Adding Gradle Task.lib Implementation

Task name: AzureTestPlanV0 Task
Description: Migrating Gradle test execution to task.lib
Documentation changes required: (Y/N) N
Added unit tests: (Y/N) N
Attached related issue: (Y/N) N
Checklist:

[ x] Task version was bumped - please check instruction how to do it
[x ] Checked that applied changes work as expected

Please check failure in build as well


Running 'python setup.py test' is no longer supported

Has been deprecated since 2019: https://github.com/pypa/setuptools/pull/1878

Merged into the 2 other PRs as they all need each others


BROWSER=none not working - react-dev-utils package from npm not up-to-date with git?

Can you reproduce the problem with latest npm?
yes
Description
I wanted to use the BROWSER=none option, to prevent react-scripts from opening a new Browser.
Setting the env variable did not work at all.
after checking the openBrowser.js file in node_modules/react-dev-utils/ I realized, that it is different
from the openBrowser.js in the github repo:
/**

Copyright (c) 2015-present, Facebook, Inc.
All rights reserved.

This source code is licensed under the BSD-style license found in the
LICENSE file in the root directory of this source tree. An additional grant
of patent rights can be found in the PATENTS file in the same directory.
*/

var execSync = require('child_process').execSync;
var opn = require('opn');
function openBrowser(url) {
if (process.platform === 'darwin') {
try {
// Try our best to reuse existing tab
// on OS X Google Chrome with AppleScript
execSync('ps cax | grep "Google Chrome"');
execSync(
'osascript openChrome.applescript ' + url,
{cwd: __dirname, stdio: 'ignore'}
);
return true;
} catch (err) {
// Ignore errors.
}
}
// Fallback to opn
// (It will always open new tab)
try {
opn(url).catch(() => {}); // Prevent unhandledRejection error.
return true;
} catch (err) {
return false;
}
}
This file does not contain the check for BROWSER=none, but in
https://github.com/facebookincubator/create-react-app/blob/master/packages/react-dev-utils/openBrowser.js
it exists.
Expected behavior
using the env variable like BROWSER=none should prevent react-scripts from opening the browser
Actual behavior
When using BROWSER=none, the Browser still opens
Environment
Run these commands in the project folder and fill in their results:

npm ls react-scripts (if you haven’t ejected):
<EMAIL_ADDRESS>/home/beac0n/dev/wine-page
└──<EMAIL_ADDRESS>

node -v: v7.5.0

npm -v: 4.1.2

Operating system:
Arch Linux

I could reproduce the issue when creating a new project with create-react-app 1.0.3.
I also ran npm cache clean, yarn cache clean - both commands with sudo and without.
I also downloaded the bundle manually from the npm registry:
https://registry.npmjs.org/react-dev-utils/-/react-dev-utils-0.4.2.tgz
The openBrowser.js file still isn't the same as in the github repository.

The change was done in master but 0.9.0 has not been released yet. It will be released soon.

0.9.0 is out now with support for this.

upgraded to 0.9.0, which resolved this issue :). Thanks a lot :+1:

Sorry, maybe I'm stupid but how were you able to update? I'm using react-dev-utils for our build setup and, I mean react-dev-utils is still on 0.5.2, no?

0.9.0 refers to the version of react-scripts, not react-dev-utils. You have the latest version.

Okay, than the information in CHANGELOG are very confusing. 🙈
https://github.com/facebookincubator/create-react-app/blob/master/CHANGELOG.md#094-march-6-2017
It's saying that the version 0.9.4 contains some fixes published on the 9th of March. So now I guess 0.9.4 stands only for the create-react-app package version, right? That's were the confusion starts at least to me. It would help if the CHANGELOG also contains the version numbers of the child packages so it's easier to track them if you use them separately.
Than again I'm looking for changes from the PR #1546 which were merged on 15th of February.
This PR is adding the content-changed message to the client socket implementation to reload the page when files in the contentBase (/public) changed.
15th of February vs. 9th of March, but not part of the package? Looking into the webpackHotDevClient.js file from the latest release, the changes from #1546 are indead also not part of 0.9.4:
https://github.com/facebookincubator/create-react-app/blob/v0.9.4/packages/react-dev-utils/webpackHotDevClient.js#L247-L265
So apart from all this I'm also confused by the fact that older changes than the latest ones are not part of the latest version of the package. 🙈 😅

Ah, now looking at #1546 a little closer I see that it changes are scheduled for 0.10.x by @gaearon. So you seem to cherry-pick changes from the current master?
Also, why is this scheduled for the next minor version? Worried about anything?
Apart from changes in a public folder, I would really love to reload the page in certain situation via webpackHotDevClient.

Changelog uses versions of react-scripts because that's the thing most people will upgrade. For other packages it's easiest to figure out what changes by looking at folder git history.
https://github.com/facebookincubator/create-react-app/pull/1546 only works with Webpack 2 (afaik). So it's not released until we release a version of react-scripts compatible with Webpack 2.
Yea, we cherry-pick stable branch from master now but the next release will be done from master.

Thank you for the explanations. I found and started to use the 0.6.0-beta release, so I can use the content reloading now.


Followup ColumnFamily directory naming change introduced in Cassandra…

… 2.1
The change was a fix for CASSANDRA-5202 and introduced in the following Cassandra patch

Hi Vinh,
Please merge this PR, because it's essential for 2.1 support.
Thanks,
Andor

LGTM.


[WIP] ak.Array and ak.Record constructors. Maybe the ak.zip function.

Copied from https://github.com/scikit-hep/awkward-1.0/issues/156#issuecomment-597366071

[X] The ak.Array and ak.Record constructor bugs (iterating over the dict keys and implementing that FIXME)
[ ] Make fromiter iterate over py::array (mentioned in #146)
[ ] Possibly, but not necessarily, ak.zip (described in #77).

@tamasgal
ak.Record({"x": 1, "y": 2.2})

now produces a record and
ak.Array({"x": 1, "y": 2.2})

raises an error. ak.Array and ak.Record are mutually exclusive and each error message points you to the other class.

array = awkward1.Array([numpy.array([1, 2, 3]), numpy.array([4, 5, 6, 7])])
assert str(awkward1.typeof(array)) == "2 * var * int64"
assert awkward1.tolist(awkward1.tolist(array)) == [[1, 2, 3], [4, 5, 6, 7]]

The implementation is cheap: when we encounter a py::array in fromiter, we call tolist() on it and deal with it as an iterable. The numbers it contains have numpy.integer, numpy.floating, and numpy.bool_ type (which aren't the same as Python int, float, and bool, which is an annoyance when converting to JSON as well!), so these are now recognized and converted as well.
A better implementation might avoid converting NumPy arrays into Python lists and iterate over it in C++, but we're just establishing behavior here; optimizing later.
At least I sorted the type checks to put the most common first. The NumPy type checks have to import numpy, so they're last.

Can't sort the type checks arbitrarily, or else True/False might be recognized as int and bytes as str.

That was quick, as always! Thanks I'll test tomorrow 😃

That last commit also removes a "skip" from the all-important "Numba cpointers" test (#118) and revealed a few other places where awkward1._numba had to be changed to awkward1._connect._numba. Thus, I have to merge this PR to make master fully work with Numba. I want to do that as soon as these tests pass; ak.view can go in later.


2 packages from jonahbeckford/tiny_httpd at 0.16

This pull-request concerns:
-tiny_httpd.0.16: Minimal HTTP server using threads
-tiny_httpd_camlzip.0.16: Interface to camlzip for tiny_httpd

Homepage: https://github.com/c-cube/tiny_httpd/
Source repo: git+https://github.com/c-cube/tiny_httpd.git
Bug tracker: https://github.com/c-cube/tiny_httpd/issues

:camel: Pull-request generated by opam-publish v2.1.0

Upstream fix: https://github.com/c-cube/tiny_httpd/pull/86


[build] Improve build system for haskell project without hard dependency to VC

See #641 for details discussion.

Use vcxproj file compile Haskell codes lead to a hard dependency to Visual C++ which is not available on other platform now. I suggest to use a customized proj file instead to eliminate this unnecessary dependency.

The current changes would use a csproj to invoke the cmake to build the gbc binary. This would get rid of the hard dependency to Visual C++.
The current changes keeps the same behaviors of origin vcxproj.

It builds only on Windows
It skips on other platform
It invoke cmake to build gbc.
It works with xbuild
It works with msbuild
It works with the sln file in particular with the postProject metadata

I think we can further improve it in the future to get rid of cmake & build scripts in .travis.yml, make this csproj works on multiple platform.

@chwarr I fixed the comments, please help to review it again.

Thank you very much for this change!


Support for EVPN single-active multihoming

Enhancement summary
This feature is pretty recent: 4.26.0F:
https://eos.arista.com/eos-4-26-0f/evpn-single-active-multihoming-preference-based-df-election/
Requesting support to configure EVPN A/S in ethernet or port-channel interfaces, including DF preference:
interface Ethernet5
   switchport mode trunk
   !
   evpn ethernet-segment
      identifier 0000:0000:0011:1100:0000
      redundancy single-active
      designated-forwarder election algorithm preference 200
      route-target import 00:00:00:00:11:11

Which component of AVD is impacted
eos_designs, eos_cli_config_gen
Use case example
Deploy some leaves with EVPN A/S, so only one of the PEs is actively forwarding traffic.
Describe the solution you would like
Describe ESIs in SERVER files with EVPN multihoming redundancy single-active and select a DF preference.
Describe alternatives you have considered
Currently i can achieve this in the SERVER file via raw cli commands:
---
routers:
    swCE1_CE2:
      rack: RackA
      adapters:
        - endpoint_ports: [et1, et1]
          switch_ports: [Ethernet5, Ethernet5]
          switches: [ DC-1-BL-2, DC-2-BL-2]
          vlans: "10,20,30,40"
          profile: TRUNK_1G
          raw_eos_cli:
              switchport mode trunk

              evpn ethernet-segment

              redundancy single-active

              designated-forwarder election algorithm preference 100

              identifier 0000:0000:0011:1100:0000

              route-target import 00:00:00:00:11:11

Additional context
No response
Contributing Guide

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

Similar issue #1163 where we are discussing the support for single-active MH with DF election for eos_cli_config_gen
we would need a separate PR for updates to eos_designs as well.
we can discuss and work on the respective PRs for   eos_cli_config_gen and eos_designs

The eos_cli_config_gen part is resolved in #1437

@dgonzalez85 do you agree that we can close this issue?

Hi @ClausHolbechArista sorry i missed this. Indeed we can close this. I was dicussing with @gmuloc about creating a separate issue to support this in the eos_designs role, but maybe thats already WIP?
thanks


Clarity on using composer upstream-require

I created a site using this upstream, and I would still like to use the "one-click update" from the Pantheon dashboard to apply upstream changes. I am confused on which composer command I should use to load/manage my site's plugins and themes. Is it best-practice to use the composer upstream-require and leave the root composer.json alone? The comments/docs are a little confusing around this, and seem to be written for using/hosting a custom upstream (maybe?) even though the README suggests using the Pantheon upstream.
For example, if I want to include the Yoast SEO plugin for my site, which command would i use to avoid conflicts when applying upstream updates?
composer require yoast/wordpress-seo

or
composer upstream-require yoast/wordpress-seo

When I try to use composer upstream-require, it tells me that I cannot use it without modifying the root composer.json (at least the name property), but I am concerned that this may cause conflicts when applying upstream changes via Dashboard. Is the purpose of the "upstream-configuration" to give the sites a separate composer.json to use to customize, or is that literally meant for hosting your own upstream and shouldn't be used when working on a site referencing the Pantheon upstream?
For that matter, shouldn't this upstream repo have its dependencies listed in the upstream-configuration/composer.json and leave the root composer.json with the minimal setup/scripts to reference the upstream config (which would include the roots/wordpress and other dependencies presumably managed by this upstream)?

For example, compare this repo's upstream-configuration/composer.json to the wordpress-project's upstream-config/composer.json. It would seem that the dependencies in the root composer.json of this repo should be moved to the upstream-configration/composer.json based on how the other upstream is set up.

The upstream/configuraion/composer.json file is for use by custom upstreams that are based on a Pantheon standard upstream, e.g. this one. Pantheon might put a dependency here, but only if it is required for operation of the site, and the end user will never have the option to change the required version of the dependency. All of the Pantheon-supplied requirements are currently placed in the root-level composer.json file so that the end-user has the option to adjust the required version if desired.
An individual site should never modify the contents of anything in the upstream configuration folder. This directory is reserved for the use of the upstream, so that additions may be made without the risk of causing merge conflicts with sites based on it.

Tracked internally as BUGS-5505

The upstream-require script has been moved to https://packagist.org/packages/pantheon-systems/upstream-management, and out of this Composer configuration, so closing this issue. pantheon-systems/upstream-management can be required explicitly for custom upstreams that require it and I believe we've updated all the relevant documentation that previously suggested using composer upstream-require over composer require but feel free to re-open if this is still an issue.


Remove calendar and clock icons from blog entry list

try removing the calender and clock icons in blog section (b.s)

A lot of designs (when displaying time information) use a clock and calendar icon to help people understand what the numbers mean at a glance. I'm curious why you want them removed.

Fair, I imagined it would still be understandable at a glance without them. Makes that space look more minimal and to the point!

The blog entry list is already quite minimal as it is, I don't feel like that's enough of a reason to remove the icons at this point in time. I'll black box this though so if need be, we can revisit it later.


Fix #621, update action versions to v3

Checklist (Please check before submitting)

[x] I reviewed the Contributing Guide.
[x] I signed and emailed the appropriate Contributor License Agreement to<EMAIL_ADDRESS>and copied<EMAIL_ADDRESS>
Describe the contribution
Update cache, checkout, and upload-artifact actions from v2 to v3. Should be a drop-in replacement and removes a warning about node.js 12 deprecation.
Fixes #621
Testing performed
Run all github workflows
Expected behavior changes
No more warnings about node.js 12 deprecation
System(s) tested on
Github hosted runner
Contributor Info - All information REQUIRED for consideration of pull request
Joseph Hickey, Vantage Systems, Inc.

@jphickey Looks good, but I don't see where the node.js warning is removed. For example, click the Format Check workflow triggered by this PR and take a look at the workflow file. It uses v3, but the warning is still there. Here is a link: https://github.com/nasa/cFS/actions/runs/3535753791

@jphickey Looks good, but I don't see where the node.js warning is removed. For example, click the Format Check workflow triggered by this PR and take a look at the workflow file. It uses v3, but the warning is still there. Here is a link: https://github.com/nasa/cFS/actions/runs/3535753791

Thanks for catching that, it looks like the warning in that particular run was from the 3rd-party action "gsactions/commit-message-checker@v1", not the github actions that were updated in this PR.
We'll need to see if there is an update/new version from the original author.  I'll check that.  I'd still recommend merging this PR, as it fixes most of them - there may be some left but I can take care of those as they appear.

I checked and yes, the "commit-message-checker" does have a version 2 now.  So I pushed another commit (see 5a1174f) that updates this action from v1 to v2 and the warning is gone.  See https://github.com/nasa/cFS/actions/runs/3593359346.
We will just have to keep an eye out for remaining deprecation warnings and watch for new versions of whatever action is triggering them.  Problem is when there are a lot, things get buried, so even if this may not fix 100% of the warnings, it will make the remaining ones easier to spot and fix.


IP model - broaden criteria for rearing upstream/downstream connectivity to spawning

Currently, rearing habitat must be downstream or upstream of spawning habitat for a given species.
We also want to include rearing habitat that while not actually 'downstream' or 'upstream' of spawning, is on a trib to a stream that is downstream/upstream of spawning.
For example, consider river X, with two tribs, stream A and stream B. Stream A meets gradient/slope requirements for rearing and stream B (another trib to X upstream from A) is modelled as spawning habitat:
  A (rearing)  B (spawning)
     |
     |           |
     |           |
X <=================

Currently, stream A will not be considered rearing because no spawning segments are upstream of segments in A. Stream B is upstream of X at intersection with A but not actually upstream of segments that make up A.
Fixing this should not be too hard, just broaden the criteria slightly to include a watershed code matching.

Fixed for upstream connectivity but adjusting the downstream query is trickier and I'm not sure it is worth the effort.
Currently, for each rearing cluster, find spawning:

downstream within 10 km
with no >=5% slope stream segment between the rearing and spawning

Expanding this to include spawning that is on tribs adjacent to the downstream trace is possible but it seems to be tricky to implement with the additional above criteria and quick visual review doesn't turn up any instances where it would make any difference - there will generally be other spawning upstream or downstream.

Note that the current downstream rearing connectivity criteria includes only streams < 10km downstream - this appears to be far too conservative, just include everything downstream. https://www.tandfonline.com/doi/abs/10.1080/00028487.2011.545004

Does not seem to be a priority, closing for now


Update cli-usage.md

The Problem/Issue/Bug:
Minor trypo ;-p
How this PR Solves The Problem:
I will be able to sleep soundly.

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

Thanks!


Could you provide the logfile of pretraining process?

Hi, Thanks for the great repo.
I want to get an understanding of what happened during the pretraining, especially the train and validation loss change.
In other work like lxmert and my own experiment, The MLM loss is highly overfitted. So I wander is that the same thing of VL-BERT? Considering the specia mask operation of VL-BERT.
Is it possible that you can share the logfile of the pretraining process?

@forjiuzhou Sorry for the late reply. The training accuracy of VL-BERT Large is listed as below:

Masked Language Modeling with Visual Clues: 67.0%
Masked Language Modeling on Text-only Corpus: 65.2%
Masked RoI Classification with Linguistic Clues: 70.1%
And I think MLM accuracy is reasonable, not highly overfitted in VL-BERT. Hope it would help you, Thanks!

@forjiuzhou Sorry for the late reply. The training accuracy of VL-BERT Large is listed as below:

Masked Language Modeling with Visual Clues: 67.0%
Masked Language Modeling on Text-only Corpus: 65.2%
Masked RoI Classification with Linguistic Clues: 70.1%

And I think MLM accuracy is reasonable, not highly overfitted in VL-BERT. Hope it would help you, Thanks!

Thanks for you information !
And what about the training accuracy of VL-BERT Base, under precomputed features configure and end-to-end configure ?


keyboard shortcuts

Fullscreen is lctrl+lshift+f
Toggle input grab is lctrl+lshift+g
Possible solutions:

fix output in wrapper.pl
change shortcuts

I updated the wrapper with the commit 862745ac7c1b5f20016b328f78848b32266b2314 and it fixed the shortcuts. Thanks ! ;)


bulletin plugin not supporting backstage version 1.20.2

Earlier, i had backstage 1.17.5 installed, also I was using the newest version of bulletin plugin but after upgrading backstage to 1.20.2 version, it is giving error on docker image build, With new backstage version we have required node version greater than 16.
Error:
yarn run v1.22.19
$ tsc
packages/backend/src/plugins/bulletin-board.ts:11:5 - error TS2322: Type 'import("/home/il58d0/smb/backstage-conf-repo/backstage-conf-repo-original/node_modules/@backstage/backend-plugin-api/dist/index").DatabaseService' is not assignable to type 'import("/home/il58d0/smb/backstage-conf-repo/backstage-conf-repo-original/node_modules/backstage-plugin-bulletin-board-backend/node_modules/@backstage/backend-plugin-api/dist/index").DatabaseService'.
  The types returned by 'getClient()' are incompatible between these types.
    Type 'Promise<import("/home/il58d0/smb/backstage-conf-repo/backstage-conf-repo-original/node_modules/knex/types/index").Knex<any, any[]>>' is not assignable to type 'Promise<import("/home/il58d0/smb/backstage-conf-repo/backstage-conf-repo-original/node_modules/backstage-plugin-bulletin-board-backend/node_modules/@backstage/backend-plugin-api/node_modules/knex/types/index").Knex<any, any[]>>'.
      Type 'import("/home/il58d0/smb/backstage-conf-repo/backstage-conf-repo-original/node_modules/knex/types/index").Knex<any, any[]>' is not assignable to type 'import("/home/il58d0/smb/backstage-conf-repo/backstage-conf-repo-original/node_modules/backstage-plugin-bulletin-board-backend/node_modules/@backstage/backend-plugin-api/node_modules/knex/types/index").Knex<any, any[]>'.
        The types of 'raw(...).transacting' are incompatible between these types.
          Type '(trx: import("/home/il58d0/smb/backstage-conf-repo/backstage-conf-repo-original/node_modules/knex/types/index").Knex.Transaction<any, any[]>) => import("/home/il58d0/smb/backstage-conf-repo/backstage-conf-repo-original/node_modules/knex/types/index").Knex.Raw<any>' is not assignable to type '(trx: import("/home/il58d0/smb/backstage-conf-repo/backstage-conf-repo-original/node_modules/backstage-plugin-bulletin-board-backend/node_modules/@backstage/backend-plugin-api/node_modules/knex/types/index").Knex.Transaction<any, any[]>) => import("/home/il58d0/smb/backstage-conf-repo/backstage-conf-repo-original/no...'.
            Types of parameters 'trx' and 'trx' are incompatible.
              Type 'Transaction<any, any[]>' is missing the following properties from type 'Transaction<any, any[]>': comment, except, havingNull, havingNotNull, updateFrom

11     database: env.database,
       ~~~~~~~~

  node_modules/backstage-plugin-bulletin-board-backend/dist/index.d.ts:8:5
    8     database: PluginDatabaseManager;
          ~~~~~~~~
    The expected type comes from property 'database' which is declared here on type 'RouterOptions'

Found 1 error in packages/backend/src/plugins/bulletin-board.ts:11

Hello together, any update on this? I'd like to as well use this plugin but blocked. Is this plugin still living or deprecated?

Yeah this is annoying. I need features in 1.20 and there doesn't seem to be maintainers keeping this plugin up to date...

It is still alive, but have been caught up on other things unfortunately. Anyone would like to contribute?


Merge 'GO:0033216 ferric iron import' into parent 'GO:0006826 iron ion transport'

Dear all,
~The proposal has been made to obsolete 'GO:0033216 ferric iron import'.
The reason for obsoletion is that this term is not precise enough. There are EXP 5 annotations and 2 IC annotations (the rest are ISO, IEA and IBA). There are no mappings. The term is not present in any slim.~
Annotations are here: https://github.com/geneontology/go-ontology/issues/16408
https://docs.google.com/spreadsheets/d/1R7q8p7s4m_PF5dhkW09o1ghgpyYRxdyGF7jr5Kb6ezo/edit#gid=0
Any comments can be  added to the issue: .
~We are opening a comment period for this proposed obsoletion. We’d like to proceed and obsolete this term on October 1st, 2018. Unless objections are received by October 1st, 2018, we will assume that you agree to this change.~
Thanks, Pascale

I'll merge into the parent GO:0006826 iron ion transport for now.

Brilliant, so in theory I don't need to edit anything.

you might need to look at a few little things ;)

https://github.com/geneontology/go-ontology/pull/16415 Done

So seeing this upon getting back from a meeting
FERRIC means iron 3 ( Fe3+); that's far more precise than iron ion.
There is also a Ferrous form (Fe2+).  Our annotations were to the Fe3+ import
In fact, one of the papers the point was to distinquish between Fe2+ vs Fe3+
"Reduction of Fe(III) to Fe(II) seems to be a prerequisite for iron uptake by the intestine in both mice and humans. This enzymatic  step  is  bypassed  if  iron  reaches  the  microvillous
membrane as Fe(II), eg, when excess ascorbic acid or orange juice is added to the radioactive iron test dose.1 We therefore compared Fe(III) and Fe(II) iron absorption steps in control B6 and b2m2/2 mice"
That distinction is now gone from our annotations.

Hi @hdrabkin
I reorganized the iron transport branch significantly - see #14892 and image below.
In cells other than bacteria, ferric iron is transported either via 'reductive iron assimilation' or by endocytosis (by binding to transferrin). That endocytic part is not yet finished, I hope to do this this week. (Note that my changes shown below are not yet merged).

Thanks, Pascale


Keep EXIF rotation during YOLO importing

Summary

How to test

Checklist

[ ] I submit my changes into the develop branch
[ ] I have added description of my changes into CHANGELOG
[ ] I have updated the documentation accordingly
[ ] I have added tests to cover my changes
[ ] I have linked related issues

License

[x] I submit my code changes under the same MIT License that covers the project.
Feel free to contact the maintainers if that's a concern.
[x] I have updated the license header for each file (see an example below)

# Copyright (C) 2022 CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT

@zhiltsov-max Please review this PR. The main changes are in util/image.py and plugins/yolo_format/extractor.py. Anything else were made just to make this PR green


Be sure that all cases are covered

We need to be sure that all cases are covered
Ref:
https://github.com/mihaeu/dephpend/blob/main/src/Analyser/DependencyInspectionVisitor.php

We can close this issue at the moment


Add isotonic regression as one of the variance reduction technique

Add isotonic regression as one of the advanced variance reduction technique, inspired by the design doc drafted last year.
In short, we take advantage of sklearn.isotonic.IsotonicRegression module to perform isotonic regression in the similar fashion as the CUPED and CAPPING implementation. This implementation will be added to the ad-hoc analysis mode dashboard.
Note: this implementation only implement univariate isotonic regression, as sklearn implementation currently doesn't support multivariate Isotonic Regression.

@bdeluna @eramirezritchie I've cleaned up the code a bit. Below are the new changes:

Remove demean version for isotonic regression.
Clean up the get_timeseries() function to make it more readable


Can enter multiple lines in the Goose terminal

I tried to type some prompt and then shift-enter to paste some more data on the next line in the Goose terminal window and it submitted the prompt before I was able to enter the additional data.  I'd like to be able to enter multi line prompts.

This seems to be an issue in intellij terminals in general.

Update- goose uses prompt toolkit which binds option+enter as newline. This works in intellij too.


Keep editing while scrolling

Is there a way to disable this feature and let my editing textbox keep alive after scroll operation?

No, when we scroll we run row/col virtualisation, so the actual element that your editor is in may have changed.


[EDIT] ngmi glossary (typo)

Entry
The glossary entry “ngmi” (not going [to] make it), e.g. under mtgDAO gets a legal notice from Wizards of the Coast, writes that they are "unfairly discriminat[ing] against web3 tech and web3 communities".
Changes
peroson → person :)
Agreement
By submitting this issue, I irrevocably agree to release my contribution under the CC-BY 3.0 License. I agree that a hyperlink or URL is sufficient attribution under the Creative Commons license.
Please attribute this contribution to:

Lucas Werkmeister
no link I think
honestly this probably falls below ToO so feel free to not credit me at all ^^

Thanks!


Fix motion on nested XML/HTML tagblock

Tag block motion on the following content does not properly move the cursor to the matching pair. To reproduce, copy one of the following content and from the first tag type vat.

Expected behavior is to have the whole content selected.
The actual behavior is that the selection stops after the first closing tag.

Hi @brammool, if it's not too much of an ask is it possible to label this PR with hacktoberfest-accepted?

sure.


Include numeric parameters when binding function return types

Some data types are parametrized for precision or storage length, and
this information needs to be preserved when binding function signatures.
This is particularly important for numeric types, where the precision
parameter changes how values sent across the wire are interpreted by
the receiver.
This changes SignatureBinder to include numeric parameters from input
types when binding its return type. If there are multiple input arguments
with different parameters, type compatibility is used to select the best
type to use.
Fixes #15279

Additionally, please add a changelog entry for 5.6.1.rst since this should be backported.

5.6.2, 5.6.1 is already released

@Mergifyio squash title+body


make app gateway optional

make app gateway setup optional

I don't think we should do this - can we close?


KeyManager - testnet tbnb addresses

Hi, I would like to understand test / prod wallet addresses better
I am creating a wallet like so:
km, err := keys.NewKeyManager()

And the public address can be obtained with:
address := km.GetAddr() // "bnb1683m5xkxa3p69yagrpdsvkp94xvx6utj863596"

But the testnet address is actually:
tbnb1683m5xkxa3p69yagrpdsvkp94xvx6utjf0cs9t
In the Go sdk, how do I derive or obtain the testnet address?

hello, @camstuart
You need to specify the network type to testnet:
//-----   Init sdk  -------------
client, err := sdk.NewDexClient("testnet-dex.binance.org", types.TestNetwork, keyManager)

or you can set global var types.Network = types.TestNetwork

Thank you so much! I need it to!


Add ProGuard rules fixes #11891 #6624

Trying to build project for Android 7 (O)
Test Plan
RN 0.47.1
        classpath 'com.android.tools.build:gradle:2.3.3' // For Android 7 (O)

    compile "com.android.support:appcompat-v7:26.0.0-alpha1"

    buildTypes {
        debug {
            debuggable true
            minifyEnabled enableProguardInReleaseBuilds
            proguardFiles getDefaultProguardFile("proguard-android.txt"), "proguard-rules.pro", "devsupport.pro"
            applicationIdSuffix ".debug"
        }
        release {
            signingConfig signingConfigs.release
            minifyEnabled enableProguardInReleaseBuilds
            proguardFiles getDefaultProguardFile("proguard-android.txt"), "proguard-rules.pro"
            manifestPlaceholders = [excludeSystemAlertWindowPermission: "true"]
        }
    }

    supportLibVersion = '26.0.1'
...
    compileSdkVersion 26

This doesn't fix the crash for me with proguard enabled.

Its because it should be this, the package names changed...
--keep,includedescriptorclasses class com.facebook.react.cxxbridge.ModuleRegistryHolder { *; }
--keep,includedescriptorclasses class com.facebook.react.cxxbridge.CatalystInstanceImpl { *; }
--keep,includedescriptorclasses class com.facebook.react.cxxbridge.JavaScriptExecutor { *; }
+-keep,includedescriptorclasses class com.facebook.react.bridge.CatalystInstanceImpl { *; }
+-keep,includedescriptorclasses class com.facebook.react.bridge.JavaScriptExecutor { *; }

@akshetpandey , can You check this?

This works for me, I did leave a comment about an extra line which doesn't seem to do anything though.

Looks like some new changes were added to the PR? This invalidates the prior approval.

At this point this should probably be changed to target 0.49/0.50 instead

Ah! That explains why this is not landing. We can only merge pull requests opened against master.
To land commits into stable releases, a release coordinator has to cherry pick the individual commit. Commenting on #16257 like you just did is the recommended approach. I'm going to close this as we can't land this PR.


Synostpool failed to create storage pool

Hi, I'm running Esxi 7.0U3 VM DSM 7.2.1-69057 using ARC loader 24.6.29 on my Oracle X8-2L which has 8x 6.4TB F640 NVMe cards installed. They are basically rebadged Intel P4608 NVMe cards.
I've added passed through all the cards and they show up on the Synology RS4021 as dual 3.2TB each as expected (each 6.4TB are essentially 2x 3.2TB SSD) for a total on 16x in the storage manager.
However I'm not able to get them to be used as ssd storage by running the Synology_enable_M2_volume. It errors out after the RAID and drives selection with "0 synostgpool failed to create storage pool". On the Synology storage manager, the drive requirements shows "This drive is installed via an adapter card and cannot be used in M.2 SSD  storage pools."

My https://github.com/007revad/Synology_HDD_db script allows creating a volume in NVMe drives in a PCIe adaptor card (which is what "This drive is installed via an adapter card and cannot be used in M.2 SSD storage pools." is referring to).
The https://github.com/AuxXxilium/arc-addons hdddb addon is v3.5.90 of my Synology_HDD_db script.
You should only need the Synology_HDD_db script, or hdddb ARC addon, (and not the Synology_enable_M2_volume script).

Hi, it worked marvellously. Thank you.


[FEAT] Some way to define how many pages will be kept in memory

Is your feature request related to a problem? Please describe.
One of the uses I have for SwiftUIPager is to load pages on demand, but after some time memory starts going up, especially due to the nature of what I have in each page
Describe the solution you'd like
It would be great to have some way to define some limit of how many pages are kept in memory, or to have some API for manually removing pages by index
Notes
I had a look at https://github.com/fermoya/SwiftUIPager/issues/186 which suggests to use the eager loading policy, but that will not be a solution for me according to the docs as there could be hundreds or thousands of pages in my use-case

@mvrsn Pager keeps by default a handful of pages in memory. Using .eager isn't recommended.
Please take a look at this section. Just about 5 pages are kept in memory depending on the page size

Thank you for the quick response @fermoya
What made me confused is that I am loading webviews into the Pager pages, and when I check the Safari developer tools I can see webviews listed under my device that should no longer exist, however, I now tested and modified the contents of one of the old webviews while outside the range of kept-in-memory webviews before navigating back, and indeed you are correct, a new one was created and the modifications are not shown
I'm not sure why the webviews are still visible within Safari though, even after restarting the program, but maybe this has something to do with the garbage collection of iOS that they are still there?

web views have some kind of cache. Perhaps creating a new one loads the last website if no other content is loaded. It might have something to do with the default configuration 🤷


Server error 500

When creating new patients, visits, observations, etc. depending on the number of data that is filled, it might prompt to which data is required and has not been filled (good) but also sometimes it throws a server error 500. Several combinations seem to throw that error but a simple one is try to add an observation, do not fill any of the fields and try to save it.

@Alvaro-FG Hey, this might be related to #327 so let's observe this further.
BTW, if you get a 500 (internal server error) can you at least post the timestamp (UTC) for when this occurred, please? Better still if just after it happens you find it in the AWS application logs, can you post the link for the erroring line in the AWS application log, please?
FYI I wouldn't suggest posting the error itself, in case there's something in there that shouldn't be publicly displayed here. At the moment, during this beta testing transition phase there shouldn't be, but still. Might be safer for you to adopt a blanket approach of not doing so.

This can be reproduced when trying to save a new and empty observation form.
https://github.com/RISPaDD/biospecdb/blob/main/biospecdb/apps/uploader/models.py#L474
if self.observable.center.count() and (self.visit.patient.center not in self.observable.center.all()):
            # Note: Don't expose centers here.

but obviously  self.observable doesn't exist. This should have been handled by the individual field validations prior to clean() being called. 🤔


window.scrollY is not supported in IE

Currently, window.scrollY is not supported in IE. Instead, document.documentElement.scrollTop is a fully compatible solution. See:
"For cross-browser compatibility, use window.pageYOffset instead of window.scrollY. Additionally, older versions of Internet Explorer (< 9) do not support either property and must be worked around by checking other non-standard properties. A fully compatible example:"
https://developer.mozilla.org/en-US/docs/Web/API/Window/scrollY?redirectlocale=en-US&redirectslug=DOM%2Fwindow.scrollY#Notes

Looks good. Thanks!


DSND-2937: Implement call to acsp-profile-data-api to PUT ACSP

Describe the changes

Takes the transformed request body and sends it to the PUT endpoint in acsp-profile-data-api.
Includes a kafka/wiremock integration test.

Related Jira tickets
DSND-2937
Developer check list
General

[ ] Is the PR as small as it can be?
[ ] Has the Jira ticket been updated with any relevant comments?
[ ] Is the README up to date?
[ ] Has the POM been updated for the latest versions of dependencies?
[ ] Has the code been double-checked against main?
[ ] Does the code adhere standards in this repository, including SonarQube checks?

Testing

[ ] Do the code changes have unit and integration tests with code coverage > 80%?
[ ] Has the code been tested locally and/or passed the API Karate tests on Tilt?
[ ] Have mandatory manual test cases been run?
[ ] Are extra Karate tests required?
[ ] Are all the test data resources up to date?

Release preparation
Where possible, add links to the respective Jira tickets when an item is checked

[ ] Have these changes been included in a release ticket?
[ ] Are changes required to the docker-chs-development deployment or test data?
[ ] Are any changes required to the environment added to chs-configs?

Notes to the tester
Add any testing hints or instructions here.

CI: No security warnings found


Sink archetype is not generating the ceOverrides

In the source archetype we get this generated, for the cloudevents override:
camel.component.knative.ceOverride[ce-type]={{kn.connector.ce.override.type:dev.knative.eventing.aws-s3}}
camel.component.knative.ceOverride[ce-source]={{kn.connector.ce.override.source:dev.knative.eventing.aws-s3-source}}
camel.component.knative.ceOverride[ce-subject]={{kn.connector.ce.override.subject:aws-s3-source}}

It seems this is missing on the sink archetype

Maybe I do not understand but why should the sink set these overrides? The source produces the ce-attributes the sink does not

/close
ah. yeah.


Add release tag labels to Kafka Channel objects

These were missed in the shuffle from the eventing repo.
Same as #544 (without the changes to Kafka CCP)

/lgtm


getting OOM on 8 nvidia GPUs with 40GB memory each

using scripts/train/train.py
yaml: yamls/mpt/finetune/7b_dolly_sft.yaml

Hey there! Thanks for trying out our repo.
Could you share any diffs you made to the YAML, or is it exactly as in the repo? Tagging @alextrott16 as the finetuning expert. We will reproduce on our side.
For an immediate fix, could you try lowering device_train_microbatch_size from 8 to say, 4, and see if that helps?

Hi!
Memory usage should be the same with finetuning as with pre-training. It basically will just depend on the model size, device_train_microbatch_size, max_seq_len and mode.attn_config.attn_impl.
I guess with FSDP sharding it'll also depend on the number of devices. 8 should be enough with 80GBs of GPU RAM, but might not be enough with 40GBs.
In any case, lowering device_train_microbatch_size to 4 is your best bet :)

i am using the exact same config. A little unclear how to use the huggingface model
i am adding this at the end of yaml
load_path: /root/.cache/huggingface/modules/transformers_modules/mosaicml/mpt-7b/d8304854d4877849c3c0a78f3469512a84419e84/
i get the cuda error in data loading stage itself , when i reduce seq_len to low value like 100 it goes away but then it happens during model loading stage
nvidia-smi gives this
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.85.12    Driver Version: 525.85.12    CUDA Version: 12.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA A100-SXM...  On   | 00000000:10:1C.0 Off |                    0 |
| N/A   26C    P0    51W / 400W |      0MiB / 40960MiB |      0%      Default |
|                               |                      |             Disabled |
+-------------------------------+----------------------+----------------------+
|   1  NVIDIA A100-SXM...  On   | 00000000:10:1D.0 Off |                    0 |
| N/A   26C    P0    51W / 400W |      0MiB / 40960MiB |      0%      Default |
|                               |                      |             Disabled |
+-------------------------------+----------------------+----------------------+
|   2  NVIDIA A100-SXM...  On   | 00000000:20:1C.0 Off |                    0 |
| N/A   27C    P0    49W / 400W |      0MiB / 40960MiB |      0%      Default |
|                               |                      |             Disabled |
+-------------------------------+----------------------+----------------------+
|   3  NVIDIA A100-SXM...  On   | 00000000:20:1D.0 Off |                    0 |
| N/A   26C    P0    52W / 400W |      0MiB / 40960MiB |      0%      Default |
|                               |                      |             Disabled |
+-------------------------------+----------------------+----------------------+
|   4  NVIDIA A100-SXM...  On   | 00000000:90:1C.0 Off |                    0 |
| N/A   26C    P0    50W / 400W |      0MiB / 40960MiB |      0%      Default |
|                               |                      |             Disabled |
+-------------------------------+----------------------+----------------------+
|   5  NVIDIA A100-SXM...  On   | 00000000:90:1D.0 Off |                    0 |
| N/A   27C    P0    55W / 400W |      0MiB / 40960MiB |      0%      Default |
|                               |                      |             Disabled |
+-------------------------------+----------------------+----------------------+
|   6  NVIDIA A100-SXM...  On   | 00000000:A0:1C.0 Off |                    0 |
| N/A   26C    P0    50W / 400W |      0MiB / 40960MiB |      0%      Default |
|                               |                      |             Disabled |
+-------------------------------+----------------------+----------------------+
|   7  NVIDIA A100-SXM...  On   | 00000000:A0:1D.0 Off |                    0 |
| N/A   25C    P0    49W / 400W |      0MiB / 40960MiB |      0%      Default |
|                               |                      |             Disabled |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

even doing this doesnt help
global_train_batch_size: 8 # assuming 8 gpus

# System
seed: ${global_seed}
device_eval_batch_size: 1
device_train_microbatch_size: 1
# device_train_microbatch_size: auto
precision: amp_bf16

@vchiley

I'll admit to being a little puzzled by this. I was just able to run cd llm-foundry/scripts/train && composer train.py yamls/mpt/finetune/7b_dolly_sft.yaml on 1 node with 8 A100-40GB.
Note: I did have to overwrite the load_path: ... line because it is just a placeholder and, unless you went through the pre-training steps to create a pre-trained checkpoint, you won't want to use load_path.
To do that, use the command: composer train.py yamls/mpt/finetune/7b_dolly_sft.yaml load_path=null
To help me better understand the issue, a couple questions:

Are you using composer train.py ...? I caught an OOM when using python train.py ....
If the problem continues, can you try starting from the recommended docker image mosaicml/pytorch:1.13.1_cu117-python3.10-ubuntu20.04?

i am using the docker image now. still getting error
root@042b5478a3f4:~/llm-foundry/scripts/train# python train.py yamls/mpt/finetune/7b_dolly_sft.yaml load_path=null
Initializing model...
cfg.n_params=6.66e+09
Building train loader...
Using pad_token, but it is not set yet.
Re-formatting dataset with "HuggingFaceH4/databricks_dolly_15k" preprocessing function.
Found cached dataset parquet (/root/.cache/huggingface/datasets/HuggingFaceH4___parquet/HuggingFaceH4--databricks_dolly_15k-6252f3495e7d2b9d/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec)
Loading cached processed dataset at /root/.cache/huggingface/datasets/HuggingFaceH4___parquet/HuggingFaceH4--databricks_dolly_15k-6252f3495e7d2b9d/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec/cache-9cf4c020b7f570d5.arrow
Building eval loader...
Building trainer...
Traceback (most recent call last):
  File "/root/llm-foundry/scripts/train/train.py", line 254, in <module>
    main(cfg)
  File "/root/llm-foundry/scripts/train/train.py", line 197, in main
    trainer = Trainer(
  File "/usr/lib/python3/dist-packages/composer/trainer/trainer.py", line 954, in __init__
    prepare_fsdp_module(model, optimizers, self.fsdp_config, precision, device, auto_microbatching)
  File "/usr/lib/python3/dist-packages/composer/trainer/dist_strategy.py", line 355, in prepare_fsdp_module
    fsdp_obj = MosaicFullyShardedDataParallel(
  File "/usr/lib/python3/dist-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py", line 1062, in __init__
    self._materialize_module(module, param_init_fn, device_from_device_id)
  File "/usr/lib/python3/dist-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py", line 1368, in _materialize_module
    param_init_fn(module)
  File "/usr/lib/python3/dist-packages/composer/trainer/dist_strategy.py", line 283, in _param_init_fn
    meta_safe_apply(module,
  File "/usr/lib/python3/dist-packages/composer/trainer/meta_safe_apply.py", line 36, in meta_safe_apply
    meta_safe_apply(module, fn, ignored_modules, curr_module_name)
  File "/usr/lib/python3/dist-packages/composer/trainer/meta_safe_apply.py", line 36, in meta_safe_apply
    meta_safe_apply(module, fn, ignored_modules, curr_module_name)
  File "/usr/lib/python3/dist-packages/composer/trainer/meta_safe_apply.py", line 36, in meta_safe_apply
    meta_safe_apply(module, fn, ignored_modules, curr_module_name)
  [Previous line repeated 1 more time]
  File "/usr/lib/python3/dist-packages/composer/trainer/meta_safe_apply.py", line 60, in meta_safe_apply
    param_applied = fn(param)
  File "/usr/lib/python3/dist-packages/composer/trainer/dist_strategy.py", line 284, in <lambda>
    lambda t: torch.empty_like(t, device=f'cuda:{torch.cuda.current_device()}'),
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 770.00 MiB (GPU 0; 39.56 GiB total capacity; 38.31 GiB already allocated; 202.56 MiB free; 38.43 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

I think I see the problem. This looks like the same error I was getting when using python instead of composer.
Can you run composer train.py yamls/mpt/finetune/7b_dolly_sft.yaml load_path=null instead?

Adding on to @alextrott16 's comment:
When you are using python train.py ..., you are launching just one process, which will run training on one GPU. In that situation, FSDP is not doing anything, and your 7B model is not sharded, and the weights+optimizer+activation memory must fit on 1xA100, and it is running into an OOM.
When you use the composer launcher such as composer train.py ... , it detects the number of GPUs on your machine, launching 8 processes to target the 8 GPUs, and the 7B model gets sharded across 8 GPUs, and now the memory should fit per-GPU and it should work!

i got a bit further. but there was issue with cuda and pytorch compatibility. i have cu11.8
so installed pytorch 2.0.1 and triton 2.0.0 But now seeing this: should i try with cuda 11.7 ?
  runtime_estimator: {}
load_path: null
dist_timeout: 600.0
n_gpus: 8
device_train_batch_size: 8
device_train_grad_accum: 1
n_params:<PHONE_NUMBER>

Starting training...
******************************
Config:
enabled_algorithms/GradientClipping: true
node_name: unknown because NODENAME environment variable not set
num_gpus_per_node: 8
num_nodes: 1
rank_zero_seed: 17

******************************
/home/ec2-user/llm-foundry/llmfoundry/data/finetuning/collator.py:188: UserWarning: Truncating TARGET sequence of length=849 to length=812, so context+target fit max_seq_len=2048. If truncation is a problem, consider increasing max_seq_len.
  warnings.warn(
Traceback (most recent call last):
  File "<string>", line 21, in _fwd_kernel
KeyError: ('2-.-0-.-0-83ca8b715a9dc5f32dc1110973485f64-d6252949da17ceb5f3a278a70250af13-3b85c7bef5f0a641282f3b73af50f599-3d2aedeb40d6d81c66a42791e268f98b-3498c340fd4b6ee7805fd54b882a04f5-e1f133f98d04093da2078dfc51c36b72-b26258bf01f839199e39d64851821f26-d7c06e3b46e708006c15224aac7a1378-f585402118c8a136948ce0a49cfe122c', (torch.bfloat16, torch.bfloat16, torch.bfloat16, torch.bfloat16, torch.bfloat16, torch.float32, torch.float32, 'fp32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32', 'i32'), ('vector', True, 128, True, True, True, 128, 128), (True, True, True, True, True, True, True, (False,), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False), (True, False)))

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 937, in build_triton_ir
    generator.visit(fn.parse())
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 855, in visit
    return super().visit(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/ast.py", line 418, in visit
    return visitor(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 183, in visit_Module
    ast.NodeVisitor.generic_visit(self, node)
  File "/home/ec2-user/miniconda3/lib/python3.10/ast.py", line 426, in generic_visit
    self.visit(item)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 855, in visit
    return super().visit(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/ast.py", line 418, in visit
    return visitor(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 252, in visit_FunctionDef
    has_ret = self.visit_compound_statement(node.body)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 177, in visit_compound_statement
    self.last_ret_type = self.visit(stmt)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 855, in visit
    return super().visit(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/ast.py", line 418, in visit
    return visitor(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 678, in visit_For
    self.visit_compound_statement(node.body)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 177, in visit_compound_statement
    self.last_ret_type = self.visit(stmt)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 855, in visit
    return super().visit(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/ast.py", line 418, in visit
    return visitor(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 319, in visit_AugAssign
    self.visit(assign)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 855, in visit
    return super().visit(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/ast.py", line 418, in visit
    return visitor(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 301, in visit_Assign
    values = self.visit(node.value)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 855, in visit
    return super().visit(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/ast.py", line 418, in visit
    return visitor(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 339, in visit_BinOp
    rhs = self.visit(node.right)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 855, in visit
    return super().visit(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/ast.py", line 418, in visit
    return visitor(node)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/compiler.py", line 797, in visit_Call
    return fn(*args, _builder=self.builder, **kws)
  File "/home/ec2-user/miniconda3/lib/python3.10/site-packages/triton/impl/base.py", line 22, in wrapper
    return fn(*args, **kwargs)
TypeError: dot() got an unexpected keyword argument 'trans_b'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/ec2-user/llm-foundry/scripts/train/train.py", line 254, in <module>
    main(cfg)
    # off_h = tl.program_id(2)
    # off_hb = off_b * nheads + off_h
    # initialize offsets
    offs_m = start_m * BLOCK_M + tl.arange(0, BLOCK_M)
    offs_n = tl.arange(0, BLOCK_N)
    offs_d = tl.arange(0, BLOCK_HEADDIM)
    # Initialize pointers to Q, K, V
    # Adding parenthesis around indexing might use int32 math instead of int64 math?
    # https://github.com/openai/triton/issues/741
    # I'm seeing a tiny bit of difference (5-7us)
    q_ptrs = Q + off_b * stride_qb + off_h * stride_qh + (offs_m[:, None] * stride_qm + offs_d[None, :])
    k_ptrs = K + off_b * stride_kb + off_h * stride_kh + (offs_n[:, None] * stride_kn + offs_d[None, :])
    v_ptrs = V + off_b * stride_vb + off_h * stride_vh + (offs_n[:, None] * stride_vn + offs_d[None, :])
    if BIAS_TYPE == 'vector':
        b_ptrs = Bias + off_b * stride_bb + off_h * stride_bh + offs_n
    elif BIAS_TYPE == 'matrix':
        b_ptrs = Bias + off_b * stride_bb + off_h * stride_bh + (offs_m[:, None] * stride_bm + offs_n[None, :])
    # initialize pointer to m and l
    t_ptrs = TMP + off_hb * seqlen_q_rounded + offs_m
    lse_i = tl.zeros([BLOCK_M], dtype=tl.float32) - float("inf")
    m_i = tl.zeros([BLOCK_M], dtype=tl.float32) - float("inf")
    acc_o = tl.zeros([BLOCK_M, BLOCK_HEADDIM], dtype=tl.float32)
    # load q: it will stay in SRAM throughout
    # [2022-10-30] TD: Triton bug - in the case of EVEN_M=True and EVEN_N=False, if we just call
    # tl.load(q_ptrs), we get the wrong output!
    if EVEN_M & EVEN_N:
        if EVEN_HEADDIM:
            q = tl.load(q_ptrs)
        else:
            q = tl.load(q_ptrs, mask=offs_d[None, :] < headdim, other=0.0)
    else:
        if EVEN_HEADDIM:
            q = tl.load(q_ptrs, mask=offs_m[:, None] < seqlen_q, other=0.0)
        else:
            q = tl.load(q_ptrs, mask=(offs_m[:, None] < seqlen_q) & (offs_d[None, :] < headdim),
                        other=0.0)
    # loop over k, v and update accumulator
    end_n = seqlen_k if not IS_CAUSAL else tl.minimum((start_m + 1) * BLOCK_M, seqlen_k)
    for start_n in range(0, end_n, BLOCK_N):
        start_n = tl.multiple_of(start_n, BLOCK_N)
        # -- compute qk ----
        if EVEN_N & EVEN_M:  # If we just do "if EVEN_N", there seems to be some race condition
            if EVEN_HEADDIM:
                k = tl.load(k_ptrs + start_n * stride_kn)
            else:
                k = tl.load(k_ptrs + start_n * stride_kn, mask=offs_d[None, :] < headdim, other=0.0)
        else:
            if EVEN_HEADDIM:
                k = tl.load(k_ptrs + start_n * stride_kn, mask=(start_n + offs_n)[:, None] < seqlen_k,
                            other=0.0)
            else:
                k = tl.load(k_ptrs + start_n * stride_kn,
                            mask=((start_n + offs_n)[:, None] < seqlen_k) & (offs_d[None, :] < headdim),
                            other=0.0)
        qk = tl.zeros([BLOCK_M, BLOCK_N], dtype=tl.float32)
        qk += tl.dot(q, k, trans_b=True)
                        ^
ERROR:composer.cli.launcher:Rank 2 crashed with exit code 1.
Waiting up to 30 seconds for all training processes to terminate. Press Ctrl-C to exit immediately.
Global rank 0 (PID 45705) exited with code 1
Global rank 2 (PID 45707) exited with code 1
----------Begin global rank 2 STDOUT----------
Initializing model...
cfg.n_params=6.66e+09
Building train loader...
Re-formatting dataset with "HuggingFaceH4/databricks_dolly_15k" preprocessing function.
Building eval loader...
Building trainer...
Logging config...
max_seq_len: 2048
global_seed: 17
run_name: llm
model:
  name: mpt_causal_lm
  init_device: meta
  d_model: 4096
  n_heads: 32
  n_layers: 32
  expansion_ratio: 4
  max_seq_len: ${max_seq_len}
  vocab_size: 50368
  attn_config:
    attn_impl: triton
tokenizer:
  name: EleutherAI/gpt-neox-20b
  kwargs:
    model_max_length: ${max_seq_len}
train_loader:
  name: finetuning
  dataset:
    hf_name: HuggingFaceH4/databricks_dolly_15k
    split: train
    max_seq_len: ${max_seq_len}
    allow_pad_trimming: false
    decoder_only_format: true
    shuffle: true
  drop_last: true
  num_workers: 8
  pin_memory: false
  prefetch_factor: 2
  persistent_workers: true
  timeout: 0
scheduler:
  name: linear_decay_with_warmup
  t_warmup: 0ba
  alpha_f: 0
optimizer:
  name: decoupled_adamw
  lr: 1.0e-05
  betas:
  - 0.9
  - 0.999
  eps: 1.0e-08
  weight_decay: 0
algorithms:
  gradient_clipping:
    clipping_type: norm
    clipping_threshold: 1.0
max_duration: 1ep
eval_interval: 1
global_train_batch_size: 64
seed: ${global_seed}
device_eval_batch_size: 8
device_train_microbatch_size: 8
precision: amp_bf16
fsdp_config:
  sharding_strategy: FULL_SHARD
  mixed_precision: PURE
  activation_checkpointing: true
  activation_checkpointing_reentrant: false
    offs_m = start_m * BLOCK_M + tl.arange(0, BLOCK_M)                                                                                [0/1864]
    offs_n = tl.arange(0, BLOCK_N)
    offs_d = tl.arange(0, BLOCK_HEADDIM)
    # Initialize pointers to Q, K, V
    # Adding parenthesis around indexing might use int32 math instead of int64 math?
    # https://github.com/openai/triton/issues/741
    # I'm seeing a tiny bit of difference (5-7us)
    q_ptrs = Q + off_b * stride_qb + off_h * stride_qh + (offs_m[:, None] * stride_qm + offs_d[None, :])
    k_ptrs = K + off_b * stride_kb + off_h * stride_kh + (offs_n[:, None] * stride_kn + offs_d[None, :])
    v_ptrs = V + off_b * stride_vb + off_h * stride_vh + (offs_n[:, None] * stride_vn + offs_d[None, :])
    if BIAS_TYPE == 'vector':
        b_ptrs = Bias + off_b * stride_bb + off_h * stride_bh + offs_n
    elif BIAS_TYPE == 'matrix':
        b_ptrs = Bias + off_b * stride_bb + off_h * stride_bh + (offs_m[:, None] * stride_bm + offs_n[None, :])
    # initialize pointer to m and l
    t_ptrs = TMP + off_hb * seqlen_q_rounded + offs_m
    lse_i = tl.zeros([BLOCK_M], dtype=tl.float32) - float("inf")
    m_i = tl.zeros([BLOCK_M], dtype=tl.float32) - float("inf")
    acc_o = tl.zeros([BLOCK_M, BLOCK_HEADDIM], dtype=tl.float32)
    # load q: it will stay in SRAM throughout
    # [2022-10-30] TD: Triton bug - in the case of EVEN_M=True and EVEN_N=False, if we just call
    # tl.load(q_ptrs), we get the wrong output!
    if EVEN_M & EVEN_N:
        if EVEN_HEADDIM:
            q = tl.load(q_ptrs)
        else:
            q = tl.load(q_ptrs, mask=offs_d[None, :] < headdim, other=0.0)
    else:
        if EVEN_HEADDIM:
            q = tl.load(q_ptrs, mask=offs_m[:, None] < seqlen_q, other=0.0)
        else:
            q = tl.load(q_ptrs, mask=(offs_m[:, None] < seqlen_q) & (offs_d[None, :] < headdim),
                        other=0.0)
    # loop over k, v and update accumulator
    end_n = seqlen_k if not IS_CAUSAL else tl.minimum((start_m + 1) * BLOCK_M, seqlen_k)
    for start_n in range(0, end_n, BLOCK_N):
        start_n = tl.multiple_of(start_n, BLOCK_N)
        # -- compute qk ----
        if EVEN_N & EVEN_M:  # If we just do "if EVEN_N", there seems to be some race condition
            if EVEN_HEADDIM:
                k = tl.load(k_ptrs + start_n * stride_kn)
            else:
                k = tl.load(k_ptrs + start_n * stride_kn, mask=offs_d[None, :] < headdim, other=0.0)
        else:
            if EVEN_HEADDIM:
                k = tl.load(k_ptrs + start_n * stride_kn, mask=(start_n + offs_n)[:, None] < seqlen_k,
                            other=0.0)
            else:
                k = tl.load(k_ptrs + start_n * stride_kn,
                            mask=((start_n + offs_n)[:, None] < seqlen_k) & (offs_d[None, :] < headdim),
                            other=0.0)
        qk = tl.zeros([BLOCK_M, BLOCK_N], dtype=tl.float32)
        qk += tl.dot(q, k, trans_b=True)
                        ^

----------End global rank 7 STDERR----------

Hi @arpitg1991 , this repo is currently only tested with torch 1.13.1 (deps here) and it will be a few weeks before we fully transition to torch2 as there are many moving pieces (Composer, Streaming, FSDP).
I would highly recommend using our public Docker image listed in the README (mosaicml/pytorch:1.13.1_cu117-python3.10-ubuntu20.04), this is the image the MosaicML NLP team uses to do all of our work, and it comes with flash-attn and triton preinstalled.

ok, i ran into disk space issues when i ran with docker, let me try to fix that

Hi @arpitg1991 , I am closing this issue for cleanup but please add a comment / file a new issue if you need additional help. Cheers!


How many maximum email addresses can be passed in Bcc using array

Q
A

Bug report?
no

Feature request?
no

RFC?
no

How used?
Symfony

Swiftmailer version
5.4.0

PHP version
7.1

Observed behaviour

I have approximately 4500 subscribers. I need to send newsletter to them. My hosting providers allows only 500 emails per hour. I am trying to do like this.
*$mailer = new Swift_Mailer($transport);
$msg = (new Swift_Message('TEST MESSAGE'))
<EMAIL_ADDRESS>=> 'XYZ'])
<EMAIL_ADDRESS>->setBcc($loe)
->setBody($message,'text/html');
$fr = $mailer->send($msg);
Where $loe is an Array of 500 emails. I will put this file in cron job and execute it every hour. So email will be sent to 500 subscribers. When I pass 500 emails in setBcc() function. It does not work. Please guide.
Expected behaviour

Example

How do you observe that it does not work? Is there an exception/error logged?

Swift_TransportException: Expected response code 250 but got code "421", too many messages.

That is likely your hosting provider SMTP server telling you you are trying to send too many emails at once. Consider that if $loe size is 500, you are effectively sending 501 emails (to + 500 bcc).
I'd suggest you try sending a lot less emails per hour/batch, or you switch SMTP provider (use something like AWS SES for instance).


Dropdown component menu default width + rounded edges

Describe the bug
On a presentational level the dropdown menu example widths are less wide than expected. Additionally, the main Flowbite Library updated the default rounded values for the menu from rounded to rounded-lg in order to improve consistency as a design system.
Here are the new examples from Flowbite: https://flowbite.com/docs/components/dropdowns/
To Reproduce
Steps to reproduce the behavior:

Go to Flowbite React Dropdown
Click on button
Dropdown width not correlating with the button aesthetically + rounded edges are rounded not rounded-lg

Expected behavior
Pass custom width classes for the dropdown menus that look out in the order. I don't think we need to do anything on a component definition level because as I can see the width of the dropdown is now based on the width of the content inside which is correct. But when we showcase the dropdowns they should look good in order to convince early adopters to use this library.
Also, the default value of the dropdown menu should be rounded-lg in order to keep consistency across the design system and make it consistent relative to the roundedness of the button.
Screenshots

Project information:

Tailwind: 3.2.4
Flowbite: 1.6.3
Flowbite React: 0.3.8
Type: Remix

Additional context
None.

The #578 fixes the rounded-lg, but this one still with the width issue.

Has this been fixed?

It seems that this one was fixed already.


refactor predict_next_token to allow clearing cuda memory between batches

This PR refactors predict_next_token so that the batched_logits aren't saved between each batch. batched_logits contains references to tensors on the GPU, which means that memory can't be released between each batch, eventually causing CUDA out of memory errors.
This PR instead runs through the full processing down to the PredictedToken list in each batch loop, so that batched_logits can be garbage collected after each batch.
I added test coverage of predict_next_token on GPT2, snapshotting probabilities and behavior both before and after the change to ensure no change of behavior is introduced by this PR.

I may have been too optimistic about this - I find that I still get occasional OOM errors with this PR, although they're much less frequent. Given that, I'm not sure if it makes sense to merge this or not as it doesn't seem to 100% solve the issue.


Better package dependency resolution

Describe the feature
Currently, when there are conflicting package versions it's hard to debug / manually fix.
Take this packages.yml for example:
packages:
  - package: fishtown-analytics/segment
    version: 0.5.1
  - package: fishtown-analytics/dbt_utils
    version: 0.6.2
  - package: fivetran/fivetran_log
    version: 0.2.0
  - package: fivetran/linkedin_source
    version: 0.1.0
  - package: fivetran/salesforce
    version: 0.1.0

This creates the error:
Version error for package fishtown-analytics/dbt_utils: Could not find a satisfactory version from options: ['>=0.1.22', '>=0.6.0', '<0.7.0', '>=0.6.1', '<0.7.0', '=0.3.0']"

A more useful error would be something like:
Version error for package fishtown-analytics/dbt_utils: could not find a satisfactory version
>=0.4.0,<0.7.0 required by fishtown-analytics/segment
0.6.2          required by dbt-learn-demo
>=0.6.0,<0.7.0 required by fivetran/fivetran_log
0.3.0          required by fivetran/salesforce

☝  It's much easier to now see that the problem here is the fivetran/salesforce dependency.
Even more useful would be the ability to override the dependency, something like this perhaps?
packages:
  - package: fishtown-analytics/dbt_utils
    version: 0.6.2
  - package: fivetran/salesforce
    version: 0.1.0
    override_dependency:
       - package_name: dbt_utils
         package: fishtown-analytics/dbt_utils
         version: 0.6.2

or this:
packages:
  - package: fishtown-analytics/dbt_utils
    version: 0.6.2
  - package: fivetran/salesforce
    version: 0.1.0
    override_dependency:
       - package_name: dbt_utils

(And then dbt would remove the range for this package from the version resolution, and end up using 0.6.2 since it's specified above)
Describe alternatives you've considered
@jtcohen6 — not sure if you've given any thought to this yourself?
Additional context
--
Who will this benefit?
Users of multiple packages
But also package maintainers, as it:

gives you more leeway when making dependency upgrades
also lets you test out changes on a branch in a dependent package by overriding the installation method with the git syntax

I'm fully supportive of the more descriptive error message.
I'm less sure about enabling users to override or ignore dependencies' dependencies. I agree that it would give users better workarounds in the short term, but it also opens a lot of possibilities for unexpected weirdness. The real remedy in this case is for the package to use a more flexible version boundaries (https://github.com/fivetran/dbt_salesforce/issues/9).
I'd be more excited about enabling dbt to perform package version resolution for local- and git-installed packages as well as hub-installed ones. This would allow users to do things like:

fork a package, change packages.yml, install from the fork via git
git clone the package, update it locally, install via local (analogous to what's required for pip conflicts, from a cursory search)

Would be awesome to do this, as currently trying out new branch of dbt (0.19.0-b1) gives this error, and would be super awesome to override for this sort of thing:
Running with dbt=0.19.0-b1
Encountered an error:
Runtime Error
  Failed to read package: Runtime Error
    This version of dbt is not supported with the 'dbt_utils' package.
      Installed version of dbt: =0.19.0-b1
      Required version of dbt for 'dbt_utils': ['>=0.18.0', '<0.19.0']
    Check the requirements for the 'dbt_utils' package, or run dbt again with --no-version-check

  Error encountered in /home/josh/dev/xxx/dbt_modules/dbt_utils/dbt_project.yml

Error encountered in /home/josh/dev/xxx/dbt_modules/dbt_utils

Hey @joshuataylor, happy to see you're testing out the v0.19 beta! You can use the --no-version-check flag to run or test without raising an version compatibility error.

Hi!
I've been struggling for a couple of hours trying to manually resolve a dependencies conflict, and would find this enhancement tremendously helpful - better than combing through all my packages' packages.yml files to try and figure out which one is causing this :
Version error for package dbt-labs/dbt_utils: Could not find a satisfactory version from options: ['>=0.8.0', '<=1.0.0', '>=0.8.6', '<2.0.0', '>=0.8.0', '<2.0.0', '>=0.9.0', '<2.0.0', '>=0.9.0', '<1.0.0', '=1.0.0-b2']

For the record, it looks like this issue is now being discussed here


Advice should include more explanations about dependency changes.

In 0.24.0 and below, the plugin is working well, but there is a gap between developers workflow and the plugin advises:

devs are working in one module, they will do changes one module at a time.
the plugin has a more holistic view of the changes.

This difference makes it so that changes in a single module are breaking because they suppose that other changes are applied in other modules. Devs cannot fix a module in isolation, test to see if this module compiles and move on. Applying the advises will create situations where compilation or annotation processing fails and the errors and stack traces they provide are very hard to make sense of.
Here is an example:
A impl -> C impl
A impl -> B impl -> C.

The plugin can say that C is not used by A and should be removed, it takes into account that B should be modified to : B api -> C.
But devs, just by looking at the advises for A will have no understanding of the changes required in B before they proceed to cleaning A.
If they apply the advises to A only and try to compile it, they can have dramatic errors that are completely unclear, and the issues are very hard to solve with the provided information.
Very often the problems they will face will be inside the class loading mechanisms of kapt/apt/javac/kotlinc and these tools don't provide fine grained info in these cases.
Ideally the plugin should be able to explain something like
dependency to C should be removed in A as it should be provided by B which requires B should have a dependency on C in the api configuration.

A workaround would be to explain devs that they should clean up modules in the topological order of modules which is not an easy notion to get, it would require assistance to do so as well.

@stephanenicolas I have made an improvement related to this a few weeks ago. The Advice model now includes used-transitive dependencies and parent dependencies (that supply this dependency transitively). Careful inspection of the advice json will tell an end-user whether a particular advice is "safe" to follow in isolation. I'm going to close this issue for now, but feel free to re-open if you think more should be done here.


refactor(es/transforms/compat): visit_mut for class constructor

for #2370

@kwonoj Thanks!
I update most of them, excpet case of direct assignment vs. map_with_mut


OpenSans font lacks licensing information

In /src/assets/fonts, the .ttf files for OpenSans have been included. However, no licensing information has been included in the font metadata for OpenSans.ttf or OpenSans-Italic.ttf, while incomplete information has been included for OpenSans-Bold.ttf.
To address this problem, consider downloading the OpenSans font files directly from Google's website:
https://fonts.google.com/specimen/Open+Sans
The "static" versions of the font (in the zip that you get when you click "download family") are both newer versions of OpenSans and include proper licensing information in the font metadata.

This has been addressed in 1.1.1. Thanks for bringing the Open Sans issue forward @123chess456! 🥇


Small tweaks

Fixed mcinstance downloads
WIP Loading Screen
WIP Custom Menu

i am now contributor on main repo, this is no longer useful


bpf: Force preallocation for SNAT maps of LRU type

As reported by a user and tgraf, the bpf/hashtab.c in the kernel has the following precondition when creating maps:
if (lru && !prealloc)
    return -ENOTSUPP;

Previously, the SNAT related maps set CONDITIONAL_PREALLOC regardless of the maps type. Thus, when HAVE_LRU_MAP_TYPE was detected and --preallocate-bpf-maps=false was passed to cilium-agent, the kernel was failing to load the map with the following error:
Map object 'cilium_snat_v4_external' rejected: Unknown error 524 (524)!

Fixes: 0e785f9675 ("bpf: initial bpf-based masquerading support")
Fix #7899

Please note that no changes are required for the Go part, as we already require the preallocation for the LRU maps: https://github.com/cilium/cilium/blob/pr/brb/fix-snat-map-prealloc-lru/pkg/bpf/map.go#L131.

This change is

test-me-please

The CI build failed due to the know issue - timeout during the VM image fetch. I'll re-run the tests once the CI infra issue has been resolved.

test-me-please

VM download timed out

test-me-please

Hit known flakes, merging


The Inline Code Black 's bg color

inline code block with custom color doesn't change it's bg color although the variable '--theme--code_inline' is defined.

I modify the theme.css, and it works.
.notion-page-content [style*='color:#EB5757']:not(.notion-text-mention-token) {
  color: var(--theme--code_inline-text) !important;
}

.notion-page-content [style*='background:rgba(135,131,120,0.15)']:not(.notion-text-mention-token) {
  background: var(--theme--code_inline) !important;
}

please update this to follow the contributing guidelines.

Expected behavior: When I define my own code-inline background color using the theme plugin, all inline code should be modified.
Actual behavior: If this inline code is in its own color, then the modification fails.
Reason: The theme.css file positions the inline code by indexing the default inline code color, so that if the inline code is not the default color, it will not be selected by the selector.


Parent's layout properties not taken into account

Hi all, first of all great work!
Now I was trying out the library and noticed that the following:
...
  render() {
    return (
      <View style={componentStyles.view}>
        <Animation
          style={componentStyles.animation}
          source={require('../animations/dawg.json')}
          loop={true}
        />
      </View>
    );
  }
}

const componentStyles = {
  view: {
    flex: 1,
    flexDirection: 'column',
    alignItems: 'center',
    justifyContent: 'center',
    backgroundColor: 'green'
  },
  animation: {
    width: 300,
    height: 200,
  }
}

produces the following:

having same issue here.

+1

found a solution:  to wrap animation in View with the same width and height and align it, not Animation

+1
@Vasiliev90  nice workaround!
Btw, I suggest an [iOS] label here, this issue does not effect Android.

same issue here! is related to mine! #135

@mesbahsabur same issue is happening on android, son both labels please

we can use a transform styling, but seems to be pixelated :(

@Vasiliev90 This indeed works! I think this should be added to the README. Or even better make it so that Animation always renders View

Still getting this problem but the workaround is working for now.

看不懂啊

I'm still having this problem even when i wrap the animation in a view with the same height and width, here's what i have
` <View
style={{
alignItems: 'center',
width: 60,
height: 60,
position: 'absolute'
}}
>
<Animation
style={{
          width: 60,
          height: 60
        }}
        source={require('./img/menuButton1.json')}
      />
    </View>`

Anyone have any suggestions, thanks.

@gmac13 you probably need to remove the alignItems and position properties, create another containing View for that.
try this:
<View style={{ alignItems: 'center', width: 60, height: 60, position: 'absolute' }} >
  <View style={{ width: 60, height: 60 }}>
    <Animation style={{ width: 60, height: 60 }} source={require('./img/menuButton1.json')} />
  </View>
</View>

I agree with @mesbahsabur, I found this issue only happening on iOS

@emilioicai I have a fix for this, here: https://github.com/3sidedcube/lottie-react-native/commit/849d1f9a89824a0f654f68fb645bff4e406c4a29. Unfortunately it seems your master has come on a long way since then and we have merge conflicts which we need to fix before I can create a PR. I'm also unsure of any other knock-on effects this could have!

@simonmitchell it would be great if you could issue a PR, I can support you with the conflicts fixes in case you find it to complex.


TLS 1.2

On February 19, 2020, Slack will end support for TLS versions 1.0 and 1.1. We've identified that one or more of your Slack apps are impacted by this change. If you don't upgrade your app to TLS 1.2, requests sent to any Slack endpoint will fail.
You must update your Slack app before February 21, 2020. Please verify which of your Slack apps are affected: https://api.slack.com/unsafe-tls-deprecation

App updated to net framework 4.7+
Need check result later


Rails 4.2 compatibility

This fixes #82

Thank you for your contribution. I think we should be at least a bit pessimistic, since we don't know if Rails 4.3 could break CASino. Something like '>= 4.1.0', '< 4.3.0' for example?

Thanks for your review! :smile: Yes, we can do this, but on the other hand we can add this if we know about some compatibility issues.
In the blogpost about the Rails 4.2 release the devs wrote:
"[..] Rails 4.2 also marks the last big release in the 4.x series. With this release out, we're now working towards the big Rails 5.0! This means rails/master is now targeting 5.0. [..]".
So I think we shouldn't have problems with this. But it's your choice :sweat_smile:

Closed by #84


feat: Print FUSEML_SERVER_URL instructions during installation

The value is already printed with current code, as part of Deploying Core step...

The value is already printed with current code, as part of Deploying Core step...

It is, but this PR makes it clear what that value should be used for. Here's an output example:
...
🚢 Deploying Core.........
✔  FuseML core component deployed (http://fuseml-core.<IP_ADDRESS>.omg.howdoi.website).

🚢 Downloading command line client...
🚢 FuseML command line client saved as /home/user/fuseml/fuseml.
Copy it to the location within your PATH (e.g. /usr/local/bin).

🚢
To use the FuseML CLI, you must point it to the FuseML server URL, e.g.:

    export FUSEML_SERVER_URL=http://fuseml-core.<IP_ADDRESS>.omg.howdoi.website

✔  FuseML installed.
System domain: <IP_ADDRESS>.omg.howdoi.website

probably needs to be rebased


module not found error

after entering
Path_to_HuggingFace:XpucT/Deliberate
I'm  encountering this error
ModuleNotFoundError                       Traceback (most recent call last)
 in
3 from IPython.utils import capture
4 from IPython.display import clear_output
----> 5 import wget
6
7 #@markdown - Skip this cell if you are loading a previous session that contains a trained model.
ModuleNotFoundError: No module named 'wget'

NOTE: If your import is failing due to a missing package, you can
manually install dependencies using either !pip or !apt.
To view examples of installing some common dependencies, click the
"Open Examples" button below.

Same here.

Me too but yesterday it worked.

Solution: put !pip install wget before import wget.

Thank You! Still, later in the training cell an avalanche of errors happen so I guess we wait for the updated colab.

Oh yes I see, hope they will fix it ASAP.

fixed


sm_dup: not working properly with strings

Because of currently is implemented as a plain copy, it does not copy dynamic strings properly.

Fixed with 90d4e9bfcd5bed420803cda1be8ecc39bc91153f


Couldnot find stream object.

It seems the current version of screenshare module is entirely differnt from earlier version.
I used to attach captured stream to the quickConnect (qConnect.addStream(stream)) object using the below code.
shareScreen = function(){
screenshare.window(function(err, constraints) {
if (err) {
return console.error('Could not capture window: ', err);
}
console.log('attempting capture with constraints: ', constraints);
localMedia = media({ constraints: constraints })
.on('error', function(err) {
console.error('Could not capture: ', err);
});
localMedia.once('capture', function(stream) {
streamObj = stream;
qConnect.addStream(stream);
});
localMedia.render(local);
});
}
But the current api is not having the "once" function in it, and no similar method is there it seems. I want to send my captured stream to my friend through a quickconnect datachannel to have a realtime desktop sharing app. How do i do this with current api?
There is bundle.js file, how do i get that file when i am running the screen share application with quickconnect server.
i could not understand the meening of sharewindow.js:bundle.js exactly in (beefy sharewindow.js:bundle.js command), who is generating bundle.js and where is it residing.
How do i get bundle.js if iam running quickconnect server instead of beefy?

Yes - there have been quite a few changes since you last worked with the code it seems.  I've added some more up-to-date instructions on using the screenshare module and how to prep things for deployment in the demo-screenshare README

@santhoshreddyk Just checking in to see how you went upgrading to the latest version.  Also the new rtc-screen package might be of interest to you also.  Same stuff under the hood, just a higher level API which actually does to the capture for you instead of just returning constraints...


Add the cffconvert github action

Should use this github action to validate the CFF file:
https://github.com/citation-file-format/cffconvert-github-action

Fixed by #687


BTR-84 balance partitions among potentially idle executors

All looks good. The only thing is that I thought that optimize_allocations should be true by default. But we can do it later, after more testing.


Show upload time remaining / upload speed

Hello, why do you not add time remain and upload speed?

I've considered this initially but decided against it as most uploads I think are too short lived to calculate an average duration for. Of course it would be nice to add this, but I'd rather add it in a way that would not add too much additional weight to the core package.
So we could route the data that renders the textual progress through a configurable function I guess? At that point I guess you could do with it what you want.

I am using this library for large files so this solution would be perfect.

Interested in that!

waiting for that.. it will be very useful

I would suggest closing it as Won't Do, I did it on my own using a button and also an Alert component from bootsrtap to show an indicator, but we can build our own based on the props that are being received in the callback function

@albertjimenez That's what I was intending to build but life got in the way, I'm slowly working on v5 of FilePond where this should become easier.


Roll Flutter Engine from 70b1c7341255 to 1b96c7739833 (7 revisions)

https://github.com/flutter/engine/compare/70b1c7341255...1b96c7739833
2023-11-21<EMAIL_ADDRESS>Roll Skia from 516357c42907 to c244996e79d6 (1 revision) (flutter/engine#48266)
2023-11-21<EMAIL_ADDRESS>Roll Dart SDK from 99d9cf9bd05a to 5e7b22caba8a (1 revision) (flutter/engine#48264)
2023-11-21<EMAIL_ADDRESS>Roll Dart SDK from 64cbfa6c51e6 to 99d9cf9bd05a (1 revision) (flutter/engine#48261)
2023-11-21<EMAIL_ADDRESS>Roll Skia from 88a9e6328f93 to 516357c42907 (1 revision) (flutter/engine#48260)
2023-11-21<EMAIL_ADDRESS>Roll Skia from a26e5a5771c8 to 88a9e6328f93 (1 revision) (flutter/engine#48259)
2023-11-21<EMAIL_ADDRESS>Roll Skia from f8daeeb7f092 to a26e5a5771c8 (2 revisions) (flutter/engine#48258)
2023-11-21<EMAIL_ADDRESS>Roll Dart SDK from f1fd14505782 to 64cbfa6c51e6 (1 revision) (flutter/engine#48257)
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AutoRoller is stopped; closing the active roll.


Miscellaneous fixes for trivial issues found by adhoc testing

Add intrisic attributes to Object.GetType/Type.GetTypeFromHandle (Object.GetType is commented out under TODO)
Implement temporary marshalling for bool since it is used by every other Win32 API
Implement HandleException method on JIT-EE interface

LGTM


e2e-bqargumentsetter Test Scenarios

@sawantpritam Please Review BQArgument Test Scenarios

Please work on all unresolved comments.... check hidden conversations...there are few unresolved comments.
ALSO ALWAYS MAKE SURE TO EXECUTE TESTS AND VERIFY ALL TESTS ARE PASSING BEFORE PUSING CHANGES. Tests Failing please check.

Your fork is not up to date, take latest and squash the commits.