced by customizations

"extensions" has been moved to "customizations/vscode"
"customizations": {
        "vscode": {
            "extensions": [
                // Ensure we have IntelliSense in VSCode when running inside container
                "ms-python.python"
            ]
        }
    }

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint.

Let's cc @Chris-hughes10 who authored this.

This is a response to a breaking change in the remote container extension and is the change that I would make. @dennisbappert have you verified that the dev container builds correctly with the new version?

I tested the "default" configuration, so CPU image.

I only tested it and do not use this configuration for development, I'm using my own dev container boilerplate.

Let me investigate further.

#1087

That's fine by me if it also works for @dbpprt


node-gyp is no longer needed; clicking on group titles toggles the selection

Proposed Changes

The node-sass dependency package has been replaced by sass so that node-gyp is no longer needed.
The prop withGroupClick was implemented. It allows click on group titles to toggle the selection of group items.

Hi,
Thank you very much for your contribution.
You seem to be adding multiple features under the same pull request which I rather we avoid to ensure we can easily review, test and rollback each change.
I didn't go over the whole PR due to that but a few quick comments -

This change requires an upgrade of the node version the project uses.
extracting the style to an external css is a breaking change and should be treated as such.

I'm happy to see through these changes but if you want to push them, please split this PR into separate PRs, each introducing a singular feature or change and we can review and merge them one by one.
Thanks again!


Finalize shock capture and add switch for interface compressibility

Description of the problem

The shock capturing approach implemented used an implicit implementation of the added viscosity. This was adequate, but lead to a non-linear system which was very difficult to converge
The interface compressibility term added was wrecking cases with surface tension

Description of the solution

Explicit the added viscosity term
Finalize the formulation to remove the added viscosity in the direction of the velocity vector
Fix the initial condition of the 3D dam break which was very discontinuous
Add a switch to consider (or not) interface compression in the VOF cases. Default value is to disable compressibility effect. The parameter is called compressible and a default value of false.

How Has This Been Tested?

Some tests had to be updated slightly

Comments

This shock capture performs well. I think that's the end of it
Interface compressibility came as a weird surprise. I was not expecting it to have such a dramatic effect inside droplets or within cases with surface tension effects
I will make another PR in the following week to add this to the theory guide!

@hepap and @AmishgaAlphonius I applied both of your suggestions. If you are cool with it,  I'll merge after CI


[WIP] feat(js): add view pager hook

Summary

Test Plan

What's required for testing (prerequisites)?
What are the steps to reproduce (after prerequisites)?
Compatibility

OS
Implemented

iOS
✅❌

Android
✅❌

Checklist

[ ] I have tested this on a device and a simulator
[ ] I added the documentation in README.md
[ ] I updated the typed files (TS and Flow)

https://github.com/user-attachments/assets/6b49824e-ac5d-44ec-9fab-41b11ec0d79d


problem sed command (unterminated address regex) in nvm.sh

Operating system and version:
Linux my-pc 5.18.6-1-MANJARO #1 SMP PREEMPT_DYNAMIC Wed Jun 22 14:16:20 UTC 2022 x86_64 GNU/Linux
nvm ls output:
      v16.13.1
  ->      v18.3.0
           system
  default -> node (-> v18.3.0)
  iojs -> N/A (default)
  unstable -> N/A (default)
  node -> stable (-> v18.3.0) (default)
  stable -> 18.3 (-> v18.3.0) (default)
  lts/* -> lts/gallium (-> N/A)
  lts/argon -> v4.9.1 (-> N/A)
  lts/boron -> v6.17.1 (-> N/A)
  lts/carbon -> v8.17.0 (-> N/A)
  lts/dubnium -> v10.24.1 (-> N/A)
  lts/erbium -> v12.22.12 (-> N/A)
  lts/fermium -> v14.19.3 (-> N/A)
  lts/gallium -> v16.15.1 (-> N/A)

sh
sh-5.1$

How did you install nvm?
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.1/install.sh | bash
What happened?
I use your alias for command cd, so when I open directory with one of my project (.nvmrc [16.13.1/8.1.2]) it print in terminal the following:
sed: -e expression #1, char 230: unterminated address regex
v16.13.1 is already installed.
Now using node v16.13.1 (npm v8.1.2)

problem is in that sed: -e expression #1, char 230: unterminated address regex
I found that expression in end of the function nvm_ls from ~/.nvm/nvm.sh file, but I'm not so good with bash for fix that by myself
so problem is in if statement (nvm v0.39.1)  in line 1317 in file ~/.nvm/nvm.sh

Please fill out the issue template in its entirety; it's there for a reason.
What exact cd code are you using?

The regex here is perfectly valid, so it's possible your sed isn't posix-compliant (manjaro has this problem occasionally, iirc)


Export grid

In the documentation here, it reference to "Export grid".  Why is this feature removed when applying filtering on fields like "Activity ID etc" ?  Can we only Export grid when we don't have applied filters ?  Why ?

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

ID: e5ff6b0b-7df1-bafd-cbf8-2613a704cd1c
Version Independent ID: e7445fad-0895-d168-a98a-5b89afa6e7ac
Content: Use Azure Data Explorer to query raw information logs - Finance & Operations | Dynamics 365
Content Source: articles/fin-ops-core/dev-itpro/lifecycle-services/azure-data-explorer.md
Service: dynamics-365-cross-app
GitHub Login: @andreashofmann1
Microsoft Alias: andreash

Thank you for your feedback. As of now we will not be updating this article. Closing as won't fix.


(Android/iOS) When user changes the app language, some elements on the main page are updated with a delay.

Please, check the video:
https://emurgo.slack.com/archives/GC9AM0E8K/p1550063746032600

I don't have access to the video but I suspect that if them main screen is TxHistory the problem is probably in too aggressive componentShouldUpdate optimization


How i can Change the Bot Mode ?

could you please elaborate, what mode requires changing, what have you tried to achieve that and in what particular way did it fail?


Upload directory into folder within bucket

I have a local folder, /build, that I would like to upload to a folder within an S3 bucket, entitled Library.
Placing individual files into the Library folder is easy:
const params = {
  localFile: './individualFile',
  s3Params: {
    Bucket: config.aws.s3Bucket,
    Key: 'Library/individualFile',
  }
}

const uploader = client.uploadFile(params); // works great!

However, I'm not sure how to configure the params to upload the contents of a directory into a folder within a bucket. I've tried this:
const params = {
  localDir: './build',
  s3Params: {
    Bucket: config.aws.s3Bucket,
    Key: 'Library/',
  }
}

const uploader = client.uploadDir(params); // doesn't work :(

The upload is successful, but the contents end up at the root of the bucket rather than inside the folder. In other words, the Key feature doesn't seem to work when it comes to directories.

s3Params: {     Bucket: "config.aws.s3Bucket",     Prefix: "Library",     // other options supported by putObject, except Body and ContentLength.      // See: http://docs.aws.amazon.com/AWSJavaScriptSDK/latest/AWS/S3.html#putObject-property


[BUG] Memory limit exceeded

Description
the program memory is very large when I load data. The program needs to be optimized
dataset.py in 155 line
In which platform does it happen?
centos, docker.
How do we replicate the issue?
When you load a large data set, the program memory will be very large, and it is obvious that the code can be optimized. （dataset: 100K userID, 50K itemID）
Expected behavior (i.e. solution)
the program memory will be very large.
Other Comments
Negative sampling only during training

hi @zerolxf, thanks for your comment, we will add this to our TODO list. In the meantime, if you see a fix, feel free to send a PR with an optimization


[Request] Hide Clip Art Icons Only

I noticed the settings allow you to hide the tool icons, but not to hide the clip art icons alone and leave the rest of the tools visible. Would it be possible to allow setting visibility of the tool icons separately? Thanks, great program!

Sorry not yet implemented for a future release


Cannot create users or databases using sqlx

Bug Description
I cant create a database user it gives me this error
DatabaseError("error returned from database: syntax error at or near "$1"")
It works if I hard code the values in the query but it breaks when trying to use bindings
Minimal Reproduction
        sqlx::query("CREATE USER $1 WITH PASSWORD $2")
            .bind(&app_user)
            .bind(&app_password)
            .execute(&mut conn)
            .await?;

        sqlx::query("ALTER DATABASE $1 OWNER TO $2")
            .bind(&db_name)
            .bind(&app_user)
            .execute(&mut conn)
            .await?;

Info

SQLx version: 0.6.2
SQLx features enabled: ["runtime-tokio-rustls", "postgres", "chrono", "uuid", "migrate", "decimal"]
Database server and version:  Postgres
Operating system: Linux
rustc --version: 1.66.0

Do you need single-apostrophe (') for the second argument? The help in pgsql says PASSWORD 'password'.

DDL statements like CREATE USER and ALTER DATABASE are not supported for use with prepared statements. This is unfortunately just bad error UX from Postgres.


Add copyright/license headers to all scripts

In our make lint and make fmt targets we ensure that all Go source files have a copyright & license comments like this:
$ head -2 cmd/jaeger/main.go
// Copyright (c) 2023 The Jaeger Authors.
// SPDX-License-Identifier: Apache-2.0

Objective:

modify ./scripts/updateLicense.py to also work for shell scripts under ./scripts/
make sure not to override the shebang line
also make sure this script works for the Makefiles, which have the pattern of Makefiles* or *.mk
invoke the script as needed from lint and fmt targets

Verification:

running make lint should flag all the scripts and Makefiles that are missing the license headers
running make lint should update them as needed

DO NOT commit the changes to the file headers, only raise a PR containing changes to the script & make targets.

i believe the ALL_SRC variable in Makefile needs to be updated too? So that the .sh for auto reformatted.
Something like:
ALL_SRC = $(shell find . \( -name '*.go' -o -name '*.sh' \)
                   -not -name '_*' \
                   -not -name '.*' \
                    ... // the rest

Also, are the .py scripts included?

Yes py scripts are included


Server crash if set.mm is not valid

Hi @tirix ,
to see if Diagnostics was implemented, I've changed the line
reelprrecn $p |- RR e. { RR , CC } $=
to
reelprrecn $p |- RR e. { RR , CCD } $=
and I get the error below:
thread 'main' panicked at 'called Option::unwrap() on a None value', /mydir/.cargo/git/checkouts/metamath-knife-c0afdf58ccf11b37/0dbd297/src/grammar.rs:1295:59
note: run with RUST_BACKTRACE=1 environment variable to display a backtrace
thread 'main' panicked at 'called Result::unwrap() on an Err value: Any { .. }', /mydir/.cargo/git/checkouts/metamath-knife-c0afdf58ccf11b37/0dbd297/src/database.rs:300:31
[Info  - 5:14:40 PM] Connection to server got closed. Server will restart.

Thanks!
This seems to be due to the fact that the stmt_parse statement parsing step of metamath-knife assumes that because previous steps have been run, its input is error-free, which is actually not the case.
I've submitted a fix in metamath-knife, but actually statement parsing step is currently unused, another option would have been to simply skip it.


Add guide for running the project locally for windows users

Add a clear documentation for windows users to run the project locally.

I have you assigned to this issue, @Brijesh206 .  Let me know if you need anything


Output: evaluate codespan as an alternative to annotate-snippets

Right now we use annotate-snippets to provide the default diagnostic output. This works well, but it's a little bit inflexible. We should evaluate codespan-reporting as a potential alternative with a more flexible data model.

Closing for now -- annotate-snippets hasn't really caused any issues.


Fixes and features for SubnetLaplace

This PR aims to address #86. Namely, this implements the following changes:

It fixes an issue where the subnet indices validity check would fail on GPU as we only allowed torch.LongTensors but not torch.cuda.LongTensors.
It technically enables marginal likelihood computation and therefore optimization with SubnetLaplace (i.e. essentially makes sure that there are no dimension errors when calling la.log_marginal_likelihood() on a SubnetLaplace model); however we should generally not recommend using this, as the marginal likelihood is probably not meaningful when computed over a subnetwork (without any additional care that would likely require original research); so I'm not sure whether we should have this feature if we don't know how it'll behave.
It adds DiagSubnetLaplace, a subclass of SubnetLaplace that uses a diagonal Hessian approximation (the existing full Hessian variant is now called FullSubnetLaplace); we initially thought that this wouldn't be useful as a full diagonal LA would probably be better in most cases and not incur much overhead, but this feature was explicitly requested in #86, so why not.

Let me know what you think!

@AlexImmer Feel free to take a look once you have some time (no rush of course). Would be great to merge this in at some point, as there seems to be some interest in this, now again with issue #90. Thanks a lot!

Sorry for holding this back. looks good to me.


Text Changes: Quick MAPS baseline (household)

e.g. https://preview.micronutrient.support/quick-maps/diet/baseline?country-id=MWI&mnd-id=Fe&measure=diet&age-gender-group-id=WRA

[ ] Replace card title with "Median apparent intake of <MN> (AFE) at district level, <country>"

[ ]  Replace card title with "Monthly apparent micronuntrient intake for <MN name> by food group in <Country>" (note MN name i.e. Iron rather than ID (Fe))

[ ]  Replace micronutrient id with micronutrient name in card title (I.e Fe -> Iron)

[ ] Replace threshold line title with "Threshold for inadequacy for AFEs"

Completed by Dan S. Closing.


Revert "staging"

Reverts Sage-Bionetworks-IT/packer-rstudio#44
Just a reminder that the staging RAN was previously used. I assume that by now changes should have been released into the normal repository.

@brucehoff It was this change in the python client, which needed to be released.
https://github.com/Sage-Bionetworks/synapsePythonClient/pull/837
It should have been released as a part of https://github.com/Sage-Bionetworks/synapsePythonClient/releases/tag/v2.3.1
I'm not completely sure which R client version was supposed to contain this, but judging by release date, I can assume it's
https://github.com/Sage-Bionetworks/synapser/releases/tag/0.10.85

Looks good.  Thanks, @zimingd !


[In-Person Event] Phony badge application for GSOC 2022 badging bot microtask by Ayush Tamra

yo yoy oy

/end

/result


Error 400

OpenAI API Response was: Error 400: This model's maximum context length is 4097 tokens. However, you requested 5444 tokens (444 in the messages, 5000 in the completion). Please reduce the length of the messages or completion. More information about this error: https://www.codegpt.co/docs/tutorial-basics/api_errors
this happens when you set the max token setting above the "model's maximum context length is 4097 tokens" hence the "5000 in the completion" which mean when we're sending a request we automatically sending our context token (444 in the messages) + the max token setting.

to fix this, just set the max token setting lower.

same here. I cleared chat out of desperation but didn't fix anything.

Update:
A couple things to try.

CodeGPT settings only takes effect after a VSCode restart. The solution could be real. I can't validate though because I di
You can uninstall/reinstall CodeGPT extension to clear its cache, which worked for me.

On my side I'm getting this error
OpenAI API Response was: Error 400: This model's maximum context length is 16385 tokens. However, your messages resulted in 28811 tokens. Please reduce the length of the messages.

I never had it before, and it's been several months that I'm using codeGPT.
The input was simply this:
In go how to get the last item of a slice ?
And here is how the extension is configured on my editor:

Also impossible to join the discord group

same here no matter how I try, a simple question like "what's the difference between next.js and react.js" results in a error 400:
OpenAI API Response was: Error 400: This model's maximum context length is 4097 tokens. However, your messages resulted in 21798 tokens. Please reduce the length of the messages. More information about this error: https://docs.codegpt.co/docs/tutorial-basics/api_errors

Update: A couple things to try.

CodeGPT settings only takes effect after a VSCode restart. The solution could be real. I can't validate though because I did 2:
You can uninstall/reinstall CodeGPT extension to clear its cache, which worked for me. Or you can
Delete C:\Users[User]\AppData\Roaming\Code\User\globalStorage\state.vscdb and state.vscdb.backup

Note that 3) would delete a bunch of other cached settings like if you trust your current WSL, or your current layout etc.. I don't use VSC enough to know the exact damage. So proceed with caution.

3 worked for me

Update: A couple things to try.

CodeGPT settings only takes effect after a VSCode restart. The solution could be real. I can't validate though because I did 2:
You can uninstall/reinstall CodeGPT extension to clear its cache, which worked for me. Or you can
Delete C:\Users[User]\AppData\Roaming\Code\User\globalStorage\state.vscdb and state.vscdb.backup

Note that 3) would delete a bunch of other cached settings like if you trust your current WSL, or your current layout etc.. I don't use VSC enough to know the exact damage. So proceed with caution.

3 worked for me

Same here

Yes, you're correct. Each model has a maximum context length, which is the total number of tokens that can be processed in a single request. This includes both the input message tokens and the tokens generated in the response. In your case, the model's maximum context length is 4097 tokens, but the request included 5444 tokens (444 from the messages and 5000 from the completion). To resolve this, you need to reduce the length of the messages or the completion so that the total number of tokens does not exceed the model's maximum context length.


fix: remove editor tabs

rolling back the editor interface to simplify things, we can in the future add the AI writer + tabs as slots :)

I'm happy to fast follow with that :)

Awesome work, let's make sure we default to showing the getting started page on mobile:

Also let's make sure the buttons are spaced like how they were previously :)

Awesome work, let's make sure we default to showing the getting started page on mobile:
Also let's make sure the buttons are spaced like how they were previously :)

ah good idea, maybe we just remove the ai writer tab and just show the getting started tab on mobile?

closing in favor of https://github.com/scalar/scalar/pull/589


README.md: Point contributors to Linux vs. Mac contribution guidelines

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

Update README to point users to the Linux vs. Mac contribution guidelines. We don't want upstream to miss important pull requests nor to receive undesired Linux-only PR's.

Thanks, Bob!


Fix lint issues using ruff

This PR adds a configuration for the ruff linter and fixes some minor issues found by it, both by hand and automatically.
I didn't add e.g. a CI step or pre-commit configuration for ruff, but that could definitely be done too :)

Rebased on top of 0.1.0...

Rebased on top of 0.2.0.


fixes a typo

If my understanding of the sentence is correct, it's missing a word.
Sorry if I misunderstood something.

Checklist

[x] I've looked at the contribution guidelines.
[x] This pull request is complete and ready for review.

Description
Just a fix for a small typo

Could someone with write access please fix these conflicts or close the PR if it's not needed?

@andikaleonardo


MdPaginatorIntl: Can't load translations asynchronously

Bug, feature request, or proposal:
Bug (or propsal, depending on how you look at it)
What is the expected behavior?
The paginator should handle string AND Observable so that asynchronous translation libaries can be used.
What is the current behavior?
I've created my own class and assigned it to the MdPaginator._intl property (see #5716 for why I'm doing this).
The problem is that, in the constructor I'm calling some code to get translations. I need to subscribe to wait for the translations, and then update itemsPerPageLabel, nextPageLabel, and previousPageLabel once they have been loaded. Doing so doesn't show the translations on the UI until I click one of the paginator's UI elements (e.g. next button).
Worse still, getRangeLabel can only return a string, so when i need to subscribe to translations here, there's no way to wait for this. I've tried using ngx-translate's "instant" method, but because the translations aren't loaded at the point where getRangeLabel is first called, the untranslated string is returned. Not ideal.
What are the steps to reproduce?
https://plnkr.co/edit/6SD4njsEDNlWDqDnUlfA?p=preview
I've added a class, PaginatorTranslated, at the bottom of the table-pagination-example.ts.  I've added methods which mock the translation service I'm using, and mock loading data from the server.
What is the use-case or motivation for changing an existing behavior?
Allow the use of translations that aren't hard-coded.
Which versions of Angular, Material, OS, TypeScript, browsers are affected?
Angular 4.0.0
Material 2.0.0-beta.7
Windows 10
TypeScript 2.3.3
Chrome 59

Closing as a duplicate of https://github.com/angular/material2/issues/5738.


Worlds not available through current code

Worlds cannot be added as a download (dynamically, excluding TBP Saver) without a program update for the end user.

feature added in beta


Apple TV setup

Got the profile working to get on the BCNGN network. Ordered device idir.
Next steps - need HDMI cables
Apply device idir
install in 137k, 138g, 138a?

Got the idir now "AppleTV" just need cables, order sent to Meaghan


Update index.rst

I think it's annoyingly this simple!
From what you sent, I saw "WARNING: Title underline too short."  And, this line in the config file tells Read the Docs to treat a warning as an error.

Codecov Report

Merging #1 (fdb08be) into main (0303dc9) will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##              main        #1   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files            1         1
  Lines           11        11
=========================================
  Hits            11        11

Continue to review full report at Codecov.

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[WIP] Nuv scan

I'm opening this PR as draft to keep track of the progress and discussion around nuv scan (it will also cover #8).
The README has some design on the scan subcommand.
I threw together a simple plan of action so it's open for discussion on what to do:
The steps to implement a pipeline for scanning a project and generating a Taskfile I imagined:

[x] Check if "packages" folder is present in current directory or given path

[x] If not present: give feedback to user and stop here

[x] Scan inside the packages folder
[x] Build a tree data structure:
root node (first level) is packages folder
second level nodes can be: folders = openwhisk packages, files = openwhisk actions (of default ow package)
third level nodes can be: files = openwhisk actions, folders = multifile openwhisk actions
[x] Parse the tree & gen a DS of Task commands based on type of node

[x] packages commands

[x] single file action commands

[x] multi file action commands

[ ] Merge together the task commands into a taskfile

This is basically thinking out loud so I'd like to polish it and understand better how nuv scan would work.
Also, I added testify to use in tests.

I would make tests simpler :)

I reviewer the PR and it relies on the afero library that is a virtual filesystem library. I admit it is a fascinating library and open positive scenarios that could be the ability to deploy over http. However after careful thinking I have to rejec the usage on the basis of 3 reasons:

first, the most important, nuv tool should work on different operating systems running different filesystems, so we will have to test against extfs, ntfs, hfps. Those have different semantics, for example the first is case sensitive, the second case insesntive and the third case preserving, not to talk of permissions I had significative problems in another project for this reasons. If we test against a virtual filesystem we miss all those potential bugs
I do not want to rely on a third part library for things as basic as filessyte acces. I want we use os.Mkdir, not affero.Mkdir, as the standard library is going to be more supprted that third part libraries.
resulting tests are pretty complex, as you have to write a lot of code to create various component. I understand it is ejoyable as go coding exercise but it is a nightmare for maintenance, if we have to test a deployment, let's include a test deployment in code. For example openwhisk has horrible tests written in scala with emedded code for testing. They are a nightmare to runs. So I do not want the test artifacts to be embedded in the tests. The should be separate and not build on the fly in the virtual filesystem

I know giudsp, I added the motivations here - we do not want to say "no" without a valid reason. Our main concern is testing again real filesytems

Code looks fine but I need a "simple" integration test
Can you create a simple folder tests in the top level and add below a sample project with the folder and subfolders?
Ideally running nuv scan it should generate a nuvolaris.yml in the top level.
Leave a nuvolaris.yml.ok to compare with, so we can implement in .githhub actions a simple Taskfile for tests as follows
  tests:
      dir: tests
      cmds:
         - nuv scan
         - diff nuvolaris.yml nuvoloaris.yml.ok

Looks fine to me - I leave it however umberged as it is scheduled for next milestone and Irina so Irina can work on the nuv setup command that we relase first.


Take a look at semgrep

Looks like it could help us write more expressive rules.

It doesn't look like they have a C# API on their roadmap.
https://github.com/returntocorp/semgrep
-------- Original Message --------
On May 9, 2020, 12:14 PM, Michael Scovetta wrote:

Looks like it could help us write more expressive rules.
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Depends on https://github.com/returntocorp/semgrep/issues/1309

This looks possible to do now with IronPython https://ironpython.net/.
We could add SemGrep as a rule type.

https://stackoverflow.com/questions/7053172/how-can-i-call-ironpython-code-from-a-c-sharp-app


flake.nix

Hey Adrián,
it's a pleasure to read so nice prolog code, I very enjoyed it :)
Searching in your repositories, it seems like you know the NIX buildsystem and I don't need expain or convince you about having a flake.nix. If you have any questions anyway, let me know…
To make it work, I changed doclog.sh to support running DocLog from others than the current directory. I implemented it by getting the paths of the arguments using realpath and dirname from coreutils (should be available on nearly every linux) and than changing into the directory of the called executable.
An alternative approach would be modifying main.pl.
You can test the flake when you are in a repository with DocLog documentation (or change the first argument):
nix run github:johannesloetzsch/doclog# . www

If you want, I could package DocLog for the official nixpkgs?

Thanks for your kind words! To be honest I don't have a Nix setup to test it, but from what I've seen it's okay (and the scripts changes too). I'll be pleased to have this package available on nixpkgs!


Cannot find module "sdp"

Browsers and versions affected
Chrome 57
Ionic Framework: 2.2.0
Description
I  have imported webrtc-adapter module as a dependence into a NPM project but it crashes.
Steps to reproduce
Import webrtc-adapter into a new NPM package
Use the new package in your Ionic project
Expected results
The problem is into the file: src/js/edge/edge_shim.js
If I modify the the line:
var SDPUtils = require('sdp');
with the full path to sdp it works!
var SDPUtils = require('../../../node_modules/sdp');
Actual results
Cannot find module "sdp"

I think that it's a problem with Ionic dependency injector. So, if you are agree, we can close the issue. 👍


remove files that should not be in source control

I munged a cleanup and an upgrade together. Note that this PR removes files we shouldn't have in SCM, and also upgrades to gradle 2.8 and groovy 2.4.4
If on a Mac, brew update and then brew install gradle

If you have an existing IDEA project, I've found the easiest way to deal with this PR is simply to create a new project from sources, choose the jenkins-automation project, and then refresh the gradle view to get the familiar gradle structure back


fix lint err result_large_err

Objective

Fix errors when I run cargo run -p ci lints

error: the `Err`-variant returned from this function is very large
   --> crates/bevy_gltf/src/loader.rs:864:6
    |
81  |     AssetLoadError(#[from] AssetLoadError),
    |     -------------------------------------- the largest variant contains at least 128 bytes
...
864 | ) -> Result<(), GltfError> {
    |      ^^^^^^^^^^^^^^^^^^^^^
    |
    = help: try reducing the size of `loader::GltfError`, for example by boxing large elements or replacing it with `Box<loader::GltfError>`
    = help: for further information visit https://rust-lang.github.io/rust-clippy/master/index.html#result_large_err
    = note: `-D clippy::result-large-err` implied by `-D warnings`
    = help: to override `-D warnings` add `#[allow(clippy::result_large_err)]`

error: the `Err`-variant returned from this function is very large
    --> crates/bevy_gltf/src/loader.rs:1239:42
     |
81   |     AssetLoadError(#[from] AssetLoadError),
     |     -------------------------------------- the largest variant contains at least 128 bytes
...
1239 | fn get_primitive_topology(mode: Mode) -> Result<PrimitiveTopology, GltfError> {
     |                                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
     |
     = help: try reducing the size of `loader::GltfError`, for example by boxing large elements or replacing it with `Box<loader::GltfError>`
     = help: for further information visit https://rust-lang.github.io/rust-clippy/master/index.html#result_large_err

error: could not compile `bevy_gltf` (lib) due to 2 previous errors

Solution

Box AssetLoadError : AssetLoadError(#[from] Box<AssetLoadError>),

@ameknite, could you cherrypick the commit from #10599 by @13ros27 into this branch? I can't merge anything until all of the CI is passing.

before merging, could you investigate why this error is not triggered in CI?

And yeah, looks like we don't need to cherrypick.

@mockersf I tried so many things and it still doesn't trigger the error in CI, only in local. Idk what is happening :/
I tried

removing the cache

running on windows and macos

running direcly clippy in ci:
cargo clippy --workspace --all-targets --all-features -- -Dwarnings

running clippy only in bevy_gltf

cd crates/bevy_gltf
cargo clippy -- -Dwarnings

denying only the lint
cargo clippy -- -D clippy::result_large_err
denying the functions directly with
#[deny(clippy::result_large_err)]
running two steps:
      - name: CI job 2
        # See tools/ci/src/main.rs for the commands this runs
        run: |
          cargo run -p ci -- lints

running it twice in the same step
        run: |
          cargo run -p ci -- lints
          cargo run -p ci -- lints

I  tried triggering others lints in the same functions. they were detected but not the errors for the lint clippy::result_large_err :/
I check the the rust-toolchain version and it seems fine.
clippy 0.1.74 (79e9716c 2023-11-13)
so I give up.

This was fixed by allowing the error, #[allow(clippy::result_large_err)] in https://github.com/bevyengine/bevy/pull/11123


Write up how this works and document how to setup

Explain what grpc-web.myhbarwallet.com is and what's behind it (envoy proxy to HAPI)
Explain how to setup your own envoy proxy and have MHW use it

superseded by #108


code in markdown fences has different widths, could use Codemirror?

Moved over from a Slack conversation:
I noticed that if embedded code blocks inside of a markdown code fence have different width than a code block… and maybe syntax highlighting is not working?
For example, on https://jsxgraph.mentat.org/ note the different widths between the code fence on top and clojure forms below:

Can we tune this at all?
Re codemirror:
@zampino noted "yeah, fenced or indented code blocks in markdown are rendered with the default code viewer (hence with clojure syntax) but with the width of prose. Now that we have stateless syntax highlighting we could try to load codemirror language support lazily at least for known languages."

Let's try to make them look the same but have a Code Listing: Clojure label.


[Bugfix] Make ObjectId JSON-serializable on generation

Thank you for contributing to LangChain!

Description: MongoDB ObjectId being non-JSON Serializable creates errors in our code generation.

Issue: #535

Dependencies: None

Twitter handle: @mongodb

[x] Add tests and docs: Added a component to the unit test that ensures the resulting metadata from an Vector Serach result is JSON Serializable.

[x] Lint and test: Run make format, make lint and make test from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/

would love a review from Casey!


One hyperlink of graphviz installation is not working

In the page: https://docs.datajoint.io/python/setup/02-DataJoint-Python-Windows-Install-Guide.html#optional-step-4-install-packages-for-erd-support
The hyperlink in the current sentence is outdated.
More specifically, the build artifacts from the Win64; Configuration: Release are recommended, available here.
I think the link should be this one now: https://ci.appveyor.com/project/ellson/graphviz-pl238/build/job/6v1apxr85ag0cj1q/artifacts but needed to be tested by a win64 user.

thanks @shenshan , thinking to remove the direct link (the one that says 'available here') since it was never very consistent and just leave the pointer to to the top-level: https://ci.appveyor.com/project/ellson/graphviz-pl238

also related, the conda install method provides datajoint, we have an issue to describe that here: https://github.com/datajoint/datajoint-docs/issues/229


Bump safe-deployments to v1.37.22

Update the safe-deployments to https://github.com/safe-global/safe-deployments/releases/tag/v1.37.22

Pull Request Test Coverage Report for Build<PHONE_NUMBER>3
Details

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.03%) to 93.641%

Totals

Change from base Build<PHONE_NUMBER>5:
-0.03%

Covered Lines:
9262

Relevant Lines:
9891

💛  - Coveralls


New tracking domains

Hello!
There is a site called iplogger.com that allows you to create and insert a tracking pixel into any email (or even a website).
Here is a link to this service:
https://iplogger.org/tracking-pixel/
In the end, the links will look something like this:
Also it would be great if you will block them in Mail Protection to
iplogger[.]com/1V8mH4.jpg
iplogger[.]org/1V8mH4.jpg
iplogger[.]ru/1V8mH4.jpg
iplogger[.]co/1V8mH4.jpg
iplogger[.]info/1V8mH4.jpg
mapper[.]info/1V8mH4.jpg
2no[.]co/1V8mH4.jpg
yip[.]su/1V8mH4.jpg
iplogger[.]com/1V8mH4.jpg
ipgraber[.]ru/1V8mH4.jpg
ipgrabber[.]ru/1V8mH4.jpg
iplis[.]ru/1V8mH4.jpg
02ip[.]ru/1V8mH4.jpg
ezstat[.]ru/1V8mH4.jpg
wl[.]gl/1V8mH4.jpg
ed[.]tk/1V8mH4.jpg
bc[.]ax/1V8mH4.jpg

Thanks for reporting this. Like are tracking protection in the extension, our email protection uses an automated method to detect tracking pixels in emails, so these should get automatically blocked.


Campus Partner - University structure

All reporting, including Maps, Reports, Charts - should accommodate the university structure. Each report/map/chart should include a filter for College/Main Unit and a cascading filter for Department/School/Unit
o	If a user selects Athletics, the second filter should only show units associated with Athletics. This way you can view the data based on the entire college (college selected) and all units selected, or based on a particular unit.
o	The order of these colleges/departments should be alphabetical.

move college above campus partner and then cascade options by college selected


Add a way to keep the terminal maximized at all times?

I use the terminal on the right side instead of the bottom. But recently I find myself using iTerm2 again since my brain feels more at home with full-width terminal usage.
Currently, there's no way to set the terminal width to be full at all times. What I mean by that is to be able to set this action workbench.action.toggleMaximizedPanel to something like terminal.integrated.MaximizedPanel to true.
I tried to configure the keybindings in a way that will open the terminal with max-width but later hide it with the same key — and this causes VSCode to hang.

{
		"key": "cmd+j",
		"command": "-workbench.action.togglePanel"
	},
	{
		"key": "cmd+j",
		"command": "workbench.action.closePanel",
		"when": "terminalFocus"
	},
	{
		"key": "cmd+j",
		"command": "workbench.action.toggleMaximizedPanel",
		"when": "!terminalFocus"
	},

Let me know if it's possible to do or please add this setting so that we can enjoy a full-width terminal experience that is toggle-able.

Version: 1.43.0
Commit: 78a4c91400152c0f27ba4d363eb56d2835f9903a
Date: 2020-03-09T19:34:44.548Z
Electron: 7.1.11
Chrome: 78.0.3904.130
Node.js: 12.8.1
V8: 7.8.279.23-electron.0
OS: Darwin x64 18.6.0

Version: 1.43.0
Commit: 78a4c91400152c0f27ba4d363eb56d2835f9903a
Date: 2020-03-09T19:34:44.548Z
Electron: 7.1.11
Chrome: 78.0.3904.130
Node.js: 12.8.1
V8: 7.8.279.23-electron.0
OS: Darwin x64 18.6.0

Hmm, the keybindings work fine on my macbook. Can you follow the instructions for mac crashes here? https://github.com/microsoft/vscode/wiki/Native-Crash-Issues#macos

+1 for the feature in the title. It would be great to have any or all of these:

A user setting to specify that new terminal windows should be maximized by default
A default hotkey to open the terminal in maximized mode (rather than the small window)
A new command that opens a full-page terminal in an "editor-like" mode. This could be similar to how the interactive preview for Python works, but instead of a preview, it's an interactive terminal (but instead of being docked at the bottom, it's a file tab).

The keybindings are meant to work, if the crash still occurs please reopen a new issue with info from following https://github.com/microsoft/vscode/wiki/Native-Crash-Issues


[Hotspots] update hotspot to use carbon colors.

What package is this for?

[x ] React
[ ] Angular

Summary
Colors used in the hotspot css do not match carbon colors. We might want to have a designer look at this.

https://github.com/carbon-design-system/carbon-addons-iot-react/blob/3133d03b2f446a68a1217264b4168c5d4ed0dda3/src%2Fcomponents%2FImageCard%2F_hotspot.scss#L15-L21
https://github.com/carbon-design-system/carbon-addons-iot-react/blob/3133d03b2f446a68a1217264b4168c5d4ed0dda3/src%2Fcomponents%2FImageCard%2F_hotspot.scss#L41-L51
The box shadows could be standardized to the helper mixin from carbon?
The white background ensures that the hotspots aren't transparent.
@dianatran18 These styles are visible on the hotspot present in the basic imagecard story


xcli error enhancements

This patch makes the executor binary emit more detailed error messages
to the stderr when they are encountered. It also modifies the libStorage
client to log the stderr of the lsx command when it sees an error.

@akutz Here is a fun one for you that I'd like to get your opinion on. From what we saw from a user yesterday, I noticed that the error message coming back from a failed xcli command was not as detailed as I would have expected. So here is my idea of how to change that, along with a small example of what could be done from the RBD executor. Ultimately this just enhances the framework -- it would be up to the driver executors to send correctly formatted Error messages up. But this allows us to see the inner messages from Goof even at the CLI. Not sure if you agree that is worthwhile.  For an example, here is a snippet from before, w/o this patch:
DEBU[0001] invoking executor cli                         args=[rbd instanceID] cmd=/var/lib/libstorage/lsx-linux host=unix:///var/run/libstorage/228061063.sock server=cute-witch-kp service=rbd storageDriver=libstorage time=1491582191203 txCR=1491582191 txID=1377a900-b79b-400e-50f5-8562f6111382
DEBU[0001] signalling executor lock                      host=unix:///var/run/libstorage/228061063.sock server=cute-witch-kp service=rbd storageDriver=libstorage time=1491582191233 txCR=1491582191 txID=1377a900-b79b-400e-50f5-8562f6111382
Oops, an error occured!

  error initializing instance ID cache

Here we got no indication of what is wrong.
If add the logging of the error from the libS client, we get a little more info:
DEBU[0001] invoking executor cli                         args=[rbd instanceID] cmd=/var/lib/libstorage/lsx-linux host=unix:///var/run/libstorage/009997218.sock server=noble-puppy-co service=rbd storageDriver=libstorage time=1491582575349 txCR=1491582575 txID=263b75ca-3ce7-4679-5159-03a68293b564
ERRO[0001] error from executor cli                       args=[rbd instanceID] cmd=/var/lib/libstorage/lsx-linux host=unix:///var/run/libstorage/009997218.sock server=noble-puppy-co service=rbd stderr=time="2017-04-07T16:29:35Z" level=debug msg="initializing configuration"
time="2017-04-07T16:29:35Z" level=debug msg="enter join" elem=[config.yml]
time="2017-04-07T16:29:35Z" level=debug msg="exit join" elem=[/etc/libstorage config.yml]
time="2017-04-07T16:29:35Z" level=debug msg="enter join" elem=[config.yaml]
time="2017-04-07T16:29:35Z" level=debug msg="exit join" elem=[/etc/libstorage config.yaml]
error: error getting instanceID: Unable to get Ceph monitors
 storageDriver=libstorage time=1491582575399 txCR=1491582575 txID=263b75ca-3ce7-4679-5159-03a68293b564
DEBU[0001] signalling executor lock                      host=unix:///var/run/libstorage/009997218.sock server=noble-puppy-co service=rbd storageDriver=libstorage time=1491582575399 txCR=1491582575 txID=263b75ca-3ce7-4679-5159-03a68293b564
Oops, an error occured!

  error initializing instance ID cache

Here at least I see the toplevel error returned by the executor, Unable to get Ceph monitors. But even then, it was missing the inner message that I know it has. so that's why I set the IncludedFieldsInError property to true. And then, we get:
DEBU[0002] invoking executor cli                         args=[rbd instanceID] cmd=/var/lib/libstorage/lsx-linux host=unix:///var/run/libstorage/551956131.sock server=button-shrieker-ir service=rbd storageDriver=libstorage time=1491585983166 txCR=1491585983 txID=1c820eee-5383-41e4-74e3-3cbf1307af19
ERRO[0002] error from executor cli                       args=[rbd instanceID] cmd=/var/lib/libstorage/lsx-linux host=unix:///var/run/libstorage/551956131.sock server=button-shrieker-ir service=rbd stderr=time="2017-04-07T17:26:23Z" level=debug msg="initializing configuration"
time="2017-04-07T17:26:23Z" level=debug msg="enter join" elem=[config.yml]
time="2017-04-07T17:26:23Z" level=debug msg="exit join" elem=[/etc/libstorage config.yml]
time="2017-04-07T17:26:23Z" level=debug msg="enter join" elem=[config.yaml]
time="2017-04-07T17:26:23Z" level=debug msg="exit join" elem=[/etc/libstorage config.yaml]
error: error getting instanceID: msg="unable to get Ceph monitors" stderr="2017-04-07 17:26:23.221788 7f9142c60780 -1 did not load config file, using default settings.\n"
 storageDriver=libstorage time=1491585983226 txCR=1491585983 txID=1c820eee-5383-41e4-74e3-3cbf1307af19
DEBU[0002] signalling executor lock                      host=unix:///var/run/libstorage/551956131.sock server=button-shrieker-ir service=rbd storageDriver=libstorage time=1491585983226 txCR=1491585983 txID=1c820eee-5383-41e4-74e3-3cbf1307af19
Oops, an error occured!

  error initializing instance ID cache

Now we get the actual stderr for the underlying  command the executor ran. I think this is helpful.
I admit, I have no idea why the stderr includes the debug messages about the Joins for the config file....

Codecov Report

Merging #504 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master     #504   +/-   ##
=======================================
  Coverage   30.51%   30.51%
=======================================
  Files          33       33
  Lines        1943     1943
=======================================
  Hits          593      593
  Misses       1286     1286
  Partials       64       64

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Hi @codenrhoden,
I'm reposting your comment without the DEBUG logs to see if it helps me visualize the difference:

@akutz Here is a fun one for you that I'd like to get your opinion on. From what we saw from a user yesterday, I noticed that the error message coming back from a failed xcli command was not as detailed as I would have expected. So here is my idea of how to change that, along with a small example of what could be done from the RBD executor. Ultimately this just enhances the framework -- it would be up to the driver executors to send correctly formatted Error messages up. But this allows us to see the inner messages from Goof even at the CLI. Not sure if you agree that is worthwhile.  For an example, here is a snippet from before, w/o this patch:
Oops, an error occured!

  error initializing instance ID cache

Here we got no indication of what is wrong.
If add the logging of the error from the libS client, we get a little more info:
ERRO[0001] error from executor cli                       args=[rbd instanceID] cmd=/var/lib/libstorage/lsx-linux host=unix:///var/run/libstorage/009997218.sock server=noble-puppy-co service=rbd stderr=time="2017-04-07T16:29:35Z" level=debug msg="initializing configuration"
time="2017-04-07T16:29:35Z" level=debug msg="enter join" elem=[config.yml]
time="2017-04-07T16:29:35Z" level=debug msg="exit join" elem=[/etc/libstorage config.yml]
time="2017-04-07T16:29:35Z" level=debug msg="enter join" elem=[config.yaml]
time="2017-04-07T16:29:35Z" level=debug msg="exit join" elem=[/etc/libstorage config.yaml]
error: error getting instanceID: Unable to get Ceph monitors
 storageDriver=libstorage time=1491582575399 txCR=1491582575 txID=263b75ca-3ce7-4679-5159-03a68293b564
Oops, an error occured!

  error initializing instance ID cache

Here at least I see the toplevel error returned by the executor, Unable to get Ceph monitors. But even then, it was missing the inner message that I know it has. so that's why I set the IncludedFieldsInError property to true. And then, we get:
ERRO[0002] error from executor cli                       args=[rbd instanceID] cmd=/var/lib/libstorage/lsx-linux host=unix:///var/run/libstorage/551956131.sock server=button-shrieker-ir service=rbd stderr=time="2017-04-07T17:26:23Z" level=debug msg="initializing configuration"
time="2017-04-07T17:26:23Z" level=debug msg="enter join" elem=[config.yml]
time="2017-04-07T17:26:23Z" level=debug msg="exit join" elem=[/etc/libstorage config.yml]
time="2017-04-07T17:26:23Z" level=debug msg="enter join" elem=[config.yaml]
time="2017-04-07T17:26:23Z" level=debug msg="exit join" elem=[/etc/libstorage config.yaml]
error: error getting instanceID: msg="unable to get Ceph monitors" stderr="2017-04-07 17:26:23.221788 7f9142c60780 -1 did not load config file, using default settings.\n"
 storageDriver=libstorage time=1491585983226 txCR=1491585983 txID=1c820eee-5383-41e4-74e3-3cbf1307af19
Oops, an error occured!

  error initializing instance ID cache

Now we get the actual stderr for the underlying  command the executor ran. I think this is helpful.
I admit, I have no idea why the stderr includes the debug messages about the Joins for the config file....

I realize part of the issue I'm encountering is that you're running the executor in the above examples with debug logging as well. Which of course is being captured in the above output. Can you reproduce the above examples without debug logging enabled? Since the executor does not detect a terminal its logs are in machine format and make it harder to remove since they're a part of the STDERR you're trying to display here.

Ah, I see what you are saying @akutz.  I don't think it's a big deal at all, then.
FWIW, here's what this patch looks like when running with the default warn loglevel:
# ./rexray -s rbd volume ls
ERRO[0001] error from executor cli                       args=[rbd instanceID] cmd=/var/lib/libstorage/lsx-linux host=unix:///var/run/libstorage/224270231.sock server=boulder-snout-sh service=rbd stderr=error: error getting instanceID: msg="unable to get Ceph monitors" stderr="2017-04-07 20:12:57.761171 7f371d455780 -1 did not load config file, using default settings.\n"
 storageDriver=libstorage time=1491595977764 txCR=1491595977 txID=500b8524-f9c0-41fb-4ca8-8f57b1fa43ef
Oops, an error occured!

  error initializing instance ID cache

It's verbose, but I think helps get to underlying problems faster.

Hi @codenrhoden,
Do you mind rebasing this PR? Once that's done I'll happily merge it.

Hi @codenrhoden,
Ugh, I'm sorry. Rebase one more time?  I didn't think it would have any overlap.

@akutz no problem. It seems to be lately that GitHub has changed, such that any commit to master makes the branches out of date, even if they don't touch the same files. Maybe it's because they have the "rebase and merge" option  now? I really don't know.

Hi @codenrhoden,
I agree that it seems this way but was avoiding saying that on purpose to not start a discussion about what that might mean for us :(


Added normalization by channel, included sqrt term for interactions

This PR incorporates the following changes:

The interaction terms are now the square root of the product of the source and neighbor channels
The minimum (non-zero) and maximum values for each channel are calculated and used to normalize each channel for training
When calculating the bleedthrough component, each channel is normalized to the minimum and maximum of each channel before multiplying by the coefficient. This should help to reduce any occurrences of negative numbers once the bleedthrough is subtracted from the original.
There was a bug in the file writing processes that was being thrown silently. This caused only the first and last images to be written. I fixed the bug so that files are written, but all of the images are 0s. It's unclear why this is happening. I didn't have time to track it down.

I've pulled in these changes.


[dashboard] Task times are off by an order of magnitude

It's likely these values are reading microseconds instead of milliseconds, which gets these off. The expect values in the example is expected to be 0 minutes for queue and 10 minutes for runtime.

Now everything is in cocoon scheduler: https://github.com/flutter/flutter/issues/92300, and the issue is fixed.


[types] Make core code address cosntant

Motivation

Made account_config::core_code_address() a constant
Makes the address more explicit, instead of relying on the derived default (formatting is a bit long and funny though)
This allows for pattern matching against the CORE_CODE_ADDRESS

Test Plan

cargo test

@bors-libra r=runtian-zhou

:pushpin: Commit 570724b has been approved by runtian-zhou

:hourglass: Testing commit 570724b299952517ced94a607babe351eb5ba338 with merge 9d3a4266900cd477c2083828836409d15ee259b4...

:sunny: Test successful - checks-circle_commit_workflow
Approved by: runtian-zhou
Pushing 9d3a4266900cd477c2083828836409d15ee259b4 to master...


Code Configurability - Visual Themes

Describe the bug
Similar to #5459 , this bug is to track making Visual Themes more configurable. Right now, Visual Themes are very difficult to set up via code and they are very difficult to modify at runtime on InteractableThemeBase.
notes:

Difficult to isolate particular property, just access via known index (see below)
Not well guarded or imposed balance between number of ThemePropertyValues in a ThemeStateProperty to the actual state objects assigned
The ThemePropertyValue is a bit overloaded and difficult to keep adding additional types
Slight weirdness in that ThemeDefinitions are copied into InteractableThemeBase at runtime so in some cases have to reference/modify two different endpoints which is a bit redundant

Related bugs:

[ ] https://github.com/microsoft/MixedRealityToolkit-Unity/issues/5971
[ ] https://github.com/microsoft/MixedRealityToolkit-Unity/issues/5497
[ ] https://github.com/microsoft/MixedRealityToolkit-Unity/issues/4554
[ ] https://github.com/microsoft/MixedRealityToolkit-Unity/issues/6009

To reproduce

var themeDefinition = ThemeDefinition.GetDefaultThemeDefinition<ScaleOffsetColorTheme>().Value;
            // themeDefinition.Easing.Enabled = false;
            // Set the offset state property (index = 1) to move on the Pressed state (index = 2)
            themeDefinition.StateProperties[1].Values = new List<ThemePropertyValue>()
            {
                new ThemePropertyValue() { Vector3 = Vector3.zero},
                new ThemePropertyValue() { Vector3 = Vector3.zero},
                new ThemePropertyValue() { Vector3 = new Vector3(0.0f, -0.32f, 0.0f)},
                new ThemePropertyValue() { Vector3 = Vector3.zero},
            };
            // Set the color state property (index = 2) values
            themeDefinition.StateProperties[2].Values = new List<ThemePropertyValue>()
            {
                new ThemePropertyValue() { Color = DefaultColor},
                new ThemePropertyValue() { Color = FocusColor},
                new ThemePropertyValue() { Color = Color.green},
                new ThemePropertyValue() { Color = DisabledColor},
            };

            Theme testTheme = ScriptableObject.CreateInstance<Theme>();
            testTheme.States = interactable.States;
            testTheme.Definitions = new List<ThemeDefinition>() { themeDefinition };

            interactable.Profiles = new List<InteractableProfileItem>()
            {
                new InteractableProfileItem()
                {
                    Themes = new List<Theme>() { testTheme },
                    Target = translateTargetObject.gameObject,
                },
            };

Expected behavior
Screenshots
If applicable, add screenshots to help explain your problem.
Your Setup (please complete the following information)

Unity Version [e.g. 2018.3.11f1]
MRTK Version [e.g. v2.0]

Target Platform (please complete the following information)

HoloLens
HoloLens 2
WMR immersive
OpenVR

Additional context
Add any other context about the problem here.

related bug:
#6509
#6800


[folding] [copy] [paste] keep code snippet folded when copy-&-pasted

I did my best. Due to the statement that an issue is moved up due to voting AND duplication (ssee last statement in https://github.com/microsoft/vscode/issues/16082), I post this issue again, with links to related issues.

When a code snippet that is folded is copied-and-pasted to another place in the file, the folded-status should be kept on paste. Currently, the snippet is unfolded again.
The desired behaviour can be observed, when a selected folded code snippet is moved using SHIFT-&-CursorUp (not down, because that adds indentation).
Use case scenario:
In a json file (e.g. .stylelintrc), order the rules alphabetically.
No folding extensions used.
IMO should be a native feature.
Related:
https://github.com/microsoft/vscode/issues/16082
https://github.com/microsoft/vscode/issues/58209
https://github.com/Microsoft/vscode/issues/49886

The suggested issue is not related to this issue.

It's a dup of #16082.
I reopen #16082 to see if other request that too.

@aeschli Thank you! Wouldn't it be necessary to make #16082 open for discussion, too? It is currently locked to collaborators. Or am I misunderstanding sth here?

Oh yes, of course. I unlocked the conversation.


/isochrone and /spt return 404 when point is missing

Describe the bug
The http://localhost:8989/isochrone endpoint is missing in my local server. I get a 404 response. The /route endpoint works flawlessly.
To Reproduce
I followed this guide:
https://github.com/graphhopper/graphhopper/blob/0.13/docs/web/quickstart.md
I use the exact same config as here: https://github.com/graphhopper/graphhopper/blob/0.13/config-example.yml
Expected behavior
I'd expect the endpoint to be available for requests and not return 404.
System Information
I used this jar version:
https://graphhopper.com/public/releases/graphhopper-web-0.13.0.jar
I'm on Windows 10 and Java is this:
java version "1.8.0_251"
Java(TM) SE Runtime Environment (build 1.8.0_251-b08)
Java HotSpot(TM) 64-Bit Server VM (build 25.251-b08, mixed mode)

Screenshots & Logs
There are no logs from the server.

Indeed we return a different 400 message for missing parameters. This could be more consistent.
But you only need to specify at least the point parameter: http://localhost:8989/isochrone?point=43.733647%2C7.415686 and see that it will work.

I just had the same problem with /spt. Returning 404 seems very wrong as it makes it look the whole endpoint is missing and we are not shown the intended error message (no point specified). There is also another problem for /spt: Since it returns text/csv the serialization of exceptions to json does not work and we are getting 500 errors instead of the error messages in json format.

@karussell don't you think this should be fixed? If not feel free to close again.

With 7df3192d137d025e3cd32a5c9eb99379207ee6b6 we now get 400 when the point is missing. Also I made sure that for /spt (which normally returns csv) we get a json error message. Not sure if we could achieve the same with framework features, so anybody who can do better please go ahead (@michaz?).
@mc51 for 0.13 you still get 404 if you do not specify the point, but obviously you need to specify a point anyway

Thanks!


Refactor #find_versions parameters in strategies

[x] Have you followed the guidelines in our Contributing document?
[x] Have you checked to ensure there aren't other open Pull Requests for the same change?
[x] Have you added an explanation of what your changes do and why you'd like us to include them?
[x] Have you written new tests for your changes? Here's an example.

[x] Have you successfully run brew typecheck with your changes locally?
[x] Have you successfully run brew tests with your changes locally?

Livecheck's strategies all contain a #find_versions method that takes input (e.g., a url, regex, cask, etc.) and uses it to identify versions from a source. All of the strategies except for ExtractPlist expect that a URL will be provided. ExtractPlist is an exception (in many unfortunate ways), as it expects a cask instead of a URL.
When ExtractPlist was created, a cask parameter was added to every #find_version method. This is because livecheck uses all the possible arguments when it calls the method, regardless of the strategy (i.e., it doesn't cater the arguments to what the strategy expects). If a strategy didn't have the cask parameter but a named cask argument was provided, Ruby would give an error.
Ideally, a given #find_versions method should only be required to have parameters for what it actually uses and we shouldn't have to update every method if one strategy needs a new parameter. This PR aims to achieve this by removing unused parameters from #find_versions methods and including an **unused parameter in each, as the double splat will take care of any arguments that don't correspond to a named parameter for a given strategy.
For example, ExtractPlist has a named cask: parameter (since it's the only strategy that works with a cask) but all the others omit this. Instead of producing an error, the cask parameter is simply part of unused (i.e., unused[:cask]).
In general, this helps to minimize #find_versions parameters to only what's used. This will make it easier to add new strategies in the future, where a new parameter wouldn't need to be added to all other strategies. Besides that, this bit of clean up helps to make things a bit more manageable before I add a couple more parameters to most #find_versions methods in the near future.

Review period will end on 2021-08-13 at 22:30:10 UTC.

Review period ended.


Problem with importing users using library WTelegramClient

I have a problem with imported contact users. For understanding, also see the uploaded photos.
Storage duration 1 month.
Link on images: https://files.fm/u/wk4bfwdvw
I used a method: "Contacts_ImportContacts"
I pass the user's phone number to this method.
And after that, my visual studio goes into an infinite cycle

No need to open an issue here if you also post it on StackOverflow


Where is Firefox add-on

What happened to the Firefox add-on? Is it no longer supported or is that temporary?

https://addons.mozilla.org/en-US/firefox/addon/visbug/

been submitted, waiting to hear back 👍🏻

we've gone back and forth a few times, I think I've made all the changes they requested in today's upload 🙏🏻

@argyleink hey was just wondering about the upload time if its almost done 🙏🏻

We've gone back and forth lots of times.. I've been waiting a week since the last interaction with the reviewer.. so sorry y'all!

no problem take your time i was just asking

@argyleink
Could you guys put the Firefox extension file to download directly from a third-party site?
In this way, we could use the Firefox extension without being vulnerable to the humor of Mozilla maintainers.
Ah, awesome extension, thanks for the job!

that's a great idea! i've captured it in a new issue here https://github.com/GoogleChromeLabs/ProjectVisBug/issues/574

Great extension, please, upload to third-party site.
Thanks for your work @argyleink

resubmitted again

Thanks @ argyleink I continue waiting to try in firefox :)

Really hope Mozilla approves this. I just found out about it and tested it in Chrome and it's great, but I prefer Firefox.

they didnt, they rejected it because it had a bundled file in it... a bundled file in just the source.. the rest of it is all good, they just "dont like" that the file is there so they reject it. lemme try again. they're being super wierd.

been 6 days since my last submission..

@argyleink How to compile the source code manually for firefox? Can you provide tutorial please?

there's some here https://github.com/GoogleChromeLabs/ProjectVisBug/wiki/Local-Extension-Dev-Testing-(DevBug)
the change you'll want to make is using the command npm run extension:firefox and make sure you have web-ext installed 👍🏻

still back and forth with them, just made another submission

Should be back!!


Need support for 21 letter vpc id and 24 letter subnet id.

AWS has recently made the change in the vpc id and subnet id format. Amazon EC2 has migrated to longer format, 17-character resource IDs.
Therefore the current VPC ID is 21 character long. (with 17 character resource Id and four characters for 'vpc-').
Similarly, the Subnet id is also upgraded to 24 character long.
The support for older format (8-character resource IDs) will continue.
Current porter version does not support new resource id format regex, can you please add the support.

Can someone please support with this issue. This is urgently needed.

@gpradhan909

AWS has recently made the change in the vpc id and subnet id format

Can you share a link for this? I want to make sure I alter the regex to match

https://github.com/adobe-platform/porter/releases/tag/v5.2.2


Export context to allow history access

Ref https://github.com/ReactTraining/react-router/issues/6362#issuecomment-425841471
Since "always render" behaviour will be removed from <Route children /> it would be good to provide a way to access context values from any part of app.
Here's a few ways and all requires to provide RouterContext.
RouterContext.Consumer
const Component = () => (
  <RouterContext.Consumer>
    {context => (
      <button onClick={() => {
        if (context) {
          context.history.push('/users')
        }
      }}>Open users</button>
    )}
  </RouterContext.Consumer>
)

Class component contextType
const Component = class extends React.Component {
  contextType = RouterContext;
  handler = () => {
    this.context.history.push('/users')
  }
}

context.unstable_read api
const Component = () => {
  const context = RouterContext.unstable_read();
  return (
    <button onClick={() => {
      if (context) {
        context.history.push('/users')
      }
    }}>Open users</button>
  )
}

I think you may be confusing 2 ideas. I'm proposing that we stop rendering something with a <Route> when it doesn't match. But it's still possible to create a <Route> that always matches. You can just use path="*" or no path at all:
<Route path="*" children={({ history }) => (
  <button onClick={() => history.push('/users')}>Go</button>
</Route>

// or even

<Route children={({ history }) => (
  <button onClick={() => history.push('/users')}>Go</button>
</Route>

In fact, we use a <Route> with no path in the implementation of withRouter, so you can use that too if you prefer to use a higher-order component instead.

BTW I'm a pretty strong -1 about exposing context as public API. That's our internal API. Our public API is <Route> and withRouter. You can get anything you need using them.

@timdorr I use many context in my app. contextType allows to achieve only one. This sucks. unstable_read is pretty useful for translations.
import { t } from '../locale.js';
// localeContext.unstable_read().t under the hook
export const Component = () => (
  t('user')
)

@timdorr unstable_read is used for suspended queries. I don't think it will be removed in favour of contextType.
https://github.com/facebook/react/pull/13337#issuecomment-425974864

@mjackson AFAIK exporting context is going to be normal/expected with what's coming. Formik is going to do the same.

Just a reminder: You will always be able to get to it via a direct import (import RouterContext from 'react-router/es/RouterContext'). So if you want to do some wonky stuff, you're free to aim the gun at your foot. This is just about making it a top-level export, which I agree with @mjackson isn't really necessary.

@jaredpalmer It just seems like context shouldn't be public. It's just a communication channel that we use to communicate between our components since we can't pass props down at every level.

While I agree with @Jackson that we shouldn't access the private context, I have a argument to why context would be better.
As we know withRouter just wraps your component in a path less route giving your component access to all the props, mainly match and history in my use case.
The downside to withRouter and the HOC is that the react dev tools show a bunch of routes everywhere.
Getting access to the context Context.Consumer? We would be able to pluck off the props we want without the HOC.
Am I totally off here or is there a secret way to gain access to router props without wrapping your component in a route.

The fact that we use context under the hood is just an implementation detail!
Take the 4.4 release, for example. If context were part of our public API, changing from the old context to the new one would have been a breaking change, and we would've had a major version bump. But since it's not, we are free to refactor and move things around while still providing the same high-level API. That's the beautiful part about us not exposing context.
Also, what if the context implementation changes again (and it could)? If we expose it as public API, we will have the same problem.

Just to address the examples in the OP:
For the first example, <Route> is basically the same as the Consumer. So, this is equivalent:
const Component = () => (
  <Route>
    {({ history }) => (
      <button onClick={() => {
        if (history) {
          history.push('/users')
        }
      }}>Open users</button>
    )}
  </Route>
)

For the second example and in preparation of facebook/react#13728 landing, we could set a withRouter'ed component's contextType to support this.context usage without the side effects. But we would have this.props available, which would be a more ideal option. I'd rewrite this as:
class Component extends React.Component {
  handler = () => {
    this.props.history.push('/users')
  }
}
export default withRouter(Component)

And for the last example, I'm not sure if unstable_read is going to survive much longer now that contextType exists.
The React team definitely wants to discourage context ~abuse~ usage, so reliance on it as an official API for a library would seem to be counter to those goals. I'm aligned with @mjackson's feelings on the subject.


[BUG] Responsive navigation

Describe the bug
Prevent menu items from being split into two lines:

@reneaaron can i work on this ?

Thanks for reaching out, but this has been resolved with #3012.
@pavanjoshi914 Please link those PRs to issues so the issues are automatically closed when the PRs are merged.


⚠ Bofrost.at has degraded performance

In be37f76, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 1034 ms

Resolved: Bofrost.at performance has improved in 96a2e4b after 7 minutes.


Descriptor loss train

Hi, first thank you for this great work which really helped me a lot!
I want to use the Superpoint model to train on my own data. The detection loss part seems normal but the descriptor loss is oscillating and cannot converge.
The input are 256*256 image and warped image with homography, and the model and loss function are the same with your repo.
The detector and descriptor loss are as below with 300 epochs.
Detector loss

Descriptor loss

Can you give me some advice?

According to my experience,  these parameters
solver:
    loss:
        positive_margin: 1.0
        negative_margin: 0.2
        lambda_d: 0.05
        lambda_loss: 10000
    base_lr: 0.001 #0.0001

, are the key parameters that affect descriptor loss, especially the lambda_loss.

Thanks very much for your help.
According to this https://github.com/rpautrat/SuperPoint/issues/164, I comment the following lines:
https://github.com/shaofengzeng/SuperPoint-Pytorch/blob/6e5c6587311cd4f98f9a5b61e84731555778c958/solver/loss.py#L126
    dot_product_desc = F.relu(dot_product_desc)

    ##l2_normalization
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc, Wc, Hc * Wc]),
                                                 p=2,
                                                 dim=3), [batch_size, Hc, Wc, Hc, Wc])
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc * Wc, Hc, Wc]),
                                                 p=2,
                                                 dim=1), [batch_size, Hc, Wc, Hc, Wc])

The train and val descriptor loss are as below with a small amount of data (100 samples).
Train descriptor loss

Val descriptor loss

These three line code is used for normalization of dot_descriptor and is it necessary for this operation after descriptors dot?
I'm not sure if this is correct and maybe the amount of data (100 samples) is too small?
Could you please give me some advice?

To the best of my knowledge， These lines,

    ##l2_normalization
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc, Wc, Hc * Wc]),
                                                 p=2,
                                                 dim=3), [batch_size, Hc, Wc, Hc, Wc])
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc * Wc, Hc, Wc]),
                                                 p=2,
                                                 dim=1), [batch_size, Hc, Wc, Hc, Wc])

are closely related to parameter lambda_loss. It seems that，this is the most different from the original paper.
2. Using l2_normalization operations are not necessarily the best choice, you can try to remove them and reset lambda_loss.
3. The training result obtained by the above method is acceptable, however，the convergence of the descriptor loss is really not good, which may be an improvement in the future.

Thanks very much for your help and explanation.
Can you give me some advice or trick for improving the convergence of the descriptor loss?

I have encountered the same problem, the loss of desc has been maintained at 1.0 ~ 2.0, the overall convergence will not be further, and the decs of the final result of the model is also very poor, may I ask if you have solved this problem

Thanks very much for your help. According to this rpautrat/SuperPoint#164, I comment the following three lines:
https://github.com/shaofengzeng/SuperPoint-Pytorch/blob/6e5c6587311cd4f98f9a5b61e84731555778c958/solver/loss.py#L126
    dot_product_desc = F.relu(dot_product_desc)

    ##l2_normalization
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc, Wc, Hc * Wc]),
                                                 p=2,
                                                 dim=3), [batch_size, Hc, Wc, Hc, Wc])
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc * Wc, Hc, Wc]),
                                                 p=2,
                                                 dim=1), [batch_size, Hc, Wc, Hc, Wc])

The train and val descriptor loss are as below with a small amount of data (100 samples). Train descriptor loss  Val descriptor loss
These three line code is used for normalization of dot_descriptor and is it necessary for this operation after descriptors dot? I'm not sure if this is correct and maybe the amount of data (100 samples) is too small? Could you please give me some advice?

Hi, first thank you for this great work which really helped me a lot! I want to use the Superpoint model to train on my own data. The detection loss part seems normal but the descriptor loss is oscillating and cannot converge. The input are 256*256 image and warped image with homography, and the model and loss function are the same with your repo. The detector and descriptor loss are as below with 300 epochs. Detector loss  Descriptor loss
Can you give me some advice?

I have encountered the same problem, the loss of desc has been maintained at 1.0 ~ 2.0, the overall convergence will not be further, and the decs of the final result of the model is also very poor, may I ask if you have solved this problem

Thanks very much for your help. According to this rpautrat/SuperPoint#164, I comment the following three lines:
https://github.com/shaofengzeng/SuperPoint-Pytorch/blob/6e5c6587311cd4f98f9a5b61e84731555778c958/solver/loss.py#L126
    dot_product_desc = F.relu(dot_product_desc)

    ##l2_normalization
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc, Wc, Hc * Wc]),
                                                 p=2,
                                                 dim=3), [batch_size, Hc, Wc, Hc, Wc])
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc * Wc, Hc, Wc]),
                                                 p=2,
                                                 dim=1), [batch_size, Hc, Wc, Hc, Wc])

The train and val descriptor loss are as below with a small amount of data (100 samples). Train descriptor loss  Val descriptor loss
These three line code is used for normalization of dot_descriptor and is it necessary for this operation after descriptors dot? I'm not sure if this is correct and maybe the amount of data (100 samples) is too small? Could you please give me some advice?

Hi, first thank you for this great work which really helped me a lot! I want to use the Superpoint model to train on my own data. The detection loss part seems normal but the descriptor loss is oscillating and cannot converge. The input are 256*256 image and warped image with homography, and the model and loss function are the same with your repo. The detector and descriptor loss are as below with 300 epochs. Detector loss  Descriptor loss
Can you give me some advice?

I have encountered the same problem, the loss of desc has been maintained at 1.0 ~ 2.0, the overall convergence will not be further, and the decs of the final result of the model is also very poor, may I ask if you have solved this problem

Not yet, the the convergence performance of the descriptor loss is not as good as the declaim of the repo https://github.com/rpautrat/SuperPoint and this repo.
Maybe we have the opportunity to discuss this issue together?

Thanks very much for your help. According to this rpautrat/SuperPoint#164, I comment the following three lines:
https://github.com/shaofengzeng/SuperPoint-Pytorch/blob/6e5c6587311cd4f98f9a5b61e84731555778c958/solver/loss.py#L126
    dot_product_desc = F.relu(dot_product_desc)

    ##l2_normalization
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc, Wc, Hc * Wc]),
                                                 p=2,
                                                 dim=3), [batch_size, Hc, Wc, Hc, Wc])
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc * Wc, Hc, Wc]),
                                                 p=2,
                                                 dim=1), [batch_size, Hc, Wc, Hc, Wc])

The train and val descriptor loss are as below with a small amount of data (100 samples). Train descriptor loss  Val descriptor loss
These three line code is used for normalization of dot_descriptor and is it necessary for this operation after descriptors dot? I'm not sure if this is correct and maybe the amount of data (100 samples) is too small? Could you please give me some advice?

Hi, first thank you for this great work which really helped me a lot! I want to use the Superpoint model to train on my own data. The detection loss part seems normal but the descriptor loss is oscillating and cannot converge. The input are 256*256 image and warped image with homography, and the model and loss function are the same with your repo. The detector and descriptor loss are as below with 300 epochs. Detector loss  Descriptor loss
Can you give me some advice?

I have encountered the same problem, the loss of desc has been maintained at 1.0 ~ 2.0, the overall convergence will not be further, and the decs of the final result of the model is also very poor, may I ask if you have solved this problem

Not yet, the the convergence performance of the descriptor loss is not as good as the declaim of the repo https://github.com/rpautrat/SuperPoint and this repo. Maybe we have the opportunity to discuss this issue together?

With pleasure, I plan to adjust the proportion of loss and have a try

Thanks very much for your help. According to this rpautrat/SuperPoint#164, I comment the following three lines:
https://github.com/shaofengzeng/SuperPoint-Pytorch/blob/6e5c6587311cd4f98f9a5b61e84731555778c958/solver/loss.py#L126
    dot_product_desc = F.relu(dot_product_desc)

    ##l2_normalization
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc, Wc, Hc * Wc]),
                                                 p=2,
                                                 dim=3), [batch_size, Hc, Wc, Hc, Wc])
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc * Wc, Hc, Wc]),
                                                 p=2,
                                                 dim=1), [batch_size, Hc, Wc, Hc, Wc])

The train and val descriptor loss are as below with a small amount of data (100 samples). Train descriptor loss  Val descriptor loss
These three line code is used for normalization of dot_descriptor and is it necessary for this operation after descriptors dot? I'm not sure if this is correct and maybe the amount of data (100 samples) is too small? Could you please give me some advice?

I delete these three lines and adjust the training parameter, lambda_d: 800
lambda_loss: 1, and then my desc_loss starts to decrease gradually from 20

Thanks very much for your help. According to this rpautrat/SuperPoint#164, I comment the following three lines:
https://github.com/shaofengzeng/SuperPoint-Pytorch/blob/6e5c6587311cd4f98f9a5b61e84731555778c958/solver/loss.py#L126
    dot_product_desc = F.relu(dot_product_desc)

    ##l2_normalization
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc, Wc, Hc * Wc]),
                                                 p=2,
                                                 dim=3), [batch_size, Hc, Wc, Hc, Wc])
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc * Wc, Hc, Wc]),
                                                 p=2,
                                                 dim=1), [batch_size, Hc, Wc, Hc, Wc])

The train and val descriptor loss are as below with a small amount of data (100 samples). Train descriptor loss  Val descriptor loss
These three line code is used for normalization of dot_descriptor and is it necessary for this operation after descriptors dot? I'm not sure if this is correct and maybe the amount of data (100 samples) is too small? Could you please give me some advice?

I delete these three lines and adjust the training parameter, lambda_d: 800 lambda_loss: 1, and then my desc_loss starts to decrease gradually from 20

My Wechat is chiu_jing_chun, we could add WeChat each other for further discussing if it is convenient for you :)

Thanks very much for your help. According to this rpautrat/SuperPoint#164, I comment the following three lines:
https://github.com/shaofengzeng/SuperPoint-Pytorch/blob/6e5c6587311cd4f98f9a5b61e84731555778c958/solver/loss.py#L126
    dot_product_desc = F.relu(dot_product_desc)

    ##l2_normalization
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc, Wc, Hc * Wc]),
                                                 p=2,
                                                 dim=3), [batch_size, Hc, Wc, Hc, Wc])
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc * Wc, Hc, Wc]),
                                                 p=2,
                                                 dim=1), [batch_size, Hc, Wc, Hc, Wc])

The train and val descriptor loss are as below with a small amount of data (100 samples). Train descriptor loss  Val descriptor loss
These three line code is used for normalization of dot_descriptor and is it necessary for this operation after descriptors dot? I'm not sure if this is correct and maybe the amount of data (100 samples) is too small? Could you please give me some advice?

I delete these three lines and adjust the training parameter, lambda_d: 800 lambda_loss: 1, and then my desc_loss starts to decrease gradually from 20

My Wechat is chiu_jing_chun, we could add WeChat each other for further discussing if it is convenient for you :)

okokok

@ericzzj1989 @jinqiua hi, I met the same descriptor loss. Have you figured out the reason?

@ericzzj1989 @jinqiua hi, I met the same descriptor loss. Have you figured out the reason?

”dot_product_desc“ does not need to do normalization, please refer to my last comment.

Hi, i remember that even if the loss of desc is not significantly reduced, you can still achieve better results~

Thanks very much for your help. According to this rpautrat/SuperPoint#164, I comment the following three lines:
https://github.com/shaofengzeng/SuperPoint-Pytorch/blob/6e5c6587311cd4f98f9a5b61e84731555778c958/solver/loss.py#L126
    dot_product_desc = F.relu(dot_product_desc)

    ##l2_normalization
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc, Wc, Hc * Wc]),
                                                 p=2,
                                                 dim=3), [batch_size, Hc, Wc, Hc, Wc])
    dot_product_desc = torch.reshape(F.normalize(torch.reshape(dot_product_desc, [batch_size, Hc * Wc, Hc, Wc]),
                                                 p=2,
                                                 dim=1), [batch_size, Hc, Wc, Hc, Wc])

The train and val descriptor loss are as below with a small amount of data (100 samples). Train descriptor loss  Val descriptor loss
These three line code is used for normalization of dot_descriptor and is it necessary for this operation after descriptors dot? I'm not sure if this is correct and maybe the amount of data (100 samples) is too small? Could you please give me some advice?

I delete these three lines and adjust the training parameter, lambda_d: 800 lambda_loss: 1, and then my desc_loss starts to decrease gradually from 20

@jinqiua I comment three lines and set lambda_d = 800 lambda_loss = 1 and my training&evaluating results look the same as yours. During training desc loss decreases to from 20 to 5, but during evaluating desc loss explode to 300~1000. Have you solved this problem?


Ebpf API should have a verbose mode for verification

Ebpf API should have a verbose mode for verification

Can you elaborate on the ask?  The verify API already has a 'verbose' argument:
 uint32_t
    ebpf_api_elf_verify_section(
        const char* file, const char* section, bool verbose, const char** report, const char** error_message);

Yep, looks like this is actually already completed. My bad.


moved induced norm functionality to parent class

@obriente please confirm these changes are acceptable. Note that we've add you as an author.
This PR will fail until we merge the SymbolicOperator PR in https://github.com/quantumlib/OpenFermion/pull/192

Did you also want to change these to functions that act on the class instead of member functions?

@jarrodmcc I decided I don't really care.

@kevinsung can you approve PR again?

@obriente I have updated your affiliation.

LGTM - my only comment would be that the induced norm is not preserved across transformations.
This isn't a huge issue - there are always plenty of norms to choose, and the one that we might state as 'the' norm is the operator norm, and this is difficult to calculate. But we might want to note it somewhere because otherwise it might trip someone up at some point.


[Publisher] Report 840 "Suggest Worksheet Lines" - OnBeforeNoOptionsChosen

Please make procedure NoOptionsChosen extensible by adding a OnBeforeNoOptionsChosen publisher with Handled pattern and var access to the boolean return value to overrule the error.

Already raised in #5103 but it was never fixed.
We want to extend report 840 by adding additional entities / data items to be included in the cash flow forecast (conditional by new options added to the 'options' requestpage) . This alows us to avoid the Text002 error in case we want to test on our custom options / booleans (if hopefully report extensions would allow us extending the cash flow forecast report).

Thanks for reporting this. We agree, and we’ll publish a fix asap, either in an update for the current version or in the next major release. We will update this issue with information about availability. Please do not reply to this, as we do not monitor closed issues. If you have follow-up questions or requests, please create a new issue where you reference this one.


Rfc30/fix dependency bug

Motivation and Context
Part of RFC30.
Description
Without this it will produce ["target.'cfg(aws_sdk_unstable)'.dependencies"]
In JSON, this is an equivalent of: {"target.'cfg(aws_sdk_unstable)'.dependencies" : ...}
To make it work, it has to be: {"target": {'cfg(aws_sdk_unstable)': {"dependencies": ...}}}
This piece of code fixes it.
Testing
NA
Checklist
NA
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

Should I merge the latest-release to the serde branch first?

@Velfi
Would you kindly merge this one first?
https://github.com/awslabs/smithy-rs/pull/2571

I will create another PR that is up to date with April release.