fixed list index out of range

This error is triggered when the length of len(groups) == 2.

Hello, @biezhi Thank you very much for your contribution. One little additional thing. Could you please add test(s) for this case?

Hello, @biezhi Thank you very much for your contribution. One little additional thing. Could you please add test(s) for this case?

Okay, I will add the unit test later and then push.😊

Okay, I will add the test case later and then push. :blush:

Great, thanks a lot

Hey @hellokaton, sorry for the delay, I'm ill a bit now. As I see, your fix breaks other tests, hope I will check it soon, it will depend on my health

@dukkee Health is very important, wish you a speedy recovery. I resubmitted a PR, which can be reviewed when there is time.


Maps with image and header overlays are triggering JS error

CartoDB.js is triggering a lot of errors when it doesn't now how to render certain types of overlays. Examples:

OverlaysFactory: 'header' does not exist -> https://my.trackjs.com/messages/filtered?hash=63ff6e2cab72f97a
OverlaysFactory: 'image' does not exist -> https://my.trackjs.com/messages/filtered?hash=cb8d537bf69d80ac

Possible solutions for this:

Filter obsolete overlays from our viz.json endpoint.
Stop logging these errors in CartoDB.js.

cc: @xavijam

Maps seem to be working properly despite of this error.

Closed via https://github.com/CartoDB/cartodb.js/pull/1518


[iOS][10.0 beta][iPad Air] Themes causing crashes

When using any theme other than default, selecting stories or trying to flow through folder trees in the app will crash. I ran it through XCode and it gives the following error:
CIColor not defined for the UIColor UIExtendedGrayColorSpace 0.666667 1; need to first convert colorspace.'
I'll try to dig deeper through the code to see where that is being called from to backtrace it.

another example of a crash causing event is clicking on the arrow to expand a collapsed folder.

This issue does not impact my iPhone 6s Plus, only my iPad

This issue persists in iOS10 beta2.

this issue hasn't been occurring in quite a while, just this ticket hadn't been updated

Thanks for staying on top of it! I fix every bug I can find, so it's likely this was addressed. I also have a nice big update coming out in the next week or wo.


Baseline MAINTAINERS, CODEOWNERS, and external collaborator permissions

Follow https://github.com/opensearch-project/.github/issues/125 to baseline MAINTAINERS, CODEOWNERS, and external collaborator permissions.
Close this issue when:

MAINTAINERS.md has the correct list of project maintainers.
CODEOWNERS exists and has the correct list of aliases.
Repo permissions only contain individual aliases as collaborators with maintain rights, admin, and triage teams.
All other teams are removed from repo permissions.

If this repo's permissions was already baselined, please confirm the above when closing this issue.

Hi maintainers @lezzago @qreshi @skkosuri-amzn @bowenlan-amzn @rishabhmaurya @tlfeng @leeyun-amzn @getsaurabh02
Who can own this item?

@sbcd90 To look into it.


What happened to JsonSchema4.TypeNameRaw?

I'm trying to upgrade some code that uses NJsonSchema versio 5.20 to version 7.6 and there was a JsonSchema4.TypeNameRaw property that no longer exists.
What's the replacement?

The typename is completely infered from the "definitions" key (or "title" property)

Thanks!


[RFC] Support pinning PEP 517 build deps in pyproject.toml

What's the problem this feature will solve?
PEP 518 defines a [build-system] section with a required = [] field. But there is no way to tell PEP 517 build front-ends to apply constraints to those build requirements while provisioning an env for them. This makes it hard to go perform predictable builds.
Describe the solution you'd like

I was thinking that pip-tools could facilitate this by either learning to manage that setting in pyproject.toml or by sourcing the requirements from that field to produce a constraints file. The former could allow to keep the builds predictable with any build front-end like pip while the latter would be helpful mostly for more flexible build front-ends like pypa/build that allow the users to provision the envs by themselves.
WDYT folks?
Alternative Solutions
N/A
Additional context
N/A

I think it would be great if pip-compile could take the build-system.requires = [] and tool.<name>.metadata.requires = [] fields from the pyproject.toml and generate a requirements.txt file from that, as it does for setup.py and requirements.in

But there is no way to tell PEP 517 build front-ends to apply constraints to those build requirements while provisioning an env for them.

Can you please clarify?
You mean the requires field, right?
When I create a package using flit, I'll have something like:
[build-system]
requires = ["flit_core >=2,<4"]
build-backend = "flit_core.buildapi"

PEP 518 specifies that requires is a list of PEP 508 deps, which may look like:
requests [security,tests] >= 2.8.1, == 2.8.* ; python_version < "2.7"

or
pip @ https://github.com/pypa/pip/archive/1.3.1.zip#sha1=da9234ee9982d4bbb3c72346a6de940a148ea686

What kind of constraints application are you talking about that is not demonstrated in these examples?

@AndydeCleyre in requires, the requirements listed are usually direct deps having wide ranges of versions. I want an additional lock file. As in pip install -r direct-requires.txt -c comprehensive-pins.txt

I've recently clarified that doing PIP_CONSTRAINT=build-constrains.txt python -m build is able to apply constraints to the deps that are listed in [build-system]requires and returned from the dynamic hooks in the chosen PEP 517 backend (setuptools' backend adds a dependency on wheel under the hood, for example).
Done this manually for now: https://github.com/cherrypy/cheroot/commit/5c1ac088c595ec91b9bda2dc818e491a23132a2c.

supporting [build-system.requires] and [project.optional-dependencies] and all the various other dependencies keys would be really great!

I too would like to gather requirements from [build-system.requires].
I also want to gather requirements from the deps sections in tox.ini. And gather constraints from openembedded. Support for plugging in gatherers might be neat.
Side note about using constraints files with pip; you may want to prefer PIP_CONSTRAINT over -c because generated pip commands do not respect constraints files in outer install command (yes, I am still annoyed by this  :sweat_smile:).

Not sure if this would be a good way to do it but looks ok to me. Thoughts?


Use machine config operator (MCO) to make kubelet conf change

This patch will use MCO for updating the dynamic resourcfile which
is added recently with openshift/machine-config-operator#2466.

Great! I remember I tried couple of months ago without luck!
/lgtm

/retest

/retest

/retest

/retest

/retest

/retest

/retest

/retest

/retest

/retest

Tested generated bundle and it does work. reserved=cpu=0m,memory=0Gi
kubelet --config=/etc/kubernetes/kubelet.conf --bootstrap-kubeconfig=/etc/kubernetes/kubeconfig --kubeconfig=/var/lib/kubelet/kubeconfig --container-runtime=remote --container-runtime-endpoint=/var/run/crio/crio.sock --runtime-cgroups=/system.slice/crio.service --node-labels=node-role.kubernetes.io/master,node.openshift.io/os_id=rhcos --node-ip=<IP_ADDRESS> --minimum-container-ttl-duration=6m0s --cloud-provider= --volume-plugin-dir=/etc/kubernetes/kubelet-plugins/volume/exec --register-with-taints=node-role.kubernetes.io/master=:NoSchedule --pod-infra-container-image=quay.io/openshift-release-dev/ocp-v4.0-art-dev@sha256:1ecbe11e2366c3a497e50e7f2f03589ff7da1c67217b28ed38d2ffa5c8e10e3b --system-reserved=cpu=0m,memory=0Gi --v=2

@cfergeau Have a look to this.

@guillaumerose @cfergeau need another round of review.

@guillaumerose @cfergeau need another round of review.

I still have the same questions/lack of understanding :) https://github.com/code-ready/snc/pull/366#pullrequestreview-630204865

This adds a script to /usr/local/sbin/dynamic-system-reserved-calc.sh which will create /etc/node-sizing.env when it's called with true/false. I'm missing what is going to call it?
And the PR you link to documents

https://github.com/openshift/machine-config-operator/pull/2466/files is not the document link but it have all the implementation about dynamic allocation of cpu/mem according to configuration when user set it true otherwise it will make 1G mem and 500m cpu default https://github.com/openshift/machine-config-operator/pull/2466/files#diff-7f8d5dd4bf4dc8e795fe99a2931facec02ff7c017da2cfec7da60bf64f4f2e3aR86-R89 , The script detect node  memory and cpu and then allocate with different if-else clause.

Oh I did not realize this commit is overwriting a file which was introduced in this other PR.
To answer my other question, this file is then used by:
name: kubelet-auto-node-size.service
enabled: true
contents: |
  [Unit]
  Description=Dynamically sets the system reserved for the kubelet
  Wants=network-online.target
  After=network-online.target ignition-firstboot-complete.service
  Before=kubelet.service crio.service
  [Service]
  # Need oneshot to delay kubelet
  Type=oneshot
  RemainAfterExit=yes
  EnvironmentFile=/etc/node-sizing-enabled.env
  ExecStart=/bin/bash /usr/local/sbin/dynamic-system-reserved-calc.sh ${NODE_SIZING_ENABLED}
  [Install]
  RequiredBy=kubelet.service

Still missing the full story though :) Are we going to enable dynamic node sizing (since you deal with it in the script)? Or do we expect to only keep using static node sizing? I'd argue the terminology is inverted btw, dynamic is no longer dynamic with that change, while static is also not static since we let the kubelet use whatever amount of memory it needs.
And more importantly, I'm worried we are changing something OpenShift consinders an internal implementation detail, and may change at any time. Is there any commitment from them/documentation/... that it's ok to replace that file with ours to do whatever we need?

As per https://kubernetes.io/docs/tasks/administer-cluster/reserve-compute-resources/#system-reserved looks like we need to only reserve the resource for system daemons services like sshd, chronyd ..etc. So I run the crc without kubelet service to find out what is actual use of resources.
top - 11:06:09 up 1 min,  1 user,  load average: 0.08, 0.07, 0.02
Tasks: 170 total,   1 running, 168 sleeping,   0 stopped,   1 zombie
%Cpu(s):  0.1 us,  0.1 sy,  0.0 ni, 99.7 id,  0.0 wa,  0.1 hi,  0.1 si,  0.0 st
MiB Mem :   8970.2 total,   8328.7 free,    329.3 used,    312.1 buff/cache           0           0

So I think 350Mb should be good enough and there is hardly any cpu uses so 100m would be enough

/retest

/test e2e-snc

/retest


Android Project doesn't contain index.js file?

I'm trying to implement push notifications in my android app.
I did some research and saw that I had to configure stuff in index.js. But because I deployed to Heroku, my project doesn't contain an index.js file.
All I was able to to was to get an "Installation" class on my parse-server. But this installation doesn't send as a notification.

This may help you.
stackoverflow.com/questions/42255907/where-can-i-access-my-index-js-file-if-i-deployed-to-heroku-parse-from-the-websi


[HELP] * Unrecognized field at: docker.cache

OMV 7 running on debian 12, with docker-ce 25.0.3 installed
Just created the sys-api container with default config (created the volume folders /data and /config on my server), put default configuration.yml into /config, but I got the following error after deploying
io.dropwizard.configuration.ConfigurationParsingException: /config/configuration.yml has an error:
  * Unrecognized field at: docker.cache
    Did you mean?:

      - host
      - enabled

That part stands as it follows in the configuration.yml file:
docker:
  enabled: true
  cache:
    enabled: true
    duration: 2
    unit: SECONDS
  # uncomment if you'd like to manually specify docker host
  # host: unix://

Thanks in advance and sorry beforehand as I am not an IT guy.

@jfromeo Did you find the solution to your problem? I am having the same issue.


Thoughts.

Film grain doesn't look like digital noise which is what your example images look like unless you are presuming the output is from a digital scanner.  There would be no rgb pixelation in a grainy film photograph (an actual photochemical photograph).  The grain is in the same color space as the image color.
I think the digital output of both film and digital if you were trying to bring out data that isn't "there" would look basically identical.  In a film photo that doesn't have "data" it would just be black, not pixelated.  From what I recall the rgb pixels say in a very very dark image are just saying "i have no idea what is here".  The other thing is that black and white photographs wouldn't have the severity of grain at night, they'd just be dark
The look of high speed black and white film at night is much different.    Noting that they did obviously get scanned by a professional film scanner.  The color examples are from the late 1960's, early 1970's.  The bw example is a modern bw film (trix) shot at 1600 ("pushed").

For what it's worth :)

It's a bit of a dead project, but thanks for the feedback nonetheless. Your point about not having grain artifacts in the dark areas makes sense. It's possible to mimic that with the script already, if desired, by adjusting the grain power triplet. The triplet has a value for lows, mids and highs, and reducing the lows value would reduce grain in dark areas.
To the defense of the settings I chose, I did indeed look at lots of analog photography when I worked with it. For example, the pictures from here: https://www.stefanworks.com/photography/ilford-delta-3200  which show a lot of noise in the dark areas.


Resnet Ops Unittests

To create unittests for all the ops in the Resnet model on GS device.
unit tests to be created under https://github.com/tenstorrent-metal/tt-metal/blob/main/tests/ttnn/unit_tests/operations

Added unit tests for the supported ops of ResNet50 which includes Conv2d, Relu, MaxPool2d and Linear. The BatchNorm2d and AdaptiveAvgPool2d are not supported.
Among 372 unit tests of Conv2d, 46 failed, 140 passed, 186 skipped
Among 12 unit tests of Relu, 12 passed
Among 8 unit tests of MaxPool2d, 4 passed, 4 skipped
Among 2 unit tests of Linear, 2 passed

commit for the unit tests is here

PR: #6865


Exit with error code 1 on failed verification

This change should facilitate the integration into shell scripts, as it removes the need to parse the verifier's output.

Thanks Arthur! Yes, this is indeed a change that will help people using the parser.

Thanks Arthur! Yes, this is indeed a change that will help people using the parser.


tee command

outputs to a local file or another stream.
could be used to output file data from repl while viewing
might be nice to have a utcNow() function or tee -rolling 5m and then could accept other units of time. then one could output a new file every execution.
dunno, maybe it's out of scope.

dunno, maybe it's out of scope.

I don't think it is. In fact, the core suggestion that there should be a way to make TypeStream "mount" a local FileSystem into its operations has come up quite consistently in the conversations I had had.
I'm very curious to understand better what you're proposing with utcNow() and tee --rolling 5m. Especially the function, I think I understand the latter:
cat books | tee --rolling 5m books.ndjson

would roll books.ndjson.<datetime> files every 5 min? That seems pretty interesting also in the context of "mounting" object storage into TypeStream (s3 comes up all the time)
Is that what you have in mind?

yes that is exactly what i had in mind! certain kinds of log or data streaming, s3 mounting would be perfect here too. I had only thought through as far as local disk. At my work, we looked at mountpoint-s3 for managing app log outputs that had a similar rolling feature.

Exciting!
I have to think a little about how to implement tee (I'm sure my brain will do that even if I try not to prio this, it's just too interesting!) before moving forward with it so I say we keep the issue open to reflect the current state: want to do, not sure yet how/when.


Names not being linked?

Hi! Not sure if I'm using this incorrectly, but my Slack step includes for example @gobetti in the message field, the option "linkify names" has the default value (yes) and still, the messages being posted to Slack have a plain text rather than a link to my Slack user.
This happens to any of our users so it's not a problem specific with my Slack account.
This also happens in all of the positions I tried to place the tag (message, text, author_name and title).
I took a look at this feature's implementation and couldn't find anything that could justify this behavior, it looks like this linking is actually made by Slack and you're following Slack's instructions to format messages, is that right? https://github.com/bitrise-steplib/steps-slack-message/pull/22
Let me know please if this is known to be an issue with Slack currently, or if I have it incorrectly configured. Thank you!

Hi @gobetti, thanks for the detailed report! 🙂
Can you please paste here a URL for a build which resulted in this behaviour?

hi @bitce , thanks for answering! I ended up finding out today after some trial and error that it works however one needs to use the Slack's username (which is a private thing to each user). Interestingly if I try to tag someone in an actual Slack message, the username doesn't work. Closing this issue :)

To be recorded: https://api.slack.com/reference/surfaces/formatting#linking_to_channels_and_users
e.g.: My text <@ID_MEMBER_OR_CHANNEL_NOT_THE_NAME> blablabla


crash import

see https://github.com/ome/omero-insight/issues/135#issuecomment-630182141

https://github.com/ome/omero-documentation/pull/2200


Introduces a shareable directory structure

This seems to prevent users from accessing any existing projects.  The server gives an error about the '.cw' file being the wrong type.  Have you thought about the migration path?

For now I have added the code to migrate the users existing code in their root dir. Is it okay or do you want a way so that they can reorganize their stuff?

This looks fine.  So long as people don't lose their existing projects!  If you think this is an improvement as is, I'll look it over and consider merging tonight.

Hmm, I'm having trouble testing these except on the live site.  I'll have to figure that out before too much longer.
Styles are a bit weird, but I'm working on fixing it.

I pushed commit 6d93aee7192a215c5dfc2f07177d899aaee54870 to fix styles.


Add Riak KV/TS to erlang

Add Riak KV/TS to erlang languages

@gpad Thanks!

There is a problem on image related to riak, giveme 1 min to fix it, sorry.

I create the new pull request to fix the problem, sorry.

@gpad It's not a problem. Thank you!


Support 3D

What problem does this solve or what need does it fill?
Would be great to be able to use this library for procedurally generated 3D worlds.
Describe the solution would you like?
Same easy to use API, but 3D :)

I think this might be out of scope for this project but, I'll leave it open for discussion. Usually tile maps just have orthogonal and isometric viewpoints.

I would be very interested in this. I am working on a prototype at the moment for a game that has 3d buildings and being able to intelligently layer buildings in 3d would be excellent.

Oh I have an update on this, it already exists in master :D. I need to create examples for it though. There were other large improvements, such as a single 3D mesh being used for every layer, and every Z level.
When you are talking "3D" though, as in actual 3D objects, you -should- be able to use 3D characters in the environment, provided you add enough space between Z layers.

I was thinking two different kinds of "3D" layering. First is having tiles both above and below a given Z Layer. I.E
An Example would be :

Z0+0.2 - Floor Tiles (Dense)
Z0+0.4 - Decal Tiles (Sparse)
Z0+0.6 - Sprite Layer (Empty)
Z0+0.8 - Overhead Tiles (Sparse) [Things like animated fans, girders, etc]

Second aspect would be having multiple floors visible at once. Think of a true top down game with a perspective camera akin to the original GTA taking place in a 4 story hotel with a glass floor over the lobby, if you walk around the floor then you would see the lobby several floors down.

Yes, master has this feature :)


Get valuta and booking date

Parse the valuta and booking date from the response and add setters and getters to the model.
Confirmed working with the DKB and the ING-Diba.

Hey @MrCrankHank
Nice PR! I just added some comments. Maybe you can have a look if you have time.
It would be also great if you could update the COMPATIBILITY.md file if you had the chance to test the library with different banks. This would be a huge help!
Have a great day!

Hi!
I readded the getDate() method and updated the compatiblity file.
Unfortunatly I only have access to the DKB and the ING-Diba, so I can't provide any further testing.
Have a great day two.

Perfect!
Merging PR and closing issue.
Thanks !


GMLake build with pytorch 2.4 failed

GMLake  failed to build with pytorch2.4, is there any adaptation plan?

同问，这个项目是不准备更新了吗


Structure tree needs update after the component style change

Technical
After change a component style the new item appears in tree but old reference is not removed.
Description
Structure tree needs update after the component style change
Steps to reproduce

Create a new project in Design Editor
Insert listview with several items
Open Structure Tree
Change style of one item
Check count of items in tree

Expected behaviour
Count of items should be the same
Actual behaviour
There is one item more

Patch has already been merged.


ISSUE: Not generating gif from USPS emails

Describe the bug
I am getting notified of packages and letters but it is not creating a gif. I even created the appropriate folder in case that was the issue.
Environment (please complete the following information):

OS: Hass.io installed in a docker
Type of device: NUC
Home Assistant version: 0.109.6
Hassio/Docker/Core? hassio in docker
Component version: 0.1.5

Logs
Paste your error logs here.
Screenshots
If applicable, add screenshots to help explain your problem.
Additional context
Add any other context about the problem here.

What do you have the image path set to?

I have the camera set as in the example. I didn't see any way in the add on to change or modify it.
`camera:

platform: local_file
file_path: /config/images/mail_and_packages/mail_today.gif
name: mail_usps`

No in the integration configuration.

Ok I see. I’m using hassio so I hd to remove the “random” checkbox as well as changing the path.

You can keep the "random" option checked, but you'll need an automation to update the camera image. I posted that automation here.


Java : Selection Sort Algorithm

@avinash201199 please assign this issue to me

@avinash201199 I have changed the topic because there is already a pr for bubble sort in java

Hi, I would like to contribute to this issue. Please assign it to me under Hacktoberfest!


HAWQ-936. Add GUC for array expansion in ORCA optimizer

Consider the query with the following pattern 'select * from foo where foo.a IN
(1,2,3,...)'. Currently, when the number of constants in the IN subquery is large,
the query optimization time is unacceptable. This is stopping customers from turning
Orca on by default since many of the queries are generated queries with such a
pattern. The root cause is due to the expansion of the IN subquery into an
expression in disjunctive normal form. The objective of this patch is to add a guc
parameter 'optimizer_array_expansion_threshold' to control the maximum
number of array elements in IN array list. By default, the GUC value is
set to 25, which means if the array size is larger than 25, the array
expansion is disabled.

This PR will give https://github.com/apache/incubator-hawq/pull/795 a free ride.

LGTM

LGTM

pushed to master:
https://github.com/apache/incubator-hawq/commit/950065bb0db627992be6b96afb4671b3c5ab1c90


Add plain string docstrings and update tests.

Coverage decreased (-2.14%) when pulling e8733155dde6cc5c3e56c94008dfb0232a109a5a on mh/bare-docstrings into 82d2b4b4684a9a6bf4842706f20ff848e1c15468 on master.

Coverage decreased (-2.14%) when pulling 92ce3f248a480b086c9b3ccd9362226be69dec55 on mh/bare-docstrings into 82d2b4b4684a9a6bf4842706f20ff848e1c15468 on master.


User is logged out when they click on Revision ID X link

Sign page then open VerifyPage extension.
Click on Revision ID 9 link in extension drop down.

The users key should be displayed. Instead the user is required to log in again.

See red arrow in the screen shot

Can't recreate after several attempts. Assuming it was a timed logout at this stage.


Add flag to ensure folder exists before copy

Add flag to ensure destination folder exists to being able to copy file to unexisted folder in one command

Thank you for the effort to improve our user experience!
I have some thoughts about adding the directory creation functionality to the copy action:

This is already achievable using the mkdir action.
Adding directory creation to the copy action would give it two responsibilities: copying files and creating directories. I think we should try to keep each action has a single responsibility, to maintain clean separation of concerns.

Instead of doing this, my recommendation is that we should focus on developing a solution that makes running multiple-step actions easier.
Currently, running multiple sansshell actions is only achievable using bash script that invokes sanssh repeatedly. It'd be nice if we have a solution that enable users to define something like a "workflow" or "chained operations".

Currently, running multiple sansshell actions is only achievable using bash script that invokes sanssh repeatedly. It'd be nice if we have a solution that enable users to define something like a "workflow" or "chained operations".

Agreed, this option gives more possibilities for us


404 400 500 responses dose not trigger the catch block

I have an existing code base which uses Axois, and I want to port to node-fetch.
All my calls are wrapped with try-catch blocks, and it's important that an erroneous response (404,400,500...) will reach the catch black and not continue executing code after the call.
try{
await axios.get('/user?ID=12345')
//If we got 404, we should not reach this line, and instead go to catch block.
}catch(){
}

When using node-fetch instead of Axios, the catch block will not be triggered. How can I change this behavior?

You cannot. That's how fetch() works, including in browsers. You could throw yourself however:
try {
  const res = await fetch(...);
  if (!res.ok) {
    // All error codes would go into this condition
    throw new Error(...);
  }
} catch (err) {
  // ...
}


The inconsistent inference results

Hi, I found that for the same checkpoints of IML-ViT, the inference results on CASIA v1 inferenced through this IMDB-IML-ViT framework is much lower (~12%) that computed within of the original code base framework IML-ViT (~70%).

Thanks for your attention to our project!
Sorry for the misleading results. Could you please attach the corresponding log for each experiment for analysis and locate the issue for us?

I located the issue, the data augmentations are inconsistent. For trained checkpoints, you have used resize with padding, for testing evaluation code in IMDLBenCo, you have used resize without padding, thus the data distribution is not aligned. On my custom dataset, I found that  resize without padding works better than resize with padding. Did you observe similar results?

Hi,
Anyway, if you utilize the demo_test_iml_vit.sh generated from the command benco init model_zoo, I believe it will be resized with padding with the parameter if_padding.
https://github.com/scu-zjz/IMDLBenCo/blob/e4f59d0d01bc85326eceefa0061788d187870670/IMDLBenCo/statics/model_zoo/runs/demo_test_iml_vit.sh#L1-L20
I am not sure how you train IML-ViT with resize without padding. Since the original code design only supports 1024x1024 input. Mostly we don't apply a traditional resize but just keep the raw resolution and pad the image to 1024x1024. Could you please specify the detailed implementation here for discussion? Thank you very much.

Oh, I was not using demo_test_iml_vit.sh for testing, but just use demo_train_iml_vit.sh for evaluation, where I put the evaluation code before the training code in the train.py. In the generated demo_train_iml_vit.sh, I believe the configs are like:
base_dir="./output_dir_imlvit_orig"
mkdir -p ${base_dir}

CUDA_VISIBLE_DEVICES=1 \
torchrun  \
    --standalone    \
    --nnodes=1     \
    --nproc_per_node=1 \
../train.py \
    --model IML_ViT \
    --edge_lambda 20 \
    --vit_pretrain_path ../mae_pretrain_vit_base.pth \
    --world_size 1 \
    --batch_size 3 \
    --data_path  /<casia_v2> \
    --epochs 200 \
    --lr 1e-4 \
    --image_size 1024 \
    --if_resizing \
    --min_lr 5e-7 \
    --weight_decay 0.05 \
    --edge_mask_width 7 \
    --test_data_path /<casia_v1> \
    --warmup_epochs 2 \
    --output_dir ${base_dir}/ \
    --log_dir ${base_dir}/ \
    --accum_iter 8 \
    --seed 42 \
    --test_period 4 \
    --resume /<resumed.pth>

where if_resizing is set to True, and the data_transform would be resize without padding, like in the code below:
self.post_transform = None
        if is_padding == True:
            self.post_transform = get_albu_transforms(type_ = "pad", output_size = output_size)
        if is_resizing == True:
            self.post_transform = get_albu_transforms(type_ = "resize", output_size = output_size)

Thank you for your feedback.
I see your points. Generally, the deep neural network fits a distribution as a function. Thus, keeping the training distribution similar to the testing distribution is essential. Just like the issue mentioned by you "I made the conclusion that it was not because
'pad' is better than 'resize', but your checkpoints were trained based on 'pad' mode."
Further, there are many possible explanations for the performance on your custom dataset. Such as:

The aspect ratio of your image is quite appropriate to 1:1. i.e. resizing operation won't twist the image.
The resolution of your image is relatively larger than CASIAv2.
Other issues may need to be discussed in a case study on those datasets.

Thanks again for your attention to our project. If you find the issue solved, please close the issue. You are also welcome to discuss further concerns and problems you met.


[SPARK-7556][ML][Doc] Add user guide for spark.ml Binarizer, including Scala, Java and Python examples

JIRA: https://issues.apache.org/jira/browse/SPARK-7556

Merged build triggered.

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Test build #32603 has started for   PR 6116 at commit 6cf8cba.

Test build #32603 has finished for   PR 6116 at commit 6cf8cba.

This patch passes all tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
A simple [Binarizer](api/scala/index.html#org.apache.spark.ml.feature.Binarizer) class provides this functionality. Besides the common parameters of InputColandOutputCol, Binarizerhas the parameterThreshold used for binarizing continuous numerical features. The features greater than the threshold, will be binarized to 1.0. The features equal to or less than the threshold, will be binarized to 0.0. The example below shows how to binarize numerical features.

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@viirya Thank you for the quick PR!  I just had a few comments.  Also, to confirm, have you run each of the examples?
Also, can you please add a little more info to the PR description since it will become the commit message?  E.g., "Added user guide example for spark.ml Binarizer, including Scala,Java,Python examples"

@jkbradley Yes, I have run all the examples.

Merged build triggered.

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Test build #32685 has started for   PR 6116 at commit 1bf9c09.

Merged build triggered.

Merged build started.

Test build #32686 has started for   PR 6116 at commit 5b7ef1d.

Test build #32685 has finished for   PR 6116 at commit 1bf9c09.

This patch passes all tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
A simple [Binarizer](api/scala/index.html#org.apache.spark.ml.feature.Binarizer) class provides this functionality. Besides the common parameters of inputColandoutputCol, Binarizerhas the parameterthreshold used for binarizing continuous numerical features. The features greater than the threshold, will be binarized to 1.0. The features equal to or less than the threshold, will be binarized to 0.0. The example below shows how to binarize numerical features.

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Test build #32686 has finished for   PR 6116 at commit 5b7ef1d.

This patch passes all tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
A simple [Binarizer](api/scala/index.html#org.apache.spark.ml.feature.Binarizer) class provides this functionality. Besides the common parameters of inputColandoutputCol, Binarizerhas the parameterthreshold used for binarizing continuous numerical features. The features greater than the threshold, will be binarized to 1.0. The features equal to or less than the threshold, will be binarized to 0.0. The example below shows how to binarize numerical features.

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Test build #32754 has started for   PR 6116 at commit 40cb677.

Test build #32754 has finished for   PR 6116 at commit 40cb677.

This patch passes all tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
A simple [Binarizer](api/scala/index.html#org.apache.spark.ml.feature.Binarizer) class provides this functionality. Besides the common parameters of inputColandoutputCol, Binarizerhas the parameterthreshold used for binarizing continuous numerical features. The features greater than the threshold, will be binarized to 1.0. The features equal to or less than the threshold, will be binarized to 0.0. The example below shows how to binarize numerical features.

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LGTM, merging into master and branch-1.4
@viirya Thanks!


Huawei's listing was rejected, obtaining SSID, IP, and BSSID before calling the privacy protocol

Ask your Question

尊敬的开发者，您好，建议参考如下调用栈协助您进行定位，谢谢。
1、未同意隐私政策，应用获取SSID个人信息
[com.reactnativecommunity.netinfo.ConnectivityReceiver.createDetailsMap(ConnectivityReceiver.java:168),
com.reactnativecommunity.netinfo.ConnectivityReceiver.createConnectivityEventMap(ConnectivityReceiver.java:136),
com.reactnativecommunity.netinfo.ConnectivityReceiver.sendConnectivityChangedEvent(ConnectivityReceiver.java:108),
com.reactnativecommunity.netinfo.ConnectivityReceiver.updateConnectivity(ConnectivityReceiver.java:101),
com.reactnativecommunity.netinfo.NetworkCallbackConnectivityReceiver.updateAndSend(NetworkCallbackConnectivityReceiver.java:115),
com.reactnativecommunity.netinfo.NetworkCallbackConnectivityReceiver$ConnectivityNetworkCallback.onAvailable(NetworkCallbackConnectivityReceiver.java:123),
android.net.ConnectivityManager$NetworkCallback.onAvailable(ConnectivityManager.java:3413),
android.net.ConnectivityManager$CallbackHandler.handleMessage(ConnectivityManager.java:3720),
android.os.Handler.dispatchMessage(Handler.java:109),
android.os.Looper.loop(Looper.java:228),
android.os.HandlerThread.run(HandlerThread.java:67)]
2、未同意隐私政策，应用获取IP地址个人信息
[com.reactnativecommunity.netinfo.ConnectivityReceiver.createDetailsMap(ConnectivityReceiver.java:211),
com.reactnativecommunity.netinfo.ConnectivityReceiver.createConnectivityEventMap(ConnectivityReceiver.java:136),
com.reactnativecommunity.netinfo.ConnectivityReceiver.sendConnectivityChangedEvent(ConnectivityReceiver.java:108),
com.reactnativecommunity.netinfo.ConnectivityReceiver.updateConnectivity(ConnectivityReceiver.java:101),
com.reactnativecommunity.netinfo.NetworkCallbackConnectivityReceiver.updateAndSend(NetworkCallbackConnectivityReceiver.java:115),
com.reactnativecommunity.netinfo.NetworkCallbackConnectivityReceiver$ConnectivityNetworkCallback.onAvailable(NetworkCallbackConnectivityReceiver.java:123),
android.net.ConnectivityManager$NetworkCallback.onAvailable(ConnectivityManager.java:3413),
android.net.ConnectivityManager$CallbackHandler.handleMessage(ConnectivityManager.java:3720),
android.os.Handler.dispatchMessage(Handler.java:109),
android.os.Looper.loop(Looper.java:228),
android.os.HandlerThread.run(HandlerThread.java:67)]
3、未同意隐私政策，应用获取BSSID个人信息
[com.reactnativecommunity.netinfo.ConnectivityReceiver.createDetailsMap(ConnectivityReceiver.java:180),
com.reactnativecommunity.netinfo.ConnectivityReceiver.createConnectivityEventMap(ConnectivityReceiver.java:136),
com.reactnativecommunity.netinfo.ConnectivityReceiver.sendConnectivityChangedEvent(ConnectivityReceiver.java:108),
com.reactnativecommunity.netinfo.ConnectivityReceiver.updateConnectivity(ConnectivityReceiver.java:101),
com.reactnativecommunity.netinfo.NetworkCallbackConnectivityReceiver.updateAndSend(NetworkCallbackConnectivityReceiver.java:115),
com.reactnativecommunity.netinfo.NetworkCallbackConnectivityReceiver$ConnectivityNetworkCallback.onAvailable(NetworkCallbackConnectivityReceiver.java:123),
android.net.ConnectivityManager$NetworkCallback.onAvailable(ConnectivityManager.java:3413),
android.net.ConnectivityManager$CallbackHandler.handleMessage(ConnectivityManager.java:3720),
android.os.Handler.dispatchMessage(Handler.java:109),
android.os.Looper.loop(Looper.java:228),
android.os.HandlerThread.run(HandlerThread.java:67)]

I did not proactively use the API before agreeing to the privacy agreement

You have asserted there is a problem without providing any of the information necessary to help you.
https://stackoverflow.com/help/how-to-ask
https://stackoverflow.com/help/minimal-reproducible-example
I believe this was handled in this module before and it should not do anything until you configure it.
I will assert - same as you with no evidence because if it's good enough to open an issue it's good enough to close an issue - that this module will not do as you assert and that you have some other code accessing the identifiers.

@qq382724935 兄弟 你解决了吗，我也碰到了该问题

@qq382724935 有没有解决办法，我碰到了该问题

@mikehardy There is no solution, I also encountered the problem, it really exists, the startup automatically obtained part of the user information

Ok @caijiami - if it does that - if this module gets some part of the user's device identifiers prior to configure, please point to the code that did it (with a link) and post a PR
If it is happening it will be somewhere around the "constants" part of the native code as that is fetched immediately. Nothing else is executed on the native side unless it is specifically requested
Note, there are no constants exported from this module (unlike device-info: https://github.com/react-native-device-info/react-native-device-info/blob/afbbd7f9bc856b90cc37372e0810e8f6ee4cf9ce/android/src/main/java/com/learnium/RNDeviceInfo/RNDeviceModule.java#L192-L221)
Your statement is an "assertion", it is the equivalent of saying "I like to think this thing"
Evidence is what we need here
Assertions do not qualify as evidence. Evidence is pointing to code. Everything else is just wasting time until there is evidence

@mikehardy Huawei application market launch process detected：Not agreeing to the privacy policy, the application obtains SSID personal information, obtains IP address personal information, and the application obtains BSSID personal information。I just add the package @react-native-community/netinfo

I'm not aware of the netinfo module gathering anything until you use one of the hook methods or call an API method to fetch state, so this is surprising @LemoHaley
Either way, the Huawei store is not a use case of mine and I don't have any free volunteer time to donate to this module for anything other than merging PRs. If you can determine that the module is gathering info prior to an API call in the module, and you post a PR, I could merge it.

Invoke "NetworkCallbackConnectivityReceiver.setCanInit(true);" after the user agrees to the agreement.

@mikehardy The reason why the application fetches the SSID at launch may be:(netinfo v5.7.1)
@LemoHaley @caijiami @qq382724935 Temporary solution In com.reactnativecommunity.netinfo.NetworkCallbackConnectivityReceiver:  The latest version has slight differences, but the overall difference is negligible. thiz.updateAndSend() may need to be changed to thiz.asyncUpdateAndSend(DELAY_MS).
Invoke "NetworkCallbackConnectivityReceiver.setCanInit(true);" after the user agrees to the agreement.

这个方法可以临时解决

@mikehardy应用程序在启动时获取SSID的原因可能是：（netinfo v5.7.1）
@LemoHaley @caijiami @qq382724935临时解决方案在com.reactnativecommunity.netinfo.NetworkCallbackConnectivityReceiver中： 最新版本有细微差别，但整体差异可以忽略不计。thiz.updateAndSend ()可能需要改为thiz.asyncUpdateAndSend(DELAY_MS)。
用户同意该协议后，调用“NetworkCallbackConnectivityReceiver.setCanInit(true);”。

可以解决这个问题，


cargo sqlx prepare do not compile in offline mode

Bug Description
When i ran the command "cargo sqlx prepare" i'm getting:
error: error returned from database: relation "public.measurements" does not exist
--> src/parse_and_database.rs:260:5
|
260 | /     sqlx::query!("INSERT into public.measurements (measurement_time, device_id, measurement_type_id, measurement_value) SELECT * FROM UNNEST...
261 | |                 &mt[..],
262 | |                 &id[..],
263 | |                 &mt_id[..],
264 | |                 &value[..]
265 | |         )
| |_________^
|
= note: this error originates in the macro $crate::sqlx_macros::expand_query which comes from the expansion of the macro sqlx::query (in Nightly builds, run with -Z macro-backtrace for more info
I undertood that cargo sqlx prepare is a way to compile in offline mode, but it is not working for me.
Minimal Reproduction
    sqlx::query!("INSERT into public.measurements (measurement_time, device_id, measurement_type_id, measurement_value) SELECT * FROM UNNEST($1::timestamp[], $2::smallint[], $3::smallint[], $4::real[])",                 &mt[..],                 &id[..],                 &mt_id[..],                 &value[..]         )         .execute(pool)         .await?;
Info

SQLx version: 0.7.4
SQLx features enabled: features = [ "postgres", "runtime-tokio", "tls-rustls", "chrono" ]
Database server and version: Postgres 15.6
Operating system: Ubuntu 23.10
rustc --version: 1.77.1

I believe I understood my mistake. I should run sqlx Migrate before running sqlx prepare.


jsonutils:fromXML() return type is wrong

Description:
jsonutils:fromXML() signature specifies it returns a json|error but on runtime, there is a case where it returns a handle : when passing a text node xml object
json|error j = jsonutils:fromXML(xml `aaa`);
The problem is not that it fails in that case, the real problem is that the runtime type is different than compile-time type
Steps to reproduce:
Insert the line above in a simple ballerina program and run it, it will cause an error (cannot cast "handle" to "json|error")
Affected Versions:
1.1.1
OS, DB, other environment details and versions:
openjdk 8, debian buster

Seems to be an issue with jsonutils:fromXML functions returning java strings rather than StringValues instances.


If user cancels save as dialog after changing the encoding of dirty f…

…ile, then encoding should not be changed in the file data structure

Late catch but still better we fixed this :+1


Gpudate.exe /force

This command is wrong.
should be Gpupdate /force. There is a p lost which makes command not running.

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

ID: a6c3533f-ff4a-cbb5-5e3b-055756def68e
Version Independent ID: 0f8acc5e-138e-61f1-a35c-4caa50899d83
Content: Configuring port ranges and a Quality of Service policy for your clients
Content Source: Skype/SfbServer/manage/network-management/qos/configuring-port-ranges-for-your-skype-clients.md
Product: skype-for-business-itpro
GitHub Login: @LanaChin
Microsoft Alias: v-lanac

@crmlgb Thank you for submitting feedback and contributing to the docs. We are currently investigating this.

@scanum bring questions to me if you have them

Hi James,
there is a wrong command showing microsoft docs,
Gpudate.exe /force (#2660)
it should be Gpupdate /force. There’s a “p” missing.
thanks
<EMAIL_ADDRESS>在 2019年7月20日，上午12:02，James Birkinshaw<EMAIL_ADDRESS>写道：
@scanum bring questions to me if you have them
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub, or mute the thread.

@jambirk I've just made a change, please merge the PR and feel free to close this issue

@crmlgb Thank you for submitting feedback. We understand that this issue has been resolved.
Please feel free to re-open this issue if there is a specific area of the docs that we can improve or make better. Thank you.


Allow 'autoplay' on YouTube

Fix #213
This PR allows 'autoplay' on YouTube.
FYI: Since April 2018, Google made some changes to the Autoplay Policy.

Thanks, released in v2.4.0!


Shortcuts

Todo

[x] Implement design
[x] Implement unregister/register all when shortcuts are toggled
[x] Implement validation
[x] Shake animation?
[x] Add X icon

This should be backwards compatible with the old setting too.

When I press Option key, it shows the Option key and also an empty white box.

When I press Option key, it shows the Option key and also an empty white box.

Fixed


Adding "junk data" tests to the MSAL Cache

These are tests I wrote to verify the cache skips/preserves unexpected values; this is a setup for a future conversation around potentially storing data from OneAuth in this cache.

Q: Should we also be able to write data there after it is populated and not affect the values we have?

Can add an additional test for this

Q: Should we also be able to write data there after it is populated and not affect the values we have?

Can add an additional test for this

Added here


problem with restoring IRv2 checkpoint

Not an issue specifically with tensorpack.
I was trying to load a checkpoint model for Inception-Resnet-v2 (uploaded here). I re-used the tf.slim model for this network mentioned here and use tensorpack as the front-end. Attached are both these file (in text format since I cant upload .py files).
I am running into restoring the graph variables problems. Here is the last portion of the error log:
W tensorflow/core/framework/op_kernel.cc:975] Invalid argument: Expected to restore a tensor of type int32, got a tensor of type int64 instead: tensor_name = global_step
         [[Node:<PHONE_NUMBER>36424/RestoreV2_908 = RestoreV2[dtypes=[DT_INT32], _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_140222649036424/Const_0,<PHONE_NUMBER>36424/RestoreV2_908/tensor_names,<PHONE_NUMBER>36424/RestoreV2_908/shape_and_slices)]]
W tensorflow/core/framework/op_kernel.cc:975] Invalid argument: Expected to restore a tensor of type int32, got a tensor of type int64 instead: tensor_name = global_step
         [[Node:<PHONE_NUMBER>36424/RestoreV2_908 = RestoreV2[dtypes=[DT_INT32], _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_140222649036424/Const_0,<PHONE_NUMBER>36424/RestoreV2_908/tensor_names,<PHONE_NUMBER>36424/RestoreV2_908/shape_and_slices)]]
W tensorflow/core/framework/op_kernel.cc:975] Invalid argument: Expected to restore a tensor of type int32, got a tensor of type int64 instead: tensor_name = global_step
         [[Node:<PHONE_NUMBER>36424/RestoreV2_908 = RestoreV2[dtypes=[DT_INT32], _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_140222649036424/Const_0,<PHONE_NUMBER>36424/RestoreV2_908/tensor_names,<PHONE_NUMBER>36424/RestoreV2_908/shape_and_slices)]]
W tensorflow/core/framework/op_kernel.cc:975] Invalid argument: Expected to restore a tensor of type int32, got a tensor of type int64 instead: tensor_name = global_step
         [[Node:<PHONE_NUMBER>36424/RestoreV2_908 = RestoreV2[dtypes=[DT_INT32], _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_140222649036424/Const_0,<PHONE_NUMBER>36424/RestoreV2_908/tensor_names,<PHONE_NUMBER>36424/RestoreV2_908/shape_and_slices)]]
W tensorflow/core/framework/op_kernel.cc:975] Invalid argument: Expected to restore a tensor of type int32, got a tensor of type int64 instead: tensor_name = global_step
         [[Node:<PHONE_NUMBER>36424/RestoreV2_908 = RestoreV2[dtypes=[DT_INT32], _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_140222649036424/Const_0,<PHONE_NUMBER>36424/RestoreV2_908/tensor_names,<PHONE_NUMBER>36424/RestoreV2_908/shape_and_slices)]]

Traceback (most recent call last):
  File "tpInception_resnet_v2.py", line 204, in <module>
    SyncMultiGPUTrainer(config).train()
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/base.py", line 64, in train
    self.setup()
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/base.py", line 146, in setup
    self.config.session_init.init(self.sess)
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/tfutils/sessinit.py", line 35, in init
    self._init(sess)
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/tfutils/sessinit.py", line 82, in _init
    saver.restore(sess, self.path)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 1388, in restore
    {self.saver_def.filename_tensor_name: save_path})
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 766, in run
    run_metadata_ptr)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 964, in _run
    feed_dict_string, options, run_metadata)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1014, in _do_run
    target_list, options, run_metadata)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1034, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Expected to restore a tensor of type int32, got a tensor of type int64 instead: tensor_name = global_step
         [[Node:<PHONE_NUMBER>36424/RestoreV2_908 = RestoreV2[dtypes=[DT_INT32], _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_140222649036424/Const_0,<PHONE_NUMBER>36424/RestoreV2_908/tensor_names,<PHONE_NUMBER>36424/RestoreV2_908/shape_and_slices)]]
         [[Node:<PHONE_NUMBER>36424/RestoreV2_688/_965 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_5427_140222649036424/RestoreV2_688", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]

Caused by op u'140222649036424/RestoreV2_908', defined at:
  File "tpInception_resnet_v2.py", line 204, in <module>
    SyncMultiGPUTrainer(config).train()
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/base.py", line 64, in train
    self.setup()
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/base.py", line 146, in setup
    self.config.session_init.init(self.sess)
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/tfutils/sessinit.py", line 35, in init
    self._init(sess)
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/tfutils/sessinit.py", line 81, in _init
    saver = tf.train.Saver(var_list=dic, name=str(id(dic)), write_version=2)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 1000, in __init__
    self.build()
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 1030, in build
    restore_sequentially=self._restore_sequentially)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 624, in build
    restore_sequentially, reshape)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 361, in _AddRestoreOps
    tensors = self.restore_op(filename_tensor, saveable, preferred_shard)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 200, in restore_op
    [spec.tensor.dtype])[0])
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_io_ops.py", line 441, in restore_v2
    dtypes=dtypes, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op
    op_def=op_def)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2240, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1128, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): Expected to restore a tensor of type int32, got a tensor of type int64 instead: tensor_name = global_step
         [[Node:<PHONE_NUMBER>36424/RestoreV2_908 = RestoreV2[dtypes=[DT_INT32], _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_140222649036424/Const_0,<PHONE_NUMBER>36424/RestoreV2_908/tensor_names,<PHONE_NUMBER>36424/RestoreV2_908/shape_and_slices)]]
         [[Node:<PHONE_NUMBER>36424/RestoreV2_688/_965 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_5427_140222649036424/RestoreV2_688", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]

Prefetch process exited.
Prefetch process exited.

This error is strange since I dont have a tensor called global_step. I even tried to change the dtype of GLOBAL_STEP_OP_NAME in tfutils/common.py to tf.int64 but I get some other error with it.
Any suggestions/pointer as to what I am doing wrong and/or how to fix this?
BTW, I am still using tf version 0.12.0rc1. Not sure if going to 1.0.0 could fix this problem.
inception_resnet_v2.py.txt
tpInception_resnet_v2.py.txt
run command: python tpInception_resnet_v2.py --gpu 0,1,2,3,4,5,6,7 --data /tank/imagenet-tensorpack-data --load googleModel/inception_resnet_v2_2016_08_30.ckpt

I updated to TF 1.0.0.
Getting a different error this time.
Traceback (most recent call last):
  File "tpInception_resnet_v2.py", line 204, in <module>
    SyncMultiGPUTrainer(config).train()
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/base.py", line 64, in train
    self.setup()
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/base.py", line 130, in setup
    self._setup()   # subclass will setup the graph
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/multigpu.py", line 133, in _setup
    self.config.tower, lambda: self._get_cost_and_grad()[1])
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/multigpu.py", line 41, in _multi_tower_grads
    grad_list.append(get_tower_grad_func())
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/multigpu.py", line 133, in <lambda>
    self.config.tower, lambda: self._get_cost_and_grad()[1])
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/feedfree.py", line 54, in _get_cost_and_grad
    self.build_train_tower()
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/feedfree.py", line 43, in build_train_tower
    f()
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/train/feedfree.py", line 36, in f
    self.model.build_graph(inputs)
  File "/home/akm/TF/tpNew/tensorpack/tensorpack/models/model_desc.py", line 113, in build_graph
    self._build_graph(model_inputs)
  File "tpInception_resnet_v2.py", line 53, in _build_graph
    logits, end_points = inception_resnet_v2(image, is_training=is_training)
  File "/home/akm/TF/tpNew/tensorpack/examples/IRv2/inception_resnet_v2.py", line 169, in inception_resnet_v2
    net = tf.concat(3, [tower_conv, tower_conv1_1, tower_conv2_2, tower_pool_1])
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/array_ops.py", line 1047, in concat
    dtype=dtypes.int32).get_shape(
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 651, in convert_to_tensor
    as_ref=False)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 716, in internal_convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 176, in _constant_tensor_conversion_function
    return constant(v, dtype=dtype, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 165, in constant
    tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_util.py", line 367, in make_tensor_proto
    _AssertCompatible(values, dtype)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible
    (dtype.name, repr(mismatch), type(mismatch).__name__))
TypeError: Expected int32, got list containing Tensors of type '_Message' instead.
Prefetch process exited.
Prefetch process exited.

I guess something to do with the concat API. I did minor mod to the file. Attaching them here.
inception_resnet_v2.py.txt
tpInception_resnet_v2.py.txt

The second problem is because TF 1.0 changes API of tf.concat. You should swap the argument order of tf.concat in inception_resnet_v2.py.
The first is because the checkpoint contains an unused variable "global_step:0" which happens to conflict with a variable tensorpack defined. In general there is no good way to solve this and it's best to remove unused variables from a checkpoint. But I'll push a change later to make it behave less strict in this case (print a warning instead of crash).

Thanks.
How does one remove a variable from a checkpoint? Simply delete that line or its more involved?

On Feb 14, 2017, at 8:40 PM, Yuxin Wu<EMAIL_ADDRESS>wrote:
The second problem is because TF 1.0 changes API of tf.concat. You should swap the argument order of tf.concat in inception_resnet_v2.py.
The first is because the checkpoint contains an unused variable "global_step:0" which happens to conflict with a variable tensorpack defined. In general there is no good way to solve this and it's best to remove unused variables from a checkpoint. But I'll push a change later to make it behave less strict in this case (print a warning instead of crash).
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You should be able to load the model with the current HEAD now (don't need to remove the variable).

I am able to load the checkpoint. I see WRN messages like this for every variable in the graph model:
...
...
Variable InceptionResnetV2/Conv2d_1a_3x3/weights in the graph not found in checkpoint!
Variable InceptionResnetV2/Conv2d_1a_3x3/BatchNorm/beta in the graph not found in checkpoint!
Variable InceptionResnetV2/Conv2d_1a_3x3/BatchNorm/moving_mean in the graph not found in checkpoint!
Variable InceptionResnetV2/Conv2d_1a_3x3/BatchNorm/moving_variance in the graph not found in checkpoint!
Variable InceptionResnetV2/Conv2d_2a_3x3/weights in the graph not found in checkpoint!
Variable InceptionResnetV2/Conv2d_2a_3x3/BatchNorm/beta in the graph not found in checkpoint!
Variable InceptionResnetV2/Conv2d_2a_3x3/BatchNorm/moving_mean in the graph not found in checkpoint!
Variable InceptionResnetV2/Conv2d_2a_3x3/BatchNorm/moving_variance in the graph not found in checkpoint!

...
...

Variable InceptionResnetV2/Repeat_2/block8_9/Branch_1/Conv2d_0b_1x3/BatchNorm/moving_mean in checkpoint not found in the graph!
Variable InceptionResnetV2/Repeat_2/block8_9/Branch_1/Conv2d_0b_1x3/BatchNorm/moving_variance in checkpoint not found in the graph!
Variable InceptionResnetV2/Repeat_2/block8_9/Branch_1/Conv2d_0b_1x3/weights in checkpoint not found in the graph!
Variable InceptionResnetV2/Repeat_2/block8_9/Branch_1/Conv2d_0c_3x1/BatchNorm/beta in checkpoint not found in the graph!
Variable InceptionResnetV2/Repeat_2/block8_9/Branch_1/Conv2d_0c_3x1/BatchNorm/moving_mean in checkpoint not found in the graph!
Variable InceptionResnetV2/Repeat_2/block8_9/Branch_1/Conv2d_0c_3x1/BatchNorm/moving_variance in checkpoint not found in the graph!
Variable InceptionResnetV2/Repeat_2/block8_9/Branch_1/Conv2d_0c_3x1/weights in checkpoint not found in the graph!
Variable InceptionResnetV2/Repeat_2/block8_9/Conv2d_1x1/biases in checkpoint not found in the graph!
Variable InceptionResnetV2/Repeat_2/block8_9/Conv2d_1x1/weights in checkpoint not found in the graph!
Variable global_step in checkpoint not found in the graph!
...

Is this the right behavior? I dont know if the checkpoint variables are being loaded/restored properly. Could you comment?
Attached is the log file till the point the epochs start.
log.log.txt

I took at look the checkpoint. It seems to the very old checkpoint format (before TF 0.8 maybe?) where the keys don't contain the :0 in the end. So there is a mismatch.
I'll fix some code to be compatible with that format.

Now it can start training with multi-GPU. You should only see the following variables not found (just some summaries):
[0216 14:52:07 @sessinit.py:110] WRN Variable learning_rate in the graph not found in checkpoint!
[0216 14:52:08 @sessinit.py:110] WRN Variable tower0/train-error-top1/EMA in the graph not found in checkpoint!
[0216 14:52:08 @sessinit.py:110] WRN Variable tower0/cost/EMA in the graph not found in checkpoint!
[0216 14:52:08 @sessinit.py:110] WRN Variable tower0/total_cost/EMA in the graph not found in checkpoint!
[0216 14:52:08 @sessinit.py:110] WRN Variable input_queue_size/EMA in the graph not found in checkpoint!
[0216 14:52:08 @sessinit.py:110] WRN Variable tower0/train-error-top5/EMA in the graph not found in checkpoint!
[0216 14:52:08 @sessinit.py:110] WRN Variable tower0/regularize_loss/EMA in the graph not found in checkpoint!

One thing that may cause some training slow-down: google's training code handles the batch norm updates manually, by only using UPDATE_OPS from the first GPU.
With tensorpack models this was done automatically.
But with slim models, currently UPDATE_OPS from all GPUs will be executed. This was from PR #81. Now it looks like "applying the UPDATE_OPS blindly" is not always what a user would want. @PatWie for comments.
One possible solution is to use slim.arg_scope to change the updates_collections option of slim.batch_norm. But I'm not familiar with slim so I'm not sure does it work.

Thanks a lot for looking into this and helping out.

On Feb 15, 2017, at 11:15 PM, Yuxin Wu<EMAIL_ADDRESS>wrote:
One thing that may cause some training slow-down: google's training code handles the batch norm updates manually, by only using UPDATE_OPS from the first GPU.
With tensorpack models this was done automatically.
But with slim models, currently UPDATE_OPS from all GPUs will be executed. This was from PR #81. Now it looks like "applying the UPDATE_OPS blindly" is not always what a user would want. @PatWie for comments.
One possible solution is to use slim.arg_scope to change the updates_collections option of slim.batch_norm. But I'm not familiar with slim so I'm not sure does it work.
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What is the batch size that you are using and how many GPUs?

Inception consumes a lot of memory. I can run it with batch 32 per GPU, Google also used this number in their recent papers.

Closing this.

If you could look into why the checkpoint loading is slow that would be helpful. This is a performance aspect not functionality. I am able to get the experiment running.

I had to change the num_classes to 1001 (line 94/95) to get this running. I thought imagenet has 1000 classes. The train folder has 1000 folders. Where is the additional 1 class/folder?

https://github.com/tensorflow/models/tree/master/slim#the-resnet-and-vgg-models-have-1000-classes-but-the-imagenet-dataset-has-1001

@ppwwyyxx Did you continue the training process for this network?
I was re-training, starting from the checkpoint and (1) the process is very slow 0.70it/sec on 8 GPUs and (2) the error rate is quite bad - 0.98 top1 and 0.84 top5 after 2 epochs.
The only change to the code I did from the ones I attached last was to change 1000 to 1001 . Learning rate is 1e-6.
Any idea what is going on?

No. Have you make sured that the network takes the same input format (rgb/bgr, value range, etc) and output class id? It may not be the same as what's used by the code here.

evalInceptionResnetv2.py.txt
inception_resnet_v2.py.txt
run.cmd.txt
I went with your advice of doing an eval on the model. The eval is giving me very bad results: Top1 Error: 0.98718, Top5 Error: 0.83158
I dont know what is going wrong and where. I added the BGR to RGB and follow preprocessing items that tf/slim does but its not helping.
Some related links:
Preprocessing: https://github.com/tensorflow/models/blob/master/slim/preprocessing/inception_preprocessing.py#L237-L275
Other efforts trying to do eval on IRv2: https://github.com/kentsommer/keras-inception-resnetV2
This dicussion also mentions something is wrong somewhere: https://github.com/kentsommer/keras-inception-resnetV2/issues/1
Could you give this code a try when you get a chance. Thanks

As I said they may not use the same class id:
https://github.com/tensorflow/models/blob/master/inception/inception/data/build_imagenet_data.py#L119

I see now what you are saying. What should I do to fix this?

You can convert the label either on the dataflow (you can use MapDataComponent) or inside the model (you can use tf.gather or tf.gather_nd).


[Fix][Connector-v2] Fix the sql statement error of create table for doris and starrocks

Purpose of this pull request

Fix the sql statement error caused by the source table having no primary key or unique key for doris and startrocks. Link #6646
Does this PR introduce any user-facing change?

How was this patch tested?

Check list

[ ] If any new Jar binary package adding in your PR, please add License Notice according
New License Guide
[ ] If necessary, please update the documentation to describe the new feature. https://github.com/apache/seatunnel/tree/dev/docs
[ ] If you are contributing the connector code, please check that the following files are updated:

Update change log that in connector document. For more details you can refer to connector-v2
Update plugin-mapping.properties and add new connector information in it
Update the pom file of seatunnel-dist

[ ] Update the release-note.

Could you check the starrocks connector too? Thanks

Could you check the starrocks connector too? Thanks

OK

We can just use common error to throw key message.

I see it. It's done

Just a record: https://github.com/apache/seatunnel/pull/6354  I add rowtype_dup_key for Doris duplicate table Source sync to Doris duplicate table Sink. After this pr merge, I will change code.


Invalid return type ‘void’ of constexpr function

Got an issue because my gcc version is 4.9. Here is a snippet of what I'm getting when building hpx:

../hpx/runtime/serialization/output_container.hpp:106:39: error: invalid return type ‘void’ of constexpr function ‘static constexpr void hpx::serialization::detail::basic_chunker::set_chunk_size(std::size_t)’
HPX_CONSTEXPR static void set_chunk_size(std::size_t)

@atrantan: what workaround would you suggest we apply?

Honestly, got no idea except considering gcc 4.9 as obsolete

@atrantran Those functions don't have to be constexpr to begin with. The optimizer should be able to get rid of those in any case. Could you prepare a patch please which removes the constexpr from the offending functions?

Sure. Done in PR #2642


Oxy

Update 15/10/21: This branch has been edited to include changes agreed at the oxygen subgroup of TG-COMP on 4th Oct. These relate to depth for oxygen, data is filtered to use the deepest sample per station and only where this is within 10m of the seabed. Since approximately 1/3rd of the data is without water column depth information this has been extracted from the emodnet bathymetry where this was missing. A flag has been added to make it clear where bottom depth is infilled from bathymetry.
The agreed statistic at the assessment area scale is 5th percentile.
This branch has been edited to use mean of the lowest quartile as the assessment statistic for oxygen, rather than minimum. I've also added the document put together by myself and @pdlamb to explain what the code is doing. It's a word doc for now but should probably be adapted into a readme.

@kcollingridge instead of merging the pull request which would have conflights to resolve, I have refactored the oxygen defiency algorithm into master using slightly difference method which give the same result. The main being that the bathymetric for missing bot. depth using the EMODnet web service instead of being dependant on a manual file(s) to be downloaded before you can run the procedure.


fix(command-deploy): sync redirects after build

- Summary
This is the CLI equivalent of https://github.com/netlify/build/pull/3259 and https://github.com/netlify/build/pull/3271
When a build plugin changes redirects we need to make sure those changes are deployed.
netlify/build returns a single config.redirects property with all the redirects from netlify.toml and _redirects in the correct priority order.
To make sure the new redirects are applied in the correct order this PR updates the deploy command's code to check if the redirects were modified and if they were:

Hides any existing _redirects file so it won't be deployed
Creates a new netlify.toml with the new redirects array (based on the existing one if there is one)
Runs the deploy
Unhides the _redirects if needed and deletes the created netlify.toml file

- Test plan
Added a new test
- A picture of a cute animal (not mandatory but encouraged)
🐱

Thanks a lot @erezrokah!
On Slack, @erezrokah and I discussed exploring whether we could re-use the logic in @netlify/config which is doing the same but in production. This would prevent code duplication and promote better separation of concerns, e.g. keeping TOML parsing/serializing to @netlify/config. This might require making then restoring a copy of the files modified by @netlify/config in production like _redirects and netlify.toml.

This PR now depends on https://github.com/netlify/build/pull/3379


Order button settings

Embedded button on external website is not working.
Added the script code to website and the button accordingly but not working.
On Chrome I get the error:
Uncaught index.php?_url=/orderbutton/js&options=1&width=600&theme_color=green&background_color=%23000000&bac…:2....etc.
TypeError: undefined is not a function

Please try to follow this tutorial and let us know if the issue persists.

Hi, let me give some details.
Our main website is WP based, running on domain.tld;
Boxbilling is running on subdomain.domain.tld;
Already tried. Loaded the  to WP header and add in page an element to trigger script Order
Resource interpreted as Script but transferred with MIME type text/html: "http://client.XXDOMAINXX.com/index.php?_url=/orderbutton/js&options=1&width=6…23000000&background_opacity=50&bind_selector=.order-button&border_radius=0".
index.php?_url=/orderbutton/js&options=1&width=600&theme_color=green&background_color=%23000000&bac…:2 Uncaught TypeError: undefined is not a functionindex.php?_url=/orderbutton/js&options=1&width=600&theme_color=green&background_color=%23000000&bac…:2 show_popupindex.php?_url=/orderbutton/js&options=1&width=600&theme_color=green&background_color=%23000000&bac…:108 (anonymous function)

Can you create a support ticket in BoxBilling.com and tell us your url so we can investigate the issue?

Sorry, I'm on free licence for now as we testing the application and can't submit any ticket on boxbilling
Anyway I can provide a test link here: http://www.hostomic.com/shared-hosting/

should add on the Order Button to do categoies

@chiareu send us your information via contact form so that we could check what is causing the issue.
@juggalox2008 please elaborate.


revert #6595 #6820

Which issue does this PR close?

Closes #6819 #6790 .
Rationale for this change

What changes are included in this PR?

Are these changes tested?

Are there any user-facing changes?

❯ SELECT "A", COUNT(DISTINCT("B"))
FROM "MyTable"
WHERE time >= now() - interval '1 month'

GROUP BY "A"

❯ SELECT "A", COUNT(DISTINCT("B"))
FROM "MyTable"
WHERE time >= now() - interval '1 month'
GROUP BY "A"
LIMIT 10;

+-----------+---------------------------+
| MyTable.A | COUNT(DISTINCT MyTable.B) |
+-----------+---------------------------+
+-----------+---------------------------+
0 rows in set. Query took 0.020 seconds.

BTW here are some tests (that I verified that this PR fixes the errors): https://github.com/apache/arrow-datafusion/pull/6836

Thanks @alamb


Handling a a logical inconsistency  RRULE

Hi,
First, I would like to thank you for nice new API for creating recurrenceSet,  it is very intuitive and flexible. Though there are breaking change from 0.15.0 to 0.17.1, the improvements in the library are worthy of the upgrade.
This issue existed since 0.15.0.  Given an illogical rrule caused by BYPOS=2
"FREQ=WEEKLY;INTERVAL=2;BYDAY=SA;BYHOUR=19;BYMINUTE=0;BYSECOND=0;BYSETPOS=2"
The RecurrenceSet#hasNext or RecurrenceSet#next will throw the following exception  below. In this situation, should the InstanceIterator a false or null instead?
java.lang.IllegalStateException: too many empty recurrence sets
at org.dmfs.rfc5545.recur.BySetPosFilter.nextSet(BySetPosFilter.java:88)
at org.dmfs.rfc5545.recur.BySetPosFilter.next(BySetPosFilter.java:69)
at org.dmfs.rfc5545.recur.RecurrenceRuleIterator.fetchNextInstance(RecurrenceRuleIterator.java:95)
at org.dmfs.rfc5545.recur.RecurrenceRuleIterator.<init>(RecurrenceRuleIterator.java:89)
at org.dmfs.rfc5545.recur.RecurrenceRule.iterator(RecurrenceRule.java:2218)
at org.dmfs.rfc5545.recurrenceset.OfRule.iterator(OfRule.java:42)
at org.dmfs.jems2.iterator.Mapped.next(Mapped.java:64)

I'm glad to hear that you enjoy the new API.
I've spent quite some time thinking about this issue. Unfortunately it's not trivial to separate rules that never emit an occurrence from those that do so every couple of thousand occurrences (see #48 for an example of that).
In case of BYSETPOS we'd have to decide whether the rule ever has that many instance in an interval. That alone can be a challenging task. Just think of something like
FREQ=WEEKLY;BYMONTH=2;BYMONTHDAY=15,29;BYDAY=SA;BYSETPOS=2

This rule doesn't make much sense and certainly can be simplified. However, the rule is valid. Yet only every 28 years / ~1450 weeks there is a February in which the 29th falls on a Saturday. You can easily modify it to never emit anything.
I see three possible solutions right now:

keep the code as it is and live with those edge cases not being treated properly
throw a custom (Runtime-) Exception instead of a generic one, so the caller can at least (reliably) distinguish that case from another IlleagalStateException  that might occur
Implement some code to recognize (at least some of) those edge cases and stop iterating without an error when no results are to be expected.

I wonder if the implementation effort and the runtime overhead are worth implementing number 3.

I've added #138 to cover option 2.

Hi Marten,
Thanks for sharing the challenges and your thoughts about the issue.
The first thing I thought when I had the problem was, wouldn't it be nice if there is a RecurrenceRule#isValid. And there is such a method but it is in private. It however checks for the well-formed-ness  of the RRule which did not handle the logic error in my case. If there is such method to check both well-formed and logical error than the onus is on the user of the library.
I do agree with you that there are always so many things to do and we must put our energy and time on what provide the best return.
If I may suggest a simpler solution to my problem. If there is a logical error in the RRule then RecurenceSet#iterator#hasNext will return false as there is nothing to return correspondingly for RecurrenceSe#iterator#next will return null. Perhaps there is an addition state to hold the error if any for diagnostic purposes.
With this, even with an illogical RRule, the user will not get any errors but instead get a null for next and a false for hasNext especially in runtime, maybe frowned upon by some of the library users though,

Hmm, the suggested behavior would violate the Iterator Contract I'd rather not do that.

Hi Marten,
I agreed adhering to the specs is important. From the JavaDoc, it seems to
imply that hasNext should not throw an exception. In my case, the hasNext
method does throw the same exception as the method next(). Would you
consider that hasNext should return a false instead of throwing an
exception for the condition I raised previously?
On Wed, May 22, 2024 at 12:22 AM Marten Gajda @.***>
wrote:

Hmm, the suggested behavior would violate the Iterator Contract
https://docs.oracle.com/javase/8/docs/api/java/util/Iterator.html#next--.
I'd rather not do that.
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memory/Ops in stm32f7

Hello @navsuda
I have implemented the KWS, how to get the memory/Ops in stm32f7.

@prashant7691,
Memory requirement comes from the model size and the Max ops can be derived by benchmarking the performance of matmul kernel on your board.

@prashant7691
In the quantization process, how to get the value of the quantization ranges -- act_max in quant_test.py .
how to set  the specific value of the parameter act_max ( x 0 0 0 0 0 0 0 0 0 0 0 ) ?


Datagrid: Reload datagrid on add data

The datagrid component needs to call reload on data being added to it to ensure that the columns are updated if new ones are to be included. Reload currently calls "open" to reload the data, but this might need to be broken up in the future if processing time seems to take too long. Otherwise, a simple call to reload should suffice.

No pull request.
Looks like it is already fixed.


cassandra_4: 4.0.7 -> 4.1.0

Automatic update generated by nixpkgs-update tools. This update was made based on information from passthru.updateScript.
meta.description for cassandra is: "A massively scalable open source NoSQL database"
meta.homepage for cassandra is: "https://cassandra.apache.org/"
meta.changelog for cassandra is: ""
Updates performed

Ran passthru.UpdateScript

To inspect upstream changes
Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
found 3.11.14 with grep in /nix/store/yxj80p90vj888xcjyq6q7m0iwl56l0sm-cassandra-3.11.14
found 3.11.14 in filename of file in /nix/store/yxj80p90vj888xcjyq6q7m0iwl56l0sm-cassandra-3.11.14

Rebuild report (if merged into master) (click to expand)

2 total rebuild path(s)

2 package rebuild(s)

First fifty rebuilds by attrpath
cassandra
cassandra_3_11

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/yxj80p90vj888xcjyq6q7m0iwl56l0sm-cassandra-3.11.14 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A cassandra https://github.com/r-ryantm/nixpkgs/archive/5d34388cd15956d0b3c7757b48e61e7ebe5dbd24.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/yxj80p90vj888xcjyq6q7m0iwl56l0sm-cassandra-3.11.14
ls -la /nix/store/yxj80p90vj888xcjyq6q7m0iwl56l0sm-cassandra-3.11.14/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review run on x86_64-linux 1

1 package built:

cassandra

Maintainer pings
cc @roberth for testing.

Automatic update generated by nixpkgs-update tools. This update was made based on information from passthru.updateScript.
meta.description for cassandra_4 is: "A massively scalable open source NoSQL database"
meta.homepage for cassandra_4 is: "https://cassandra.apache.org/"
meta.changelog for cassandra_4 is: ""
Updates performed

Ran passthru.UpdateScript

To inspect upstream changes
Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
found 4.1.0 with grep in /nix/store/pf0qq94sm95jaz0w8l3gcv4s6g4wgkl4-cassandra-4.1.0
found 4.1.0 in filename of file in /nix/store/pf0qq94sm95jaz0w8l3gcv4s6g4wgkl4-cassandra-4.1.0

Rebuild report (if merged into master) (click to expand)

1 total rebuild path(s)

1 package rebuild(s)

First fifty rebuilds by attrpath
cassandra_4

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/pf0qq94sm95jaz0w8l3gcv4s6g4wgkl4-cassandra-4.1.0 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A cassandra_4 https://github.com/r-ryantm/nixpkgs/archive/038878daac70be4b7996c3b3ce81a40106329989.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/pf0qq94sm95jaz0w8l3gcv4s6g4wgkl4-cassandra-4.1.0
ls -la /nix/store/pf0qq94sm95jaz0w8l3gcv4s6g4wgkl4-cassandra-4.1.0/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review run on x86_64-linux 1

1 package built:

cassandra_4

Maintainer pings
cc @roberth for testing.


inconsistent behavior when combining default and constructor

dry-struct behaves inconsistently when there is an attribute with both default and constructor. Using constructor_type :schema, if you don't specify value for the attribute, the default is used and is run through the constructor, but if you specify nil as the attribute value, the default is still used, but is NOT run through the constructor. I think it may be open to discussion whether the defaults should be run through the constructor (for me it makes sense to do it), but I don't think it's right to run them through in one case and not in the other.
I've created a spec for this behavior here.

I agree this maybe a bit surprising, but it's up to the user to provide a valid value in the default block. However, it will stay like this and should be documented.
@solnic what do you think if we add a second argument to the default block? E.g.
RoundTime = Types::Time.constructor(&:round)
RoundTime.default { |value, type| type[Time.now] }

@flash-gordon not a bad idea

hell, why did I call that "second"?
Anyway, support for RoundTime.default { |type| type[Time.now] } was added to dry-types (currently in master), we need to update the docs


Android native plugin doesn't support AGP 8.0

The native Android plugin of this package doesn't support Android gradle Plugin 8.0, in 8.0 the package name of a library or application should be defined in build.gradle in the app module in the android block as a namespace instead of specifying it in the package attribute in AndroidManifest.xml, however, that might break compatibility with gradle versions older than 7.0, but gradle 8.0 will be required sooner or later, I think all the packages that have native plugin should update android gradle plugin to 8.0 so people start to migrate their build system to 8.0 to significantly improve the build system of android and how the app is packaged, All applications and libraries that use plugin have gradle version less than 8.0 can't migrate unless they update it manually but that is not a good solution since after any upgrade or clean the changes will reverted back
Also see https://github.com/mogol/flutter_secure_storage/issues/557
Fore more information

@juliansteenbakker The issue has been fixed, why not release a new version to pub ?

@juliansteenbakker All my plugins are compatible with AGP 8.0 except yours, is there a reason to not release this fix?


"Publish to GitHub" with no repo does nothing, no error, no message

Type: Bug
When I run "Publish to GitHub" (command github.publish) from the command palette, nothing happens.
I haven't initialized a git repo yet: if that is the issue, it should at least tell me instead of just doing nothing.

Well no, that's the point of this issue: suppose I'm a newbie dev or I forgot to initialize the git repo, or maybe I thought "Publish to GitHub would create a gist or a repo automatically... I would expect VS Code to remind me that to run this command I first need to initialize my git repo instead of just silently failing when I run the Publish to GitHub command.

Indeed I tried again (with 1.96.0) after first opening a folder in VS Code and Publish to GitHub created a repo for me and published it just fine.
So it seems Publish to GitHub only fails silently when I just have loose files with no folder open, which is probably expected, but maybe just add a message in that case to tell the user that they first need to at least open a folder before Publish to GitHub can publish it as a new git repository?

Thanks for the clarifications. I pushed a change so that we do not show the command in an empty workspace.


Calling to_h on Dry::Types::Map does not work with map values

Description
Calling to_h on a Dry::Types::Map wont call to_h on the values of the Map.
Example:
module Types
  include Dry::Types.module

  class LinkObject < Dry::Struct
    transform_types { |type| type.meta(omittable: true) }

    attribute :href, Types::String
    attribute :meta, Types::Hash
  end

  Link = String | Constructor(LinkObject)
  Links = Map(key_type: Symbol, value_type: Link)
end

Types::Links.call({ self: "", reltive: { href: "", meta: { count: 1 } } }).to_h
=> {:self=>"", :reltive=>#<Types::LinkObject href="" meta={:count=>1}>}

Notes
Using master branch for dry-types and dry-struct

Hi @pablocrivella,
Thanks for opening the issue ❤
Actually the return value from calling Types::Links.call is actually returning a ruby Hash so calling to_h on that result is actually calling in ruby Hash
I think the output from the example is right if you want to have a hash like representation of reltive you would need to call to_h on it.
links = links = Types::Links.call({ self: "", reltive: { href: "", meta: { count: 1 } } })
=> {:self=>"", :reltive=>#<Types::LinkObject href="" meta={:count=>1}>}
links[:reltive]
=> #<Types::LinkObject href="" meta={:count=>1}>
links[:reltive].href
=> ""
links[:reltive].meta
=> {:count=>1}
links[:reltive].to_h
=> {:href=>"", :meta=>{:count=>1}}

Thanks for the detailed explanation @GustavoCaso :)
I think was expecting something different because of this scenario:
class Foo < Dry::Struct
  attribute :link, Types::Constructor(Types::LinkObject)
end

foo = Foo.new(link: { href: "", meta: { count: 1 } })
foo.link
=> #<JSONAPI::Types::LinkObject href="" meta={:count=>1}>
foo.to_h
=> {:link=>{:href=>"", :meta=>{:count=>1}}}

Yeah is a different method in that context to_h is actually from Dry::Struct library https://github.com/dry-rb/dry-struct/blob/master/lib/dry/struct.rb#L150
Did it help? @pablocrivella


Feature Request to add environment variables

It would be better, If you provide options for adding environment variables while executing playbook.

You sand define environment in the playbook itself and use variables which you can pass to the playbook as usual.

I understand that we can add environment variables in playbook.
When using anible with AWS, AWS credentials has to be exported as env before you start processing the playbook. (To access the dynamic inventory)


Could it be possible to not show the code on the Inspector after page.PauseAsync()?

I felt uncomfortable when I ran this code.
        private static async Task LaunchCodegen(string url)
        {
            using var playwright = await Playwright.CreateAsync();
            var bto = new BrowserTypeLaunchOptions
            {
                Headless = false,
                //Proxy = new Proxy
                //{
                //    Server = "http://myproxy:8080",
                //    Username = "myname",
                //    Password = "mypass",
                //    Bypass = ".ignore.com"
                //},
                Channel = "msedge" // "msedge", "chrome"
            };
            await using var browser = await playwright.Chromium.LaunchAsync(bto);
            //var context = await browser.NewContextAsync();
            var context = await browser.NewContextAsync(new BrowserNewContextOptions
            {
                Locale = "ja-JP",
            });

            // Open new page
            var page = await context.NewPageAsync();
            await page.GotoAsync(url);
            await page.PauseAsync();
        }

Because whole my code is shown on the Inspector including sensitive part, even if I build it as exe.

Perhaps I just don't know how to avoid this.
Any suggestions will be appreciated.

The computer where you run the code, has also access to the source-code. So it would be not a great security protection to just hide it since the user could access it anyway. Also keep in mind that you should never store secrets inside source code, usually you get them e.g. from environment variables or read them from some other external secret store.
There is currently no way to hide it.

There is currently no way to hide it.

Aside from storing secrets inside source code (I know how stupid it is), I think that showing the code on the Inspector window at the beginning is meaning less because it will be cleared after an operation on the browser while Record mode anyway.
It would be nice to have an option that begins with Record mode with empty lines.
Thank you.


Lineage cross links displayed incorrectly

Describe the bug
Some of cross links displayed behind lineage cards.
Set up
(How do you run the app?
Which version of the app are you running? Provide either docker image version or check commit hash at the top left corner. We won't be able to help you without this information.)
Steps to Reproduce
You. can see this bug in e.g. "CUSTOMER_CHURN_MONTH" entity lineage.
Expected behavior
Display cross links between cards.
Screenshots

Resolved in #694


missing battery % on EV

i get a lot of sensors, including fuelDistanceRemaining and fuelRemaining but fuelRemaining is at 0% and fuelDistanceRemaining at 99km so i think that there must be a batteryRemaining value in the api but i'm not sure how to get it.
also, how to setup how often to update everything?
Thanks :)

Thanks for taking the time to test this!
Could you send the log generated by docker? Everytime the info is updated, the data is printed in the log
I will add any missing fields :)

can't see that value.. the requst on the API is reporting everything?
{'lastUpdatedTimestamp': '20241008080738', 'latitude': 45, 'longitude': 12, 'positionTimestamp': '20241008080536', 'fuelRemainingPercent': 0.0, 'fuelDistanceRemainingKm': 81.0, 'odometerKm': 41326.2, 'doors': {'driverDoorOpen': False, 'passengerDoorOpen': False, 'rearLeftDoorOpen': False, 'rearRightDoorOpen': False, 'trunkOpen': False, 'hoodOpen': False, 'fuelLidOpen': False}, 'doorLocks': {'driverDoorUnlocked': False, 'passengerDoorUnlocked': False, 'rearLeftDoorUnlocked': False, 'rearRightDoorUnlocked': False}, 'windows': {'driverWindowOpen': False, 'passengerWindowOpen': False, 'rearLeftWindowOpen': False, 'rearRightWindowOpen': False}, 'hazardLightsOn': False, 'tirePressure': {'frontLeftTirePressurePsi': 33.0, 'frontRightTirePressurePsi': 36.0, 'rearLeftTirePressurePsi': 35.0, 'rearRightTirePressurePsi': 33.0}}

Thank you for this!
I looked into the official home assistant integration code, I will have to add the API call for the electric car. I assumed it would all be at the same place.


Creation of UserVoice content provider

Hi guys,
Creation of a simple content provider for your consideration. This one is for uservoice articles.

Not to standard.


def initialize causes nil error with Mongoid::Document (simple class)

I saw a strange bug today and created a simple class to test it:
class Alpha

  def initialize
     puts 'initialize Alpha'
  end
end

This class inits fine (Alpha.new). But if I add "include Mongoid::Document" I get this error:
>> Alpha.new
initialize Alpha
NoMethodError: You have a nil object when you didn't expect it!
You might have expected an instance of Array.
The error occurred while evaluating nil.[]
	from /home/user/.rvm/gems/ruby-1.9.2-p290/gems/mongoid-2.4.3/lib/mongoid/inspection.rb:32:in `block in inspect_fields'

Mongoid 2.4.3. The full failing source is:
class Alpha
  include Mongoid::Document

  def initialize
     puts 'initialize Alpha'
  end
end

Rails::VERSION::STRING
=> "3.1.1"
RUBY_VERSION
=> "1.9.2"

I thought adding a simple field (field :name, type: String) might fix it but didn't change anything.

If you're going to override #initialize , you need to accept the correct arguments, and call #super . Eg:
  def initialize(attrs = nil, options = nil)
    super
    # your code here
  end

You can find the #initialize from Mongoid::Document here .

This might be good to put into the Mongoid documentation - I had a really hard time sorting this bug out; it doesn't come up quickly on a search. Also the initialize(attrs = nil, options = nil) declaration above, while perhaps technically correct, isn't necessarily encouraged most ruby documentation either. As an example, see https://www.ruby-lang.org/


AJV is no longer a direct dependency

Closes #139
Now that we moved the resolver, validator, etc to oas-kit, we don't actually use ajv directly!

Coverage remained the same at 87.187% when pulling ac2d296998994544b87c727e91b5ba5c40f0332d on remove-ajv into b32b5fad203ec712f3a5360578b4afe92c5b30a3 on master.

Coverage remained the same at 87.187% when pulling ac2d296998994544b87c727e91b5ba5c40f0332d on remove-ajv into b32b5fad203ec712f3a5360578b4afe92c5b30a3 on master.

Coverage remained the same at 87.187% when pulling ac2d296998994544b87c727e91b5ba5c40f0332d on remove-ajv into b32b5fad203ec712f3a5360578b4afe92c5b30a3 on master.

Coverage remained the same at 87.187% when pulling ac2d296998994544b87c727e91b5ba5c40f0332d on remove-ajv into b32b5fad203ec712f3a5360578b4afe92c5b30a3 on master.


Close #38: Add TypedStruct

Simple definition syntax - without repeating field names.
Short syntax for simple fields - workds with IDE completion.
Full ts.Field(...) syntax to define default value, validators etc.
meta field that can be used to provide metadata for reflection.
Support for typechecked list, dict and Bunch fields.

Future plans(will need more design):

Hooks/signals for doing things when users change the fields.
Bubble up? Parent TypedStruct's hook get activated when
fields of nested TypedStructs are changed?

@koreno: I've merged validate and convert into preprocess, but also added helper methods to Field for setting them individually.
Old style:
class Foo(ts.TypedStruct):
    a = ts.Field(int,
                 # Only even numbers between 10 and 30
                 validate=[lambda n: n % 2 == 0, range(10, 31).__contains__],
                 # Accept strings and floats by converting them to int
                 convert={str: int, float: int})

New style - manually implemented function:
def preprocess(obj):
    if isinstance(obj, str) or isinstance(obj, float):
        obj = int(obj)

    assert obj % 2 == 0, 'not an even number'
    assert obj in range(10, 31), 'out of range([10, 30])'

    return obj

class Foo(ts.TypedStruct):
    a = ts.Field(int, preprocess=preprocess)

New style - helper functions:
class Foo(ts.TypedStruct):
    a = ts.Field(int)

    a.add_validation(lambda n: n % 2 == 0, Exception, 'not an even number')
    a.add_validation(range(10, 31).__contains__, Exception, 'out of range([10, 30])')

    a.add_conversion(str, int)
    a.add_conversion(float, int)

The helper functions style is preferred, because with our manual implementation the first validation(number is even) will fail with a generic TypeError if if gets a non-numeric value, instead of failing on the more specific InvalidFieldType. We can't check the type before, because then preprocess won't be able to do conversions.


Enimity Plugin isn't show correct info

I am having an issue where after the early access I am not getting acurate info from the Enimity plugin. It is either not showing correct hp(pc allies only) or anything at all. It also isn't color coding the roles like it used to.
Is this an issue with your plugin or the ravahn/FFXIV_ACT_Plugin?
Screenshots attached:

did some playing around and it looks like to me that the ffxiv act plugin does indeed report the correct info by looking at the overlay from the plugin it self.

If you want to file enmity plugin issues, can you do them on the enmity plugin repository?
The HP is not correct in the latest version of this enmity plugin, as I tried to make clear in the release notes: https://github.com/quisquous/ACT_EnmityPlugin/releases/tag/v<IP_ADDRESS>

Sorry thanks for the info. Didn't know there was another repository for it.

Just an FYI found an working one https://github.com/qitana/ACT_EnmityPlugin