Manage dataURI for annotationurl attribute?

We tried to configure a <iiif-storyboard> component with a dataURI like data:application/json;base64,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 in the annotationurl attribute.
But it does not work :-(
Is there a way to pass annotations as "raw json" to the <iiif-storyboard> component ? (because our annotations are not served over http).
If not, what do you think about managing dataURI for annotationurl attribute ? (we can try to contribute this feature with a PR if you are ok)

@sebprunierserli You can serve "raw" json with the application. I think the idea of of a dataURI is also interesting but I have included an example with raw json below. Is dataURI still of interest to you?

I added dataURIs.

Thanks a lot for your help. And thanks also for the fix concerning the dataURI !
Everything works fine for us now.

@sebprunierserli Glad I could help. Please let me know if you have any links you can share with me, I would love to add some examples to our in the wild page. If you don't feel comfortable with that I would love any links you would be able to send me just to be able to see how the tool is being used.

@GGoetzelmann  If you remove the everything before base64, it should work. So if you have base64,[datauri];base64,[datauri];base64,[datauri] it will render.


Runtime: Use system.tables instead of information_schema.tables for clickhouse OLAP queries

Clickhouse playground allows access to system.tables but blocks access to information_schema.tables. We can route our information_schema queries to system.tables instead to make our integration work with clickhouse playground.
Current Query:
SELECT
	T.table_schema AS SCHEMA,
	T.table_schema = currentDatabase() AS is_default_schema,
	T.table_name AS NAME,
	T.table_type AS TABLE_TYPE,
	C.column_name AS COLUMNS,
	C.data_type AS COLUMN_TYPE,
	C.ordinal_position as ORDINAL_POSITION
FROM information_schema.tables T
JOIN information_schema.columns C ON T.table_schema = C.table_schema AND T.table_name = C.table_name
WHERE lower(T.table_schema) NOT IN ('information_schema', 'system')
ORDER BY SCHEMA, NAME, TABLE_TYPE, ORDINAL_POSITION

Updated Query:
SELECT
    T.database AS SCHEMA,
    T.database = currentDatabase() AS is_default_schema,
    T.name AS NAME,
    if(lower(T.engine) like '%view%', 'VIEW', 'TABLE') AS TABLE_TYPE,
    C.name AS COLUMNS,
    C.type AS COLUMN_TYPE,
    C.position AS ORDINAL_POSITION
FROM system.tables AS T
INNER JOIN system.columns AS C ON (T.database = C.database) AND (T.name = C.table)
WHERE lower(T.database) NOT IN ('information_schema', 'system')
ORDER BY
    SCHEMA ASC,
    NAME ASC,
    TABLE_TYPE ASC,
    ORDINAL_POSITION ASC

NOTE :

It is possible that some other hosting or clickhouse playground in future blocks access to system.tables as well. Relevant configs : https://github.com/ClickHouse/ClickHouse/pull/38970
It is also possible that some users give access to information_schema but blocks access to system.
The type for both queries are not equivalent. The table types can have multiple values for information_schema.tables like BASE TABLE, FOREIGN TABLE etc. For simplicity I just kept TABLE and VIEW in new query.

Update : A few system tables (tables, columns, databases, and some constant tables like one, contributors) are accessible for everyone


[Bug]-[1191]:Scroll is not working on swapping columns position when some of the column focus are out of the viewport

Is there an existing issue for this?

[X] I have searched the existing issues

Current Behavior
It is observed that on the table property pane when some of the columns are outside of viewport and upon try to swap the columns below/top the scroll does not work
https://loom.com/share/80abebc67fa744c4825e47cc2332ebf0
Steps To Reproduce

Launch appsmith app in release environment
Drag and drop table widget
Open property pane
Add a few more columns
Keep the table property focus where few columns can be visible and few outside the viewport
Try to swap/ repositioning the column from top to bottom and observe the scroll is not functional

Environment
Release
Version
Cloud

I think there's already an issue for this. Let me see if I can find it.

Stats
Calculated the reach by looking at users who have updated the columnOrder in the Table widget.

Stat
Values

Reach
1191

Effort (months)
0.5

I am closing this issue because it is not reproducible in production right now.


Migrate from CircleCI to Github Actions

Summary
The PR build (CI) is a reusable required workflow
Ticket Link
Ticket: https://mattermost.atlassian.net/browse/CLD-4816

Codecov Report

:exclamation: No coverage uploaded for pull request base (main@d4782ea). Click here to learn what that means.
Patch has no changes to coverable lines.

Additional details and impacted files
@@           Coverage Diff           @@
##             main       #8   +/-   ##
=======================================
  Coverage        ?   39.28%
=======================================
  Files           ?        3
  Lines           ?      140
  Branches        ?        0
=======================================
  Hits            ?       55
  Misses          ?       84
  Partials        ?        1

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

:umbrella: View full report at Codecov.
:loudspeaker: Do you have feedback about the report comment? Let us know in this issue.

https://github.com/mattermost/mattermost-plugin-link-filter/issues/9

thanks @hanzei


Add SPM support, update Quick/Nimble and codecov.yml

Add support for Swift Package manager (#21)
Update codecov.yml
Update Quick and Nimble versions for Swift 5
Delete CODEOWNERS file
Some general test cleanup

Codecov Report

Merging #27 into master will not change coverage.
The diff coverage is n/a.

@@          Coverage Diff          @@
##           master    #27   +/-   ##
=====================================
  Coverage     100%   100%
=====================================
  Files           3      3
  Lines         237    237
=====================================
  Hits          237    237


Compact Progress Bar in React Bootstrap

As an engineer, I want to have the compact progress bar available in React Bootstrap, so I can use it in my application.

@enowak1031
preview
https://deploy-preview-166--modus-react-bootstrap.netlify.app/components/progress-bars/

@msankaran0712
In API table for bsprefix description is missing but it is present in the https://react-bootstrap-v4.netlify.app/components/progress/

@msankaran0712
In API table for bsprefix description is missing but it is present in the https://react-bootstrap-v4.netlify.app/components/progress/

Good observation. We should be good with it, for now, we will upgrade the React-bootstrap library really soon so this will be fixed automatically.

@enowak1031 @msankaran0712 Verified this ticket. Hence moving it to PO review

Closing the issue as it already done.


Document Upload Function - Lambdas

Linked to #280

Lambda Submission Function

Little change should be necessary...
Ensure file urls are passed through to DynamoDB formData

Reliability Queue Lambda

Little changes in main code body
Ensure file urls are passed through to Notify and Vault processing functions

Notify processing function (Reliability Lambda lib)

Read up on Notify's file attachment API structure: Notify API
Fetch appropriate files from S3 storage and process into type required by Notify (base64 encoded string)
On successful submission to Notify delete files from S3.

Vault processing function (Reliability Lambda lib)

Read files from S3 and move to Vault S3 storage
Delete files from temporary storage

Reopening because even if the PR has been merged we are still testing and debugging live in staging


Onboarding progress indicator - repository level

Related to #5675

After discussing with @eladlachmi about the onboarding progress indicator in a BI perspective I understand we currently plan to collect 'preflight' checks events.
In addition to these events, can we also collect different stages of the widget lifecycle events? e.g widget had appeared, opened, dismissed.
@ozkatz @itaiad200 FYI

After discussing with @eladlachmi about the onboarding progress indicator in a BI perspective I understand we currently plan to collect 'preflight' checks events. In addition to these events, can we also collect different stages of the widget lifecycle events? e.g widget had appeared, opened, dismissed. @ozkatz @itaiad200 FYI

Thanks @NoyDavidson2 & @eladlachmi! Is the plan to add 'preflight' checks events in this PR or later on? About widget lifecycle events, do we collect UI events today (asking since I think it's a new, quite intrusive, information).

After discussing with @eladlachmi about the onboarding progress indicator in a BI perspective I understand we currently plan to collect 'preflight' checks events. In addition to these events, can we also collect different stages of the widget lifecycle events? e.g widget had appeared, opened, dismissed. @ozkatz @itaiad200 FYI

Thanks @NoyDavidson2 & @eladlachmi! Is the plan to add 'preflight' checks events in this PR or later on? About widget lifecycle events, do we collect UI events today (asking since I think it's a new, quite intrusive, information).

@itaiad200 The preflight events were already added, similarly to other endpoints.
However, this doesn't provide us with any information regarding if/how the checklist is used. We can measure secondary effects and attribute all or part of growth to this checklist. However, that's not the same as measuring interaction with the checklist.
We don't currently measure client-side interactions directly AFAIK. It would be helpful if we did, but as you mentioned, we need to discuss if and how we want to implement this.

After planning today: please open a tech debt issue to determine whether import has occurred without looking for an import branch. That branch is deprecated and going away!

After planning today: please open a tech debt issue to determine whether import has occurred without looking for an import branch. That branch is deprecated and going away!

The issue created by @N-o-Z to resolve this can be found here


 It is only the short description on the first line that should be lowercased :-)
I.e., instead of

vim doesn't have unset function. To turn off an option vim uses "no" prefix.

it should say

Vim doesn't have unset function. To turn off an option vim uses "no" prefix.

Oh, sorry. I just noticed that your commits are having paluh<EMAIL_ADDRESS>as author and this doesn't seem to match what is set in your GitHub account. Is this intentional? If it is not, then I think you need to configure Git and redo these three commits.

Sorry @rycee for this mess! I'm going to configure git properly (on my new Nix machine ;-)), fix these commits and ping you back!

I hope that everything is cleaned now...

I'm closing this as there is API change on the way - #69...


tri 2 retrospective

link to post
link to vid

Grade: 0.94/1
Feedback:

Maybe some more images of the code
Some more orginization to the page

Otherwise pretty good, video explains a lot and takes care of the visual represenation in the blog.


Too much graphics memory!

RuntimeError: CUDA out of memory. Tried to allocate 12.44 GiB

I also encountered this problem,how to solve this problem?

What's the size of your image? Maybe try the cpu mode? It only takes a few seconds for 1280x853 image on i7-9700K.

@bryandlee 为什么使用GPU运行test.py都显示gpu显存不够，但是使用cpu就可以呢？我的gpu显存是12G的


[Addition]: 2 new deeper hotspot circles, only communicating with eachother

Hotspot b58 Addresses
Circle 1:
112WJL4c6skuLnBuxbv3xo1VzHfw8hsq8MUAJBBGq2TzYvPkccPx
1123KkRyjFXYvSqV2sf2mK6nAW4S1VRcSFoDhAGRj4wiK3scfauL
112VJ9PT4GojSRX8rZ2RaNG9mxp6RZxfiKwK5KeURAEiVm4K6mpr
112NVT4JzD5kzorjxA9XfPfGb2HSc3chesomrLiTZ5Qdp5KLteVu
1128LjDW2yu85PEH1ZDtVFbp4vWmqfLLB4kk7jQrMH3DRWFCcYtR
Circle 2:
112mieyD56Q2fyweLeDrjdzxYu4uREeW2Q5BY6UbHMhZ9fQjrBqW
1126eJVQCvXvS9sVHDeBjKyitvGS3MMK2q67qog73GfMxE4AL2DA
112UCm8EzHbXjFQoCiJtNyz3micYqf5cNwzuTKFNbxaevi4w3pYS
112EMixzjB5aAUAswx1TFNzk5yK6cBhF9pwjawVPw7K1gUnMmkq7
Discord Handle
MrStark2301
Reason(s)
all from maker deeper, only communicate with each other altough there are legit and reachable hotspots from other makers, all of them where added nearly on the same day.

Exact same problem here in Bourges (France)
https://github.com/helium/denylist/issues/2300

they appear all over the world at the moment and all of them where added inbetween 48h and everewhere you see the same thing, only transmitting between them and not communicating to other legit hotspsots with good rssi´s ect....

I want to know what's being done about it? It's been going on for a long time now. Makes me want to either sell all my gear while it still has some value, or figure out how to game too. If you can't beat them join them! lol

I want to know what's being done about it? It's been going on for a long time now. Makes me want to either sell all my gear while it still has some value, or figure out how to game too. If you can't beat them join them! lol

i love you said, cant beat them then join them, haha , totally agreed

All hotspots have been included in
https://github.com/helium/denylist/pull/2471
--> You can close

Perfect! Thank you!!


Remove track tab and rounded corners

This PR's goal is to gain vertical real-estate by removing track tabs in
favor of a track header that is now aligned with tracks, to their left.
This is also similar to how most track UI applications display tracks.
Note that there are many things we could do to enhance the look of
tracks, like fine tuning text and collapsible arrow position, coloring on
hover, better separation of header and track. All those changes are
welcome but outside the scope of this PR. This basically takes our existing
tabs and moves them to the left of the tracks.

Does the accessibility for all elements still work correctly?

@reichlfl , it looks like it:

Does the accessibility for all elements still work correctly?

@reichlfl , it looks like it:

Cool, thanks for checking! Can you check the TimerPane as well? That should be the area which only contains the timers, it might now span the whole track. That would probably be an easy fix within the AccessibleTrack implementation - if not, I also think it's not a big deal because the tests (AFAIK) only test for existence, not exact extents of this.

I can't judge how this looks for sub-tracks, could you provide a screenshot?

@reichlfl , @florian-kuebler , how can I test this? Memory track?

One more thing: The labels in the timers in your screenshot seem to start before the actual timer box. Is that an unrelated bug or could this be triggered by your margin changes?

@beckerhe , I noticed that too, but this is unrelated to this change. I think this comes from the Qt text rendering change, I've noticed other artifacts like text overlapping sometimes.

Memory track is probably the easiest, yes

@reichlfl , the memory track seems a bit broken, thanks for pointing this out, will fix soon. Cheers!

The memory track issue was the legend being drawn outside the track, it is fixed now:
file:///home/pierric/Pictures/Screenshots/mem_track.png
I still have to check for track that contain children, not sure how to do that easily, I'll try setting up a hierarchy in code.

@reichlfl , @florian-kuebler, I don't see how I can test subtracks on a generic Linux capture, would you know how? Would you have some test data perhaps, or maybe you could compile this branch and test on your side? Thanks.

https://github.com/google/orbit/blob/main/contrib/automation_tests/testdata/OrbitTest_1-72.orbit could be a good example.
But, Ill also check the gpu tracks tomorrow.

Thanks for checking @reichlfl . I'll try out the data and fix the issues. Concerning the big headers, I also found the same at first, but got really accustomed to it using other tools that have this layout. I think it might be a great place to put extra information about track stats too. One thing I want to add is the ability to resize the header part, so we could go from what is suggested to what you are suggesting when minimizing the header width.

One thing I want to add is the ability to resize the header part, so we could go from what is suggested to what you are suggesting when minimizing the header width.

But then why scraping out the current header, when we are going to add it back again? Maybe we should collect a bunch of screenshots from other tools with this track like format, and see if we find a common sense (as said, I am a big fan of reducing vertical gaps). I looked at tools like final cut pro (which has the header) and fruity loops (which has the left part, but much smaller).

Just for reference. This is how a more condensed ui with the current implementation logic could look like:

I made all the gaps smaller, removed the rounding, reduced the size of the triangle and shifted the header to the left (including reducing the width).

Also, I extracted the property controls from here to https://github.com/google/orbit/pull/4600, as it is nice for testing/playing around.

@florian-kuebler , thanks looking into this, I'll fix the remaining issues with the left headers. And then we can compare the different  approaches.

@reichlfl , @florian-kuebler , the PR is in a better state, I'd love to get your feedback. Thanks!

@reichlfl , @florian-kuebler , the PR is in a better state, I'd love to get your feedback. Thanks!

Thanks. I'll have a look and test it tomorrow.

Thanks for the capture @ronaldfw!

Thanks for the changes so far. I played around with the current state, and mostly like it.
Despite my comment on the TrackHeader::GetHeight method, which I think must be resolved, I found three remaining bugs:

If you expand the GpuTrack and then collapse the submission subtrack, the header position is off (see screenshot). The same happens, if the submissions only have a depth of 1.

Similarly, if you have a track with gpu debug markers and have that one collapsed, the position of the header is also off:

If you have empty thread tracks, that only have thread state, there is a spacing at the bottom missing:

Also, I do like the new indicators for expand/collapse. I am wondering whether they should be swapped, however. @reichlfl what are your thoughts on that?
Finally, I would decrease the width of the header from 350 to 250.

Hi @florian-kuebler , thanks for your comments. I fixed 1, 2 and 3. I didn't want to spend too much time on 2 as I think the subtracks should be completely overhauled in favor of a full track hierarchy where subtracks are treated as full-fledged tracks, with their own header. Thanks again for your reviews.

I am wondering whether they should be swapped, however

Apparently the current version is also what the latest Material UI accordion elements use. Even though I find this confusing, I guess we should stick with it. To be sure: "arrow down" means it's currently collapsed, "arrow up" means it's expanded, right?

@reichlfl , @karupayun, thanks for the review and comments, I'll address them soon, I might revert the arrows for now too. As pointed out, they seem to render weirdly sometimes. I don't fully understand why, but it seems primitives are sometimes off by one pixel.

@reichlfl , @karupayun, @florian-kuebler , I addressed most of the comments. Concerning the GPU subtracks issue, is that blocking? I feel like it might be faster if someone who knows the code better implemented a quick fix rather than going back and forth...  Also, I rebased this change in another PR if you want to see it with the latest UI changes. thanks for your help!

The green line with the mouse can be seen a bit more to the left than the content, do you know why is that?

N/A in the rebase branch, and I couldn't repro on Windows weirdly.

The toggles of the subtracks seems a bit broken.

Reverted, the ceiling code was the reason behind the weirdness.

The title of the FrameTrack intersect with the average time in the most common case, could you move this line to be only drawn in the content part?

fixed

Thanks for addressing the comments. I think it looks good now, but I want to do another full review. Shall I do it here, or at the #4727 pr?

Closing as https://github.com/google/orbit/pull/4727 supersedes this PR.


[Feature]: Allow putting pages under namespaces (that are in same list as modules in generated documentation)

Plugin
@knodes/typedoc-plugin-pages
What would you want ?
Example repo: https://github.com/Hi-Fi/typedoc-plugins-example/tree/external_pages
When documentation is generated, external page can only be put at main level, not under "module" (which is actually namespace).

If trying to put page under module_2, it's not possible as it's not with moduleRoot as that produces error:
Error: Invalid pages configuration: could not find a workspace named "module_2"

And if just adding empty page, that would duplicate module_2 in list.

Hi,
The whole behavior of pages tree building is currently in a complete rework. Yet, I didn't thought about the ability to put pages in namespaces, or modules in a non-monorepo structure.
Currently, and in the upcoming release, only plain modules in monorepo are searched to attach pages to. This behavior is mainly intended for monorepos containing multiple independent packages. I'll keep this open waiting for some upvotes in order to see if this is a behavior multiple users need, or not.


Kbar style breaks for long post content

Describe the bug
Kbar style breaks for long post content
To Reproduce
See https://dariuszwozniak.net/ or add some long blog titles
Expected behavior
Correct spacing is applied
Screenshots

Tested it on the default one and it works - might be some style clash on the site


adding LogTransform to app causes Duplicate callback output error

When adding the LogTransform as an app transformation:
transforms=[ServersideOutputTransform(backends=[backend_dir]),
                                    LogTransform()]

Upon opening, my app now has a Duplicate callback outputs error, despite not having the error without the transform.
The particular output in question uses a allow_duplicate=True flag as needed.

It is probably related to the recent change in callback structure when allow_duplicate=True flag was added. Could you post a small example demonstrating the issue?

I have the same issue. It came up as I upgraded my project dependencies from 0.1.13 to 1.0.4. It seems that there is an undocumented breaking change in 1.0.0?
Interestingly, I just tried deploying my app with the LogTransform added using 0.1.13 and, while it works on my localhost, I do not see any logging messages on my deploy server.

I have tried replicating the issue with a small example but I am not able to replicate it on a small example. Here is the code I used in an attempt to replicate it:
import secrets
from dash_extensions.enrich import (
    DashProxy,
    LogTransform,
    Input,
    Output,
    State,
    DashLogger
)
from dash import dcc, html, no_update
import flask

server = flask.Flask(__name__)
app = DashProxy(
    transforms=[
        LogTransform(),
    ],
    external_stylesheets=[],
    server=server,
)

app.server.secret_key = secrets.token_urlsafe(16)

app.layout = html.Div([
    dcc.Input(id='text_input'),
    html.Button("Click me", id="input_button"),
    html.Button("Click me 2", id="input_button2"),
    html.H2(id="output_region")
])

@app.callback(
        Output("output_region", "children", allow_duplicate=True),
        State('text_input', 'value'),
        Input("input_button", "n_clicks"),
        prevent_initial_call=True,
        log=True,
    )
def callback1(
    input_text: str,
    button_clicks: int,
    dash_logger: DashLogger
    ):
    if not input_text:
        dash_logger.warning("Please input some text value before clicking")
        return no_update
    return input_text

@app.callback(
        Output("output_region", "children", allow_duplicate=True),
        State('text_input', 'value'),
        Input("input_button2", "n_clicks"),
        prevent_initial_call=True,
        log=True,
    )
def callback2(
    input_text: str,
    button_clicks: int,
    dash_logger: DashLogger
    ):
    if not input_text:
        dash_logger.warning("Please input some text value before clicking")
        return no_update
    return input_text

# Run App
if __name__ == "__main__":
    app.run(debug=True)

The app that I am running is a fairly large multi-page application. The outputs that triggered the error were not, in fact, duplicate outputs. Still, I added the allow_duplicate=True argument but it has no effect.
The other thing that I found interesting about the callbacks that triggered the error is that they are on two of my sub-pages which are fairly deep into the application. I thought that the error would have been triggered by one of my earlier callbacks.

Should be fixed in the 1.0.12 release.

The issue still appears to occur, I will try to develop another MRE to indicate

@emilhe, I might be mistaken but I think adding allow_duplicate=True to Outputs in 1.0.12 didn’t help for reasons well described in this issue: https://github.com/plotly/dash/issues/2486
In my particular situation, I have two callbacks that share the same Inputs but had different Outputs, which works fine. However, after adding log=True to those callbacks, they now share the notification_provider Output with the same uid, which now does cause the “Duplicate callback outputs” issue.
I've been trying to make the log_id unique inside setup_notifications_log_config() and wasn't successful yet, but maybe that's a step in right direction?


Follow up on multiple UEs registration and other topics

Hello,
Following the guidance you have provided me about increasing the UPF's buffer size, it seems it worked fine to register 100 UEs. My problem was, indeed that I needed to "make UPF" again so many thanks for this, in Free5GC they do not specify this.
Following with this subject, I have been assinged to study Free5GC capabilities, one of them is to study its limits in terms of the number of UEs registrated that it can support. Since it seems that increasing such buffer increases the maximum number of UEs allowed, my question is this: Have you got to any conclusion abouta maximum number of UEs that can be registered? What about the maximum number of UEs to be registered at the same time? I do not know if I will get to a conlcussion if I just keep rising the buffer and the number of UEs to register, both simultaneously and consecutively.
On the other subject I commented in the forum with you, I'm trying to conect the core network to internet, first with a single ping to, for instance, Google DNS (<IP_ADDRESS>). I have tried to put such address in the config file but I do not get a response. I guess something is wrog with my network configuration but I cannot find my error. The following script is used in my run.sh for the core network where you can see how I create and delete my network interfaces and iptables . My laptopt local IP address is <IP_ADDRESS> in the wlp2s0 interface:
sudo ifconfig eno1:amf <IP_ADDRESS> up
sudo ifconfig eno1:gnbn <IP_ADDRESS> up
sudo ifconfig eno1:smfp <IP_ADDRESS> up
sudo ifconfig eno1:upfp <IP_ADDRESS> up
sudo ifconfig eno1:gnbg <IP_ADDRESS> up up
sudo ifconfig eno1:upfg <IP_ADDRESS> up
sudo ifconfig eno1:ue <IP_ADDRESS> up
sudo sysctl -w net.ipv4.ip_forward=1
sudo iptables -t nat -A POSTROUTING -s <IP_ADDRESS>/24 -j SNAT --to-source <IP_ADDRESS>
sudo systemctl stop ufw
Then I only change amfcfg.config, smfcfg.config and upfcfg.yaml according such interfaces.
amfcfg.config:
configuration:
amfName: AMF
ngapIpList:
- <IP_ADDRESS>
smfcfg.config:
pfcp:
addr: <IP_ADDRESS>
userplane_information:
up_nodes:
gNB1:
type: AN
an_ip: <IP_ADDRESS>
UPF:
type: UPF
node_id: <IP_ADDRESS>
links:
- A: gNB1
B: UPF
ue_subnet: <IP_ADDRESS>/16
upfcfg.yaml:
pfcp:
- addr: <IP_ADDRESS>
gtpu:
- addr: <IP_ADDRESS>
# [optional] gtpu.name
# - name: upf.5gc.nctu.me
# [optional] gtpu.ifname
# - ifname: gtpif
dnn_list:
- dnn: internet
cidr: <IP_ADDRESS>/24
# [optional] dnn_list[*].natifname
natifname: wlp2s0
With all this setup I have read in the forums I should be able to get a ping to internet, but it doesn't seem to work. I cannot even ping to my gateway <IP_ADDRESS>. Any ideas on this?
Something which I have found these last days is that if I read the traffic with Wireshark passing through these interfaces it  does not catch anything, all the traffic seems to go through the loopback interface but I do not understand why since if I do not create such interfaces the core does not start properly. the following shows my ifconfig:
eno1: flags=4099<UP,BROADCAST,MULTICAST>  mtu 1500
ether b8:ca:3a:d7:5b:82  txqueuelen 1000  (Ethernet)
RX packets 0  bytes 0 (0.0 B)
RX errors 0  dropped 0  overruns 0  frame 0
TX packets 0  bytes 0 (0.0 B)
TX errors 0  dropped 0 overruns 0  carrier 0  collisions 0
device interrupt 20  memory 0xf7e00000-f7e20000
eno1:amf: flags=4099<UP,BROADCAST,MULTICAST>  mtu 1500
inet <IP_ADDRESS>  netmask <IP_ADDRESS>  broadcast <IP_ADDRESS>
ether b8:ca:3a:d7:5b:82  txqueuelen 1000  (Ethernet)
device interrupt 20  memory 0xf7e00000-f7e20000
eno1:gnbg: flags=4099<UP,BROADCAST,MULTICAST>  mtu 1500
inet <IP_ADDRESS>  netmask <IP_ADDRESS>  broadcast <IP_ADDRESS>
ether b8:ca:3a:d7:5b:82  txqueuelen 1000  (Ethernet)
device interrupt 20  memory 0xf7e00000-f7e20000
eno1:gnbn: flags=4099<UP,BROADCAST,MULTICAST>  mtu 1500
inet <IP_ADDRESS>  netmask <IP_ADDRESS>  broadcast <IP_ADDRESS>
ether b8:ca:3a:d7:5b:82  txqueuelen 1000  (Ethernet)
device interrupt 20  memory 0xf7e00000-f7e20000
eno1:smfp: flags=4099<UP,BROADCAST,MULTICAST>  mtu 1500
inet <IP_ADDRESS>  netmask <IP_ADDRESS>  broadcast <IP_ADDRESS>
ether b8:ca:3a:d7:5b:82  txqueuelen 1000  (Ethernet)
device interrupt 20  memory 0xf7e00000-f7e20000
eno1:ue: flags=4099<UP,BROADCAST,MULTICAST>  mtu 1500
inet <IP_ADDRESS>  netmask <IP_ADDRESS>  broadcast <IP_ADDRESS>
ether b8:ca:3a:d7:5b:82  txqueuelen 1000  (Ethernet)
device interrupt 20  memory 0xf7e00000-f7e20000
eno1:upfg: flags=4099<UP,BROADCAST,MULTICAST>  mtu 1500
inet <IP_ADDRESS>  netmask <IP_ADDRESS>  broadcast <IP_ADDRESS>
ether b8:ca:3a:d7:5b:82  txqueuelen 1000  (Ethernet)
device interrupt 20  memory 0xf7e00000-f7e20000
eno1:upfp: flags=4099<UP,BROADCAST,MULTICAST>  mtu 1500
inet <IP_ADDRESS>  netmask <IP_ADDRESS>  broadcast <IP_ADDRESS>
ether b8:ca:3a:d7:5b:82  txqueuelen 1000  (Ethernet)
device interrupt 20  memory 0xf7e00000-f7e20000
lo: flags=73<UP,LOOPBACK,RUNNING>  mtu 65536
inet <IP_ADDRESS>  netmask <IP_ADDRESS>
inet6 ::1  prefixlen 128  scopeid 0x10
loop  txqueuelen 1000  (Local Loopback)
RX packets 202863  bytes<PHONE_NUMBER> (1.0 GB)
RX errors 0  dropped 0  overruns 0  frame 0
TX packets 202863  bytes<PHONE_NUMBER> (1.0 GB)
TX errors 0  dropped 0 overruns 0  carrier 0  collisions 0
upfgtp: flags=4305<UP,POINTOPOINT,RUNNING,NOARP,MULTICAST>  mtu 1500
inet6 fe80::1b10:b665:a53c:a039  prefixlen 64  scopeid 0x20
unspec 00-00-00-00-00-00-00-00-00-00-00-00-00-00-00-00  txqueuelen 1000  (UNSPEC)
RX packets 100  bytes 7600 (7.6 KB)
RX errors 0  dropped 0  overruns 0  frame 0
TX packets 100  bytes 4800 (4.8 KB)
TX errors 10  dropped 0 overruns 0  carrier 0  collisions 0
wlp2s0: flags=4163<UP,BROADCAST,RUNNING,MULTICAST>  mtu 1500
inet <IP_ADDRESS>  netmask <IP_ADDRESS>  broadcast <IP_ADDRESS>
inet6 fe80::da1d:331e:54da:adab  prefixlen 64  scopeid 0x20
ether 3c:a9:f4:0c:cd:84  txqueuelen 1000  (Ethernet)
RX packets 39376  bytes 22515176 (22.5 MB)
RX errors 0  dropped 17  overruns 0  frame 0
TX packets 14098  bytes 3148792 (3.1 MB)
TX errors 0  dropped 0 overruns 0  carrier 0  collisions 0
Again thank you very much for the help offered.

Hi sorry for the delay answer. What test of my5G RAN Tester are you using? Can you please show a pcapng(with icmp and gtp) or log? It will help we understand better the problem

Hi, here is the pcap from Wireshark when pinging <IP_ADDRESS>. You cant see no reply is recieved. If I change ping address to <IP_ADDRESS> whcih is supposed to be my router address, it does not get a reply either. I only gets reply to my local machine (laptop) 192.168.60 or other UE preconfigured <IP_ADDRESS>.
I cannot upload the pcap file so I have uploaded into googledrive so you can download it and check it if you wish to.
https://drive.google.com/file/d/1DZ8fKDUXSQdz1KrSZ3hMlnovBf829ENj/view?usp=sharing, https://drive.google.com/file/d/1zswTx98zHRCw2WhL8yLcL4MY338bYbfH/view?usp=sharing
Thank you

Hey classo88, sorry for the delay answer. Can you check this page https://github.com/my5G/my5G-RANTester/wiki/Using-containers and testing m5G-RANTester with containers. I think that will solve your problem because we will use  the same environment and here works fine(with large number of ues too).

Hey classo88, sorry for the delay answer. Can you check this page https://github.com/my5G/my5G-RANTester/wiki/Using-containers and testing m5G-RANTester with containers. I think that will solve your problem because we will use  the same environment and here works fine(with large number of ues too).


Add missing toString() to GrpcConnectionKey

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alluxio-bot, merge this please

alluxio-bot, cherry-pick this to branch-2.2 please


⚠ PrivateHD has degraded performance

In 1bcefcf, PrivateHD ($PHD) experienced degraded performance:

HTTP code: 200
Response time: 1869 ms

Resolved: PrivateHD performance has improved in 7053057.


Check StorageConfig's sequence for both OCI and non-oci cases, since …

…metadata is used in both

/lgtm

/label bugzilla/valid-bug
/label valid-bug

/label jira/valid-bug

This PR is a duplicate of #649
Closing in favor of that PR


How much parallel speedup is there on multicore CPUs?

How much parallel speedup is there? None? Or a bit? Or full support?
Also how much effort would it be to rewrite the library in with parallel support?
PS: very impressed with the Rasterific library! Fantastic! Also because there is not so much documentation on gezira that I found. Even more impressive.

Right now, absolutely none. The biggest bottleneck is the edge sample: sorting
What could be parallelized easily:

Composition, after the sorting, all CoverageSpan can be applied to the canvas
in parallel
Primitive decomposition, but the cost to recombine them before sorting
could be high

Maybe sorting in parallel could be done, but tuning performance can be tricky. A word of warning though, lists are used lazily across the library, and changing allocation/storage can also be tricky.

I am closing this issue as this is at the moment more a feature request than a bug.
See also the discussion on reddit.


[QA] FIX Minor bug in test framework

Reviewers
@jesuspg
Description
FIX Minor BUG when XML response is empty.
Tested
Locally

LGTM


ULP support for ESP32-S3  (IDFGH-7564)

As per the article, https://www.esp32.com/viewtopic.php?t=21906, which lists the status of various ESP-IDF features on ESP32-S3; ULP coprocessor is Not supported.
We would like to know when this support will be enabled as we are migrating from esp32 to esp32-s3 and our current esp32 based design use ULP for ADC wakeup in deep sleep mode.
Any alternate suggestions for the same use case will also be highly appreciated.

Hi,
Basic ULP support for S3 is already merged to our internal master branch, and will be available the next time our internal branch is synced to Github

Thank you @ESP-Marius. Will you be able to share a timeline on when this will be available on the Github?

Looks like it synced this weekend, so it's possible to use the S3 ULP now. There is no example for using ADC from the ULP at the moment though, but I'm planning to work on adding one for the ULP-Riscv this week.
Are you looking at using the ULP-FSM or the ULP-Riscv core?

Thank you @ESP-Marius . Sorry for the delay in response. Currently we are referencing the ULP-FSM ADC eg. But we are open to using the ULP-Riscv provided we can use the ADC.
Are the changes available in the stable/release/pre-release branches or the current master branch(4.3.3)?

An example of using the ADC ULP-Riscv is under review at the moment and will be available on the latest master when merged. For the ULP FSM there is no ADC example yet (the current example is only tested for the ESP32), but it is on our todo list.
The changes for the ULP are currently only available on the latest master, but a backport for 4.4 is also on the way.

Thanks for reporting, fix on master branch is available at https://github.com/espressif/esp-idf/commit/6cc871d793cbd6f7da9d3dcb276c963ea3a2203f, and on release/4.4 at https://github.com/espressif/esp-idf/commit/f8729d905e9556d17272698fd17d566bba2b0d6d. Feel free to reopen.


CelebHQ sampling

Hi,
I would like to make some samples based on CelebHQ dataset when inferencing. When runing the scripts provided, I got errors saying that the model size mismatched
May I know how to use the CelebHQ checkpoints，how to set parameters in the script?
Thanks a lot.

Hi,
Thank you for your great repository!
However, I also tried to interpolate using the published checkpoints as you did and got the error that the model size is different. I got the error on CelebA64.
I am embarrassed to say that I don't know where to start to fix this and would appreciate your guidance.
Thanks.

Hi, it would be great if you can post some error logs for the same. I will try to run the scripts on my end but this might not be immediately feasible due to limited bandwidth.

Hi,
I noticed there is no command for celebahq in the script named test_ddpm.sh. So I changed the dataset of one of the comands into celebahq like:
python main/eval/ddpm/sample.py +dataset=celebahq/test
...
dataset.ddpm.evaluation.chkpt_path='/CIS44/DiffuseVAE-main/checkpoints/diffvae_chq256_form1_loss=0.0361.ckpt' \
But it seems that none of the commands suits for the celebahq.
The error logs are as below:
main/eval/ddpm/sample.py:26: UserWarning: The version_base parameter is not specified.
Please specify a compatability version level, or None.
Will assume defaults for version 1.1
  @hydra.main(config_path=os.path.join(p, "configs"))
/root/.local/share/virtualenvs/DiffuseVAE-main-m2EH8SNx/lib/python3.7/site-packages/hydra/_internal/hydra.py:127: UserWarning: Future Hydra versions will no longer change working directory at job runtime by default.
See https://hydra.cc/docs/1.2/upgrades/1.1_to_1.2/changes_to_job_working_dir/ for more information.
  configure_logging=with_log_configuration,
Global seed set to 0
Error executing job with overrides: ['+dataset=celebahq/test', 'dataset.ddpm.data.norm=True', "dataset.ddpm.model.attn_resolutions='16,'", 'dataset.ddpm.model.dropout=0.0', 'dataset.ddpm.model.n_residual=2', "dataset.ddpm.model.dim_mults='1,2,2,4,4'", 'dataset.ddpm.model.n_heads=1', 'dataset.ddpm.evaluation.guidance_weight=0.0', 'dataset.ddpm.evaluation.seed=0', 'dataset.ddpm.evaluation.sample_prefix=gpu_0', "dataset.ddpm.evaluation.device='gpu:0'", 'dataset.ddpm.evaluation.save_mode=image', "dataset.ddpm.evaluation.chkpt_path='/CIS44/DiffuseVAE-main/checkpoints/diffvae_chq256_form1_loss=0.0361.ckpt'", 'dataset.ddpm.evaluation.type=uncond', 'dataset.ddpm.evaluation.resample_strategy=spaced', 'dataset.ddpm.evaluation.skip_strategy=quad', 'dataset.ddpm.evaluation.sample_method=ddim', 'dataset.ddpm.evaluation.sample_from=target', 'dataset.ddpm.evaluation.batch_size=16', "dataset.ddpm.evaluation.save_path='/CIS44/DiffuseVAE-main/data/celebahq'", 'dataset.ddpm.evaluation.n_samples=500', 'dataset.ddpm.evaluation.n_steps=25', 'dataset.ddpm.evaluation.workers=1']
Traceback (most recent call last):
  File "main/eval/ddpm/sample.py", line 87, in sample
    strict=False,
  File "/root/.local/share/virtualenvs/DiffuseVAE-main-m2EH8SNx/lib/python3.7/site-packages/pytorch_lightning/core/saving.py", line 153, in load_from_checkpoint
    model = cls._load_model_state(checkpoint, strict=strict, **kwargs)
  File "/root/.local/share/virtualenvs/DiffuseVAE-main-m2EH8SNx/lib/python3.7/site-packages/pytorch_lightning/core/saving.py", line 201, in _load_model_state
    keys = model.load_state_dict(checkpoint["state_dict"], strict=strict)
  File "/root/.local/share/virtualenvs/DiffuseVAE-main-m2EH8SNx/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1498, in load_state_dict
    self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for DDPMWrapper:
        size mismatch for online_network.decoder.input_blocks.0.0.weight: copying a param with shape torch.Size([128, 6, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 3, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.4.0.in_layers.2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 128, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.4.0.in_layers.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.4.0.emb_layers.1.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
        size mismatch for online_network.decoder.input_blocks.4.0.emb_layers.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.4.0.out_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.4.0.out_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.4.0.out_layers.3.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.4.0.out_layers.3.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.5.0.in_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.5.0.in_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.5.0.in_layers.2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.5.0.in_layers.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.5.0.emb_layers.1.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
        size mismatch for online_network.decoder.input_blocks.5.0.emb_layers.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.5.0.out_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.5.0.out_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.5.0.out_layers.3.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.5.0.out_layers.3.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.6.0.op.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.6.0.op.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.7.0.in_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.7.0.in_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for online_network.decoder.input_blocks.7.0.in_layers.2.weight: copying a param with shape torch.Size([256, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.10.0.in_layers.2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 256, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.10.0.in_layers.2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.10.0.emb_layers.1.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]).
        size mismatch for online_network.decoder.input_blocks.10.0.emb_layers.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.10.0.out_layers.0.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.10.0.out_layers.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.10.0.out_layers.3.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.10.0.out_layers.3.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.11.0.in_layers.0.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.11.0.in_layers.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.11.0.in_layers.2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.11.0.in_layers.2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.11.0.emb_layers.1.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]).
        size mismatch for online_network.decoder.input_blocks.11.0.emb_layers.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.11.0.out_layers.0.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.11.0.out_layers.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.11.0.out_layers.3.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.11.0.out_layers.3.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.12.0.op.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
        size mismatch for online_network.decoder.input_blocks.12.0.op.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.13.0.in_layers.0.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.13.0.in_layers.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for online_network.decoder.input_blocks.13.0.in_layers.2.weight: copying a param with shape torch.Size([512, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.0.0.weight: copying a param with shape torch.Size([128, 6, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 3, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.4.0.in_layers.2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 128, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.4.0.in_layers.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.4.0.emb_layers.1.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
        size mismatch for target_network.decoder.input_blocks.4.0.emb_layers.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.4.0.out_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.4.0.out_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.4.0.out_layers.3.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.4.0.out_layers.3.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.5.0.in_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.5.0.in_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.5.0.in_layers.2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.5.0.in_layers.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.5.0.emb_layers.1.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
        size mismatch for target_network.decoder.input_blocks.5.0.emb_layers.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.5.0.out_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.5.0.out_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.5.0.out_layers.3.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.5.0.out_layers.3.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.6.0.op.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.6.0.op.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.7.0.in_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.7.0.in_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for target_network.decoder.input_blocks.7.0.in_layers.2.weight: copying a param with shape torch.Size([256, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.10.0.in_layers.2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 256, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.10.0.in_layers.2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.10.0.emb_layers.1.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]).
        size mismatch for target_network.decoder.input_blocks.10.0.emb_layers.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.10.0.out_layers.0.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.10.0.out_layers.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.10.0.out_layers.3.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.10.0.out_layers.3.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.11.0.in_layers.0.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.11.0.in_layers.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.11.0.in_layers.2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.11.0.in_layers.2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.11.0.emb_layers.1.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]).
        size mismatch for target_network.decoder.input_blocks.11.0.emb_layers.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.11.0.out_layers.0.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.11.0.out_layers.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.11.0.out_layers.3.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.11.0.out_layers.3.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.12.0.op.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
        size mismatch for target_network.decoder.input_blocks.12.0.op.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.13.0.in_layers.0.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.13.0.in_layers.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for target_network.decoder.input_blocks.13.0.in_layers.2.weight: copying a param with shape torch.Size([512, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
I just change the name of the dataset and the path of the checkpoint, maybe I need to change other configurations. But I don't know what I should change.
I'm looking forward to your help. Thank you very much.
Best wishes.
郭博菲
@.***
Original Email
Sender:"Kushagra Pandey"< @.*** >;
Sent Time:2023/4/20 22:46
To:"kpandey008/DiffuseVAE"< @.*** >;
Cc recipient:"nikki0205"< @.*** >;"Author"< @.*** >;
Subject:Re: [kpandey008/DiffuseVAE] CelebHQ sampling (Issue #15)
Hi, it would be great if you can post some error logs for the same. I will try to run the scripts on my end but this might not be immediately feasible due to limited bandwidth.
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you authored the thread.Message ID: @.***>


How to enable paste from system clipboard in mouse mode (Mobaxterm)

I am using MobaXterm and connect to SSH with tmux. After setting tmux_conf_copy_to_os_clipboard=true in .tmux.conf.local, I can copy from tmux to os clipboard. But when I try to paste from clipboard via right button of my mouse (this works in non-mouse mode as I unbind -n MouseDown3Pane), but in mosue mode it does nothing and cannot paste anything.

Hello @jiang-yuan 👋
If I understood correctly, you need to bind MouseDown3Pane to something like xsel -b.

@jiang-yuan are we good?


Change Webcam Driver

Hi,
Is it possible to add something that change webcam name and drivers like is done for ahci?

This question is out of purpose of issues of this loader. Figure out that yourself. Closed.

Sorry, the purpose of this loader is to mitigate vm detection.
Using a webcam, the name is "virtual box-..." and the vendor ID is 80ee (virtual box).
You change the name and the serial number of the hdd for the same reason so I thought my question was related to this.


Automated Package Upgrade

:tada: This PR is included in version 25.6.80 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Add aliases for commands that are useful for development

Codecov Report

Merging #16 (edda746) into main (957121a) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##             main      #16   +/-   ##
=======================================
  Coverage   63.56%   63.56%
=======================================
  Files          10       10
  Lines         667      667
=======================================
  Hits          424      424
  Misses        243      243

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Clarify the callback reuse for useContextSelector

I'm setting this bug to P0, but feel free to lower if this doesn't cause any serious issues.
The question is with what deps should go to useCallback in the assets/src/edit-story/utils/context.js.
IMHO the selector/equalityfn should be always reenterable and immutable. The fact that it's very convenient to inline this function should not change the architecture significantly, IMHO. I think we'll be better of to pick the first version of each function and use them for the lifecycle of a component that uses the hook. Otherwise, we are regenerating the useCallback each time and thus the useCallback is not even really used.

This should probably be fixed by ref'ing the two arguments so the callback is stable:
export const useContextSelector = (
  context,
  selector,
  equalityFn = shallowEqual
) => {
  const ref = useRef();
  const selectorRef = useRef(selector);
  const equalityFnRef = useRef(equalityFn);

  useEffect(
    () => selectorRef.current = selector,
    [selector]
  );
  useEffect(
    () => equalityFnRef.current = equalityFn,
    [equalityFn]
  );

  const equalityFnCallback = useCallback(
    (state) => {
      const selected = selectorRef.current(state);
      if (equalityFnRef.current(ref.current, selected)) {
        return ref.current;
      }
      ref.current = selected;
      return selected;
    },
    []
  );

  // Update the selector fn to memoize the selected value by [equalityFn].
  const patchedSelector = equalityFn ? equalityFnCallback : selector;
  return useContextSelectorOrig(context, patchedSelector);
};

@barklund this looks good, but one question. Do we need useEffect in this case? It'd just be enough to do:
const selectorRef = useRef();
...
selectorRef.current = selector;

const callback = useCallback(() => {
  ... selectorRef.current(...); ...
}, []);

const selectorRef = useRef();
selectorRef.current = selector;

🤦
Why did I never think of this? Of course this works! It does unnecessarily re-set the ref even if selector doesn't change, but I'm pretty sure that doesn't matter at all!
I've been doing that other thing way too often - probably just because it's necessary with a useState but of course not a ref... D'oh!
Or am I missing something? Hm... Not sure about anything anymore really.

Actually useCallback isn't needed at all, since useContextSelector uses the selector without re-rendering when the fn changes:
https://github.com/dai-shi/use-context-selector/blob/master/src/index.js#L69
Creating the 'equalityFnCallback' lambda is cheap, as it only creates a temporary object to wrap equalityFn and selector.
I think 'selectorRef' shouldn't be used, as the selector could technically change between calls to useContextSelector.

@cvolzke4 yeah, i see your point. imho in that case let's remove useCallback?

@cvolzke4 why close with still a PR open?

@cvolzke4 why close with still a PR open?

I thought that I had merged the PR. The is merged now.


[TC-IDM-10.2] ICD Management requirements wrongly defined for Matter 1.4

Summary Title:
ICD Management requirements wrongly defined for Matter 1.4. The new features are still in provisional state.
Description:
Test failed if the device support LIT and other ICDM features which for Matter 1.3 were provisional.
Logs:
[MatterTest] 08-14 08:12:42.870 INFO
Problem: ProblemSeverity.ERROR
    test_name: IDM-10.2
    location:
       Endpoint: 0,
       Cluster:  70 (0x46) IcdManagement
      Attribute:65532 (0xfffc)
    problem: Disallowed feature with mask 0x01
    spec_location:

[MatterTest] 08-14 08:12:42.871 INFO
Problem: ProblemSeverity.ERROR
    test_name: IDM-10.2
    location:
       Endpoint: 0,
       Cluster:  70 (0x46) IcdManagement
      Attribute:65532 (0xfffc)
    problem: Disallowed feature with mask 0x02
    spec_location:

[MatterTest] 08-14 08:12:42.871 INFO
Problem: ProblemSeverity.ERROR
    test_name: IDM-10.2
    location:
       Endpoint: 0,
       Cluster:  70 (0x46) IcdManagement
      Attribute:65532 (0xfffc)
    problem: Disallowed feature with mask 0x04
    spec_location:

[MatterTest] 08-14 08:12:42.872 INFO
Problem: ProblemSeverity.ERROR
    test_name: IDM-10.2
    location:
       Endpoint: 0,
       Cluster:  70 (0x46) IcdManagement
      Attribute:6 (0x06)
    problem: Attribute 0x06 is included, but is disallowed by conformance. Conformance: P, UAT, implemented features: CIP,UAT,LITS
    spec_location:

[MatterTest] 08-14 08:12:42.872 INFO
Problem: ProblemSeverity.ERROR
    test_name: IDM-10.2
    location:
       Endpoint: 0,
       Cluster:  70 (0x46) IcdManagement
      Attribute:8 (0x08)
    problem: Attribute 0x08 is included, but is disallowed by conformance. Conformance: P, LITS, implemented features: CIP,UAT,LITS
    spec_location:

@cecille

Per Yinyi Hu "This error is expected because ICD is still provisional till SVE.
During TE2, we should ran with "bool-arg": "allow_provisional:true" We should do the same for SVE. This will not be an issue when the ICD feature eventually becomes non-provisional

does the information about additional param is documented somewhere?
It will be the best to provide the list of expected test parameters which need to be set

No - we don't generally have a good solution for exposing test parameters. This one is extra complicated because it's definitely disallowed during certification so it needs to be checked by the ATLs.
We have a list of common test failures here: https://github.com/project-chip/matter-test-scripts/blob/main/docs/common_test_failures/TC-IDM-10.2.md. If you want to add that info to the documentation, it would be welcome. The TH team has an ongoing issue to expose that documentation in the TH.

@doublemis1 usually VS doc list out all python script commands along with the parameters that needs to be passed. The only Catch is , we should not allow to use this parameter during certification runs, so we will have to update the VS after SVE.


FIT_FILL does not behave as described

Dear Spatie,
In the documentation it is said that Manipulations::FIT_FILL behaves like FIT_CONTAIN, but adding extra empty pixels. However it actually behaves like FIT_MAX and adding extra pixels.
Uploading an image from 200x100 and doing the manipulation ->fit(Manipulations::FIT_FILL, 400, 400) results in the behaviour that the image does end up as 400x400 but it not upscales and it only remains 200x100 adding extra pixels to fill up the empty space.
complete function call (media-libary)
        $this->addMediaConversion('medium')
            ->performOnCollections($collection)
            ->format(Manipulations::FORMAT_PNG)
            ->fit(Manipulations::FIT_FILL, 400, 400);

I tried to chain function calls to behave like FIT_CONTAIN and FIT_FILL.
        $this->addMediaConversion('medium')
            ->performOnCollections($collection)
            ->format(Manipulations::FORMAT_PNG)
            ->fit(Manipulations::FIT_CONTAIN, 400, 400)
            ->fit(Manipulations::FIT_FILL, 400, 400);

I also tried it to manipulate it with the width operator.
$this->addMediaConversion('medium')
            ->performOnCollections($collection)
            ->format(Manipulations::FORMAT_PNG)
            ->width(400)
            ->fit(Manipulations::FIT_FILL, 400, 400);

However this does not result in the desired behaviour.
Is there a way to make a call to get the FIT_FILL behaviour as described?
Your products are amazing, and I already thank you for your help!
Greetings Friso

Hi, we currently don't have the time to look at this, but feel free to submit a PR with tests that fixes this.

Greetings. I think this can be resolved with a documentation fix. I was also a little confused when I saw the docs describing the behaviours and seeing output that was a little different. I created a PR (#150) to copy the docs from Glide that describe the behaviours. They seemed to clear up my confusion.
It might be worth giving the Manipulations::FIT_CROP a try. This will resize your image and trim any excess to the dimensions you supplied. Also If you need to chain fit methods you can give the apply method a try.
One of these should be able to do the desired behaviour that you are describing above.
Example:
# Crop
$this->addMediaConversion('medium')
         ->performOnCollections($collection)
         ->fit(Manipulations::FIT_CROP, 400, 400)

# apply()
$this->addMediaConversion('medium')
         ->performOnCollections($collection)
         ->fit(Manipulations::FIT_CONTAIN, 400, 400)
         ->apply() # Apply the contain change before running fill
         ->fit(Manipulations::FIT_FILL, 400, 400);

Apply reference here:
https://spatie.be/docs/image/v1/usage/advanced-manipulations#example-usage-1


Is it possible to change the name of a category in the typedoc-sidebar.cjs?

What package is your question related to?
docusaurus-plugin-typedoc
What would you like to ask?
Hi,
is it possible to change the name of a category in the typedoc-sidebar.cjs?
I have the following typedoc-sidebar.cjs:
const typedocSidebar = { items: [
  {
    "type": "category",
    "label": "SDK/C.S.SDK.ADO",
    "items": [
      {
        "type": "category",
        "label": "Classes",
        "items": [
          {
            "type": "doc",
            "id": "api/SDK/C.S.SDK.ADO/classes/ADOConnectionBuilder",
            "label": "ADOConnectionBuilder"
          }
          ]
      }
    ]
    }
  ]
};

What i would like to get:
const typedocSidebar = { items: [
  {
    "type": "category",
    "label": "C.S.SDK.ADO", /*<-- Remove the SDK here*/
    "items": [
      {
        "type": "category",
        "label": "Classes",
        "items": [
          {
            "type": "doc",
            "id": "api/SDK/C.S.SDK.ADO/classes/ADOConnectionBuilder",
            "label": "ADOConnectionBuilder"
          }
          ]
      }
    ]
    }
  ]
};

With kind ringars,
David

@DavidBal  the top level category label is essentially the resolved typedoc module name that contains the exported symbols. You can control this with the @module tag - see https://typedoc.org/tags/module/.


Update README.md

Added tech stack icons and Discord link+icon

hi @HKAgrwl could you please make sure images and text aligned? seems like images are placed little down. see the image below

Yeah, I'll fix it...

Yeah, I'll fix it...

thanks @HKAgrwl

I cant't use CSS or html style in readme.md as github doesn't allow that. Still made some improvements. Please review....

hi @HKAgrwl are you going to work on this or should i pick this up? please let me know

I have already raised a PR.Please look into it and suggest any further changes ...

@HKAgrwl you haven't worked on the request changes yet. please look into it.


Add support to build and publish against the latest Mill dev version

Enable the workflow described in https://github.com/com-lihaoyi/mill/issues/2466#issuecomment-1537986552.

Added support to lookup and build against the latest Mill dev version
Publish on workflow_dispatch and include build for latest Mill dev version

Thank you for the contribution @lefou! If you don't mind I would refactor the code to match my taste. Let me know if it's ok for me to push on your PR.
I want to read an environment variable with sys.env. I know that it doesn't get updated in server-client mode, but this needs to work in especially CI so I would prefer to reduce the build complexity accept the limitation.

@lolgab Feel free to refactor this PR and push as you like.

Merged the PR. Thank you very much @lefou ❤

Merged the PR. Thank you very much @lefou heart

You are welcome. Is it ok for you, if me or other Mill devs trigger the workflow_dispatch workflow in your repo?

Workflow running here:
https://github.com/lolgab/mill-mima/actions/runs/4946434693
Can you see the option with your current permissions? In case you can't I need to raise them, so you can publish when I'm not available.

Thanks! I also see the workflow run button for "ci" workflow. Permissions seem to be enough.

@lolgab Unfortunately, it didn't work. There were no artifacts published at all from the manual run.

Yes, it wasn't since we have an if in the actions workflow that skips commits that are not tagged. I'm opening a PR to fix it (for some reason Github doesn't let me open the PR).
Branch here.

@lefou It worked now: https://central.sonatype.com/artifact/com.github.lolgab/mill-mima_mill0.11.0-M8-24-7d871a_2.13/0.0.19-6-d10548


Add initial CSS Basics page

After skimming over the lessons on LHTP, I compiled a few things I thought were important. Another plug to Bootstrap, adding div shortcuts, testing CSS linkage, and a Mozilla link regarding cascading.
Tests

All off-site and local links have been tested and work as of this PR.
Link to page from content sidebar works correctly.

Additional Notes
weight = 2, to be shown after HTML Basics
updated = updated

Noticed a few spelling errors, will PR after new commit


Material icon from material.io not found

Hey,
today i noticed that many of the icons from https://material.io/tools/icons/?style=baseline aren't implemented in the Icons class. Maybe there is an possibility to update the icons.
 This is one for example that isnt in the Icons class.
My flutter doctor output:
Doctor summary (to see all details, run flutter doctor -v):
[✓] Flutter (Channel master, v0.5.6-pre.76, on Mac OS X 10.13.5 17F77, locale de-DE)
[✓] Android toolchain - develop for Android devices (Android SDK 28.0.0)
[✓] iOS toolchain - develop for iOS devices (Xcode 9.4.1)
[✓] Android Studio (version 3.1)
[!] IntelliJ IDEA Ultimate Edition (version 2018.1.5)
    ✗ Flutter plugin not installed; this adds Flutter specific functionality.
    ✗ Dart plugin not installed; this adds Dart specific functionality.
[✓] VS Code (version 1.24.1)
[✓] Connected devices (1 available)

Closed as duplicate of google/material-design-icons#786


feat: Show Item Kind in completion menu | Show full expanded snippet in documentation window

easy to identify
in tailwindcss, color properties show Color and rest are Constant
update items.lua

Hey, thank you so much for the PR. I have not checked everything yet, but it looks awesome! I just need a little more time to test it out.

Take your time. Thank you for the plugin, such a life saver.

Hi! Thank you for your patience. I reviewed your PR last night and here's a few questions that I would like to ask.

I noticed using "color:" instead of "color" produces more accurate results. Can you explain why you chose to omit the colon for "color"?

This is what I see before applying your PR:

And this is after applying changes you suggested:

I tried to remove the duplicates but have not found a way to do so. Do you have any idea why this might be occurring?

It appears that the syntax highlighting within the documentation window only works when the text is wrapped with a pair of curly brackets. Based on my understanding, this is the correct behavior, as this is also how you enable syntax highlighting for CSS in a markdown file. (please correct me if I'm wrong). So I'm looking for ways to wrap the documentation text with { } like this:

(ignore the top part)

I noticed you managed to get this working without wrapping it with { } and I'm curious how that was possible.

Hey :) it got merged! Thank you for your effort.
I used "color:" for better results but let me know if you think the one without the colon is better.
I solved the second problem by setting completion_item.detail to nil.

Thank you for merging.
I probably did that in case the insert text is color : rgb(1,1,1). ( Yes, this logic makes sense for fill and stroke too )
Actually a better solution would be to use color%s*: ( and so on for fill and stroke ), basically spaces can be there before : for a valid color.
Anyway, this is all meaning less if in items.lua css is properly inserted.
About the documentation thing, it's showing some syntax highlight because i use the noice.nvim markdown renderer for cmp. Although technically, it shouldn't work as without the braces it's not valid css code.


Forking the repo and renaming it no longer renders the website properly.

@danielvmoore Thanks for reporting and trying. In _config.yml change:
path: /jekyll-minimal-theme
url:  'http://henrythemes.github.io/jekyll-minimal-theme'

to your repo settings. Cheers.


Add PHP 7.2 support, drop HHVM

Update Travis configuration
Check Travis results

@froschdesign It can be closed now, version 2.7.0 with PHP 7.2 support is now released.

Fixed with #19


Need to update React and Babel

React, Babel and Parcel Bundler is outdated and needs an update.

Thanks!


Provide Type Arguments to History::new()

Hello,
Wondering if it would be possible to provide type arguments to History::new()?
Using lazy_static and other such libraries requires Send+Sync, but I dont' see a way to add these traits in History constructor.
use undo::{Action, History, Merged, Signal};
use enum_dispatch::enum_dispatch;

lazy_static::lazy_static!{
    static ref APP_STATE: AppState = AppState::new();
}

pub struct AppState{
    names: Vec<String>,
    history: History<Box<dyn AppAction>, Box<dyn FnMut(Signal) + Send + Sync>>
}

impl AppState{
    pub fn new()->Self{
        AppState{
            names: vec![],
            history: History::new(),
            // history: History::new<Box<dyn AppAction>, Box<dyn FnMut(Signal) + Send + Sync>>(),
        }
    }
    pub fn add_name(&mut self, name: String){
        self.names.push(name.clone())
    }
    pub fn remove_name(&mut self, name: String){
        let keep =  self.names.clone().into_iter().filter(|n|*n != name).collect();
        self.names = keep
    }
}

pub struct AddName(String);

#[enum_dispatch]
pub enum AppActionEnum {
    DoAddName(AddName),
}

#[enum_dispatch(AppActionEnum)]
pub trait AppAction: Send + Sync{
    fn apply(&mut self, target: &mut AppState) -> Result<(), String>;

    fn undo(&mut self, target: &mut AppState) -> Result<(), String>;

    fn redo(&mut self, target: &mut AppState) -> Result<(), String> {
        self.apply(target)
    }

    fn merge(&mut self, test: &mut AppActionEnum) -> Merged {
        Merged::No
    }
}

impl AppAction for AddName{
    fn apply(&mut self, target: &mut AppState) -> Result<(), String>{
        target.add_name("Test".to_string());
        Ok(())
    }

    fn undo(&mut self, target: &mut AppState) -> Result<(), String>{
        Ok(())
    }

    fn redo(&mut self, target: &mut AppState) -> Result<(), String> {
        self.apply(target)
    }

    fn merge(&mut self, test: &mut AppActionEnum) -> Merged {
        Merged::No
    }
}

impl Action for AppActionEnum {
    type Target = AppState;
    type Output = ();
    type Error = String;

    fn apply(&mut self, target: &mut AppState) -> Result<(), String> {
        AppAction::apply(self, target)
    }

    fn undo(&mut self, target: &mut AppState) -> Result<(), String> {
        AppAction::undo(self, target)
    }

    fn redo(&mut self, target: &mut AppState) -> Result<(), String> {
        AppAction::redo(self, target)
    }

    fn merge(&mut self, other: &mut AppActionEnum) -> Merged {
        AppAction::merge(self, other)
    }
}

fn main(){
    dbg!("test");
}

gives error:
21 |             history: History::new(),
   |                      ^^^^^^^^^^^^^^ expected trait `FnMut(Signal) + Send + Sync`, found trait `FnMut(Signal)`

You need to use the builder for history. It is located in the history module.

yes, this worked!


Parser Error: Could not find type "ImGuiFont" in the current scope.

Triggers when launching game within editor.  When a C# code change takes place, after first error launching again works fine.  Using "imgui-godot-6.0.1-csharp-only.zip" on Godot 4.3.beta2.mono
Specifically this happens after c# code change and the use of "Run Project hotkey". Works fine if you Build project and then use hotkey
on line 4 of ImGuiConfig.gd:
@export var Fonts: Array[ImGuiFont]

Those two simple resource scripts are a self-contained unit, they don't depend on anything else, so this is almost certainly a Godot bug.
But good news, a PR was just merged to address similar issues, and that fix will be in 4.3-beta3.

Should be fixed upstream in 4.3.0.

The issue is still present in version v4.3.stable.mono.official [77dcf97d8].
I'm using ImGui v6.2.1
Thanks for your work on ImGui !

Alright, there's a workaround I can try. I'm pretty sure it'll work but this is basically impossible to test. It'll be in the next release.

Also, I can only reproduce this issue on Windows. On my linux laptop there is no issue.

I'm also seeing this problem, but it is intermittent, I don't think it's related to build changes, it just fails occasionally.   I have kind of a weird [Tool] based setup but I'm seeing some other weird frame stalls also, so I will try doing some more debugging.   If anyone else has additional details to share, please do.

this does appear to be an upstream/godot issue: https://github.com/godotengine/godot/issues/82392

Sorry, I committed a workaround last month, but I haven't tagged a new release yet. I'll do that today or tomorrow.

Fix released in v6.3.0. Let me know if you still encounter similar errors.


remove configmap suffix

use generatorOptions to disable configmap suffix
refer to generatorOptions example
Signed-off-by: Lan Luo<EMAIL_ADDRESS>

Codecov Report

Merging #2724 (6e7073a) into main (d8d70ac) will decrease coverage by 19.69%.
The diff coverage is n/a.

@@             Coverage Diff             @@
##             main    #2724       +/-   ##
===========================================
- Coverage   60.70%   41.01%   -19.70%
===========================================
  Files         285      158      -127
  Lines       23003    19272     -3731
===========================================
- Hits        13965     7904     -6061
- Misses       7544    10621     +3077
+ Partials     1494      747      -747

Flag
Coverage Δ

kind-e2e-tests
?

unit-tests
41.01% <ø> (-0.07%)
:arrow_down:

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

Impacted Files
Coverage Δ

pkg/ovs/openflow/default.go
0.00% <0.00%> (-100.00%)
:arrow_down:

pkg/util/runtime/runtime.go
0.00% <0.00%> (-100.00%)
:arrow_down:

pkg/agent/cniserver/pod_configuration_linux.go
0.00% <0.00%> (-100.00%)
:arrow_down:

pkg/ovs/openflow/logs.go
9.52% <0.00%> (-90.48%)
:arrow_down:

pkg/apis/controlplane/register.go
0.00% <0.00%> (-90.00%)
:arrow_down:

pkg/agent/nodeportlocal/k8s/annotations.go
0.00% <0.00%> (-83.88%)
:arrow_down:

pkg/agent/agent_linux.go
0.00% <0.00%> (-80.00%)
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pkg/agent/client.go
0.00% <0.00%> (-77.42%)
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pkg/ovs/ovsconfig/ovs_client_linux.go
0.00% <0.00%> (-76.93%)
:arrow_down:

pkg/flowaggregator/certificate.go
0.00% <0.00%> (-76.58%)
:arrow_down:

... and 231 more

@antoninbas  thanks for the explanation, personally I would prefer the first one if we have a solution to fix the agent restart issue since I feel there are quite a few time I am resolving the antrea-config name conflict issue during code merge or rebase, if we use the first option, it would save developers from this trivial stuff.


[IOTDB-1540] [To rel/0.12] Bug Fix: 500 when using IN operator

Does master have this bug?

Does master have this bug?

I will cherry-pick to master.

Merge the latest rel/0.12? The CI has been fixed.


Minor README.md proofreading.

Here are some really minor corrections to the README.md file.

Thanks!


Add stack-install-cabal target and confirmation messages

For stack users that want to install auto cabal with the required minimum version to work with hie
As bonus, i've added some confirmation messages when installing cabal and when installing hie using cabal

The pr should fix the behaviour described in https://github.com/alanz/vscode-hie-server/issues/131#issuecomment-539478925

Btw, is cabal still reqired for stack projects when using the hie bios?
Cc @fendor

I dont think so. Stack should depend only on stack.

However, stack cradle depends on ghc. @power-fungus


Docker Hub failed to build consul-server and consul-agent against 0.6.4

Pull the latest image of consul-server and consul-agent from Docker Hub, then run:
$ docker run -d --name consul-server gliderlabs/consul-server:latest
$ docker exec consul-server /bin/consul version
Consul v0.6.3
Consul Protocol: 3 (Understands back to: 1)

$ docker run -d --name consul-agent gliderlabs/consul-agent:latest
$ docker exec consul-agent /bin/consul version
Consul v0.6.3
Consul Protocol: 3 (Understands back to: 1)

Definitely would be nice to have resolved. Are we able to get x.y.z tags on Docker Hub? As opposed to just x.y?

Looks like the gliderlabs/consul docker image failed to build and it used the older version of the container to build consul-server and consul-agent using 0.6.3.
Are you able to kick off a rebuild?
https://hub.docker.com/r/gliderlabs/consul/builds/buuyepcuwhatskhhbvnwgmc/

New builds have evidently been triggered and consul-server and consul-agent now both report 0.6.4. I believe this is resolved.

@ianmcorvidae Indeed, the problem is resolved. I'm closing this issue.


Linux workloads

Hi,
I just wanted to confirm, workload-automation currently has only two workloads that run on Linux systems - lmbench and hackbench (apart from idle). Right?

There are several others:

apache
deepbench
dhrystone
meabo
memcpy
mongoperf
openssl
rt_app
shellscript (this is sort of a meta-workload that allows running arbitrary scripts)
stress_ng
sysbench

Cool, Thanks for your prompt response!


Readme: Add section about how translations work

Closes https://github.com/openstreetmap/id-tagging-schema/issues/55
I had to search around for this – again – just now for https://github.com/bryceco/GoMap/issues/562. I think this should be clarified right in the Readme.

Looking into this with the Feedback of Minh in https://github.com/openstreetmap/id-tagging-schema/pull/245#discussion_r739155984, there are two more thinks I think we should look at

[ ] The docs read as if anyone can translate. It that true? Just double checking if this is correct.
[ ] How does the review process work? There was a GitHub issue a few weeks ago where someone requested access (cannot find it anymore). Should we explain this here in it's own section?
[ ] As a follow up, we should also update https://github.com/openstreetmap/iD/blob/develop/CONTRIBUTING.md#translating with sub headlines and link to this new section for the part about presets.
[ ] Are other information from https://github.com/openstreetmap/iD/blob/develop/CONTRIBUTING.md#translating relevant and should be added here? Like the {variable}-part?

The docs read as if anyone can translate. It that true? Just double checking if this is correct.

Transifex has a button to ask to join the translation team for a given locale. In the past, the administrators of this Transifex project would approve requests routinely, only rejecting requests for overly specific locales.

How does the review process work?

Do you mean the review process for translations? Transifex does have a separate Reviewer role in order to mark translations as reviewed. This Transifex feature is generally only used for projects that rely on freelancers or contractors to provide initial translations. However, for Vietnamese, iD only pulls in reviewed translations: several years ago, someone used the Vietnamese locale as a dumping ground for their machine translation project, so this extra level of review prevented the machine translation from going live automatically.

Are other information from https://github.com/openstreetmap/iD/blob/develop/CONTRIBUTING.md#translating relevant and should be added here? Like the {variable}-part?

Nothing in interim/source_strings.yaml currently uses this placeholder syntax. There is the <…> syntax used for terms strings; Transifex renders each of those placeholder as a token with a tooltip when you hover over it.

Just seeing this is a duplicate of: #200. I think the additional info added here will be useful as well. When you find the time, please do make appropriate change.

@1ec5 thanks for those answers. I updated the PR. I left out a some of the parts you answered since – now that I know – I think they are not too relevant to be explained to everyone.
I added a bullet to answer the question "when will I see my translations in iD(…)".
Another review would be great.
@mbrzakovic Would it be possible to squash-merge this and remove the part from #200 as part of resolving conflicts (in the github web UI)? If not, I have to checkout and rebase once I find time …

@mbrzakovic Would it be possible to squash-merge this and remove the part from #200 as part of resolving conflicts (in the github web UI)? If not, I have to checkout and rebase once I find time …

It's possible for the person doing the merge in GitHub to do the squash as part of the merge.
Or alternatively you can do it as part of a PR in your branch to do it all on the website.


Helm install using values-istio-demo.yaml fails to install mutatingwebhookconfiguration

Bug description
Helm install using values-istio-demo.yaml fails to install mutatingwebhookconfiguration
kubectl get mutatingwebhookconfiguration
No resources found.
Expected behavior
installation should proceed.
Steps to reproduce the bug
helm install  install/kubernetes/helm/istio --name istio --namespace istio-system --values install/kubernetes/helm/istio/values-istio-demo.yaml
Version (include the output of istioctl version --remote and kubectl version and helm version if you used Helm)
Helm v2.14.3
Istio 1.3.5
KUbectl v1.14.8
How was Istio installed?
helm install  install/kubernetes/helm/istio --name istio --namespace istio-system --values install/kubernetes/helm/istio/values-istio-demo.yaml
Environment where bug was observed (cloud vendor, OS, etc)

`
global:
proxy:
accessLogFile: "/dev/stdout"
resources:
requests:
cpu: 10m
memory: 40Mi
disablePolicyChecks: false
sidecarInjectorWebhook:
enabled: true
If true, webhook or istioctl injector will rewrite PodSpec for liveness
health check to redirect request to sidecar. This makes liveness check work
even when mTLS is enabled.
rewriteAppHTTPProbe: false
pilot:
enabled: true
autoscaleEnabled: false
replicaCount: 1
traceSampling: 100.0
resources:
requests:
cpu: 10m
memory: 100Mi
mixer:
policy:
enabled: true
autoscaleEnabled: false
resources:
requests:
cpu: 10m
memory: 100Mi
telemetry:
enabled: true
autoscaleEnabled: false
resources:
requests:
cpu: 50m
memory: 100Mi
adapters:
stdio:
enabled: true
grafana:
enabled: false
tracing:
enabled: true
kiali:
enabled: false
createDemoSecret: false
gateways:
istio-ingressgateway:
autoscaleEnabled: false
resources:
requests:
cpu: 10m
memory: 40Mi
istio-egressgateway:
enabled: true
autoscaleEnabled: false
resources:
requests:
cpu: 10m
memory: 40Mi
global:
controlPlaneSecurityEnabled: false
mtls:
enabled: true
`

istioctl version --remote
client version: 1.3.5
control plane version: 1.3.5

helm will generally mention when something goes wrong, right? is there any error messages from helm? does this work if you install without tiller (using helm template)? Does your cluster have webhooks enabled?

it doesnt mention any issue, when i try with helm template it takes the default values file and installs everything mentioned in that file.
Also noticed although rewriteAppHTTPProbe is true in values file it doesnt pick it up and has to be done manually

I am not sure what happened here, but I don't think we can debug further without the output from Helm. Since helm support has been dropped in Istio, I think we can close this. Sorry we didn't resolve this sooner


Add Astral Credits (XAC) to token list

Howdy!
Just looking to add our projects token to your approved token list.
Astral Credits (XAC) is an openzeppelin ERC20 token on the SONGBIRD blockchain.
XAC is distributed freely to the community using a faucet with a built-in deflationary supply schedule.
The project is live and Blazeswap looks to be the DEX of choice for our community.
You can find details regarding our project on our website - https://astralcredits.xyz/
Any questions, let me know!
MKZI⚡

Thanks for the submission, may I ask you to:

verify the contract source code on the explorer
use the correct dimensions and padding for the svg file
move the tokens.json entry below to keep the sorting by symbol name
to comply with the listing rules, please?

Hi @alexdupre,
I have updated the image file to be the correct spec (500*500px, 8px padding) and moved the tokens.json entry as requested.
Apologies but I'm not sure if I can verify on the explorer. I have the original .sol file but not the fully compiled copy of the source code including original deps. I can use this to rebuild and interact with the contract on remix but unfortunately when flattened and attempt to verify, the bytecode doesn't match.
The contract uses the default openzeppelin ERC20 configurations. Is there anything that can be done? We would really love to use your platform.


Add docker compose tests in the pipeline

https://github.com/jabrena/spring-boot-relational-database-poc/pull/69


Bundle tutorial

Signed-off-by: liach<EMAIL_ADDRESS>

Will update when I have time later today.


Fix for hovered rows after onRelease on Android

On Android measureInWindow returns undefined width and height. This causes the releaseAnim not to start.
More Info:
https://github.com/facebook/react-native/issues/9382
https://facebook.github.io/react-native/docs/view.html#collapsable

Looks good. But another PR beat you to it. See https://github.com/computerjazz/react-native-draggable-flatlist/pull/22/files
This can be closed. Thank you

@computerjazz close?

whoops, looks like this PR was actually opened first. Thanks for finding the issue!


compileGroovy ends up removing compileJava output from build/classes

I have a multi-project build and one of the subprojects has the java and groovy plugin applied. The groovy source code depends on some java classes of the same subproject. However when performing compileGroovy it seems that all the classes that were previously compiled by compileJava are removed from build/classes and groovy complains that it cannot find the classes.
When performing only the compileJava task, all classes are properly compiled and outputted in the build/classes folder of my subproject.
Expected Behavior

Expected is that compileGroovy can safely rely on the previous output of the compileJava task.
Current Behavior

All output of the compileJava task seems to have been removed.
Context

Previously my subproject compiled all using the compileGroovy task:
sourceSets {
main {
java {
srcDirs = []
}
groovy {
srcDirs += ["src/main/java"]
}
}
}
I wanted to get rid of this and make sure groovy relies on java and not vice versa. I changed my code and removed this block, but then I bump into the problem described.
Steps to Reproduce (for bugs)

Your Environment

Build scan URL: https://scans.gradle.com/s/isi4ren6g3ndu#infrastructure
The scan above is from when everything was still compiled using compileGroovy only.

In order to fix your build you need to delete your .gradle directory in your project and run a clean. The problem which you are facing is caused by the following:
The GroovyCompile task snapshots its outputs after each run. So it remembers that it produced all the .class files for the Java files. Now the Groovy compiler is actually a CleaningGroovyCompiler which removes all the outputs of the previous execution before it starts to compile again. This yields to the behavior you are seeing. The history for the outputs is persisted in the .gradle directory within your project directory. So cleaning that removes the "memory" of the GroovyCompile task.

k, thx. That worked. I assume after my change all developers have to do exactly the same in order to avoid compilation problems ?

@kristofdepypere Thank you for the well-formed issue. We may or may not be able to address this as we fix #821 which is "in progress".

This has been fixed as part of the work on #821