Produce empty images using adventure.yaml

Hi @chungyiweng, thanks for the great work! I encountered an issue "Produce empty images; reload the init model" (similar to #43) when using adventure.yaml for training. This issue consistently happens on zju-mocap and custom datasets  and only happens with adventure.yaml. The config with single_gpu.yaml had no problem.
I did several tests myself and found the possible reason could be the patch size:
adventure.yaml uses the default patch size 32x32. If the patch size is set to 24x24 or 20x20 in adventure (like in single_gpu), the issue does not occur. BTW there is no fatal error (e.g., out of memory) when running the code using 32x32 on my machine. It just produces empty images.
If the cause is truly the patch size, can you help me understand why the patch size is so critical during training such that it could lead to empty images if not set properly. Thank you!

I encountered the same question, not on zju-mocap, but just only on my custom dataset.

I encountered the same question, not on zju-mocap, but just only on my custom dataset.

I also encountered the 'Produce empty images' issue when working with custom videos, but I was able to train using zju-mocap. Do you have any solutions to this problem?

This is because the intialization of the cananical output is too small for rbg and there are five network need to be added in optimization. In this case, the lr and loss weight need to be tuning to make the network converge in the first 5000 iteration.

Also the bgcolor is randomly generated and some time the bgcolor may be too large i guess?

So i am using the vscode and debug mode.
I will set up a breakpoint in the raws2outputs return and check the rgb map and acc map
if the value is too small here, you can manually tuning the lr and loss weight to see whether you can have an acceptable value.
This is really hard to say the exact reason, maybe the bounding box is not correct?
Or the ray mask masked out too many rays and there are not enough ray come into model.

So i am using the vscode and debug mode. I will set up a breakpoint in the raws2outputs return and check the rgb map and acc map if the value is too small here, you can manually tuning the lr and loss weight to see whether you can have an acceptable value. This is really hard to say the exact reason, maybe the bounding box is not correct? Or the ray mask masked out too many rays and there are not enough ray come into model.

According to your suggestion ，I check the value of the rgb map in the function raws2output during process images, and for zju-mocap, it always reaches a value bigger than 10^-5.
However, for custom data, the maximum value of rgb map is around 10^-11 no matter how I modify lr and loss weight.
And I also had the same problem of generating empty images when I tried to use the video from the author's project home page for training.

所以我正在使用 vscode 和调试模式。我将在 raws2output 返回中设置一个断点，并检查 rgb map 和 acc map 如果这里的值太小，您可以手动调整 lr 和 loss weight，看看是否可以有一个可接受的值。这真的很难说确切的原因，也许边界框不正确？或者光线遮罩遮盖了太多光线，并且没有足够的光线进入模型。

根据您的建议，我在处理图像时检查函数raws2output中rgb映射的值，对于zju-mocap，它总是达到大于10^-5的值。
但是，对于自定义数据，无论我如何修改lr和减肥，rgb map的最大值都在10^-11左右。
当我尝试使用作者项目主页上的视频进行培训时，我也遇到了生成空图像的相同问题。

这可能是由不正确的pts_mask引起的，这是论文中显示的前景概率，您可以仔细检查，因为三线性插值可能无法在自定义数据集中正确工作
I think there's something wrong with metadata.json. I used zju_mocap387 to experiment. The experiment worked successfully when I replaced the cameras.pkl and mesh_infos.pkl generated by my own metadata.json with the correct cameras.pkl and mesh_infos.pkl.

所以我正在使用 vscode 和调试模式。我将在 raws2output 返回中设置一个断点，并检查 rgb map 和 acc map 如果这里的值太小，您可以手动调整 lr 和 loss weight，看看是否可以有一个可接受的值。这真的很难说确切的原因，也许边界框不正确？或者光线遮罩遮盖了太多光线，并且没有足够的光线进入模型。

根据您的建议，我在处理图像时检查函数raws2output中rgb映射的值，对于zju-mocap，它总是达到大于10^-5的值。
但是，对于自定义数据，无论我如何修改lr和减肥，rgb map的最大值都在10^-11左右。
当我尝试使用作者项目主页上的视频进行培训时，我也遇到了生成空图像的相同问题。

这可能是由不正确的pts_mask引起的，这是论文中显示的前景概率，您可以仔细检查，因为三线性插值可能无法在自定义数据集中正确工作
I think there's something wrong with metadata.json. I used zju_mocap387 to experiment. The experiment worked successfully when I replaced the cameras.pkl and mesh_infos.pkl generated by my own metadata.json with the correct cameras.pkl and mesh_infos.pkl.

I think this is possible, if the camera poses and the skeleton info mismatch, then the empty result is reasonable

I used the rembg library to split images to form masks, and they look OK.
I just looked at the paper and noticed that the author said, "We additionally resize video frames to keep the height of subject at approximately 500 pixels."
So there seems to be some size requirements for images with custom data.

Hello,
Did you train on custom dataset?
I am getting data loader issue  similar to https://github.com/chungyiweng/humannerf/issues/4#issue-1275272277
Not quiet sure what could be the case for the loader issue for custom data. If you can help it will be wonderful or give any notion. Great

@louhz @reaper19991110
I also got an error in the rendering when using metadata.json
https://github.com/chungyiweng/humannerf/issues/73#issue-1750928287
Do you potentially know the issue here. If you can go through it once.
Thanks in advance.

使用元数据时，我在渲染中也遇到了错误.json #73（评论）
您可能知道这里的问题吗？如果你能经历一次。
提前谢谢。

hi, I also don't know the reason for the problem, but thank you very much for your questions in ROMP to help me use ROMP to complete metadata.json. Logically, ROMP should calculate the correct SMPL parameters. But I still render an empty image.

使用元数据时，我在渲染中也遇到了错误.json #73（评论）
您可能知道这里的问题吗？如果你能经历一次。
提前谢谢。

hi, I also don't know the reason for the problem, but thank you very much for your questions in ROMP to help me use ROMP to complete metadata.json. Logically, ROMP should calculate the correct SMPL parameters. But I still render an empty image.

I used the processed file for H36m that they gave under dataset.md,
However, since no camera params were given, I am unable to solve it.
Actually, I also got empty images at first, but when I used np.eye(4) as extrinsic and intrinsic as fx,fy = 443.4 ( given as per FOV = 60 on ROMP )
I did not got any empty images, but the rendering was horrible.

使用元数据时，我在渲染中也遇到了错误.json #73（评论）
您可能知道这里的问题吗？如果你能经历一次。
提前谢谢。

hi, I also don't know the reason for the problem, but thank you very much for your questions in ROMP to help me use ROMP to complete metadata.json. Logically, ROMP should calculate the correct SMPL parameters. But I still render an empty image.

I used the processed file for H36m that they gave under dataset.md, However, since no camera params were given, I am unable to solve it.
Actually, I also got empty images at first, but when I used np.eye(4) as extrinsic and intrinsic as fx,fy = 443.4 ( given as per FOV = 60 on ROMP )
I did not got any empty images, but the rendering was horrible.

So i think i find the reason for this, did you count how many validate rays in your custom dataset?
In zju-mocap, the valid rays number is 15000 approximately, so the batch size is 32000 to make sure that all valid rays will be counted and also the pose -refiner will work as usual to optimze the entire human pose
However, if you set the chunk size to much more smaller value like 6144, then the result is empty, and you need to set up your resize_img_scale to 0.125 to have a valid output.
In your case, it looks like the picture is 1080p? i guess and you can increase the chunk size or resize the image?

使用元数据时，我在渲染中也遇到了错误.json #73（评论）
您可能知道这里的问题吗？如果你能经历一次。
提前谢谢。

hi, I also don't know the reason for the problem, but thank you very much for your questions in ROMP to help me use ROMP to complete metadata.json. Logically, ROMP should calculate the correct SMPL parameters. But I still render an empty image.

I used the processed file for H36m that they gave under dataset.md, However, since no camera params were given, I am unable to solve it.
Actually, I also got empty images at first, but when I used np.eye(4) as extrinsic and intrinsic as fx,fy = 443.4 ( given as per FOV = 60 on ROMP )
I did not got any empty images, but the rendering was horrible.

So i think i find the reason for this, did you count how many validate rays in your custom dataset? In zju-mocap, the valid rays number is 15000 approximately, so the batch size is 32000 to make sure that all valid rays will be counted and also the pose -refiner will work as usual to optimze the entire human pose However, if you set the chunk size to much more smaller value like 6144, then the result is empty, and you need to set up your resize_img_scale to 0.125 to have a valid output.
In your case, it looks like the picture is 1080p? i guess and you can increase the chunk size or resize the image?

Thank you for the message. I resolved the issue. It was becoz of the camera values  or the smpl values.
It generates empty images becoz the projections return 0

使用元数据时，我在渲染中也遇到了错误.json #73（评论）
您可能知道这里的问题吗？如果你能经历一次。
提前谢谢。

hi, I also don't know the reason for the problem, but thank you very much for your questions in ROMP to help me use ROMP to complete metadata.json. Logically, ROMP should calculate the correct SMPL parameters. But I still render an empty image.

I used the processed file for H36m that they gave under dataset.md, However, since no camera params were given, I am unable to solve it.
Actually, I also got empty images at first, but when I used np.eye(4) as extrinsic and intrinsic as fx,fy = 443.4 ( given as per FOV = 60 on ROMP )
I did not got any empty images, but the rendering was horrible.

So i think i find the reason for this, did you count how many validate rays in your custom dataset? In zju-mocap, the valid rays number is 15000 approximately, so the batch size is 32000 to make sure that all valid rays will be counted and also the pose -refiner will work as usual to optimze the entire human pose However, if you set the chunk size to much more smaller value like 6144, then the result is empty, and you need to set up your resize_img_scale to 0.125 to have a valid output.
In your case, it looks like the picture is 1080p? i guess and you can increase the chunk size or resize the image?

Thank you for the message. I resolved the issue. It was becoz of the camera values or the smpl values.
It generates empty images becoz the projections return 0

How do you get the true camera values and smpl values? I use ROMP to get the smpl and use the camera like

I can render image, but the results are terrible.

使用元数据时，我在渲染中也遇到了错误.json #73（评论）
您可能知道这里的问题吗？如果你能经历一次。
提前谢谢。

hi, I also don't know the reason for the problem, but thank you very much for your questions in ROMP to help me use ROMP to complete metadata.json. Logically, ROMP should calculate the correct SMPL parameters. But I still render an empty image.

I used the processed file for H36m that they gave under dataset.md, However, since no camera params were given, I am unable to solve it.
Actually, I also got empty images at first, but when I used np.eye(4) as extrinsic and intrinsic as fx,fy = 443.4 ( given as per FOV = 60 on ROMP )
I did not got any empty images, but the rendering was horrible.

So i think i find the reason for this, did you count how many validate rays in your custom dataset? In zju-mocap, the valid rays number is 15000 approximately, so the batch size is 32000 to make sure that all valid rays will be counted and also the pose -refiner will work as usual to optimze the entire human pose However, if you set the chunk size to much more smaller value like 6144, then the result is empty, and you need to set up your resize_img_scale to 0.125 to have a valid output.
In your case, it looks like the picture is 1080p? i guess and you can increase the chunk size or resize the image?

Thank you for the message. I resolved the issue. It was becoz of the camera values or the smpl values.
It generates empty images becoz the projections return 0

How do you get the true camera values and smpl values? I use ROMP to get the smpl and use the camera like

I can render image, but the results are terrible.

If you used ROMP, how is that your intrinsic? They use a different value which is given in the config file.
Check that

Thank you!
I just run "romp --mode=video --calc_smpl --render_mesh -i=/home/shengbo/data/kinect -o=/home/shengbo/data/param_kinect" in ROMP, so all configs are default?
# focal length: when FOV=50 deg, 548 = H/2 * 1/(tan(FOV/2)) = 512/2. * 1./np.tan(np.radians(25))
# focal length: when FOV=60 deg, 443.4 = H/2 * 1/(tan(FOV/2)) = 512/2. * 1./np.tan(np.radians(30))
# focal length: when FOV=72 deg, 352 = H/2 * 1/(tan(FOV/2)) = 512/2. * 1./np.tan(np.radians(36))

my images is (1920,1080), the default FOV=60 deg, so my focal_length= H/2 * 1/(tan(FOV/2)) = 1920/2. * 1./np.tan(np.radians(30))，is that right?
thank you !

Thank you! I just run "romp --mode=video --calc_smpl --render_mesh -i=/home/shengbo/data/kinect -o=/home/shengbo/data/param_kinect" in ROMP, so all configs are default?
# focal length: when FOV=50 deg, 548 = H/2 * 1/(tan(FOV/2)) = 512/2. * 1./np.tan(np.radians(25))
# focal length: when FOV=60 deg, 443.4 = H/2 * 1/(tan(FOV/2)) = 512/2. * 1./np.tan(np.radians(30))
# focal length: when FOV=72 deg, 352 = H/2 * 1/(tan(FOV/2)) = 512/2. * 1./np.tan(np.radians(36))

my images is (1920,1080), the default FOV=60 deg, so my focal_length= H/2 * 1/(tan(FOV/2)) = 1920/2. * 1./np.tan(np.radians(30))，is that right?
thank you !

You can use your focal length with that calculation and see if it renders. When I asked the person from Romp, he told me to use 443.4 as the fx and fy ( focal length ) since they use FOV = 60

Thank you! I just run "romp --mode=video --calc_smpl --render_mesh -i=/home/shengbo/data/kinect -o=/home/shengbo/data/param_kinect" in ROMP, so all configs are default?
# focal length: when FOV=50 deg, 548 = H/2 * 1/(tan(FOV/2)) = 512/2. * 1./np.tan(np.radians(25))
# focal length: when FOV=60 deg, 443.4 = H/2 * 1/(tan(FOV/2)) = 512/2. * 1./np.tan(np.radians(30))
# focal length: when FOV=72 deg, 352 = H/2 * 1/(tan(FOV/2)) = 512/2. * 1./np.tan(np.radians(36))

my images is (1920,1080), the default FOV=60 deg, so my focal_length= H/2 * 1/(tan(FOV/2)) = 1920/2. * 1./np.tan(np.radians(30))，is that right?
thank you !

You can use your focal length with that calculation and see if it renders. When I asked the person from Romp, he told me to use 443.4 as the fx and fy ( focal length ) since they use FOV = 60

Hello, I could render the images. However, I find that the free view rendering and T-pose rendering results are incorrect.
Free view:

T-pose:

使用元数据时，我在渲染中也遇到了错误.json #73（评论）
您可能知道这里的问题吗？如果你能经历一次。
提前谢谢。

hi, I also don't know the reason for the problem, but thank you very much for your questions in ROMP to help me use ROMP to complete metadata.json. Logically, ROMP should calculate the correct SMPL parameters. But I still render an empty image.

I used the processed file for H36m that they gave under dataset.md, However, since no camera params were given, I am unable to solve it.
Actually, I also got empty images at first, but when I used np.eye(4) as extrinsic and intrinsic as fx,fy = 443.4 ( given as per FOV = 60 on ROMP )
I did not got any empty images, but the rendering was horrible.

So i think i find the reason for this, did you count how many validate rays in your custom dataset? In zju-mocap, the valid rays number is 15000 approximately, so the batch size is 32000 to make sure that all valid rays will be counted and also the pose -refiner will work as usual to optimze the entire human pose However, if you set the chunk size to much more smaller value like 6144, then the result is empty, and you need to set up your resize_img_scale to 0.125 to have a valid output.
In your case, it looks like the picture is 1080p? i guess and you can increase the chunk size or resize the image?

Hello @louhz,
I am getting empty images for a new dataset which has the following image size
I was wondering if my image is of size 2448 x 2048, should I set the chunk value to lets say
2448 x 20 equals 48960 so approx 50k
20 - patch size that I am using as I am training on single gpu

使用元数据时，我在渲染中也遇到了错误.json #73（评论）
您可能知道这里的问题吗？如果你能经历一次。
提前谢谢。

hi, I also don't know the reason for the problem, but thank you very much for your questions in ROMP to help me use ROMP to complete metadata.json. Logically, ROMP should calculate the correct SMPL parameters. But I still render an empty image.

I used the processed file for H36m that they gave under dataset.md, However, since no camera params were given, I am unable to solve it.
Actually, I also got empty images at first, but when I used np.eye(4) as extrinsic and intrinsic as fx,fy = 443.4 ( given as per FOV = 60 on ROMP )
I did not got any empty images, but the rendering was horrible.

So i think i find the reason for this, did you count how many validate rays in your custom dataset? In zju-mocap, the valid rays number is 15000 approximately, so the batch size is 32000 to make sure that all valid rays will be counted and also the pose -refiner will work as usual to optimze the entire human pose However, if you set the chunk size to much more smaller value like 6144, then the result is empty, and you need to set up your resize_img_scale to 0.125 to have a valid output.
In your case, it looks like the picture is 1080p? i guess and you can increase the chunk size or resize the image?

Hello @louhz, I am getting empty images for a new dataset which has the following image size
I was wondering if my image is of size 2448 x 2048, should I set the chunk value to lets say 2448 x 20 equals 48960 so approx 50k 20 - patch size that I am using as I am training on single gpu
So I resized the images to 1024, 1024 and used the default chunk now of 32000, I am still getting empty results,
What could be the reason here now? Also you mentioned something regarding valid_rays for zju_mocap, how did you find that?

So, the number of validate rays can be find by counting the mask validate pixel number, ie, mask.nonzero()
The biggest reason about this setting is because in humannerf,  we train the mlp (the inverse lbs) as a backward warping function and they assume in the single view video, the surface topology of reconstructed human only have positional difference and each frame share the volumetric consistency, thus we can train the mlp to map each ray on each frame back to smpl canonical model.
In humannerf, the sampling strategy is patch based sampling and all patch in same batch need to come from same image frame (unlike classic nerf, which is random sampling over the entire sequence)
So you need all pixel that contains the human information to be sampled by each batch
Also, my personal suggestion is that you should check humanrf, which is sota work for avator reconstruction, they use occupancy grid to guide the ray sampling and implicitly manage human surface topology.
They achieve great quality for both rigid and non rigid motion!


Configuration required to potentially have datanode task on namenode or journal node

thanks @nigoel! The concern here is that it adds more complexity to our configuration although it will allow us to run on fewer machines. @brndnmtthws, in your experience with production HDFS ops, were there issues with I/O related to running datanodes on the namenode machines?

Hi elingg, For the same, I have kept the default in code to keep the behavior same. In my case, I had an exclusive set of compute machines (by attributes in mesos) on which I wanted to run my particular job. That job had some data sandboxing issues, so required a separate hdfs through resource reservations. Making it a requirement to ave 3+ node, makes a "less resource utilization" solution to me. Reason for choosing the mesos was to have optimal resource utilization. Since ultimately mesos will run everything in linux containers (typical installation of mesos has containerization on), it should not matter whether we actually run them on different physical boxes or same.

@elingg It's probably unwise to run datanodes and namenodes together.
Furthermore, separate services should write to separate volumes to avoid OS disk buffer issues.

@elingg @brndnmtthws Are there some architectural issues with this specific implementation of hdfs on Mesos. Because normal installation of hdfs don't otherwise restrict it.
For example, this public document provides the default documentation where DN and NN are on same node. https://hadoop.apache.org/docs/r2.4.1/hadoop-project-dist/hadoop-hdfs/HdfsUserGuide.html
Mesos is in fact one step more safe from the perspective of resources rather DN and NN on same node on normal cluster, because there will be no memory, disk and CPU contentions between DN and NN tasks. In Mesos, architecturally DS nodes will horizontally scale. If I have high end cluster machines, why should I waste resources and order more machines.

I understand Mesos does have great isolation, but there is still room to go. There will still be high IO usage/ Disk Buffers issues especially since we haven't made use of persistent volumes as of yet. Another issue is with increasing the possibility of failures. I would love more input here though @brndnmtthws, @kensipe, @gabrielhartmann, please let me know your input

@elingg  I was about to come on that. Usage of persistent volume will solve that problem. It is very unfair to assume that world is going to use this implementation of yours in a set-up that mesosphere has designed. For example, we in our project are working on using the persistent volumes and that's the problem we need to fix while running the docker or our cluster provisioning. Not everything meant to be fixed in hdfs-mesos. Since people using it will understand the repercussions, we should not strictly make it unusable for people who had already solved the issue with their own definition of containerizers or their custom executors that ensures higher level of sandboxing.  Having said that, I strongly believe default setting should not allow this. Same is reflected in PR.

I'd prefer to be conservative, and err on the side of reducing risk associated. My 2 cents.

I'm reluctant to merge this change, especially pre persistent volumes, for the reason @brndnmtthws mentioned.

Maybe we could add a comment "Use at your own risk" in order to let people know the associated risks

@elingg  I went to persistent volume docs on mesos. Even that doesn't solve the case. It can just ensure that you get "your persisted id" resource back where you have stored some data. But there is no isolation in terms of disk buffers. This can only be achievable by creating a virtual environment.
Also, I am not sure what strategy normal hdfs installation (without mesos) have to prevent this. I believe it doesn't.

@nigoel, yes you are correct that the first version of persistent volumes does not prevent these issues. I'm pretty sure that this design will evolve to increase isolation since that is what we do with memory and cpu in the Mesos containerizer-why not disk. Normal HDFS installation does not prevent this, as you mentioned, it is up to the operator to install on the appropriate machines.
I am still considering if we should make this option configurable and "use at your own risk" or whether we should avoid this risk and require the user to deploy on more machines. At the moment, I'd still like to err on the side of caution. Community input appreciated...

I have update the warnings and moved the configuration to commented tags

@elingg I recommend we merge this.  It's not a huge code change and we have necessary warnings in place to prevent production users from unknowingly shooting themselves in the foot.

Thanks @nigoel for adding the warning. This is a small code and change and should be fine to merge with that warning. Could you kindly rebase with master and then we can merge? Thanks!

Thanks @elingg. Done.


Chaotic Feat: Wonky sounds!

Describe your chaotic idea
To add to the chaos, we need noise! My idea is to add a sound effect whenever the mouse is clicked or a key is pressed. Noises are pretty much just farm noises (eg. chicken, cow, cat, etc), or wonky noises. There's many noises and its basically just random each time. (btw this is my first time doin this sry if I get anything wrong!! > <)
Add Screenshots or Sketches
I havent got any :/ But I searched up it, sounds can autoplay if the user interacts (eg click), haven't tested it but I chose to believe it haha.
Confirm

[X] I understand that my idea will add to the chaos and I'm okay with it
[X] I agree to follow this project's Code of Conduct
[X] I want to work on this feature
[X] I'm GSSOC'24 Extd registered Contributor
[X] I'm Hacktoberfest registered Contributor

Great idea! I have some tips for you on this

add a separate js folder and add the script.js (dont forget to update the route) and create new js file for sound named sound.js and create function to play sound so we can import it and use it on any page
the random sound shouldnt occur on clicking anywhere on the page, it should occur on clicking buttons only, like on navbar, or other buttons

All the best 🚀
Happy coding!

Completed ✅


Allow links to render correctly in adminMessage and infoMessage

Currently, messages with links show escaped html

If I'm not mistaken, this change will lead to XSS issues when those messages contain html.
Before doing this, you'd need to escape the HTML in there.

Are you sure? These and standard messages run through Mustache, and the message template has {{{message}}} (line 100, same file).
If this is a problem, I'm not seeing the additional parsing for standard messages.

Yeah but in the message template, the messages are sanitized first (https://github.com/candy-chat/candy/blob/dev/src/view/pane/message.js#L100-103)...

Still trying to get used to git, been on SVN a long time.

Will verify this patch soon, time's limited at the moment.


escToCloseWindow is Not work

Describe the bug
in function optimizer.watchWindowShortcuts.
2nd parameter's property escToCloseWindow is Not work.
the code just read window.close property, but not run it.
in code https://github.com/alex8088/electron-toolkit/blob/master/packages/utils/src/optimizer.ts#L68
 if (escToCloseWindow) {
          if (input.code === 'Escape' && input.key !== 'Process') {
            window.close    // <-- HERE!
            event.preventDefault()
          }
        }

Electron-Toolkit Version
latest
Electron Version
any
Validations

[X] Follow the Code of Conduct.
[X] Read the Contributing Guidelines.
[X] Read the docs.
[X] Check that there isn't already an issue that reports the same bug to avoid creating a duplicate.

You found a bug, I will fix it soon. 🤝

@electron-toolkit/utils 2.0.1 is out!


fix(aws-codecommit): make the CodePipeline Action CloudWatch Event re…

…spect creating the branch as well.
Fixes #1310

Pull Request Checklist
Please check all boxes, including N/A items:
Testing

[x] Unit test and/or integration test added
[x] Toolkit change?: integration tests manually executed (paste output to the PR description)
[x] Init template change?: coordinated update of integration tests (currently maintained in a private repo).

Documentation

[x] README: README and/or documentation topic updated
[x] jsdocs: All public APIs documented

Title and description

[x] Change type: Title is prefixed with change type:

fix(module): <title> bug fix (patch)
feat(module): <title> feature/capability (minor)
chore(module): <title>  won't appear in changelog
build(module): <title> won't appear in changelog

[x] Title format: Title uses lower case and doesn't end with a period
[x] Breaking change?: Last paragraph of description is: BREAKING CHANGE: <describe exactly what changed and how to achieve similar behavior + link to documentation/gist/issue if more details are required>
[x] References: Indicate issues fixed via: Fixes #xxx or Closes #xxx

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache-2.0 license.

Missed updating an integration test in the aws-codebuild package.


Label fails to underline keyboard shortcut key until Alt key is pressed

Describe the bug
Windows used to always underline keyboard shortcut keys. Recent version have that behavior off by default, but it can be activated as described below. Most apps honor this setting, but Avalonia Labels do not.
To Reproduce
Configure Windows to always underline keyboard shortcut keys:

Given a window with this xaml:
<Window xmlns="https://github.com/avaloniaui"
        xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml"
        xmlns:d="http://schemas.microsoft.com/expression/blend/2008"
        xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006"
        mc:Ignorable="d" d:DesignWidth="800" d:DesignHeight="450"
        x:Class="MyApp.MainWindow"
        Title="MyApp">
    <StackPanel>
		<Label Content="Select _textbox" Target="{Binding #txtbox}" />
		<TextBox Name="txtbox" />
	</StackPanel>
</Window>

Run the program
Expected behavior
The "t" in "Select textbox" should be underlined immediately.
Screenshots
Without the alt key pressed:

With the alt key pressed:

Desktop (please complete the following information):

OS: Windows 11
Avalonia version: 0.10.18

Yeah I'm afraid we don't yet have an API to surface that setting inside of Avalonia.

At some point we might need to have some alternative of SystemParameters from WPF.
Unfortunately, most of the platforms don't have as many parameters available for apps, like Windows does.

I wonder if some use of Microsoft.Extensions.Configuration might be useful to back the SystemParameters class. On Windows, it could include a data source that is the OS itself. For OSs that don't define as many of these parameters, end users or app developers could still control these settings by way of an appsettings.json or user settings.json file.


cit_magic3 fails with Canopy Python

The "builtins" module isn't part of the Canopy package, although future is installed.  (not sure if this is relevant.... builtins issue)
Because of this, cit_magic3 fails with an import error.  Also, pdb is referenced in the code but never imported.  I fixed these issues locally so that I can run cit_magic3, but I didn't want to muck around with it without understanding why it was set up that way!

muck away!

On Sep 12, 2016, at 10:28 AM, moonshoes87<EMAIL_ADDRESS>wrote:
The "builtins" module isn't part of the Canopy package, although future is installed. (not sure if this is relevant.... builtins issue https://github.com/datamade/dedupe/issues/374)
Because of this, cit_magic3 fails with an import error. Also, pdb is referenced in the code but never imported. I fixed these issues locally so that I can run cit_magic3, but I didn't want to muck around with it without understanding why it was set up that way!
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub https://github.com/PmagPy/PmagPy/issues/68, or mute the thread https://github.com/notifications/unsubscribe-auth/AAKrDSF1LJXb8PMCNZCe-G3v-XhG43Diks5qpYutgaJpZM4J60-3.

Do go ahead and muck away. That the builtins import statement can simply be removed or commented out for the moment (it is some Python3 code and snuck into the main repo).
Some context for why this line of code ended up in there:
We have been exploring how tricky it will be to get all of PmagPy running in Python 3 rather than Python 2.7. It turns out that it isn't very tricky at all. At present, @Caoimhinmg has a fork of PmagPy that runs in Python 3 including the GUIs (using the wxPython library Phoenix: https://wxpython.org/Phoenix/docs/html/index.html). This Python2 to Python3 transition needs to be made at some point before long given that the sun sets on Python 2.7 in 2020. @moonshoes87 it would be great if at some point you are able to play around with the https://github.com/Caoimhinmg/PmagPy running it using both a Python2 and Python3 distro (it should work in both, although @Caoimhinmg can provide some caveats). It has been a pleasant surprise that the wxPython code is effectively the same and that the 2to3 translator in the standard Python library (https://docs.python.org/2/library/2to3.html) did the trick on the rest of the code.

Is this still an issue @moonshoes87?

sorry for the delay!  I was on a hut-to-hut mountain bike trip.
This issue is resolved for me.  I'm hoping to have a look at the Python 2 --> 3 stuff soon.


4.3.3 not on MvnRepository

Latest version is 4.3.2: https://central.sonatype.com/artifact/com.google.maps.android/maps-compose?smo=true, https://mvnrepository.com/artifact/com.google.maps.android/maps-compose
However latest GitHub release is 4.3.3

Thanks, just confused of why my imports doesn't work

The issue is now fixed.

Sorry for the delay folks! Our automated release process broke down and we had to manually release the artifact.


Weave returns an error when trying to pull the latest from DockerHub

Run this Vagrant file to provision 2 VMs on VirtualBox:
https://github.com/weaveworks/guides/blob/ubuntu-all-edits/ubuntu-all-in-one/Vagrantfile
Next, try running the shell script to launch weave here:
https://github.com/weaveworks/guides/blob/ubuntu-all-edits/ubuntu-all-in-one/launch-simple-demo.sh
(this will fail and weave won't launch)
then ssh onto one of the VMs and launch weave from there:
weave launch
Unable to find image 'weaveworks/weave:1.2.1' locally
1.2.1: Pulling from weaveworks/weave
Pulling repository docker.io/weaveworks/weave
Status: Downloaded newer image for weaveworks/weave:1.2.1
docker.io/weaveworks/weave: this image was pulled from a legacy registry.  Important: This registry version will not be supported in future versions of docker.
Error deleting container: Error response from daemon: Unable to remove filesystem for f101788e50646c12e09b3f758301f57d884c9e4649536e4f8a4798a56576821d: remove /var/lib/docker/containers/f101788e50646c12e09b3f758301f57d884c9e4649536e4f8a4798a56576821d/mqueue: device or resource busy

Weave does, however launch afterward despite the message.
machine configuration is as follows:
docker info
Containers: 5
Images: 75
Server Version: 1.9.0
Storage Driver: aufs
 Root Dir: /var/lib/docker/aufs
 Backing Filesystem: extfs
 Dirs: 83
 Dirperm1 Supported: false
Execution Driver: native-0.2
Logging Driver: json-file
Kernel Version: 3.13.0-63-generic
Operating System: Ubuntu 14.04.3 LTS
CPUs: 1
Total Memory: 490 MiB
Name: weave-gs-01
ID: EBJ4:DO6U:647D:S7IJ:55ZL:2CGO:JC54:K6BU:NJNB:AEEO:Q2YF:M7NJ
WARNING: No swap limit support

I have replicated the symptom, thanks.
The error comes when Docker tries to remove the container that is running the main weave script.
It does not come if you do something simpler like weave version.
I shall continue to investigate.

Filed https://github.com/docker/docker/issues/17902
Confirmed this does not happen if you use a newer kernel.  I guess we should update that Vagrantfile.

Looks like a duplicate of #1647


Add the ability to mark read on delete

This provides the functionality for #591 as a reimplementation of #579 fixing the issues that were mentioned.
I'm not too sure I understand or entirely get the threading and MessageActor model in this class (which I consider overly long and complex - a bit God-like for a single controller.
I had some trouble initially with the message being moved before the actual server command to apply the flag was ran meaning it wasn't actually updated. Hence the current design.

This is missing changes to com.fsck.k9.preferences.AccountSettings so the new setting can be imported and exported.
Also, I feel the code to mark a message that is about to be deleted as read should probably go into MessagingController.deleteMessagesSynchronous().


fix(STONEINTG-939): update checkruns correctly

Before this commit:

When we were updating a pre-existing checkrun,
the correct status wouldn't get reflected on the
GH until the test is finished.
This is expected behaviour as per GH: An already
"completed" checkrun should NOT be updated to
a non-completed status.
Instead, we should create another checkrun with
the same external ID and that would reset the
already completed the checkrun correctly.
Source: "https://github.com/isaacs/github/issues/1530#issuecomment-599958904"

After this commit:

The users can see the correct status AND total
duration of Checkrun, while retriggering their tests.

Maintainers will complete the following section

[ ] Commit messages are descriptive enough (hints)
[ ] Code coverage from testing does not decrease and new code is covered (check the PR coverage on codecov)
[ ] Controllers diagrams are updated when PR changes controllers code  (if applicable)

I think the e2e-test failed while deleting build plr that failed with:
"message": "Pipeline integration2-izyb-tenant/ can't be Run; it contains Tasks that don't exist: Couldn't retrieve Task \"\": retryable error validating referenced object buildah: Timeout: request did not complete within requested timeout - context deadline exceeded",

looks flaky
/test integration-service-e2e

CLICK HERE TO VIEW THE BEFORE & AFTER SCREENSHOTS
BEFORE:

(Notice the wrong status and current duration while the test is running)

(Notice the wrong total duration that should've been ~5 mins)

AFTER:

(Notice the correct status and current duration)

(Notice the correct duration of ~5 mins)

Codecov Report
Attention: Patch coverage is 30.76923% with 9 lines in your changes missing coverage. Please review.

Please upload report for BASE (main@5af9731). Learn more about missing BASE report.

Files
Patch %
Lines

status/reporter_github.go
30.76%
7 Missing and 2 partials :warning:

Additional details and impacted files
@@           Coverage Diff           @@
##             main     #770   +/-   ##
=======================================
  Coverage        ?   72.80%
=======================================
  Files           ?       42
  Lines           ?     4008
  Branches        ?        0
=======================================
  Hits            ?     2918
  Misses          ?      795
  Partials        ?      295

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

Thanks for the patch, it looks good to me! Some more test for the code will be better.

@hongweiliu17 Ack! I added the test coverage now, PTAL.
Thanks!

/test integration-service-e2e


possible duration bug for calculating days

"2.10.3"
moment.duration(123456, 'minutes').asDays()
85.73333333333333
moment.duration(123456, 'minutes').days()
25
"2.10.5"
moment.duration(123456, 'minutes').asDays()
85.73333333333333
moment.duration(123456, 'minutes').days()
24
should this be 25 days?

This has months in it, so depends on how you count them. The logic changed for the better. So its a feature.

Isn't this inconsistent with how the other similar methods in durations work?
moment.duration(1234567, 'minutes').asMonths()
=> 28.167746999139837 (2 years + 4 months)
moment.duration(1234567, 'minutes').months()
=> 4

moment.duration(12345, 'minutes').hours()
=> 13
moment.duration(12345, 'minutes').asHours()
=> 205.75 (8 days + 13 hours)

@ioloie I don't get your comment. 28.16 is 24 + 4 (2 years and 4 months), and 205 is 8 * 24 + 13, so what is your point exactly, and what is inconsistent.
Those examples are from 2.10.5. To be fair, the exact same examples produce the exact same result in 2.10.3 :)

@amccarthyMatchbook to be more accurate, moment.duration(123456, 'minutes').asDays() // 85 days is 2 months and 24 days in 2.10.5 and 2 months and 25 days in 2.10.3, so in one case 60 days is two months (less accurate), in the other its 61 (more accurate).
All of those are approximations, so I don't think changing the values a bit should affect anybody (they are just displayed for convenience). If you have 2 date difference -- use the special duration constructor { from, to }. It will preserve number of months and days exactly.

The inconsistency occurs in the case of days where the output is one less than the remainder of the output of asDays:
moment.duration(123456, 'minutes').asDays()
=> 85.73333333333333 (2 months + 25 days)
moment.duration(123456, 'minutes').days()
=> 24 (1 less than 25)

If you count 2 months as 60 days. It can be more / less.


Two ads aren't being detected

I've found two ads that are not being detected by the script.
I'm investigating how to detect them to create a fix for those too.

Create a database with flagged "songs" so that users can blacklist ads songs. Maybe even a online database so community can add blacklisted songs?

It's not necessary to have a db actually. The problem is that those type of ads don't show up in the event logs. I'm still debugging to know more.

There's no way to detect those Ads. The good thing is that they don't show too often so it's not a big problem


When using the @skip directive with an alias, the generated type does not make the field optional

Issue workflow progress
Progress of the issue based on the Contributor Workflow

[x] 1. The issue provides a reproduction available on Github, Stackblitz or CodeSandbox

Make sure to fork this template and run yarn generate in the terminal.
Please make sure the Codegen and plugins version under package.json matches yours.

[x] 2. A failing test has been provided

[ ] 3. A local solution has been provided

[ ] 4. A pull request is pending review

Describe the bug
When using the @skip directive with an alias, the generated type does not respect the @skip directive and mark the field as optional.
When an alias is not used, the generated type correctly marks the field with @skip directive as optional.
To Reproduce
Stackbliz repro https://stackblitz.com/edit/github-kvkzyn-rf4chd?file=types.ts
Steps to reproduce the behavior:

My GraphQL schema:

type Query {
    user(id: ID!): User!
}

type User {
    id: ID!
    username: String!
    email: String!
}

My GraphQL operations:

query user {
    user(id: 1) {
        userid: id @skip(if:true)
        email
    }
}

My codegen.yml config file:

schema: schema.graphql
documents: document.graphql
generates:
  types.ts:
    plugins:
      - typescript-operations

Expected behavior
I expect the generated type to be
export type UserQuery = { __typename?: 'Query', user: { __typename?: 'User', email: string, userid?: string } };

Specifically the userid? property is optional
Actual behaviour
The generated type is
export type UserQuery = { __typename?: 'Query', user: { __typename?: 'User', email: string, userid: string } };

Specifically the userid property is not optional.
However if I don't use an alias on the id field, then the generated type is correct.
Stackbliz repro https://stackblitz.com/edit/github-kvkzyn-ltndu9?file=document.graphql
query user {
    user(id: 1) {
        id @skip(if:true)
        email
    }
}

export type UserQuery = { __typename?: 'Query', user: { __typename?: 'User', id?: string, email: string } };

Environment:

OS:
@graphql-codegen/...:

  "dependencies": {
    "@graphql-codegen/add": "^3.1.1",
    "@graphql-codegen/cli": "^2.4.0",
    "@graphql-codegen/typescript": "2.4.8",
    "@graphql-codegen/typescript-operations": "2.3.5",
    "graphql": "^16.2.0"
  }

NodeJS:

Additional context

I've created a failing test for this https://github.com/dotansimha/graphql-code-generator/commit/9dd7a0395abf51d0209c8c62f8e811e557029eb3
    it('On avoidOptionals:true, aliased fields with @skip, @include should make container resolve into MakeMaybe type', async () => {
      const schema = buildSchema(/* GraphQL */ `
        type Query {
          user(id: ID!): User!
        }

        type User {
          id: ID!
          username: String!
          email: String!
        }
      `);

      const fragment = parse(/* GraphQL */ `
        query user {
          user(id: 1) {
            id
            username
            useremail: email @skip(if: true)
          }
        }
      `);

      const { content } = await plugin(
        schema,
        [{ location: '', document: fragment }],
        {
          avoidOptionals: true,
          preResolveTypes: false,
        },
        {
          outputFile: 'graphql.ts',
        }
      );

      expect(content).toBeSimilarStringTo(`
        export type UserQueryVariables = Exact<{ [key: string]: never; }>;

        export type UserQuery = (
          { __typename?: 'Query' }
          & { user: (
            { __typename?: 'User' }
            & Pick<User, 'id' | 'username'>
            & MakeMaybe<{ useremail: User['email'] }>, 'useremail'>
          ) }
        );
      `);
    });


arm/trustzone: time interrupt setting failed

Summary
we should use a secure clock when the CPU is in secure mode
Impact
none
Testing
ostest

Please fix
armv7-a/arm_timer.c: In function 'arm_timer_initialize':
Error: armv7-a/arm_timer.c:279:14: error: 'GIC_IRQ_SEPTM' undeclared (first use in this function); did you mean 'GIC_IRQ_PTM'?
  279 |   irq_attach(GIC_IRQ_SEPTM, arm_timer_interrupt, lower);
      |              ^~~~~~~~~~~~~
      |              GIC_IRQ_PTM
armv7-a/arm_timer.c:279:14: note: each undeclared identifier is reported only once for each function it appears in


add interactive developer console

add custom executor for run-commands

allows console to be interactive
fixes bug when running serve that broke serverless-offline output

add custom console script for repl
add lib generator that includes console

console README:

Run yarn console <SERVICE/LIBRARY_NAME> to start the console
Any files in src/index for that service/lib will be auto-loaded into the repl's context
If you make a change to a file, you can reset the console using .re in the repl which will reload all the files
IMPORTANT NOTE: There is a known issue with node's require being slow (~700ms per require). This means the more files you include in your modules src/index, the longer it will take for the console to load/reload. Please keep this in mind when developing using this feature. This will also use your .env so if you have database connections you're testing, these will be live/hot/real so proceed with extreme caution.

Closes #4

Based on current implementation got the following working:

Challenges to resolve:

reloading doesn't actually work using current load from index pattern as files are not busted
this pattern only worked on the shared module due to its definition - need to define something more generic that can work for both services and the lib or possibly even combine the 2

@jtomchak I've made some updates since I DM'd you on Twitter. I'm currently vibing with this setup but want a second opinion still. Does this seem like a feature you would use if made available?


Change all agent related paths to be under dir cosmic

In the process of extracting the agent packaging logic from the bulk packaging scripts, we are renaming all artifacts and directories to cosmic. This PR changes the agent module in the same fashion.
In the process we also removed the debian directory which contained packing scripts for debian

LGTM :+1:


Getting Error code from burrow execution

Description of the Change
Add possibility to get info why Burrow execution failed, what is stateful validation error code

Issue

Benefits
Ability to get error code from smart contract execution, know why it failed

Possible Drawbacks

Usage Examples or Tests [optional]

Alternate Designs [optional]

Do we need to read engine_err_response field in a query?

Do we need to read engine_err_response field in a query?

There is problem when I wanted to add new field in response, because query result is implemented using boost::tuple which has max 10 elements, and result tuple can have 11 elements, so I came up with this solution

@Pawlak00 It seems c++ code uses only 9 arguments from request. You can exchange unused one. It seems permissions doesn't uses https://imgur.com/3P90itj.png

@Pawlak00 It seems c++ code uses only 9 arguments from request. You can exchange unused one. It seems permissions doesn't uses https://imgur.com/3P90itj.png
@iceseer
the problem is here: https://github.com/hyperledger/iroha/blob/4c4adf9be2a2374623c250e5b42cc76f40bb2700/irohad/ametsuchi/impl/postgres_specific_query_executor.cpp#L341 becouse QueryTuple and PermissionTuple are concatated and resulting tuple has max 10 elements, so if we add new field to QueryTuple it would have 11 elements which is bad :(

Is this PR still relevant? @baziorek @iceseer

Is this PR still relevant? @baziorek @iceseer

@appetrosyan @Pawlak00 Could You please tell us if the PR is ready, or is to close?


fontFamily Consolas, Use space but not ALIGN

VSCode Version: Code 1.17.1 (1e9d36539b0ae51ac09b9d4673ebea4e447e5353, 2017-10-10T14:24:50.851Z)
OS Version: Windows_NT x64 10.0.15063
Extensions:

Extension
Author (truncated)
Version

vscode-great-icons
emm
2.1.16

material-icon-theme
PKi
2.2.2

(6 theme extensions excluded)

Steps to Reproduce:

Reproduces without extensions: Yes/No

Duplicate of #36385
If you do not feel this is a duplicate, please provide some additional information about this issue such as the expected behavior and some steps to reproduce the problem


Add  CVE as reference in existing importers

Some importers (eg https://github.com/nexB/vulnerablecode/blob/87ffa8109e4f5dcb22b4c8d71eaf1711c82068d7/vulnerabilities/importers/istio.py#L201-L204, https://github.com/nexB/vulnerablecode/blob/87ffa8109e4f5dcb22b4c8d71eaf1711c82068d7/vulnerabilities/importers/alpine_linux.py#L174) do not add the CVE as a reference when it already exists as vulnerability_id.
This has been discussed here: https://github.com/nexB/vulnerablecode/pull/393#discussion_r609769729

Note that this will be also be always an alias


update damper system kinematic calculations

add kinematics calculations wheel system
refactor name convention from spanish to english
add damper kinetics and force analysis

Useful link for shock absorber calculations
https://www.extrica.com/article/21436


26 add text review workflow

@kygoffe - Finally ready for your review (in your own time, no rush). Please could you try it out locally, following the vignette? Let me know if anything is not working for you.

Little comments but happy to merge. thanks, this looks great!!!! 💯🥇

Latest 2 commits were resolving the last few issues and I updated the README with the new functionality and files (that file tree is a pain!). Happy for me to merge, or want to have a double check first?

Little comments but happy to merge. thanks, this looks great!!!! 💯🥇

Latest 2 commits were resolving the last few issues and I updated the README with the new functionality and files (that file tree is a pain!). Happy for me to merge, or want to have a double check first?

happy for you to merge! thanks for this!


Compositor cannot choose xdg-surface state before first frame

From IRC:
23:45 <emersion> in short:
23:45 <emersion> when a new xdg-surface appears:
23:45 <emersion> - it can request to be fullscreen/maximized/whatever
23:46 <emersion> - we have to send a configure event with the xdg-surface state (accepting requests, or not)
23:46 <emersion> - then the client knows how to draw itself and can commit a buffer
23:46 <emersion> the issue is:
23:47 <emersion> the compositor doesn't know about the xdg-surface before the first non-NULL commit
23:48 <emersion> ie. before it's mapped
23:48 <emersion> so there are two solutions:
23:48 <emersion> 1. accept all requests before the first non-NULL commit directly in wlroots
23:49 <emersion>    (if the compositors doesn't want this, the first frame will be not drawn in the correct state)
23:50 <emersion> 2. emit new_surface for unmapped xdg-surfaces, to let the compositor choose the xdg-surface state
23:50 <emersion> acrisci: what do you think
23:51 <acrisci> let me understand the problem first
23:51 <acrisci> so the window can ask to be fullscreen or something before it is mapped?
23:51 <emersion> yeah, for instance mpv
23:52 <emersion> there's a flag to launch it fullscreen
23:52 <acrisci> so if the compositor doesn't know about it, then wlroots makes the decision
23:52 <emersion> yeah
23:53 <emersion> let me give you another example
23:53 <acrisci> but the compositor should make the decision of course
23:53 <emersion> in sway apps are in containers
23:53 <emersion> containers have a size
23:54 <emersion> when a client creates an xdg-surface it doesn't know how to choose its size
23:54 <emersion> so before the first frame, the compositor should send a configure event with the desired size
23:55 <emersion> but right now the compositor doesn't know about the xdg-surface before the first frame because new_surface hasn't been emitted
23:55 <emersion> so in sway, the first frame has a size choosen by the client, then the compositor sends a request to resize the client
23:56 <emersion> this is bad
23:58 <acrisci> yep that's a problem
00:04 <acrisci> I'm afraid of leaking details on what constitutes a mapped/unmapped xdg-surface
00:05 <acrisci> I want to keep compositor commit handlers as small as possible
00:09 <emersion> hmmm
00:09 <emersion> let's create an issue about it
00:10 <acrisci> I wonder if we should do map/unmap events
00:10 <emersion> yeah

Also see #681

Map/unmap event could be in line with Xwayland.
Whether or not unmap makes a lot of sense for xdg...


Helm is ignoring service account annotations when defined in values

Describe the bug
When using the external-secrets upstream helm chart and defining annotations under serviceAccount.annotations,  the resulting service account is missing the annotation.
To Reproduce
Steps to reproduce the behavior:
k8s version: v1.24.14-gke.1200
Chart.yaml
apiVersion: v2
name: external-secrets
description: A Helm chart for Kubernetes
type: application
version: 0.0.1
dependencies:
  - name: external-secrets
    version: 0.9.1
    repository: "https://charts.external-secrets.io"

values.yaml
serviceAccount:
  # -- Specifies whether a service account should be created.
  create: true
  # -- Automounts the service account token in all containers of the pod
  automount: true
  # -- Annotations to add to the service account.
  annotations:
    iam.gke.io/gcp-service-account<EMAIL_ADDRESS>  extraLabels: {}
  # -- The name of the service account to use.
  # If not set and create is true, a name is generated using the fullname template.
  name: ""

When running helm -n external-secrets template external-secrets external-secrets I get the following output for the service account:
---
# Source: external-secrets/charts/external-secrets/templates/serviceaccount.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
  name: external-secrets
  namespace: "external-secrets"
  labels:
    helm.sh/chart: external-secrets-0.9.1
    app.kubernetes.io/name: external-secrets
    app.kubernetes.io/instance: external-secrets
    app.kubernetes.io/version: "v0.9.1"
    app.kubernetes.io/managed-by: Helm

Expected behavior
I expect the output to be the following:
---
# Source: external-secrets/charts/external-secrets/templates/serviceaccount.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
  name: external-secrets
  namespace: "external-secrets"
  annotations:
    iam.gke.io/gcp-service-account<EMAIL_ADDRESS>  labels:
    helm.sh/chart: external-secrets-0.9.1
    app.kubernetes.io/name: external-secrets
    app.kubernetes.io/instance: external-secrets
    app.kubernetes.io/version: "v0.9.1"
    app.kubernetes.io/managed-by: Helm

It was a mistake on my end and forgot to add these values under the charts key
external-secrets:
  serviceAccount:
    # -- Specifies whether a service account should be created.
    create: true
    # -- Automounts the service account token in all containers of the pod
    automount: true
    # -- Annotations to add to the service account.
    annotations:
      iam.gke.io/gcp-service-account<EMAIL_ADDRESS>    extraLabels: {}
    # -- The name of the service account to use.
    # If not set and create is true, a name is generated using the fullname template.
    name:


Basic TS calculator function

Description
added functions: add(), sub(), multiply(), divide() to issue Medium create a TS calculator
errors to the console when dividing by 0
type safe so  you get "Argument of type ______" when trying to use calculator on anything other than a number
Additional Context
https://www.mycompiler.io/view/5pSSu2EbBzS - link to online test

Merged

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Thank you for your contribution! Your pull request has been merged. The files have been reset for the next contributor.
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If you're looking for more ways to contribute, I invite you to check out my other projects. Just click here to find more. These projects contain real issues that you can help resolve. You can also check out the Influences section in the README to find more projects similar to this one.
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HBASE-28127 Upgrade avro version to 1.11.3

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dupname asflicense javac spotless xml hadoopcheck compile

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Improve Scale DC/OS package

Improve the Scale DC/OS package:

Have the Scale web server be launched as its own separate app
Group all of the Scale pieces (scheduler, web server, logstash, db, etc) as a Marathon group
Clean up dcos_cli.py to use good Python conventions
Re-write the entrypoint script in Python

There are a couple challenges here:

We cannot build multiple images if the Dockerfiles reside at the root of the source tree. Docker Hub automated builds do not allow for customizing the file name that represents the Dockerfile. A possible approach is to place the scheduler Dockerfile within the Scale source tree, but that also seems awkward. If we did a separate UI+StaticDemo / API+Docs / Scheduler+Bootstrap image we'd be getting pretty close. Splitting this way would allow the existing structure to remain with Dockerfiles in /, /scale-ui, and /scale.
We have no current way to entirely contain all Scale components within a Marathon group. DC/OS packaging does not natively support groups (see https://github.com/mesosphere/universe/issues/569), so would, at best, be stuck with a kludge where the initial app was outside of the group with all bootstrapped apps living within. This kind of defeats the purpose of grouping, if it doesn't apply to everything.

Another alternative is to perform all the builds manually, eliminating the Docker Hub automated builds. This could be done in TravisCI and then the dockerfiles and context passed could be controlled in a more flexible manner.


[Weird] Server Crashed!

Suddenly no Monsters LOL! All Lanes Empty Everything Dead! LOL!

Why is this being posted here? What does this have to do with the script

It's up again now anyways.


Update to latest XcodeEdit version

Xcode.swift has been renamed to XcodeEdit.
This updates to XcodeEdit version 1.0

Check-out branch xcode-edit
Delete Xcode.swift directory: rm -rf Xcode.swift
Update XcodeEdit submodule: git submodule update --init

Since it isn't 2014 anymore, maybe we should move away from git submodules; They're annoying.
I'll update this PR to use Swift Package Manager instead, and throw away all the submodules.

Work complete. R.swift can now be build with SPM.

So, release script works, tests all run correctly with Fastlane and from Xcode on my local machine. Only Bitrise is not happy yet, it gives us a linking error when running the tests from Fastlane.
Fixing Bitrise is the only thing preventing me from merging this atm, will take a look if I can fix Bitrise tomorrow!


Extended Hero Block impl

Fix #135 #248 #156
Test URLs:

Before: https://main--hlx-test--urfuwo.hlx.live/blog/2023/11/idc-marketscape-sap-a-leader-cloud-enabled-sourcing-applications
After: https://hero-2--hlx-test--urfuwo.hlx.live/blog/2023/11/idc-marketscape-sap-a-leader-cloud-enabled-sourcing-applications
https://hero-2--hlx-test--urfuwo.hlx.live/draft/mhaack/hero-demo
https://hero-2--hlx-test--urfuwo.hlx.live/draft/mhaack/hero-demo1
https://hero-2--hlx-test--urfuwo.hlx.live/draft/mhaack/hero-demo2
https://hero-2--hlx-test--urfuwo.hlx.live/draft/mhaack/hero-demo3
https://hero-2--hlx-test--urfuwo.hlx.live/draft/mhaack/hero-demo4

Should hero without image leave whitespace on right side?
https://hero-2--hlx-test--urfuwo.hlx.live/draft/mhaack/hero-demo3

I have applied this new hero to the Julia White full author profile page:

https://hero-2--hlx-test--urfuwo.hlx.live/author/juliawhite

It will require some tweaking, but that should be done in a separate ticket:

"Executive Board" should be a pre-title, not a subtitle
We need an option to disable the metadata line (author avatar + name, publish date, reading time line)

cc @mhaack

Should hero without image leave whitespace on right side?
https://hero-2--hlx-test--urfuwo.hlx.live/draft/mhaack/hero-demo3

This is how the web component works.

It appears as if the line height of the textbox h1 seems to be too small, the text lines bleed into each other (see  https://hero-2--hlx-test--urfuwo.hlx.live/draft/mhaack/hero-demo4, all viewports)

@pahupe good catch that is actually caused by the update of the udex web component lib which added new CSS tokens which we don't have in our theme CSS.


tic or tinylic is not valid argument

I'm new to Compress ai. In the example directory, I followed the instruction  to use  'python examples/train.py -m tinylic -d mydataset/ --epochs 400 -lr 1e-4 --batch-size 8 --cuda --save ' , 'python train.py -m tinylic -d mydataset/ '  , 'python train.py -m tic -d mydataset/' and 'python train.py -d mydataset/'.
But I always get the same error of tic argument. So I wonder how to train TIC?

I made a mistake in command line of installation and another repo (TIC) was cloned by you. I have corrected it and now you can re-clone it. Sorry for my carelessness.

I re-clone the repo and try to train again. But a new import error seems like this.

You can now use "tinylic" instead of "tic" as the model for training.

No matter I use 'tinylic' or 'tic', the import error is always there like cannot import 'tic'.

Oh, I see. You should remove line 37 and 50 in zoo/init.py or re-clone the repo, I have updated it.

Thanks for your answer, now everything works well.


Improve test suite to be able to test with multiple configuration sets

Closes #83.
It's been a long time, but I think this is finally ready.
For details about the goals and motivation of this change, see issue #83. For details on how to run the tests, as well as how the tests work on a technical level, see TESTING.md.

This PR is designed to support CircleCI with the following project settings:

There are security considerations to be made here, in that a malicious pull request could quite easily retrieve the AWS IAM key and secret that's used for testing. But due to the way the permissions are set up, this IAM key only grants permission to create/delete buckets starting with "gatsby-plugin-s3-tests-". Even so, malicious actors could incur extra costs on your Amazon account by uploading large files, or perhaps they could upload illegal content to your account in order to share it.
In order to discourage this, I highly recommend that you install the included Lambda script to tidy up old test buckets. Currently when it runs it deletes any "gatsby-plugin-s3-tests-*" buckets created more than an hour ago, but I think this can safely be lowered to 15 minutes. You should be able to comfortably run this script once every 5 minutes without going out of the Always Free tier.

Yes yes! Very cool, glad you were able to finish it.
Regarding security: with the old testing setup with travisCI I just had PR's disabled entirely to prevent the key from leaking.
I get that this is not very feasible thoug, it defeats most of the point of having a CI flow in the first place, but I just couldn't risk the keys leaking out.
The auto deletion script however kind of feels like putting a bandaid on a bursted pipe (forgive the awful metaphor), if any malicious actor gets a hold of the key, it's still very possible they could incur major charges to my AWS bill by e.g. creating loads of buckets + uploading data from multiple hosts simultaneously.
In 15 minutes you can still do a lot of damage, and I'm not sure if I'm comfortable with that.
I briefly checked and it seems that circleCI has an additional approval functionality which might be worth investigating:
https://circleci.com/docs/2.0/workflows/#holding-a-workflow-for-a-manual-approval
If this could be done in combination with a bot that would place a comment

informing the PR author that it's waiting for approval
containing a link for contributors that links to the approval page

That would make this pretty realistic in my eyes.
You and I check our email fairly regularly (because you often beat me in response times 😛), and we could just briefly check if a PR does not contain anything malicious before doing an actual review, and approve it.
It's not ideal, but at least we would still hold full control over what gets ran on the AWS environment, and more importantly, prevent the key from leaking out.
I will give the rest of the PR a review this evening.

The auto deletion script however kind of feels like putting a bandaid on a bursted pipe (forgive the awful metaphor), if any malicious actor gets a hold of the key, it's still very possible they could incur major charges to my AWS bill by e.g. creating loads of buckets + uploading data from multiple hosts simultaneously.
In 15 minutes you can still do a lot of damage, and I'm not sure if I'm comfortable with that.

That's fair enough, especially when you consider that an attacker can automate it and create a new bucket and upload files every 15 minutes. You might not even notice until you got the bill.
I think I was happy once I got it to the point of "it would be unprofitable to exploit", but I wasn't counting the possibility that someone might have a grudge against you (or just do it for lulz).

I briefly checked and it seems that circleCI has an additional approval functionality which might be worth investigating:
https://circleci.com/docs/2.0/workflows/#holding-a-workflow-for-a-manual-approval
If this could be done in combination with a bot that would place a comment
1. informing the PR author that it's waiting for approval

2. containing a link for collaborators that links to the approval page

We'd have to test it, but I think CircleCI's integration with GitHub Checks would actually handle this for us.

Waiting for approval from a project maintainer before running e2e tests. https://circleci.com/workflow-run/

[AUTOMATED MESSAGE]
Waiting for approval from a project maintainer before running e2e tests.
@jariz @JoshuaWalsh https://circleci.com/workflow-run/2284182e-cebe-4d79-93d2-625e3711f6ac

I briefly checked and it seems that circleCI has an additional approval functionality which might be worth investigating:
https://circleci.com/docs/2.0/workflows/#holding-a-workflow-for-a-manual-approval
If this could be done in combination with a bot that would place a comment
1. informing the PR author that it's waiting for approval

2. containing a link for collaborators that links to the approval page

That would make this pretty realistic in my eyes.

Done this part. Will try to address the remaining items soon.

@jariz I believe I've made all the requested changes.

Now the notifications work as a GitHub App instead of using a GitHub Personal Access Token!
Check it out here.

Great! I'll merge this now and do the setup tonight!

Next step is to write tests for some of the new features we've implemented, as well as some of the currently pending PRs.
I'm busy with work for the next couple of months, so I think someone else might have to take the lead on that.

Hi @jariz ,
Have you done the setup for this yet? Last I saw, #155 encountered an error during tests related to a missing Context.
I'd like to be able to ask contributors to add test coverage to their PRs.
Thanks,
Josh

Hey @JoshuaWalsh,
Apologies for the initial delay, but it's all up and running now.
See #160 for an example.
I'm afraid I have some bad news however, from the fork, I am able to update the circleCI configuration, and it accepts this as valid, making it possible to completely bypass our hold check (#161)

Thus, I've disabled the 'build forked PR's' setting for now. ☹
I'm sorry I'm being so picky about this, but the security is something I need to have locked down for me to be able to sleep at night.
I'll start thinking of some alternatives and will let you know, maybe you have some ideas?
A different (much minor) problem I've noticed is that the workflow on master also requires a manual approval, is there a way to bypass this for master? If not, no big deal.

I am able to update the circleCI configuration, and it accepts this as valid, making it possible to completely bypass our hold check

I have a hunch that this might only be for project maintainers. I'll do some tests on my own repo.

Good point. Worth checking out.

I just created an alt account (#163) that does not have any access whatsoever, but as you can see, I can still remove the approval step.
I have an alternative idea (and some free time 😛) lined out in #162 that I'm hoping to put together today.


Add Language & Build System Support Table

Hello this is an issue similar to #733. It is currently very unclear what is and is not supported by this project. So it is hard to know if this project can even fit my use-cases, because it is not clear what projects I can use this for.
One example of this is, is I was interested in using this in one of my Rust projects as that there is support generating Rust APIs, but there is no standalone tool I can use, I have to use Gradle, which for most projects primarily developed in Rust is a non-starter.
It would be nice if there was a section in documentation that detailed what languages and build systems are currently compatible with Smithy codegen, and what language APIs can be generated from smithy's codegen.

Good idea. We'll work on getting some kind of status quo added to the docs.
Smithy is only supported in Java today, and the only build tool we offer support for is Gradle. You can use the Dockerfile we provide too, which bundles it all up.
To help me understand -- If you're building something in Rust, do all the build tools you use need to be implemented in Rust? Would you care what Smithy was implemented in if it used Java but was built as a standalone executable?

To help me understand -- If you're building something in Rust, do all the build tools you use need to be implemented in Rust? Would you care what Smithy was implemented in if it used Java but was built as a standalone executable?

It doesn't to be implemented in Rust for me to use it, it needs to be at least build.rs friendly. A free-standing binary would be a solution for using what is currently supported. However, I think my follow-up question would be, how would I be able to extend that free-standing binary's functionality beyond what is available?
For example, would I be to write my own Smithy projection in my preferred language, without needing upstream changes or using Java? If Smithy is a free-standing tool, I would kinda hope that I can integrate with it with a language agnostic protocol.

If we shipped a standalone tool for the Java reference implementation, it would likely be done using JLink, which means that it could still load JARs that weren't compiled into the binary. Regardless though of a standalone tool or not, the only supported extension mechanism today is to write code in Java.
We realized in AWS that it takes a huge investment to create build tooling and code generators from scratch in each programming language we support, so every Smithy generator we're building is written in Java using shared tooling (for example, smithy-rs and aws-sdk-rust). We also do what's called model-ignorant code generation, so there's no runtime Java dependency needed to use any of the generated code nor is the model needed at runtime.
smithy-rs is meant to be a generic Smithy code generator for Rust, and aws-sdk-rust extends it to add AWS-specific functionality. Smithy-rs will eventually be polished up to work well with Rust build tools and be able to generate clients and servers, but it's not quite there yet. There's also a project to implement parts of Smithy in Rust, but it's still very early in development: https://github.com/johnstonskj/rust-atelier.

We realized in AWS that it takes a huge investment to create build tooling and code generators from scratch in each programming language we support, so every Smithy generator we're building is written in Java using shared tooling (for example, smithy-rs and aws-sdk-rust). We also do what's called model-ignorant code generation, so there's no runtime Java dependency needed to use any of the generated code nor is the model needed at runtime.

I definitely understand why AWS would focus on single language tooling. However I will say that I don't see these two things as incompatible or diverging paths, and a lack of language agnostic extensibility makes this project hard to adopt for non-Java teams even with AWS' own codegen tooling. Most projects I work on where I would want to use, I want to target platforms and languages that aren't and may never be priority for AWS to provide tooling for, but I still would want to use Smithy as the IDL for those platforms. Writing my own target projection would be acceptable provided that I could write something that would integrate well with the project, but requiring Java is too much of a barrier to use this in a personal project, and there's no way I could get the buy in from a team to add a custom Java package dependency to our build process just to be able to use Smithy for the project if we weren't already using Java.
I'm not sure why additional backends would require JLink. Smithy already provides a language agnostic API in terms of its JSON AST as an intermediate representation language, any other language can read that. So a minimal version of this could just be smithy ./sdk.smithy -o json | smithy-codegen-acme. I think ideally it would output JSON that's more tool/machine friendly, and a less human friendly version of the AST that's gone through validation and trait resolution, so all of that logic can remain part of the mainline smithy tool, and the target backends can focus just on generating code.

I appreciate your input! I've updated the docs to list all things we've shipped, what we're working on, and their status. The PR with those doc updates closed this issue. Do you want to update the title and reopen as a feature request?
What I meant with JLink was that if we provided a standalone CLI tool that removed the need for Gradle, it would still be able to load additional JARs. That isn't to say that some kind of process-based smithy-build plugin couldn't be added (e.g., the Smithy CLI could invoke some referenced process as part of this). The JSON AST representation of a Smithy model and the central tool handling validation does make it easier for other tools to use. I think it would end up being significantly more work to build codegen tooling from scratch in another language that can load and traverse the metamodel, but it sounds like that's an acceptable tradeoff in your case.
If you want a use case like ./sdk.smithy -o json | smithy-codegen-acme, then it's not really that far off from what we have now, since the CLI has an ast command. We'd just need to ship a standalone CLI (and I guess in the meantime you could Docker):
./smithy ast MODEL1 MODEL2 ... | smithy-codegen-acme


Loss Graphs into Gradio Interface

Will a similar function be added to Applio? — LINK
It looks interesting.

no, tensorboard is just great for that


Understand behavior of absolute symlinks for namespaces and chroot

For encoding absolute symlinks, we typically remove the prefix of the continuity context root from the link target and store that as the resource target. When this gets "applied", the meaning of this absolute target becomes unclear in the context of chroot or linux filesystem namespaces. If we are inside a chroot or namespace, and applying the manifest to "/" (the root path of the chroot), it is unclear whether we have to write the full path, as it appears in the filesystem or just the path rooted at the context. It is also unclear whether this behaves differently for chroot and namespaces.
If this works correctly for both chroot and namespaces, we can likely avoid any complexity. If they need to be written differently for a given context, we need to provide the necessary hooks to allow the caller to adjust how absolute links are created.
Ideally, we'd find a nice solution to this, as options and flags that affect symlinks are notoriously finicky.

Closed by #24.


Output csv file header documentation

Hi,
I have generated the following .csv file in RL

Agent
Prior
Target
Score
SMILES
Scaffold
Dockstream Docking
Dockstream Docking (raw)
QED
QED (raw)
step

20.6034
20.6034
-18.8154
0.0139693
NC(N)=NN=c1[nH]c2ccccc2[nH]1
N=c1[nH]c2ccccc2[nH]1
0.0007012
0
0.2782901
0.2783
1

What do Agent, Prior, Target, Score, Scaffold columns mean?

The first 3 are the respective NLLs, see eqs. 5 and 6 in the paper.
Score is the total aggregated score of all components.
Scaffold is the scaffold from the SMILES column.
If you want to use an expensive scoring component like docking, you should probably use staged learning/CL to first ramp up the total score before you attempt to go into docking.

Hi @halx
Thank you for your response
Yes, I use staged learning already and this is output on the 5th epoch. I plan to finetune model on 50 epochs and after that use chkpt file to generate new smiles with maximum precision. Is this what you mean by 'ramp up the total score'?

With staged learning you are able to run RL in stages where each stage can have its own parameter set.  At the moment this primarily means scoring components.  In this way you can do curriculum learning (CL).  The idea of CL, originallly at least, is to start learning from simpler examples and then use this as a basis to learn more complex examples, similar to how humans learn.
Another motivation to do CL for molecule optimization is that scoring can be computationally very expensive.  It can be very inefficient to apply e.g. docking right from the beginning as either generated compounds may not dock or lack in quality in the other scoring components.  Therefore, in practice you would first run a stage with cheap components and then run a stage with the expensive components added in.  As components can push in opposite directions (multi-objectice optimization problem) it will take some experimentation as to how to run the stages and how to adjust the weights of each component.
In a typical project, it is not the aim of RL/CL to create a focused agent.  The agent is merely an artefact and what you are really interest in is compounds with good scores overall.  These can be generated in epoch although typically with higher probability towards the end of the run.  If you just sample from a final agent you have no control over its properties as the agent will still produce compounds of low quality.  You would need to post-process those compounds to sort for the wanted ones.  It therefore would seem better to simply continue with another stage that is identical to the previous one.  In practice though one would generate a certain amount of compounds, post-process those e.g. by clustering and choosing representative, and discuss those with the team.

@halx
Got it. Thank you for your response!


Add text elements

Text elements are the basic unit of content, paragraphs will be composed of multiple text elements...

+1

+1


Undocumented parameter row.classes in summary-list

The row.classes parameter is undocumented in the yaml for the summary-list component.

Thanks for flagging this, @dabd 👍
We've fixed this in #1556, but just to let you know the change won't show up in the Design System until we roll out the next release.


fix: ignore unreachable hosts

Fixes: #33

:tada: This PR is included in version 1.4.5 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


fix: keep @ts-ignore for headingIcon in library #476

Description
Sorry, I thought removing @ts-ignore would be better, but for projects not having any *.png declaration this will produce an error. I also don't have a better solution, while I don't like using @ts-ignore.

The error happens even with types/png.d.ts? Is it because Typescript doesn't loads /types dir by default?

Yes previously it didn't work, only if you own project/app has a declaration für *.png. That's why our app didn't complain.
If I import import "./types/png.d.ts" into the Maplibre.ts it works – but this also makes the type bleed into the app code of the user. Not sure about other options with typeRoots...

I really can't find a better solution without bleeding into user space. I think the speciality is, we aren't building the lib at all. So I guess this solution must do it.
Was the decision to not have a build step at all and ship plain TS discussed somewhere?


Feat/ai proxy identity providers

Description
Added more detailed instructions for multiple cloud providers and their respective authentication.
Testing instructions
Preview link:
Checklist

[x] Review label added
[x] Conditional version tags added, if applicable.

@tysoekong Thanks for writing these up! I'm reading them over now, and was wondering if you had the credentials for Azure, Gemini Vertex (business/enterprise), and Bedrock (business/enterprise) that we could borrow for testing? I like being able to test the workflows myself so I can make note of anything that tripped me up that I could add to docs 🙂


Using vectors

@Chubek I did not replace every [u8] you had in there.
Also never forget to format your code via the cargo fmt tool.


typo: Provder -> Provider

Yes, it does fix the broken xrefs, @nschonni. Do you want to approve the PR now, @mairaw?


renaming/refactoring output directories

autotop directories in the work folder should live inside another folder

'seg_{modality}' doesn't make sense - vol? (to go with surf?)

xfm or transform folder to store warps? (or warps?)

think about a coords folder (or subfolder?)

only allow user to specify 1 modality at a time  -- this would allow removal of the {modality} wildcard in filenames/folders and simplify outputs alot

workflow mode vs bids app:

workflow mode:
-results/sub-
-results/work
logs

bidsapp mode:
sub-
work
logs

config['root']

point 5. above is dealt with in #137

I think that we should change seg to vol, merge it with anat (which is typically nearly empty), and then place warps and coords subfolders inside that. I think this would be fine for both work and root. @akhanf thoughts?
Related bug: from-unfold_to-corobl_mode-image_xfm files are showing up in the results and i'm not sure why - I don't see them in the common.smk or in the warps.smk

instead of subfolders for warps and coords, we could just make them siblings, e.g. contents of hippunfold/sub-001 could be:
vol
warps
coords
surf

actually regarding naming of the vol folder, I think I actually prefer to just call it anat, as it would contain the _{T1w/T2w}.nii.gz and _dseg.nii.gz images, so from a BIDS perspective that would be the required location for those BIDS derivatives files. It also leaves the door open for func and dwi folders, e.g. when we get around to adding rules to import and resample that data..

re: that from-unfold_to-corobl_mode-image_xfm file showing up in results, I can take a look, it could be using root=root in some generic rule..
In any case, we should probably finish merging in  #153 before we branch with more refactoring to make our lives easier