Use libxc's parsing routines instead of hardcoded lists

Hi,
I just had a look at https://github.com/sunqm/pyscf/blob/master/dft/libxc.py and noticed that you're using hardcoded functional lists.
However, libxc has had the functionality to parse functional keywords and id numbers for a long time:
int   XC(functional_get_number)(const char *name);
char *XC(functional_get_name)(int number);
which implement the necessary functionality. I would recommend removing XC_CODES, XC_KEYS, LDA_IDS, GGA_IDS, etc from dft/libxc.py, and replacing them with the two above functionals.
The functions is_lda, is_gga and so on can be reimplemented by checking the functional family with
int   XC(family_from_id)(int id, int *family, int *number);
or by checking the func.info->family entry of
xc_func_type func;
that has been initialized to the used functional. The character of the functional (x, c, or xc) can be similarly checked from func.info->kind.
It doesn't really make sense to replicate this information, since that entails more maintenance. The stuff is already maintained within libxc, where it is always up to date.
Also, I don't see how you handle range separated hybrids. Are they not supported in pyscf?

The functional list XC_CODES is hardcoded because it is designed to be hardcoded.   When you run in python shell, it's straightforward to check what has been supported by typing

from pyscf import dft
dft.lib.X_C    # dft.libxc.XC_CODES
dft.xcf.X                 # dft.xcfun.XC_CODES

I don't see any other way more simple and consistent to do this in python shell.
What  is_lda, is_gga functions did is more than a single check for one functional ID, it is a part of the parser function parse_xc,  which allows you customizing functionals like ".218HF + .073LDA + .709MPW91, .871LYP + .129*VWN".  I don't know whether libxc has this feature in recent version.  But I'm sure it's not when I implemented the libxc.py interface.  They have to be there until I found better solution.
I agree LDA_IDS, GGA_IDS is duplication of XC(family_from_id) function.  I can reimplement it in the future when I optimize the DFT code.
Range separated hybrids are not coded in the dft module.  The required integrals should be all available.  Let me know if you need this functionality.  I can show you where to access the integrals or I can implement it in next release.
Qiming

So, this is already half-solved by #120, the only remaining issue is the handling of the functional list, i.e. the same issue as in Psi4 (psi4/psi4#793)
This could also be constructed by polling libxc which functionals are available. Maybe the easiest thing would be to add in a libxc function that dumps out a list of valid functional ids and keywords.

Range separated hybrids are not coded in the dft module.

If range separated functionals don't work properly, an error or warning should be raised when they are called.
Also, I'm not sure if this is just unclear to me or generally unclear, but when using a XC functional, does it need to be listed twice and comma separated? Listing it twice gives a different energy.
x_and_c = 'XC_LDA_XC_ZLP, XC_LDA_XC_ZLP'
x_or_c = 'XC_LDA_XC_ZLP'
mol = pyscf.gto.M(atom='H 0 0 0; H 0 0 1.2', basis='ccpvdz', symmetry=True)
m_rks = dft.rks.RKS(mol)

m_rks.xc = x_and_c
m_rks.kernel()

m_rks.xc = x_or_c
m_rks.kernel()

converged SCF energy = -1.74990822400141
converged SCF energy = -1.10688299662763

In the 1.4.* release,  there is no code to check whether an XC functional is range-separated functional.  So there is no way to assert the input.  Range separated functionals and relevant code are implemented in dev branch.  For example
https://github.com/sunqm/pyscf/blob/dev/examples/dft/33-nlc_functionals.py#L16
Depending on the type of functional, the input x_and_c  x_or_c are both supported.
When you input 'x,c', means x_and_c, where the first part (before comma) is X functional and the second part is C functional,  like  'LDA,VWN',  'LDA,P86', '0.5HF+0.5LDA,LYP'
When you input 'xc' without comma, it will treat the XC functional as X functional only. But some of the XC functional include both X and C like 'B3LYP'.  So you just need to input xc='b3lyp'.
Note the xc input parser does not prevent you input meaningless XC functional. For example, it allows you to specify xc='b3lyp,0.5*p86' which means b3lyp plus a few p86 C functional. If you input xc='b3lyp,b3lyp', it will compute the b3lyp twice.

This issue could probably be solved now much easier than before, since thanks to the Psi4 developers, libxc now has a working Python interface as shown in
https://gitlab.com/libxc/libxc/tree/master/pylibxc

The Python interface was included in libxc 4.1.0, but you can just update to the latest 4.3.4 release.

libxc 5 is out, including up to 4th derivatives for all functionals, meta-GGAs included.

Hi @susilehtola , has this been resolved?

Using PR #2377, the XC list are now dynamically generated via the libxc library.


Koofr backend

What is the purpose of this change?
Implements a backend for the Koofr cloud storage service.
Was the change discussed in an issue or in the forum before?
No
Checklist

[X] I have read the contribution guidelines.
[X] I have added tests for all changes in this PR if appropriate.
[X] I have added documentation for the changes if appropriate.

[X] I'm done, this Pull Request is ready for review :-)

I had a quick go with the backend and managed to successfully upload and download 1000 files :-)
It gave me these rather unfriendly looking errors which I'm not sure what they mean - a retry cleared them up.
2019/02/26 15:05:49 ERROR : sewewot7c/mefipuz7ka/dutamor1: Failed to copy: Invalid response status! Got 400, expected [200 201]; headers: map[Cache-Control:[no-cache, no-store, must-revalidate] Content-Length:[0] Date:[Tue, 26 Feb 2019 15:05:49 GMT] Expires:[0] Pragma:[no-cache] Set-Cookie:[PLAY_SESSION=; Expires=Mon, 25 Feb 2019 15:05:50 GMT; Path=/; HTTPOnly] X-Request-Id:[a2f2d2ed-0059-43fb-925a-421a9156f185] X-User-Id:[64ee1c28-c9ac-4f50-97d0-b24cfe05482f]], content:

The backend doesn't implement the pacer so doesn't do low-level retries.
It also uncovered a bug as the errors that httpclient return are not comparable as they don't contain a slice.  This needs this fix
diff --git a/fs/fserrors/error.go b/fs/fserrors/error.go
index a2ede7416..39fd9fb64 100644
--- a/fs/fserrors/error.go
+++ b/fs/fserrors/error.go
@@ -194,7 +194,7 @@ func Cause(cause error) (retriable bool, err error) {
                        // this case.
                        err = prev
                }
-               if err == prev {
+               if reflect.DeepEqual(err, prev) {
                        // Unpack any struct or *struct with a field
                        // of name Err which satisfies the error
                        // interface.  This includes *url.Error,
@@ -215,7 +215,7 @@ func Cause(cause error) (retriable bool, err error) {
                                }
                        }
                }
-               if err == prev {
+               if reflect.DeepEqual(err, prev) {
                        break
                }
        }

To fix.
I note that Koofr supports Webdav - does rclone work with the webdav interface? What advantage does using the API give? MD5 support seems like one of them.
I can't find docs for the API anywhere - can you link them?

wrt to the integration tests, I've ran
test_all -backends koofr
and it passes with flying colours; is there more to the integration tests? (but, more importantly, we pushed our local windows test build to our CEO who used to use rclone via our webdav interface, and I still have the job, so I suppose it's mostly working)
the advantage over the webdav interface is speed. the webdav interface is quite limited wrt to concurrency as it strictly adheres to the webdav locking spec.
the unfriendly looking errors: any idea which part of rclone do they come from? the Put or Copy methods?
API docs and some examples can be found at http://k00.fr/cug7u

wrt to the integration tests, I've ran
test_all -backends koofr
and it passes with flying colours; is there more to the integration tests?

No that is it - and good news :-)

(but, more importantly, we pushed our local windows test build to our CEO who used to use rclone via our webdav interface, and I still have the job, so I suppose it's mostly working)

Excellent :-)

the advantage over the webdav interface is speed. the webdav interface is quite limited wrt to concurrency as it strictly adheres to the webdav locking spec.

It appears to support MD5 hashes also which isn't a standard part of the webdav spec IIRC.

the unfriendly looking errors: any idea which part of rclone do they come from? the Put or Copy methods?

That was from Put - I just tried to upload a directory of 1000 smallish files with the default concurrency.  Every 1 in 20 or so files gave that error, but uploaded fine on a retry.

API docs and some examples can be found at http://k00.fr/cug7u

Cool - thanks.  I note that koofr could support some more optional methods

PublicLink to provide a public link to a file or directory
About to provide used/free/quota space (which then makes df on rclone mount  work nicely)
Purge - maybe DELETE folder deletes a folder and its contents?  If so this would implement Purge

ok, the 400 errors are a legit response of our API on attempting to create a folder which already exists. it should have been a 409, but it's a pain to change the API with a ton of clients out there. so, I have fixed this in the our rclone backend.
fwiw, attempts to create existing dirs are due to concurrent Put()s with each one try to create the complete directory hierarchy which ends up in races between a fileinfo in one thread, reporting a nonexisting folder, then a mkdir in another thread, followed by yeat another mkdir in the first one, with this last one erroring out.
I'll also do the reverse type renaming, and see about the implementation of the 3 optional methods. Closing this PR, will submit another one tomorrow.

ok, the 400 errors are a legit response of our API on attempting to create a folder which already exists. it should have been a 409, but it's a pain to change the API with a ton of clients out there. so, I have fixed this in the our rclone backend.

That makes sense.

fwiw, attempts to create existing dirs are due to concurrent Put()s with each one try to create the complete directory hierarchy which ends up in races between a fileinfo in one thread, reporting a nonexisting folder, then a mkdir in another thread, followed by yeat another mkdir in the first one, with this last one erroring out.
I'll also do the reverse type renaming, and see about the implementation of the 3 optional methods. Closing this PR, will submit another one tomorrow.

Great :-)


make a weapon quick-switcher mechanism

[ ] triangle button to action
[ ] detect between single press and double-press
[ ] change states accordingly
[ ] load weapons in and out of the equip slots to the weapon mount
[ ] connect and disconnect fire signals

(copied from #38)
functionally to equip a weapon it needs to be
re-parented under player/MeshInstance/weapon_mount
signals need to be connected current_weapon.connect("fire", player, "_on_weapon_fire") and weapon.connect("magazine_count_changed", dui_root, "_on_magazine_count_changed")

not re-hooking up  "magazine_count_changed", magazines are not important right now.

done with #38


ERROR: Could not find solrconfig.xml on MacOS

When I enter as documents:
 solr-9.0.0 % bin/solr zk -upconfig -z localhost:9983 -n tapioca -d configsets/tapioca
I have:
ERROR: Could not find solrconfig.xml at /Users/lu/Documents/solr-9.0.0/configsets/tapioca/solrconfig.xml, /Users/lu/Documents/solr-9.0.0/configsets/tapioca/conf/solrconfig.xml or /Users/lu/Documents/solr-9.0.0/server/solr/configsets/configsets/tapioca/conf/solrconfig.xml

It looks like you are running this command from the directory where Solr is installed on your machine, so instead of configsets/tapioca you need the path to your clone of this repository (followed by /configsets/tapioca).

Antonin Delpeuch @.***>于2022年10月11日 周二06:10写道：

It looks like you are running this command from the directory where Solr
is installed on your machine, so instead of configsets/tapioca you need
the path to your clone of this repository (followed by /configsets/tapioca
).
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create jon stewart page

https://www.youtube.com/watch?v=WFhqPnieR3s

The great Jon Stewart/deep dish back and forth of 2013:
It all began when One World Trade Center was completed...  http://www.cc.com/video-clips/8o83j9/the-daily-show-with-jon-stewart-tower-record
Chicago then responded.  A lot.  http://www.cc.com/video-clips/zb44o8/the-daily-show-with-jon-stewart-strife-of-pie
There was a moment of zen - http://www.cc.com/video-clips/v9soal/the-daily-show-with-jon-stewart-moment-of-zen---chicago-vs--the-daily-show
The daily show then went about justifying New York pizza  (I'd totally forgotten the healthcare.gov timing there) - http://www.cc.com/video-clips/ga8340/the-daily-show-with-jon-stewart-strife-of-pie---new-york-pizza-is-magic
And finally, there was a truce, orchestrated by one of the Lou Malnati's family members  - http://www.cc.com/video-clips/g4hb45/the-daily-show-with-jon-stewart-strife-of-pie---a-pizza-truce


How do you use custom_hear_middleware for the ask method?

The documentation explains how custom_hear_middleware can be used the hear method and also how it can be swapped out for the entire conversation controller. However, how do I use it just for an ask method?
For example, to add in a NPL intent/entity extraction before I process the response from an ask?

@ninajlu this is not currently possible... but it should be! I will try to add this soon.

I actually realized this wasn't necessary for my purposes as I found a workaround. I just added the NLP intent/entity extraction into controller.middleware.receive.use and then I only look at the added message.intent and message.entity fields in the ask and ignore them during a normal controller.hear method where I default to the pattern matching.

Cool! But we should still make it work like the hears function. Thanks for the idea.


ERROR in TypeError: Cannot read property 'search' of undefined

Hi,
Could someone possibly help me out please? I am getting the following error and don't understand why:
ERROR in TypeError: Cannot read property 'search' of undefined
    at Object.eval (webpack:///(webpack)-dev-server/client?:31:28)
    at eval (webpack:///(webpack)-dev-server/client?:248:30)
    at Object../node_modules/webpack-dev-server/client/index.js?http://localhost:8081 (evalmachine.<anonymous>:276:1)
    at __webpack_require__ (evalmachine.<anonymous>:30:30)
    at eval (webpack:///multi_(webpack)-dev-server/client?:1:1)
    at Object.0 (evalmachine.<anonymous>:377:1)
    at __webpack_require__ (evalmachine.<anonymous>:30:30)
    at evalmachine.<anonymous>:79:18
    at evalmachine.<anonymous>:82:10
    at webpackUniversalModuleDefinition (evalmachine.<anonymous>:3:20)

The command I am using to start the server is webpack-dev-server --mode development
The versions are:
static-site-generator-webpack-plugin: ^3.4.1
webpack-cli: ^2.1.3
webpack: ^4.8.1,
webpack-dev-server: ^3.1.4
node: 8.11.1

My webpack looks like this:
/*global require, module*/
const path = require("path")
const ExtractTextPlugin = require("extract-text-webpack-plugin")
const StaticSiteGeneratorPlugin = require('static-site-generator-webpack-plugin')

module.exports = {
    entry: "./src/entry.js",
    output: {
        filename: 'index.js',
        path: path.resolve("dist"),
        libraryTarget: 'umd'
    },
    module: {
        rules: [
            {
                test: /\.scss$/,
                use: ExtractTextPlugin.extract({
                    fallback: "style-loader",
                    use: ["css-loader", "sass-loader"]
                })
            },
            {
                test: /\.css$/,
                use: [
                    { loader: "style-loader" },
                    { loader: "css-loader" }
                ]
            },
            {
                test: /\.js$/,
                exclude: /node_modules/,
                use: "babel-loader"
            }
        ]
    },

    plugins: [
        new ExtractTextPlugin("dist/styles/main.css"),
        new StaticSiteGeneratorPlugin({
            paths: [
                '/'
            ],
            globals: {
                window: {}
            }
        })
    ]
}

And finally the entry file looks like this:
module.exports = function render(locals) {
    return '<html>Hello World</html>'
}

I am grateful for any feedback regarding the issue I am having. This is the first time I am using this plugin.

Resolved here.  I removed webpack-cli and used the following versions:
"webpack": "2.3.3",
"webpack-dev-server": "1.16.4"

I am currently facing the same issue as described here.
Imho, downgrading webpack by two major versions is not an acceptable solution.
Did anyone figure this out already?

Hello, any solution to this?

Use this plugin only in production, not together with the webpack dev server.
Something like !isDev ? staticSiteGeneratorPlugin : htmlWebPackPlugin

This can be avoided, even with latest webpack-dev-server, by not using the 'inline' option, using 'hot' is still fine.
For example, in package.json:
"devDependencies": {

 "webpack-cli": "^3.1.2",
 "webpack-dev-server": "^3.1.9",

And in webpack.conf.js:
 module.exports = {
  mode: 'development',
  devtool: 'eval',
  devServer: {
    inline: false,
    hot: true,
  },
  ...


Update gonzales-pe

Keen to get this updated as it fixes an issue that is blocking me from migrating to sass-lint from scss-lint

We're currently working with the author of gonzles-pe to fix the outstanding parse issues we have with the new release.

Since there are still issues. We can't update yet.

Soon enough! We've got a fair bit of work to do to update sass-lint for all the breaking changes made in 3.0.0 of gonzales-pe as you can see from the test results of your PR but we'll be going as quick as we can once as @bgriffith mentioned the outstanding issues are fixed.

@DanPurdy Any movement on this? any way I can help?

@dane-harnett nope, unfortunately gonzales still hasn't seen any more updates so we are a little stuck at the moment I'm afraid. If you want to contribute to the gonzales repo with fixes that's the only way to help out at the moment really..


Only month and year picker

Can this be modified to be used as only month and year picker? I would need this for getting the credit/debit card validity date.

It could be, but I doubt it is worth the effort.
The year selector is actually pretty well hidden, the day and month selector are combined in a calendar view. I think you'd need to change the entire design to create a decent month/year selector.
In any case, the code is open source, so you're free to give it a shot :-)

How to use this lib in eclipse ?

@Vipul12Thawre please create a new separate issue instead of poluting existing ones.
You can find more information on android library modules here and here

In a calendar pick i would selected all dates but i want to display only month and year in a Textview. plzz help me


tabindex issue

If there more than one element with tabindex >= 0,  when the sidebar is opened a second time, tabindex is set to "-1" to all alements except first one.
To reproduce the bug,

Browse to https://echeung.me/ng-sidebar/
Click on "Opened"
In Chrome inspector, change a <closesidebar=""> FOR <closesidebar="" tabindex="1">
Click on "This will close the sidebar too"
5 If click again on "Opened", the tabindex will be at "-1" instead of 1.

I actually tried setting the button to have a tabindex of 2 and the anchor with closesidebar to 1. They both seem fine after opening/closing multiple times. Did you do anything else too?

Hi,
see here https://www.youtube.com/watch?v=AQdweW2cXGI&feature=youtu.be

@vipdorian I don't think the video's permissions are set to public.

Ok, try this one  https://youtu.be/AQdweW2cXGI
2017-04-24 22:53 GMT-04:00 Eugene Cheung<EMAIL_ADDRESS>
@vipdorian https://github.com/vipdorian I don't think the video's
permissions are set to public.
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@vipdorian Thanks, the video works now. I can reproduce it on my end too, so I'll be looking into this in the coming days.

This is actually pretty hard to reproduce consistently, but I did look over the code and made some small edits that should hopefully fix this. Feel free to reopen this if it's still happening in v4.2.2+.

Hi,
Thanks for the quick response.
I upgraded to 4.2.2 and I can reproduce it.
You can find a live example at http://ci.prescription.dorianpharmatech.com/pharmacie
I think the problem is in sidebar.component.ts at around line 411.
If the element does not have a property tabindex, it's tabindex should be set to 0.
Try to change
if (existingTabIndex !== null) {
el.setAttribute('tabindex', existingTabIndex);
}
by
if (existingTabIndex !== null) {
el.setAttribute('tabindex', existingTabIndex);
}
else {
el.setAttribute('tabindex', '0');
}

I don't think explicitely setting a tabindex is correct either. After all, elements don't have it normally anyway.

Yeah you're right.
But, setting tabindex="-1" for elements which had no tabindex property is
worst. It means that elements which were tabable are not tabable anymore.
I think the solution would be : if the element did NOT have a tabindex
property, to not setting one when the sidenav is opened again.
2017-04-26 20:05 GMT-04:00 Eugene Cheung<EMAIL_ADDRESS>
I don't think explicitely setting a tabindex is correct either. After all,
elements don't have it normally anyway.
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.

That's intentionally done so that the elements aren't focusable when the sidebar is closed (and presumably out of the visible viewport). The current logic should already account for removing the tabindex if there was none initially.


What is parameter x in data?

Could you please provide more information about the parameter labeled as x in the data?
The model already receives parameters such as pos and height.
It would be helpful to clarify the specific meaning or purpose of the x parameter.
Thank you in advance!

Normal vector information or RGB


Update recipe

Overview
Add hooks for auto-enable extension in Jupyter Notebooks.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

@ocefpaf Could you please review to make sure that I'm doing this right? Thanks

LGTM
(To be honest I never packaged anything that need this step, so let's merge and see how it goes.)


Long term stats for HA Energy

Hi @hesselonline. Great work you've done. As you know HA launched Energy panel and integrations need to configure their entities correctly so Home Assistant knows that we need to track statistics for it and how. Metered entities have a value that keeps increasing until reset, like energy consumption or production. To have Home Assistant track this entity a last_reset property needs to be included. https://developers.home-assistant.io/docs/core/entity/sensor/#long-term-statistics
Would you be so kind to include it? Thanks for your great work!

Hi, I haven't had any time to look into this, but I will certainly make time in the near future. So, I will have a look and let you know what's possible in this regard.

Could be possible to "download" from Wallbox Portal the "Monthly summary Energy"? That will give the necessary data to create an Utility_meter sensor inside HomeAssistant, that parameter gives the kWh consumed charging the car....

Hi. Actually after my last request and further investigation you can in fact have long term stats for wall box. First add this to customize.yaml
sensor.wallbox_portal_added_energy:
device_class: energy
state_class: measurement
last_reset: "1970-01-01T00:00:00+00:00"
Then, under configuration.yaml
utility_meter:
wallbox_monthly:
name: Wallbox Monthly
source: sensor.wallbox_portal_added_energy
cycle: monthly
Which this you can monitor individual devices (such as wall box) under Energy portal and also a sensor is created with monthly added energy for Wallbox.

I heard the last_reset parameter will change again in 2021.9.
So be careful adding this in. However, the sensor proposed here would a very nice addition to the Energy dashboard.
Question is how many times we would update the sensor? Is it polled on a regular basis from the web api?

I will add this in a future release of the HA integration. Not sure if I will also add it to the custom component (the integrated HA component is quite different at this point in time so I would need to invest some time in combining these).
I will be using the added_energy sensor for this.


Fix loading video frames for vp_test from mp4

When running vp_test with the clevrer config, in case video frames have to be extracted directly form the video, frames are returned as list of numpy images. Instead, a torch tensor of the form [T, 3, H, W] is expected.
This PR fixes the issue by treating the frames the same way as if they were loaded from jpg images instead of returning prematurely.

Hi, thanks for pointing this out! It's fixed in #2


bug: generic structs where generic is bounded to some trait fails on type deduction to compile when implemented

Bug Report
Cairo version:

1.0.0-alpha.7
Current behavior:

If as in code below one doesn't provide TCopy and GCopy  as here ... of Copy<B<T, G>> compiler will crash trying to deduce possible implementations of Copy trait
Generic structs where generic is bounded to some trait fails to compile when one wants to implement any trait.
Expected behavior:

Compiles succesfully. Also would be great to implement following rust's RFC.
Steps to reproduce:

Compile code below.
Related code:

trait Trait<T> {}

struct B<T, G, impl GTriat: Trait<G>> {
    t: T,
    g: G,
}

impl BCopy<T, G, impl GTriat: Trait<G>> of Copy<B<T, G>>;

initially stubmled upon trying to compile this:
struct A<T> {
    a: T,
}

impl ACopy<T, impl TCopy: Copy<T>> of Copy<A<T>>;
impl ADrop<T, impl TDrop: Drop<T>> of Drop<A<T>>;

#[derive(Copy)]
struct C {
    c: felt252
}

struct B<T, G, impl GCopy: Copy<G>, impl TCopy: Copy<T>> {
    b: T,
    g: G,
}

impl BCopy<T, G, impl GCopy: Copy<G>, impl TCopy: Copy<T>> of Copy<B<T, G>>;

Other information:

thread 'main' panicked at 'Internal error, cycle detected:

DatabaseKeyIndex { group_index: 4, query_index: 74, key_index: 0 }
DatabaseKeyIndex { group_index: 4, query_index: 84, key_index: 0 }
DatabaseKeyIndex { group_index: 4, query_index: 78, key_index: 0 }
', /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/lib.rs:490:48
stack backtrace:
   0: rust_begin_unwind
             at /rustc/9eb3afe9ebe9c7d2b84b71002d44f4a0edac95e0/library/std/src/panicking.rs:575:5
   1: core::panicking::panic_fmt
             at /rustc/9eb3afe9ebe9c7d2b84b71002d44f4a0edac95e0/library/core/src/panicking.rs:64:14
   2: core::panicking::panic_display
             at /rustc/9eb3afe9ebe9c7d2b84b71002d44f4a0edac95e0/library/core/src/panicking.rs:147:5
   3: salsa::QueryTable<Q>::get::{{closure}}
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/lib.rs:490:48
   4: core::result::Result<T,E>::unwrap_or_else
             at /rustc/9eb3afe9ebe9c7d2b84b71002d44f4a0edac95e0/library/core/src/result.rs:1503:23
   5: salsa::QueryTable<Q>::get
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/lib.rs:490:9
   6: <DB as cairo_lang_semantic::db::SemanticGroup>::impl_def_concrete_trait::__shim
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:51:1
   7: <DB as cairo_lang_semantic::db::SemanticGroup>::impl_def_concrete_trait
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:51:1
   8: cairo_lang_semantic::items::imp::UninferredImpl::concrete_trait
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/items/imp.rs:713:49
   9: cairo_lang_semantic::items::imp::module_impl_ids_for_trait_info
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/items/imp.rs:620:33
  10: <cairo_lang_semantic::db::ModuleImplIdsForTraitInfoQuery as salsa::plumbing::QueryFunction>::execute
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:414:21
  11: salsa::derived::slot::Slot<Q,MP>::read_upgrade::{{closure}}
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:218:13
  12: salsa::runtime::Runtime::execute_query_implementation
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/runtime.rs:330:21
  13: salsa::derived::slot::Slot<Q,MP>::read_upgrade
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:215:26
  14: salsa::derived::slot::Slot<Q,MP>::read
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:148:9
  15: <salsa::derived::DerivedStorage<Q,MP> as salsa::plumbing::QueryStorageOps<Q>>::try_fetch
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived.rs:170:13
  16: salsa::QueryTable<Q>::try_get
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/lib.rs:494:9
  17: salsa::QueryTable<Q>::get
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/lib.rs:490:9
  18: <DB as cairo_lang_semantic::db::SemanticGroup>::module_impl_ids_for_trait_info::__shim
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:51:1
  19: <DB as cairo_lang_semantic::db::SemanticGroup>::module_impl_ids_for_trait_info
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:51:1
  20: cairo_lang_semantic::items::imp::find_impls_at_module
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/items/imp.rs:675:28
  21: cairo_lang_semantic::items::imp::find_possible_impls_at_context
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/items/imp.rs:760:16
  22: cairo_lang_semantic::expr::inference::Inference::try_to_resume_impl_var
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/expr/inference.rs:957:26
  23: cairo_lang_semantic::expr::inference::Inference::relax_impl_var
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/expr/inference.rs:987:9
  24: cairo_lang_semantic::expr::inference::Inference::new_impl_var
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/expr/inference.rs:248:9
  25: cairo_lang_semantic::expr::inference::Inference::infer_generic_arg
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/expr/inference.rs:867:69
  26: cairo_lang_semantic::resolve::Resolver::resolve_generic_arg
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:772:24
  27: cairo_lang_semantic::resolve::Resolver::resolve_generic_args
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:749:31
  28: cairo_lang_semantic::resolve::Resolver::specialize_type
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:707:13
  29: cairo_lang_semantic::resolve::Resolver::specialize_generic_module_item
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:481:44
  30: cairo_lang_semantic::resolve::Resolver::resolve_next_concrete
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:370:20
  31: cairo_lang_semantic::resolve::Resolver::resolve_concrete_path
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:196:20
  32: cairo_lang_semantic::types::maybe_resolve_type
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/types.rs:288:19
  33: cairo_lang_semantic::types::resolve_type
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/types.rs:276:5
  34: cairo_lang_semantic::resolve::Resolver::resolve_generic_arg
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:786:26
  35: cairo_lang_semantic::resolve::Resolver::resolve_generic_args
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:749:31
  36: cairo_lang_semantic::resolve::Resolver::specialize_trait
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:645:13
  37: cairo_lang_semantic::resolve::Resolver::specialize_generic_module_item
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:525:45
  38: cairo_lang_semantic::resolve::Resolver::resolve_next_concrete
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:370:20
  39: cairo_lang_semantic::resolve::Resolver::resolve_concrete_path
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/resolve/mod.rs:196:20
  40: cairo_lang_semantic::items::imp::priv_impl_declaration_data_inner
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/items/imp.rs:273:9
  41: cairo_lang_semantic::items::imp::priv_impl_declaration_data
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/items/imp.rs:239:5
  42: <cairo_lang_semantic::db::PrivImplDeclarationDataQuery as salsa::plumbing::QueryFunction>::execute
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:361:21
  43: salsa::derived::slot::Slot<Q,MP>::read_upgrade::{{closure}}
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:218:13
  44: salsa::runtime::Runtime::execute_query_implementation
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/runtime.rs:330:21
  45: salsa::derived::slot::Slot<Q,MP>::read_upgrade
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:215:26
  46: salsa::derived::slot::Slot<Q,MP>::read
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:148:9
  47: <salsa::derived::DerivedStorage<Q,MP> as salsa::plumbing::QueryStorageOps<Q>>::try_fetch
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived.rs:170:13
  48: salsa::QueryTable<Q>::try_get
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/lib.rs:494:9
  49: salsa::QueryTable<Q>::get
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/lib.rs:490:9
  50: <DB as cairo_lang_semantic::db::SemanticGroup>::priv_impl_declaration_data::__shim
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:51:1
  51: <DB as cairo_lang_semantic::db::SemanticGroup>::priv_impl_declaration_data
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:51:1
  52: cairo_lang_semantic::items::imp::impl_semantic_declaration_diagnostics
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/items/imp.rs:176:5
  53: <cairo_lang_semantic::db::ImplSemanticDeclarationDiagnosticsQuery as salsa::plumbing::QueryFunction>::execute
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:368:21
  54: salsa::derived::slot::Slot<Q,MP>::read_upgrade::{{closure}}
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:218:13
  55: salsa::runtime::Runtime::execute_query_implementation
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/runtime.rs:330:21
  56: salsa::derived::slot::Slot<Q,MP>::read_upgrade
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:215:26
  57: salsa::derived::slot::Slot<Q,MP>::read
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:148:9
  58: <salsa::derived::DerivedStorage<Q,MP> as salsa::plumbing::QueryStorageOps<Q>>::try_fetch
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived.rs:170:13
  59: salsa::QueryTable<Q>::try_get
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/lib.rs:494:9
  60: salsa::QueryTable<Q>::get
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/lib.rs:490:9
  61: <DB as cairo_lang_semantic::db::SemanticGroup>::impl_semantic_declaration_diagnostics::__shim
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:51:1
  62: <DB as cairo_lang_semantic::db::SemanticGroup>::impl_semantic_declaration_diagnostics
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:51:1
  63: cairo_lang_semantic::db::module_semantic_diagnostics
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:863:36
  64: <cairo_lang_semantic::db::ModuleSemanticDiagnosticsQuery as salsa::plumbing::QueryFunction>::execute
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:761:8
  65: salsa::derived::slot::Slot<Q,MP>::read_upgrade::{{closure}}
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:218:13
  66: salsa::runtime::Runtime::execute_query_implementation
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/runtime.rs:330:21
  67: salsa::derived::slot::Slot<Q,MP>::read_upgrade
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:215:26
  68: salsa::derived::slot::Slot<Q,MP>::read
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived/slot.rs:148:9
  69: <salsa::derived::DerivedStorage<Q,MP> as salsa::plumbing::QueryStorageOps<Q>>::try_fetch
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/derived.rs:170:13
  70: salsa::QueryTable<Q>::try_get
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/lib.rs:494:9
  71: salsa::QueryTable<Q>::get
             at /Users/edwin/.cargo/registry/src/github.com-1ecc6299db9ec823/salsa-0.16.1/src/lib.rs:490:9
  72: <DB as cairo_lang_semantic::db::SemanticGroup>::module_semantic_diagnostics::__shim
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:51:1
  73: <DB as cairo_lang_semantic::db::SemanticGroup>::module_semantic_diagnostics
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-semantic/src/db.rs:51:1
  74: cairo_lang_compiler::diagnostics::DiagnosticsReporter::check
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-compiler/src/diagnostics.rs:113:35
  75: cairo_run::main
             at /Users/edwin/Documents/projects/cairo/cairo/crates/cairo-lang-runner/src/cli.rs:43:8
  76: core::ops::function::FnOnce::call_once
             at /rustc/9eb3afe9ebe9c7d2b84b71002d44f4a0edac95e0/library/core/src/ops/function.rs:250:5

It fails on a cycle by any chance?
This has been known for a while, and it's because the semantic model of the generic params is on the encompassing item...
Need to do some separation there..

It fails on a cycle by any chance?
Yes. My bad forgot to attach stacktrace

@spapinistarkware would like to take this issue.
Fix idea would be adding a declaration for impl like it is done for functions currently. That's why this code doesn't cycle because generic parameters inside priv_free_function_body_data fetched from priv_free_function_declaration_data. So idea is to have the same for impl. So declaration: impl & path_with_possible_generics
fn trtr<T, G, impl GTrait: Trait<G>, impl TDrop: Drop<T>, impl GDrop: Drop<G>>(t: T, g: G) {

}

fn asd<T, G, impl GTrait: Trait<G>, impl TDrop: Drop<T>, impl GDrop: Drop<G>>(t: T, g: G) {
    asd::<T, G, GTrait, TDrop, GDrop>(t, g);
}

@gilbens-starkware is working on this.
The solution he is doing is making a separate query for the semantic model of a generic param, that doesn't depend on the item semantic model.
Separating impl to declaration is less good IMO, since you can also have the cycle in the generics themeselves.

Hmm, yeah, I think your solution is better. But would you say that have ItemImplDeclaration is unnecessary at this point? I think it would be consistent with functions model + would be entry point for all ItemImpl, ItemImplAlias and ItemImplAnonymous(impl without trait)

Im general, the declaration separation is important in order to make other functions still compile even if the body of this item doesn't.
That means the a declaration is everything another item needs to know about this one.
Thus, the declaration of an impl is "impl Name of ConcreteTrait". So, there is already a separation of this in the code.

Makes sense

Solved in #3360.


Edit Recipe

Changes
As a user who's created a recipe, I should be able to edit that recipe after its creation.

Editing a recipe seems to work relatively well. I'm sure there are bugs to iron out at some point.


added show address in ledger signer

@webmaster128 The function is required by the ledger team as one of the requirements to publish the ledger live app.
https://developers.ledger.com/docs/nano-app/publish-introduction/

The application is compatible with a wallet app with a GUI (a CLI is not enough)

It shows the address in the ledger device. Had added it to our fork  here. Since cosmjs then did not have support for other coin-types.
Would like to have it in cosmjs and remove the dependency on the fork.

@webmaster128 could you please review the latest changes. Thank you.

For some reason, circle CI does not build and test this anymore :/ I will check and finalize after the interface change in LaunchpadLedger

Thank you for your contribution. I'll wrap this up now in a separate PR.
I'm closing here to avoid duplicate work.

Could you have a look at https://github.com/cosmos/cosmjs/pull/1008? I want to release this with CosmJS 0.27.1 very soon. This integrates the new functionality also in the node.js and web demo, so it can easily be tested.


consider more than one frame in dicom

🚀 🚀 Pull Request
Impact

[x] Bug fix (non-breaking change which fixes expected existing functionality)
[ ] Enhancement/New feature (adds functionality without impacting existing logic)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Description
deeplake.read wasn't considering the 3rd dimension of the dicom image

Things to be aware of

Things to worry about

Additional Context

 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.


fixed invoice issue

Issue Reference
#7178

@shivendra-webkul
Remove the unnecessary space between the contact and country name.

unnecessary space between the contact and country name fixed

@shivendra-webkul
This is working fine, please find the screenshot Here


[New Process Improvement Need]: Recommended A&A Best Practices

Checked for duplicates
Yes - I've already checked
Category
Security - application, network, hardware, etc. security topics
Describe the need
We have a need for:

Best practices for authentication and authorization
Specifically: supporting multiple A&A systems

+1'd from @LucaCinquini @mcduffie

@ramesh-maddegoda has done some great work on this for the Unity SDS project. It'd be really great to share the general best practices he developed in SLIM.

@ramesh-maddegoda has done some great work on this for the Unity SDS project. It'd be really great to share the general best practices he developed in SLIM.

@riverma, We have most of our security related topics documented under https://github.com/unity-sds/unity-cs/wiki#security as follows.

Unity Security Use Cases
Unity Security Guidelines
Unity Authorization Model
Amazon Cognito Authentication with JupyterHub
Getting Cognito JWT Tokens in Command Line
Token Management

Some of these topics are generic and some are Unity specific. Should we have these docs written in a generic way (can be applicable in any project)? If those have to be generic, we will have to write few new wiki pages in a generic way.

Wow. This is really great stuff @ramesh-maddegoda! Thanks for sharing. Let me look over this and offer some thoughts. I think some generic versions of your guides could be really great, and maybe even some sort of automation that sets things up. Have to look a bit more into what you've been working on in detail.
CC @jpl-jengelke @jpl-btlunsfo for cognizance.

In addition, we also have some code examples implemented as follows, so the developers can use those as reference implementations.

HySDS UI - authentication with Auth 2.0 Authorization Code Grant with PKCE (Proof Key for Code Exchange)

https://github.com/unity-sds/unity-cs-security/tree/main/code_samples/hysds_ui_with_auth

Secured RESTful API - protected with API Gateway

https://github.com/unity-sds/unity-cs-security/tree/main/code_samples/hysds_mozart_mock
https://github.com/unity-sds/unity-cs-security/tree/main/code_samples/aws_rest_api_gateway

REST API Consumer - authentication with Auth 2.0 Client Credential Grant for app-to-app (machine-to-machine) communication.

https://github.com/unity-sds/unity-cs-security/tree/main/code_samples/hysds_mozart_mock_consumer

@ramesh-maddegoda - had some time to go through your material, and wow! You've done such a comprehensive and thorough job - thanks so much for sharing. You're rocking the security work!
Wanted to brainstorm which aspects of your work could be most helpful to the SLIM community.
Here's an idea I was thinking: a push-button instantiation of your security architecture to support the Earthdata auth / JPL auth integrated security layer around a pre-existing API or web-UI running on AWS. In other words, we could generalize / publish a limited set of your docs along with the requisite Terraform (or other tool) to automatically spin up the AWS infrastructure needed. This is in-line with our philosophy of automation > guides.
I can imagine several projects benefiting from something like that, but I wonder if Unity devs would even benefit from instantiating a test venue to test out their app's security before integration with U-CS.
Let me know your thoughts! @jpl-jengelke FYI.

+1'd by @nttoole

@awdtinio   Given all of the recent confusion, and efforts in various projects related to A&A, I suggested in a SLIM meeting today, that SLIM think about ways that they can help to alleviate/streamline A&A efforts in the future.  These could be ways to proactively use security best practices, and proactively address the A&A “controls”.
Rishi created a ticket here, where we are starting to gather thoughts.
I mentioned that you might be a good point of contact to provide some information about what the controls are (is there an overall list?), and also might have some thoughts about this area, since you have been involved in this.  So feel free to chime in on this ticket, if you have any ideas.


add --kubeconfig option

In kubectl there is the option for --kubeconfig='' It is the path to the kubeconfig file to use for CLI requests.
I would like to be able to to the same with helm.

Here's a small fragment I've used in some of my programs, which may involve some cruft that client-go no longer mandates:
// Assume: fs *pflag.FlagSet
// Assume: interactive bool
loadingRules := clientcmd.NewDefaultClientConfigLoadingRules()
fs.StringVar(&loadingRules.ExplicitPath, "kubeconfig", "",
	`Path to the kubeconfig file to use`)
overrides := &clientcmd.ConfigOverrides{}
// This adds a whole bunch of related flags that we find in kubectl.
clientcmd.BindOverrideFlags(overrides, fs, clientcmd.RecommendedConfigOverrideFlags(""))

var clientConfig clientcmd.ClientConfig
if interactive {
	clientConfig = clientcmd.NewInteractiveDeferredLoadingClientConfig(loadingRules, overrides, os.Stdin)
} else {
	clientConfig = clientcmd.NewNonInteractiveDeferredLoadingClientConfig(loadingRules, overrides)
}

Is there any problem with specifying the KUBECONFIG env variable? Helm does honor it

I'd be find adding a global option for this. It should be pretty straightforward, since this would follow the same pattern as --host and $HELM_HOST.

@thomastaylor312 using KUBECONFIG works, but I personally prefer a --kubeconfig option if I just have one command to run.
Then it is just one command to type (helm) instead of two (export and helm).

Per my earlier comment, I think that if you're going to allow specification of a configuration file, you should also accept the same override flags that kubectl does.

I think helm should provide the same UX experience like kubectl, where it make sense.  Most of the time I use --kubeconifg instead of export & kubectl or helm

Using --kubeconfig when running the helm command would help reduce ambiguity if running helm on a automated basis. When using environment variables in this manner, race conditions might occur and you might end up running your helm chart against a k8s stack you didnt want to.

could I take a crack at this issue?

re-opening as #2621 was reverted due to breaking $KUBECONFIG as seen in #3378

It'd be nice to have this implemented... again. :laughing:

First time contributor - can I pick this up?

Yep!

I've got a PR up. I'd appreciate a review! :)

@rchakra3 Thank you! Any idea when this will get merged in? I'm currently in a situation where the  --kubeconfig flag would be very helpful!

Feel free to test this feature with v2.10.0-rc.3!

Meanwhile another option when running from bash is this:
KUBECONFIG=path/to/config kubectl ...

I ended up being lame for now, and adding a zsh function to my shell.
kubecctx() {
    KUBE_CONTEXT_DEFAULT_FILE=config.yml
    KUBE_CONTEXTS_DIR=~/.kube/contexts
    KUBE_CONTEXTS=$(ls -d ${KUBE_CONTEXTS_DIR}/* | xargs -n 1 basename)
    KUBE_CONTEXT_CURRENT_CONTEXT=$(echo "${KUBE_CONTEXTS}" | fzf)

    KUBECONFIG="${KUBE_CONTEXTS_DIR}/${KUBE_CONTEXT_CURRENT_CONTEXT}/${KUBE_CONTEXT_DEFAULT_FILE}"

    echo "Switched to KUBECONFIG '${KUBECONFIG}'."
}


Correct variable and URL references

Updated to correct SPONSORBLOCK_SERVER variable name and URL.

I see that this issue is already solved and the PR can be closed

Thanks!


iOS crash

Godot version
3.5.1
System information
Windows 10
Issue description
Hi all 🙂
I noticed, that my iOS app crashes sometimes. In Xcode I found the logs, but I have no idea what does it mean. Any ideas?
Thread 0 name:
Thread 0 Crashed:
0   Deisei_in_German              	0x0000000104ff9418 OSIPhone::touch_press(int, int, int, bool, bool) + 320
1   UIKitCore                     	0x0000000192324ce0 -[UITouchesEvent _sendEventToGestureRecognizer:] + 576 (UITouchesEvent.m:518)
2   UIKitCore                     	0x0000000192c30f98 -[UIGestureEnvironment _deliverEvent:toGestureRecognizers:usingBlock:] + 172 (UIGestureEnvironment.m:1361)
3   UIKitCore                     	0x0000000192366520 -[UIGestureEnvironment _updateForEvent:window:] + 188 (UIGestureEnvironment.m:1345)
4   UIKitCore                     	0x000000019236ad94 -[UIWindow sendEvent:] + 3268 (UIWindow.m:3482)
5   UIKitCore                     	0x000000019236a054 -[UIApplication sendEvent:] + 676 (UIApplication.m:12664)
6   UIKitCore                     	0x0000000192368340 __dispatchPreprocessedEventFromEventQueue + 1768 (UIEventDispatcher.m:2414)
7   UIKitCore                     	0x00000001923b1018 __processEventQueue + 5576 (UIEventDispatcher.m:2764)
8   UIKitCore                     	0x0000000193023e48 updateCycleEntry + 160 (UIEventDispatcher.m:116)
9   UIKitCore                     	0x00000001928c04b0 _UIUpdateSequenceRun + 84 (_UIUpdateSequence.mm:114)
10  UIKitCore                     	0x0000000192f24c8c schedulerStepScheduledMainSection + 144 (_UIUpdateScheduler.m:1015)
11  UIKitCore                     	0x0000000192f241e8 runloopSourceCallback + 92 (_UIUpdateScheduler.m:1164)
12  CoreFoundation                	0x00000001902d6128 __CFRUNLOOP_IS_CALLING_OUT_TO_A_SOURCE0_PERFORM_FUNCTION__ + 28 (CFRunLoop.c:1957)
13  CoreFoundation                	0x00000001902e27b4 __CFRunLoopDoSource0 + 176 (CFRunLoop.c:2001)
14  CoreFoundation                	0x00000001902675e8 __CFRunLoopDoSources0 + 244 (CFRunLoop.c:2038)
15  CoreFoundation                	0x000000019027d0d4 __CFRunLoopRun + 828 (CFRunLoop.c:2953)
16  CoreFoundation                	0x00000001902823ec CFRunLoopRunSpecific + 612 (CFRunLoop.c:3418)
17  GraphicsServices              	0x00000001cb71f35c GSEventRunModal + 164 (GSEvent.c:2196)
18  UIKitCore                     	0x000000019260f6e8 -[UIApplication _run] + 888 (UIApplication.m:3782)
19  UIKitCore                     	0x000000019260f34c UIApplicationMain + 340 (UIApplication.m:5372)
20  Deisei_in_German              	0x0000000104ffcd6c main + 124

Steps to reproduce
No need
Minimal reproduction project
No need

You will need to provide a minimum reproduction project, this isn't enough information to find the issue

A small Godot project which reproduces the issue, with no unnecessary files included. Be sure to not include the .godot folder in the archive (but keep project.godot).
Drag and drop a ZIP archive to upload it. Do not select another field until the project is done uploading.
Note for C# users: If your issue is not Mono-specific, please upload a minimal reproduction project written in GDScript or VisualScript. This will make it easier for contributors to reproduce the issue locally as not everyone has a Mono setup available.

@AThousandShips I think its not possible. I don't have any problems or crashes during the debug via Xcode. These crashes are from App Store Connect.
So I have no idea how to create the project to reproduce. The only thing I have is crash report.

I could add the full crash report, if needed. But thats all I have.

That won't help us really, we can't tell what's going wrong from just the report, or every single iOS project would be crashing, we need what kind of project is causing it
Please try to create a project to reproduce, or we can't do anything, if you can't figure out how to reproduce it when it's your project, how can we?

@AThousandShips It's just not possible to create a project to reproduce. Take a look:

Imagine I create a simple project to reproduce the bug. Done.
I need to upload it to the App Store: The App Store review will NOT approve it at any case because it won't be a final product (I've already had problems with it).
Imagine if they approved it by some luck. I have to wait about 1-2 months to get a crash report. It is very unstable and happens 0-3 times a month.
THEREFORE it is not possible to create a playable project.

If the crash report doesn't say anything, then the issue simply cannot be resolved and we can close the issue.

And then, to reproduce it. You also have to upload same project to App Store and wait for 1-2 months.

How do you know this is caused by the app store? How do you know it doesn't crash otherwise?
You need to consider the process of reviewing bugs
Just posting a crash report without any details on what's going on in the project isn't helping, do you understand?

So how can I create the project to reproduce, if it does not crash locally for me and I cannot reproduce this error locally?

So to get this clear:
This bug never happens on its own, only happens when the project is downloaded through the store?

I didn't notice it locally after download from App Store to my devices.
I got this crash report from App Store Connect. So it crashes on some device.

So it is some kind of unstable crashes.

So to get this clear: This bug never happens on its own, only happens when the project is downloaded through the store?
Also this isn't for bug fixing individual projects, this is for fixing bugs in the engine, we do not provide bug fixing for projects, for that turn to the community linked above

The forum is not working because of some transfer and no one is responding in discord. Probably no one knows what it is. That's why I'm here.

Then I would say that you need to try to reproduce it locally, and if you can you can update this report with an MRP
But if you can't there's nothing we can do, understand?

I dont know if the problem is in Engine or not.
But ok, I see. Thanks.

If you can provide an MRP please do so, but I hope you can see how it's impossible for us to figure out what is going on without any information on where things are going wrong


Lance Dataset Iteration does not honor batch_size

When using lance.torch.kmeans.KMeans, the train batch size used by the iterator does not match the batch_size given by the user.
In particular, this line. When the lance dataset is written with a multiple .add(batch) where batch is of size 1,000, the chunk size returned gets upper bounded by 1,000.
Further, even if the writing is done with a batch_size of 2,000; the reading batch_size gets upper bounded by 1,024

Hi,
This is because we use arrow::Scanner under the hood. arrow::Scanner does not concat batches across row group boundaries; default row group size is 1024. I have opened a PR that addresses this issue by buffering and concating batch together in python.
Note that in the PR we do not try to hit the exact batch size specified as that would require complicated logic. Instead we yield a batch when ever adding a new batch would go over the batch size specified.

Thanks that will be very helpful - I will then implement a simple assert on my side to set the desired batch_size  to be either < 1,024 or a multiple of 1,024


[Lecture2-2][1009] Convolutional Autoencoder vs. (Deep) CNN

In the lecture, we discussed the use of convolutional layers in autoencoders. I previously studied deep convolutional neural networks (CNNs), and I'm trying to understand the distinctions between the two. Based on my research, I noted that:

CNNs typically have more layers (at least five), while autoencoders can function with fewer layers, even one, although deeper architectures tend to perform better.
Both are feedforward networks, but autoencoders may also utilize recirculation during training.
Autoencoders have a broader range of applications beyond image processing, while CNNs are generally used for image-related tasks.

Could you clarify these differences or provide more insights into how autoencoders and CNNs differ in their structure and applications?
Thank you in advance!
Cosima Balzer

I think you can simply think of it this way:

CNNs are just neural networks with convolutional layers, and they can learn meaningful visual features through the overall network design.
Autoencoders are networks with two components: an encoder and a decoder, and they aim to learn efficient encoding in the latent space by minimizing the reconstruction error.

While the encoder and decoder in autoencoders are often built with fully connected layers, they can also be formed with convolutional layers like in the "convolutional" autoencoder, that is, CNN being part of autoencoder architecture.

@mosouka @jleem99 Thanks for the question and the comment:)
jleem's answers are correct. To add to that:

Autoencoders can also have multiple layers. For example, the Autoencoder in Noh et al., an early approach utilizing ConvTranspose2D, employs a VGG16 CNN classification network as the encoder.
For specific tasks, such as in diffusion-based generation methods, models like UNet (Autoencoder + skip connections) are used repeatedly (we'll cover this later). However, in most cases, Autoencoders follow a single feedforward process.

Thus, CNNs and Autoencoders are not inherently in the same category. While we can design an Autoencoder using a CNN architecture, convolutional layers are widely used across various applications in computer vision.


Review layout of space-critical classes

Critical classes like header, message, basic_fields should have their members reviewed to determine if a rearrangement of order results in a space savings.

See https://wandbox.org/permlink/7jGi94XsRIxgbCmq

Make the following change to Empty in the unit test empty_base_optimzation_test.cpp and observe which C++ implementations fail to compile it, in various C++ standard modes:
struct Empty final {
    operator bool() { return true; }
};

Done


tensorflow intent classification is very sensititive! What to do?

Hey,
I use for german language the tensorflow embedding.

I recognize a high sensitivity of the intent classifictaion with just slightly changes of sentences like adding just one whitespace between words!

trained in german sentences with just maskulin adjective forms. Testing on feminine adjective forms, which in this case is just removing one letter at the end of the word, changes intent drastically!

My intent greet is just words like hi, hey...
Adding hi or hey to one of a well trained sentence, so hi+sentence gives intent greet!

So, I am thinking I have to play with params for my specific use cases to overcome such sensitivity. Can you give me some experience on which params I have to focus?

for all of there problems It definitely looks like you are overfitting. How many epochs are you training for? do you have a separate test set?
for 3. you could try creating a multi-intent

@ctrado18 could you please add a bit more details:

what do you mean just one whitespace between words: there was a whitespace and you add the second (that should not change anything) or there was a long German word and you split it into two (in this case you create completely new words that might even be out-of-vocabulary because the classifier by default uses whitespace tokenizer, so it ignores them during prediction)?
Removing one letter at the end of the word creates completely different word from the point of view of this classifier! So no wonder it performs differently. For this you need to consider to use some lemmatizer for preprocessing.

@amn41 Yes, I suppossed so too. This results from the sklearn intent classifier preveously. Now you don't need anymore so much training data, right?
Multi-Inent: Yes, but this is confusing. When I need an intent just for ProductA (just for imagination...)  like Costs_ProductA_Scenario1, Costs_ProductB_Scenario2...
I need also just the intent Costs but I have no and need no intent for ProductA
Because at one post you said you need to have all subintent separately!
But I don't need to have all subintent..Maybe I want just at one level a distinction but not all all intent levels...
Do I need the tokenizer_whitespace? And what is it actually. Maybe that's my issue with whitespaces?
This is my pipleine for version 12.3.
pipeline:
  - name: "nlp_spacy"
  - name: "tokenizer_spacy"
  - name: "ner_crf"
  - name: "ner_synonyms"
  - name: "intent_featurizer_count_vectors"
  - name: "intent_classifier_tensorflow_embedding"
    intent_tokenization_flag: true
    intent_split_symbol: "_"

@Ghostvv Yes lemmatizer...But for german spacy is not really good! Is there anything for german? Also spacy distinguishes betwen upper and lower capital letters for words, but in chatbot you write in small letters typically....

how much training data do you have? number of intents, examples per intent etc

@ctrado18 thank you for detailed answer. For multi-intent, strictly speaking you do not need separate data for all subintent, I think it is worth to try as you described without subintent for Product and check the performance.
If you use spacy, you do not need tokenizer.
I know that German language have such structure, but intent_classifier_tensorflow_embedding doesn't know it, it builds vocabulary from words you provide, so if even one character is different, it will treat it as different word. If you want to deal with different endings, you could try to create preprocessor that cuts the ending of all words or smth like this. Unfortunately, I do not have any suggestions for you about good lemmatizers for German language

I would say I have 500 examples for the one intent and for my other specific intents just 30 examples. I think imbalances are handled well with tensorflow?
For the 500 examples I created with some sentence structures with Chatito many exmaples in the way that I just plugged in many  entitiy values for alle these sentences. So, this is why I ended up with so many  examples. But maybe with tensorflow this not a good approach since the sentence is the same instead of one word?
Soe questions the tensorflow algorithm:
What happens if I set the intent_tokenization_flag to False? Oris there any differences in both ways how the algo classifies the intents?
Afterwards I train my intents with _. Might this fix somehow the senitivity for mixing up intents like hey, I want to buy something without traiing it? I have the feeling that wenn you use intent tokenization, the algo is more sensitive when you mix up intent in one sentence...
Does the algo really create a vocabulary with only the trained words? So, the algo is really sensitiv to slightly changes of a word? I did'nt thought of that. I thought it uses similiarity measures that similiar words are really similiar...

Please note that if you provide spacy, then intent_featurizer_count_vectors uses lemma_ from spacy as tokens. You'll need to overwrite this if you want to use custom preprocessor

But you need it for NER_CRF? What if I want to try sthe standard intent_featurizer_count_vectors ? I am confused...

Does the algo really create a vocabulary with only the trained words? So, the algo is really sensitiv to slightly changes of a word? I did'nt thought of that. - It does precisely that!

Thank you. Indeed, sklearn performs better but with lower confidence. I found out that the spacy model for german captures a lot of my specific vocab I think (I just tested a few words). Could you combine both embeddings?
One question to spacy model: If a word is inside the model then, are there all other forms of that word (plural etc.) inside?
I recognized that both pipelines are still very sensitiv to white space such that if I plugg in an addditionaly space between two words of a sentence...Bot for my intents where I use round 40 examples, so overfitting should not be an issue?
@Ghostvv Still the pipeline question is open. SInce I use CRF I need somehow spacy.

ctrado18 Could you please explain your whitespace issue. If you already have a whitespace and you add the second one, it shouldn't make any difference.
ner_crf without spacy is introduced in the last master

@Ghostvv Is the master a diferent version? I like to stick first to 12.3.
Example:
I need doctor
I need  doctor
Add oine whitespace before doctor. For me this is sensitive and also changes intent !
But I recognize that it only changes the intent for my 3 somehow similiar intents. Those 3 are thought to hanlde hierarchical intents like where the difference is just the kind of employment. So: I am working and need doctor. versus I study and need doctor. There, plug in before or after the kind of employment changes intent...

yes, for ner_crf tokenizer_spacy is enough.
very strange behavior with whitespace, could you please add examples in German exactly as they are when you experience this problem?

I tried to add more example and I think the whitespace issue is somehow more stable. But I will look at this.
What I still like to know if there is any difference of the algo when or when not using the Multiple Intent flag? Because, the trainig data is the same. I also could have some intents like Greet_Intent1_Intent2 just using normal intent classification and train all these intents. SO, where is the difference when I set the flag for multiple intents to true?! What advantages I have?
And I don't want to train those multiple intents. But I am a little bit sad about this mising up intent when I use a greeting together with a normal sentence like in my starting post or here https://github.com/RasaHQ/rasa_nlu/issues/1182
I have an intent order, like I want to order something with right intent, but using hey, I want to order something  it gets intent greet. So, I have to train those occurences or using multiple Intent, right? But is this a normal behaviour?
I just want to know I this is normal or I am doing wrong with my training data. But I think many have this "greet" issue.
It would be nice if @amn41 @akelad can have a look at. 😄

@ctrado18 thanks for all the info you provided. @Ghostvv is the expert on the tensorflow pipeline. I think this discussion now contains too many ideas and questions for it to be fully resolved, so I'd propose we close it in favour of more specific issues.
If adding an extra whitespace between two words is really giving different results, that sounds like a bug. If you could create a minimal reproducible example that would be extremely helpful, please create a separate issue for that.
To your earlier comment: spacy_sklearn might be giving lower confidences, but that doesn't mean the model is worse. In fact very very high confidences are a strong signal that you are overfitting.
I see some other questions about the way the tensorflow pipeline works, which I'm sure other people would also be interested in. I think it would be very helpful if you could create a reproducible example of the models behaving differently with and without intent tokenization,

Thanks. I will test more specifically my data. But some questions were specific think. So, can I conluce there should be no difference with and without intent tokenization?
Still, i have a high sensitivity as I expained on examples before. I have just 5 intent, for the first 500 utterances or more and the other 4 just about 50 utterances. Have you experimented with the embedding to give some rule of thumbs for trainin data? Sensitiviy (change of the intent) when doing a mispelling or append just a single letter to a word is high. Is my training data too low?  I think a forumale very specific and I think you this could be a general case for most data sets.
To understand the embedding algo correctly, you need to train actually a large dat set consisting of "every" word since there are many similiar words meaning the same like the words hoch, viel in wie viel kostet or wie hoch sind die Kosten... If you have never used the word hoch (in this context, but maybe in another context) this word will be neglected?

One short question to the intent_spacy_sklearn classifier: What and where is this "spacy_doc". But I assume that it just contains for every word the word vector coming from spacy. So the features for intent classification are just those word vectors?
I find fastText very interesting and try that too such hta I can compare all 3 methods.

One thing you can also try is to change the analyzer in the CountVectorFeaturizer ( which wraps sklearn's CountVectorizer to use character ngrams instead of whole tokens

for the documentation of spacy_doc please spacy documentation: https://spacy.io/api/doc.
about sensitivity, yes it is the problem for embedding classifier, that is difficult to tackle. For German language lemmatization, I found this post https://datascience.blog.wzb.eu/2017/05/19/lemmatization-of-german-language-text/

To compare intent classification for all 3 methods I want to look if some of my custom words are in those pre trained models. But what the heck is going on here? In spacy it seems every word is inside this model. I tried many words and garbage and the follwoing gives that this word `u'sdasfaf``is inside spacy and is ADJ:
import spacy

nlp = spacy.load('de_core_news_sm')
doc = nlp(u'sdasfaf')

for token in doc:
    print(token.text,token.lemma, token.lemma_, token.pos_)
    print("has_vector:", token.has_vector)

@Ghostvv This spacy doc is not so helpful. But, for intent with sklearn classification you just use the word vectors? It is not so clear from the code since there is just "spacy_doc".

yes for intent sklearn classification, we use word vectors

@Ghostv thanks. Any idea about my code for checking if it has vecor? Why does garbage yield true?

Interesting observations. I think the problem is in collecting training data and the complexity of German language. For the issue above please ask on spacy forums.


[ENG-4376] Add Check for User Notable Domains to Spam Check

Purpose
Currently users this hammed notable domains were still getting there nodes flagged during routine spam checks, that resolves that by skipping the check for verified users.
Changes

adds simple check to spam function
adds test to ensure correct behavior

QA Notes

Verify a user whose's domain is hammed can't have a resource flagged as spam.
Verify

What are the areas of risk?
Any concerns/considerations/questions that development raised?
Documentation

Side Effects

Ticket
https://openscience.atlassian.net/browse/ENG-4376

This should be handled by the user.is_hammy check here: https://github.com/CenterForOpenScience/osf.io/blob/456e4c23c904df5ddc254aa466ae57569e6eac36/osf/models/mixins.py#L2081
Is there a place where we're calling do_check_spam instead of check_spam inappropriately?

@jwalz ahhhh, but look again, Here's OSFUser class now here's the user's function It's a little confusion between SpamMixin and SpamoverrideMixin that caused the bug.
Hmm, though having stated that I guess this is not the desired fix, I will look at correctly implementing that method for users.

Sorry about that! I see the error more clearly now, easier fix.

Tricky valuation order bug:

(False or None or 0) or (0 or None or False)
False
(False or None or 0) and (0 or None or False)
0


"ds-test/test.sol" Not Found

import {DSTest} from "ds-test/test.sol";
"ds-test/test.sol" :- doesn't exsist

Please provide steps to reproduce

Me too. When i complied "lib/forge-std/src/Test.sol" in remix, And it response me "Error: not found ds-test/test.sol". I hava already placed the test.sol file in the expected directory, however it doesn't work.
And another problem, it shows 'stack too deep' when compiling the file in "src/P256Verifier.sol", and here are the detials.

CompilerError: Stack too deep. Try compiling with --via-ir (cli) or the equivalent viaIR: true (standard JSON) while enabling the optimizer. Otherwise, try removing local variables.
--> src/P256Verifier.sol:326:54:
|
326 |         uint256 comp_M = addmod(mulmod(3, mulmod(x1, x1, p), p), mulmod(a, mulmod(zz1, zz1, p), p), p); //M = 3*(X1)^2 + a*(zz1)^2
|                                                      ^^

versions 1.8.0 and later of forge-std removed ds-test as a dependency, but earlier versions have it.  The stack too deep error is not a foundry issue, but specific to the P256Verifier contract. Closing since everything seems to be working as expected from my testing, but if you are still having issues provide concrete steps to reproduce (e.g. how are you getting forge-std into remix?) and I may be able to help


Add integration with GStreamer 1.16 recipes in openembedded-core/poky and also in meta-gstreamer1.0

GStreamer 1.16 introduced the WPE plugin. In order to build it in Yocto/OE, meta-webkit is needed. Also, a new PACKAGECONFIG has to be added to https://github.com/openembedded/openembedded-core/blob/master/meta/recipes-multimedia/gstreamer/gstreamer1.0-plugins-bad_1.16.0.bb (and the --disable-wpe switch in EXTRA_OECONF has to be removed).
However, when I tried that, I got a lot of compilation errors.
Unfortunately, I no longer have the error log. However, it is straightforward to reproduce.

Add meta-webkit to your bblayers.conf.

Add this line to gstreamer1.0-plugins-bad_1.16.0.bb:
PACKAGECONFIG[wpe] = "--enable-wpe,--disable-wpe,"wpewebkit wpebackend-fdo virtual/egl libxkbcommon"
(The PACKAGECONFIG lines in that bitbake recipe are sorted alphabetically)

Remove the --disable-wpe switch in EXTRA_OECONF (also remove "wpe" from the "these plugins have no corresponding library in OE-core or meta-openembedded" comment block to be thorough).

Add "wpe" to the gstreamer1.0-plugins-bad PACKAGECONFIG line (for example in your local.conf: PACKAGECONFIG_append_pn-gstreamer1.0-plugins-bad = " wpe " - pay attention to the whitespaces surrounding "wpe" !)

Then try to build gstreamer1.0-plugins-bad.

I found a build issue indeed, should be fixed now, can you check again after back porting https://gitlab.freedesktop.org/gstreamer/gst-plugins-bad/commit/5105bc804154144d94bc91a8a912bf1a491270ae ?


Fix errors on Unity 5.5

This adds some conditional compilation flags to retain compatibility with Unity 5.5.

@nloewen,
Thanks for your contribution.
To ensure that the project team has proper rights to use your work, please complete the Contribution License Agreement at https://cla.microsoft.com.
It will cover your contributions to all Microsoft-managed open source projects.
Thanks,
Microsoft Pull Request Bot

@nloewen, thanks for signing the contribution license agreement. We will now validate the agreement and then the pull request.
Thanks, Microsoft Pull Request Bot

What isn't working on 5.5? I've been using the toolkit without any issues besides the ones resolved by this pull request.

https://github.com/Microsoft/HoloToolkit-Unity/issues/600


Initialize reseed_gen_counter to 1, like it is done in master [1.1.1]

master initializes this to 1, while 1.1.1 initializes to 0,
likely master is more correct.

SP800-90A r2 actually shows pseudo code that sets this counter to start at 1 in multiple places (not zero). See section B.3.2 for example.

SP800-90A r2 actually shows pseudo code...

Interesting... I didn't know that revision 2 has been published meanwhile. Where can I get it from? It's neither listed as official publication nor as draft.

sorry. my mistake.. r1 is the final version.

No problem. And thanks for giving the reference to the pseudo code.

ping @paulidale

Merged to 1.1.1 branch as 9bc987f.  Thanks!


exception by selecting model GPT-4

Super project!!! Thx.
In Chrome browser GPT-4 is correctly selected as default.
Ran correctly until now.
Since 1 day (?) unfortunately always the model GPT-3.5 is selected using this ChatGPT_Client.
The WebUI has changed a bit ;-(
calling
chatgpt.switch_model("GPT-4")
returns the error message:
Exception has occurred: ElementClickInterceptedException       (note: full exception trace is shown but execution is paused at: _run_module_as_main)
Message: element click intercepted: Element ... is not clickable at point (1177, 49). Other element would receive the click:
...

  (Session info: chrome=114.0.5735.133)

Would be great if this works again to use the pro account properly.

Hello,
Can you try with the latest commit  203a0a8 and let me know if it is working on your end?

wow ... quick reaction ;-)
Unfortunately bad news.
Same problem, same exception.
No change ;-(

Try passing --no-cache-dir to pip install

the two files are up to date to your patch-level (i checked manually) and the debugger also the latest code is executed.
Unfortunately i am not so good at xpath.
Since mouse-over at "GPT-4" in Firefox as well as in Chrome a drop-downmenu appears ... could it be that 2 actions are necessary?

mouse-over GPT-4
then select "Default"

Hey,
I don't have a premium account anymore so I am not sure if that functionality works. If you can provide screenshots of that and DOM, I can do my best to make sure that function is working. Otherwise, you are welcome to send a PR with a working version.
In my free account, that function opens a modal to funnel into the premium account subscription, that's why I thought it should have worked. However, it seems like there may be an extra step.

ok i got it.
The exception was raised by the "ChatGPT: Tips for getting started" Dialog.
The dialog must be closed first.
in login-function:
	# Find password textbox, enter password
        pass_box = self.sleepy_find_element(By.ID, 'password')
        pass_box.send_keys(password)
        logging.info('Filled password box')
        # Click continue
        pass_box.send_keys(Keys.ENTER)
        time.sleep(1)
        logging.info('Logged in')

        # NEW
        # Click Okey Let's go for ChatGPT: Tips for getting started - Dialog
        OkeyLetsGo_button = self.sleepy_find_element(By.XPATH, '//div[text()="Okay, let’s go"]')
        OkeyLetsGo_button.click()
        time.sleep(1)
        logging.info('Clicked Okay, let’s go button')
        # END NEW

        try:
            # Pass introduction

switch_model works now too (little bit hard coded, but tested):
from selenium.webdriver.common.action_chains import ActionChains
...
def switch_model(self, model_name : str, mode : str = 'Default'):
        '''
        Switch the model for ChatGPT+ users.

        Args:
            model_name: str = The name of the model, either GPT-3.5 or GPT-4
            mode: str = For GPT-4 : Name of the Mode: either 'Default', 'Code Interpreter' or 'Plugins'
        Returns:
            bool: True on success, False on fail
        '''
        if model_name in ['GPT-3.5', 'GPT-4']:
            logging.info(f'Switching model to {model_name}')
            try:
                if model_name=='GPT-3.5':
                    self.browser.find_element(By.XPATH, self.gpt_xq.format(model_name)).click()
                    return True
                elif model_name=='GPT-4':
                    element = self.browser.find_element(By.XPATH, self.gpt_xq.format(model_name))
                    actions = ActionChains(self.browser)
                    # only move mouse for mouse over
                    actions.move_to_element(element).perform()
                    # now select the right mode
                    modeElement = self.browser.find_element(By.XPATH, '//span[text()="{}"]'.format(mode))
                    modeElement.click()
                    return True
                else:
                    return False
            except Exceptions.NoSuchElementException:
                logging.error('Button is not present')
        return False

would be great if you could take the code adapted

It is interesting that I can pass the info screen on my end but not you, I will take a look at this later on.

This problem is now fixed with 30606eabc69b3d9dbe0f8dfef94687b84032525d, the id selector was not working properly, now we skip the tutorial page without clicking anything. Thank you!


Make levels in multilevel lists more distinct

When we have multilevel lists we would like a greater indent to distinguish between the levels of the list. I don't know if we should also have different bullet marks beyond the two that we use now. They currently look like this (see learn_linkingMechanisms on the lemdo-dev site):

This example list is a bit of a beast (I believe currently five levels of nested lists...) and I will rework it, but it is a good example of what happens when we have lists inside of lists, which has popped up in a few places.

Yes I agree this could use sorting out.

The default indent (--listIndentBornDig) is only 0.25rem, and the list markers are set inside the paragraph, which makes them harder to distinguish:
body[data-catrefs*="BornDig"] main ul, body[data-catrefs*="BornDig"] main ol, body[data-catrefs*="BornDig"] main div[data-el="list"] {
  font-family: var(--primarySerif);
  font-size: var(--paraFontSizeBornDigMobile);
  color: var(--paraFontColor);
  margin: var(--paraMargin);
  margin-left: var(--listIndentBornDig);
  list-style-position: inside;
}

list-style-type is disc for the top level, then circle for all the subsequent levels. I would recommend a bigger indent, moving the list markers outside the text block, and providing a series of distinct markers for (say) four levels.

I've styled these nested lists (disc, square, circle, repeating to 4 levels, with more margin), but I think nesting beyond two levels is confusing. In the example given I would organize it with a series of sub-heading questions to organize the flow chart like meaning. Keep the lists to one level deep for the specifics. Like this:
Are you linking to something in your own portfolio (your own edition)?
YES?

Is your file going to be published as a PDF?
Are you pointing to a non-canonical reference that cannot be known until the PDF is generated (e.g., page or line numbers)?

If yes to the above, Use the <ptr> element and see "How to Encode Pointer Links" for instructions.
No?
What are you trying to link to?

An act, scene, or speech: use the <ptr> element and the xml:id of the act, scene, or speech.
A specific point in a text: use the <ptr> element and a single anchor.
A span of text (including a line): use the <ptr> element and two anchors.
A paragraph in your own critical paratexts: use the <ptr> element and the xml:id of the paragraph.
A figure in your annotations or critical paratexts: use the <ptr> element and the xml:id of the figure.

Thanks for this helpful feedback, @pszpak! Your timing is perfect because @LEMDO-PM is revising the chapter this week.


How to install for ubuntu

sudo apt-get install ruby1.9.1-dev
sudo gem install git_stats

No offense, is this a problem?

Of course not. The tool works great.
I just wanted to document how to install it for ubuntu.
But now that I'm thinking about it, it seems like proposing a change to the README would have been more appropriate :)

Yeah, I think you can just send a PR to add it :+1:


Unexpected resolving of git repository tag

I was trying to do this
bower.json
{
  "name": "autogenerated",
  "dependencies": {
    "lodash": "git@github.com:lodash/lodash.git#4.0.0-npm-packages",
  },
  "resolutions": {
    "lodash": "git@github.com:lodash/lodash.git#4.0.0-npm-packages",
  }
}

I was expecting to get repository contents at tag "4.0.0-npm-packages". However, instead of that I seemingly ended up with repository contents at branch "npm-packages". Quickly thinking I'm not sure what goes wrong with that.
Context:

https://github.com/kikonen/bower_vendor/issues/8

=> duh! my own mistake


update nfft to 3.3.1

This is the most recent NFFT release.  make check now requires cunit

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

Looks like some of the OSX tests are failing:
../.libs/libnfft3_threads.dylib -L/Users/travis/miniconda3/envs/_build/lib /Users/travis/miniconda3/envs/_build/lib/libfftw3_threads.dylib /Users/travis/miniconda3/envs/_build/lib/libfftw3.dylib -lpthread -lm /Users/travis/miniconda3/envs/_build/lib/libcunit.dylib -L/Users/travis/miniconda3/conda-bld/work/CUnit-2.1-3/CUnit/Sources -lc -lncurses -fopenmp
ld: warning: directory not found for option '-L/Users/travis/miniconda3/conda-bld/work/CUnit-2.1-3/CUnit/Sources'
/Applications/Xcode.app/Contents/Developer/usr/bin/make  check-TESTS
../config/test-driver: line 95: 22961 Trace/BPT trap: 5       "$@" > $log_file 2>&1
FAIL: checkall
../config/test-driver: line 95: 22981 Trace/BPT trap: 5       "$@" > $log_file 2>&1
FAIL: checkall_threads
Making all in data
make[6]: Nothing to be done for `all'.
make[6]: Nothing to be done for `all-am'.
============================================================================
Testsuite summary for NFFT 3.3.1
============================================================================
# TOTAL: 2
# PASS:  0
# SKIP:  0
# XFAIL: 0
# FAIL:  2
# XPASS: 0
# ERROR: 0
============================================================================
See tests/test-suite.log
Please report to<EMAIL_ADDRESS>============================================================================
make[4]: *** [test-suite.log] Error 1
make[3]: *** [check-TESTS] Error 2
make[2]: *** [check-am] Error 2
make[1]: *** [check-recursive] Error 1
make: *** [check-recursive] Error 1
Command failed: /bin/bash -x -e /Users/travis/build/conda-forge/nfft-feedstock/recipe/build.sh

i can reproduce locally on a laptop with osx.  The failures are due to CUnit not being found properly.  If I look in the test logfile, the errors are:
FAIL: checkall
==============

dyld: Library not loaded: @rpath/libcunit.1.dylib
  Referenced from: /Users/lee8rx/anaconda/conda-bld/work/nfft-3.3.1/tests/.libs/checkall
  Reason: image not found

FAIL: checkall_threads
======================

dyld: Library not loaded: @rpath/libcunit.1.dylib
  Referenced from: /Users/lee8rx/anaconda/conda-bld/work/nfft-3.3.1/tests/.libs/checkall_threads
  Reason: image not found

There is also a related warning that occurs earlier:
ld: warning: directory not found for option '-L/Users/lee8rx/anaconda/conda-bld/work/CUnit-2.1-3/CUnit/Sources'

I probably just need to make sure it is linking to ~/anaconda/envs/_build/lib/ which does contain the cunit libraries

@pelson
The problem with make check was related to @rpath.  So far, the workaround I came up with and tested locally is to modify LDFLAGS via
LDFLAGS="$LDFLAGS -Wl,-rpath,${PREFIX}/lib"

prior to calling configure.  Is this an acceptable solution or might it have undesired effects?  (I have minimal familiarity with resolving rpath issues).
I am not sure how to only modify the rpath only for the two binaries generated by make test.  The two files that need the rpath fix to run are:  $SRC_DIR/tests/.lib/checkall and $SRC_DIR/tests/.lib/checkall_threads.  However these are both generated and run by make check so there doesn't seem to be a way to modify them after they are built but before they are run.

So long as your recipe adds a comment along those lines, I think it is perfectly reasonable to set the RPATH in that way. 👍

Just FYI, there are some build difficulties ATM ( https://github.com/conda-forge/staged-recipes/issues/613 ). So, if some things don't build here and you need them ASAP, you could try pinning the use of conda-build to 1.20.1 or earlier.


Hyprlock does not follow display scaling on Sway

Regression?
No
Hyprlock Info and Version
v0.4.1
 Hyprlock config
background {
  blur_passes=3
  blur_size=8
  path=screenshot
}

general {
  hide_cursor=true
  no_fade_in=false
}

input-field {
  monitor=
  size=200, 50
  dots_center=true
  fade_on_empty=false
  font_color=rgb(202, 211, 245)
  inner_color=rgb(91, 96, 120)
  outer_color=rgb(24, 25, 38)
  outline_thickness=5
  placeholder_text=Password...
  position=0, -80
  shadow_passes=2
}

Compositor Info and Version
 System/Version info
sway 1.9

Description
I set sway to scale my monitor *2, however, hyprlock is not respecting that and displaying only in the lower quarter of my monitor. This is the case as soon as any scaling is being used in sway.
How to reproduce
Set sway to scale a display and use hyprlock.
Crash reports, logs, images, videos
logs.txt

Thanks for the quick response!
I get the following error tho:
╰─>$ nrun github:hyprwm/hyprlock/9393a3e94d837229714e28041427709756033f5a
[CRITICAL] Hyprlock threw: EGL_EXT_platform_base not supported

also occurs on HEAD and v0.4.1

Using nix run will use the nixpkgs version that flake.lock in the hyprlock repo specifies.
That leads to mesa version mismatches with your system. You need to build it with the nixpkgs version you currently use on your system.
AFAIK easiest way to test it out is to clone hyprlock, then use nix flake lock --override-input nixpkgs github:Nixos/nixpkgs/<your nixpkgs hash> and then you can nix run .

Seems to work perfectly, thanks a lot for your help!
Could it makes sense to add the run instruction to the readme ? --override-input can also be used on nix run, so nix run github:hyprwm/hyprlock --override-input nixpkgs nixpkgs (to use the system nixpkgs).

Could it makes sense to add the run instruction to the readme ? --override-input can also be used on nix run, so nix run github:hyprwm/hyprlock --override-input nixpkgs nixpkgs (to use the system nixpkgs).

Idk if it fits in the README of hyprlock, since it is very nix specific.
But I actually did not know that nix run also accepts --override-input.
That is cool :)

I'll add such info in the wiki, if I remember to. PRs are also welcome.