feat(Column): allows 0 width column size for column offset

Changes offset props to allow for 0 width offset.

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

📬Published Alpha Packages:@codecademy/brand-components@0.8.1-alpha.ba1a94.0+ba1a94cb@codecademy/gamut-templates@2.5.1-alpha.ba1a94.9+ba1a94cb<EMAIL_ADDRESS>
🚀 Styleguide deploy preview ready!https://5e826ab3573c05e41de0115e--codecademy-styleguide.netlify.comDeploy Logs

📬Published Alpha Packages:@codecademy/brand-components@0.8.2-alpha.41d0c0.0+41d0c075@codecademy/gamut-templates@2.5.2-alpha.41d0c0.0+41d0c075<EMAIL_ADDRESS>
🚀 Styleguide deploy preview ready!https://5e834590b5d98e01b088d029--codecademy-styleguide.netlify.comDeploy Logs


[WIP] android ndk r19 and gradle update

NDK r19 toolchain injection mods
update gradle to 5.1
gradle: use logical facefilter target syntax for new gradle
add missing comma in gradle cmake 'arguments'

I'm going to close this for now, as the correct path forward seems to depend on upstream cmake and android-ndk decisions:
https://gitlab.kitware.com/cmake/cmake/issues/18787#note_520775
We can add a note to the README stating NDK r19 isn't supported for now, as users can specify their own ndk.dir (<= r18x) in their local.properties file.


I am looking for a different kind of Pie Chart.

I have been searching your charts library but couldn't find a customized chart like the one I am looking for, attaching the issue with example so you can explore it. Can you improvise your package and include such charts?  Else I can work on this and produce a Pull Request.
https://github.com/hashirshoaeb/star_book/issues/214#issue-825889704
Look into the attached issue.

Hi, which part is missing?
I think you can put a circle card above the pie chart (using the Stack widget) to achieve that result.

Thanks @imaNNeoFighT

If you think your issue is resolved, feel free to close this issue.
Thanks!

@imaNNeoFighT Yup it is resolved. Thanks.


Deployment first time blocked by dependencies

When you try to deploy the framework the first time you might get an issue if you dont deploy all classes in the same deploy command.
Because the TestFactory.cls indexes the maker methods, if they don't already exist (which they wont yet) you will get a deployment conflict when trying to save each class separately.
The solution is to deploy everything as one package, or to comment out the Map in TestFactory the first time you deploy, which delinks the references to the maker methods without breaking any code (until run time, which the references will need to be present):
public static final Map<Entity, c_TestFactoryMaker> makers = new Map<Entity, c_TestFactoryMaker> {

 /*...Map your Entity labels to their maker class here...* /

<references temporarily removed>

 //...Add more here as you go...*/

};

Closed, unless deployments are blocked by this issue.

UPDATE: On the event of receiving 'Dependent class is invalid and needs recompilation: Class c_TestFactory' issues when deploying.
This will happen if ONE or more references indexed in the 'makers' map is not able to compile then the TestFactory wont be able to compile which will mean the deploy will not be able to complete and errors will be listed for all your maker classes, saying that the dependent class is invalid etc.
Solution: Identify the Maker class in the error list and fix the issue or remove it from the index to allow deployment to complete for the other classes.


Cherry pick the database backoff timer to improve the stability when the database connection is list

PR Checklist
PR Structure

[ ] This PR has reasonably narrow scope (if not, break it down into smaller PRs).
[ ] This PR avoids mixing refactoring changes with feature changes (split into two PRs
otherwise).
[ ] This PR's title starts with name of package that is most changed in the PR, ex.
paymentservice.stellar, or all or doc if the changes are broad or impact many
packages.

Thoroughness

[ ] This PR adds tests for the most critical parts of the new functionality or fixes.

What
Cherry pick the commit that implements the database backoff timer to improve the stability when the database connection is list
Why
Improve the stability of the stellar payment observer
Known limitations
N/A

Reference Server Preview is available here:https://anchor-ref-pr796.previews.kube001.services.stellar-ops.com/SEP Server Preview is available here:https://anchor-sep-pr796.previews.kube001.services.stellar-ops.com/

Something went wrong with PR preview build please check


.dropdown-center and .dropup-center in .navbar not working

Prerequisites

[X] I have searched for duplicate or closed issues
[X] I have validated any HTML to avoid common problems
[X] I have read the contributing guidelines

Describe the issue
When a Dropdown with .dropup-center or .dropdown-center is inside .navbar the centering is not working.
Because it checks itself if it's inside .navbar  and will disable popper auto positioning:
see:
https://github.com/twbs/bootstrap/blob/v5.2.0/js/src/dropdown.js#L309
Reduced test cases
https://stackblitz.com/edit/jbtery?file=index.html
What operating system(s) are you seeing the problem on?
Windows, macOS, Android, iOS, Linux
What browser(s) are you seeing the problem on?
Chrome, Safari, Firefox, Microsoft Edge, Opera
What version of Bootstrap are you using?
v5.2.0

Hello @Sysix.
It is a fair observation. Is happening because most of documented dropdown position-classes are handled by javascript (popper).
In case we have a dropdown inside navbar, we do not use the popper engine
It may be closed by #35901

Any workarounds? I'm surprised this was overlooked and apparently complicated enough to still not be resolved. Makes me feel better about trying to figure out the problem for the last hour.

i taught im missing something.
when will there be a fix?

hello, here is a workaround i found for bootstrap 5.2, run this code when the page loads:
  let dropdowns = document.querySelectorAll('.dropdown-toggle')
  for (let i = 0; i < dropdowns.length; i++) {
    let dropdownToggle = dropdowns[i];
    dropdownToggle = new Dropdown(dropdownToggle, {
      popperConfig(defaultBsPopperConfig) {
        return { ...defaultBsPopperConfig };
      }
    });
    dropdownToggle._inNavbar = false;
  }

i am bundling bootstrap with webpack, if you are using bootstrap with a cdn then instead of using new Dropdown you might need to use new bootstrap.Dropdown or similar, not sure


Support FastSurferCNN on Apple M1

I'm trying to run FastSurfer CNN for segmentation on my MacBook Pro with the Apple M1 chip. I was able to build to docker container for CPU using your instructions (example 4) by adding in --platform linux/x86_64, but there seems to be some problem running the program. When I execute the following (note the added platform here as well)
docker run --platform linux/x86_64 -v $SUBJECT_DIR:/data \
           -v $outpath:/output \
           --rm --user 501 fastsurfercnn:cpu \
           --i_dir /data \
           --in_name mri/mprage.mgz \
           --o_dir /output \
           --out_name mri/aparc.DKTatlas+aseg.deep.mgz \
           --log deep_surfer.log \
           --no_cuda

I get the following output
Total Dataset Size is 1
Running Fast Surfer on sub01
Reading volume /data/sub01/mri/mprage.mgz
Conforming image to UCHAR, RAS orientation, and 1mm isotropic voxels
Input:    min: 0  max: 1851
rescale:  min: 0.0  max: 831.099  scale: 0.30682265289694727
Output:   min: 0.0  max: 255.0
Cuda available: False, # Available GPUS: 0, Cuda user disabled (--no_cuda flag): True, --> Using device: cpu

The program creates the correct output folder structure but there is no output files in there. Any clue what might be going wrong?
Environment

FastSurfer Version: Pulled from Github 2022/02/25
FreeSurfer Version: 7.2.0 (know this is higher than recommended but not used for the segmentation right?)
OS: MacOS 12.1
CPU: Apple M1 Pro

Hi Emil,
we do not support the M chips yet. Probably in the future. Maybe it is easy or maybe not. We can keep this issue open, for people to post if they have success getting it running.
And also 7.2 is not only not recommended, it is not supported. Use 6.0 for now. But you are right, for only the segmentation it is not used and should not matter.

Maybe also a memory issue (see issue https://github.com/Deep-MI/FastSurfer/issues/40)? In order to run FastSurfer you need around 10 GB RAM, but Docker Desktop on MAC is set to use 2 GB runtime memory by default. You can overwrite the settings under Docker Desktop --> Preferences --> Resources --> Advanced, slide the bar under Memory to 10 GB; see: https://docs.docker.com/docker-for-mac/ for details.
Kind regards,
Leonie

It seems to work with increasing the RAM, set it to 20 GB to try. It runs now and seems to use about 7.2 GB. Let's see how long it takes to finish.

Update: I actually managed to run FastSurferCNN natively on my Mac without using docker. There was a massive speed up from not using Docker. Results looks good! Thanks!

Thanks for the update. Can you let readers know how you did it? Anything special you had to do or did it run out of the box? Thanks

It worked straight out of the box actually. Just installed the pre-reqs as instructed and it worked!

CNN Segmentation on CPU only:
I got a docker with aarch64 running on Apple M1 by pointing the docker file to the correct miniconda:
ARG CONDA_FILE=Miniconda3-py38_4.11.0-Linux-aarch64.sh
I also had to modify some dependencies versions in the fastsurfer_env_cpu.yml and drop the pip stuff (which is needed for recon_surf and not for the CNN). Increasing Docker memory to 15GB I was able to segment an image in below 30 mins (using the dev version).
In order to get recon_surf running we would need to install the pip dependencies also and compile FreeSurfer for ARM, for that see: https://github.com/freesurfer/freesurfer/issues/964

I now managed a native install on a MacBook Pro M1-max mainly using  pip3, changed a few version numbers slightly in requirements.txt and had to use brew to install a newer bash. I also solved issues with installing h5py by:
brew install hdf5
export HDF5_DIR="$(brew --prefix hdf5)"
pip3 install --no-binary=h5py h5py

Run time for one full segmentation on CPU (multi threads) with current dev branch is only 5 mins and 25 seconds now, not bad. This is all three views and view aggregation. So don't use docker on ARM.

And I got this running on the GPU with MPS support in PyTorch nightly (will create a branch for this at some point). Currently aten::max_unpool2d is missing (reverting to CPU). I put in a request for accelerated implementation here:
https://github.com/pytorch/pytorch/issues/77764#issuecomment-1215920185
Please consider upvoting that there.
Run time down to 2:30 mins now. On a MacBook.

I traced the MPS issues (code producing -inf values) a little further. The first big difference between the CPU and the MPS code occurs in nn.BatchNorm2d. See my Issue here:
https://github.com/pytorch/pytorch/issues/84962

The BatchNorm2 ddifferences are solved in MacOS Ventura. Another issue https://github.com/pytorch/pytorch/issues/85230 is that loading the weights directly to mps device fails. There is a workaround to move the model to cpu, load checkpoint and then move the model back to mps. And ...
Tadaaa :-) mps works! It takes 2 min 40 seconds for all three networks (VINN) on MPS and view aggregation on cpu. Nice. I will put in a pull request soon, so that this can go into the next release 2.0. And don't forget to up-vote support for max_unpool2d here: https://github.com/pytorch/pytorch/issues/77764#issuecomment-1215920185 . should get even faster once that is native on MPS.

Has been solved with #191


Spelling

This PR corrects misspellings identified by the check-spelling action.
The misspellings have been reported at https://github.com/jsoref/miri/actions/runs/4699927237#summary-12751183650
The action reports that the changes in this PR would make it happy: https://github.com/jsoref/miri/actions/runs/4699927572#summary-12751184493

Thanks, the changes look good! However we don't need 52 commits of this, could you squash this into one?

Sure, as long as you're happy with the changes. I might have time (and a laptop) this afternoon.

I have also reviewed all the changes and I like them. I've been meaning to fix these at some point, just always had other things to worry about first.

I should have asked if you had a preference for the commit message. This is my default, I'm not attached to it or anything else.

Seems fine. Thanks!
@bors r+

:pushpin: Commit 282840b33761990b30b9edaec16f2d9735f323b6 has been approved by RalfJung
It is now in the queue for this repository.

:hourglass: Testing commit 282840b33761990b30b9edaec16f2d9735f323b6 with merge bf51be1095fc60961ad24cbfebba2f81ba94b58f...

:sunny: Test successful - checks-actions
Approved by: RalfJung
Pushing bf51be1095fc60961ad24cbfebba2f81ba94b58f to master...


Fix default parameters parsing and typo in logs when no links found

Changed the old way parameters were parsed as this was not taking the default "ril_export.html" file when none were precised, nor the "pocket" option

Thanks!


Token type collision

I've tried printing the token stream for the following template:
{% if hello and
    world %}
{% endif %}

This was the result:
PHP Fatal error:  Method Twig\Token::__toString() must not throw an exception, caught LogicException: Token of type "13" does not exist.

Additionally, if I try to do the same for the following template:
{% if hello %}
{% endif %}

This is the result:
BLOCK_START_TYPE()
ARROW_TYPE( )
NAME_TYPE(if)
ARROW_TYPE( )
NAME_TYPE(hello)
ARROW_TYPE( )
BLOCK_END_TYPE()
BLOCK_START_TYPE()
ARROW_TYPE( )
NAME_TYPE(endif)
ARROW_TYPE( )
BLOCK_END_TYPE()

The ARROW_TYPE seemed odd to me, so after digging a bit it looks to me as the issue lies in the constants used by TwigCS which have conflicts with Twig.
More precisely, here is defined a constant which should represent whitespace, but eventually Twig caught up with the numbering.
So these two seem to be kinda connected.
As a reference, I was toying around with v3.2.2.

Just gonna add some more info related to this.
Template as a reference point:
{% set foobar = foo|map(bar => baz) %}

Tried using the Official ruleset on this (more precisely - used , the following was the result:

l.1 c.29 : ERROR There should be 1 space(s) before ">".

When I printed out tokens, the following was the result:
BLOCK_START_TYPE()
ARROW_TYPE( )
NAME_TYPE(set)
ARROW_TYPE( )
NAME_TYPE(foobar)
ARROW_TYPE( )
OPERATOR_TYPE(=)
ARROW_TYPE( )
NAME_TYPE(foo)
PUNCTUATION_TYPE(|)
NAME_TYPE(map)
PUNCTUATION_TYPE(()
NAME_TYPE(bar)
ARROW_TYPE( )
OPERATOR_TYPE(=)
OPERATOR_TYPE(>)
ARROW_TYPE( )
NAME_TYPE(baz)
PUNCTUATION_TYPE())
ARROW_TYPE( )
BLOCK_END_TYPE()

I've also found out about #69 but I'm not sure whether that means versions older than 4 would not be getting the arrow token support?

The easiest way to fix this would be to change the numbers of the custom tokens Twigcs introduces but it feels like it's just a workaround. This problem lies inside a greater problem I'm trying to figure out how to solve: keeping up with twig versions in a consistent way.
Nowadays I'm tempted to go with some opinionated choices:

Stripping the Lexer from the official library, we copy it inside Twigcs and maintain it separately with our needed code (custom tokens, newlines handling): no more collisions, no more twig dependency inside composer, we gain full control on that.
Killing twigcs 3.x as fast as possible (so many unfixable things like arrow functions)
Adding Twig 1, 2 and 3 support inside twigcs 4.x before it is out of beta (using 3 rulesets ?)

I've submitted a PR that will fix this issue here : #114.

I'm closing this as the PR got merged!


Workflow re: securing the recovered files

Currently recovered files are written to a subdirectory below the R session temp dir.
I personally managed to lose them again by restarting R. Luckily you can just run recover() again. But I imagine that won't work once you've, for example, started to create new Untitled's?
Does it make sense to offer to write to a less perishable place? I think you can pretty much count on being in an interactive session with a highly motivated user, who will be happy to select from a couple choices (e.g. subdir of temp dir vs. project dir).

It does. I have updated this so that it writes to the project folder itself, in a recovered_XXX folder.


FR: import all dashboards command

Add command:
$ wizzy import dashboards
to import all dashboards under dashboards directory.

merged....


_destroy_helper_block_e8_32s40s + 24 (AFHTTPSessionManager.m:0)

I often get a crash report about this
objc_release + 16
__destroy_helper_block_e8_32s40s + 24 (AFHTTPSessionManager.m:0)
How to solve it would like to give some advice.
0   libobjc.A.dylib               	0x000000019a265de0 objc_release + 16 (objc-object.h:756)
1   CoreFoundation                	0x0000000185f206b8 cow_cleanup + 168 (NSCollectionAux.h:48)
2   CoreFoundation                	0x0000000185dad5f8 -[__NSDictionaryM dealloc] + 144 (NSDictionaryM.m:439)
3   AFNetworking                  	0x00000001057ba0f4 __destroy_helper_block_e8_32s40s + 24 (AFHTTPSessionManager.m:0)
4   libsystem_blocks.dylib        	0x00000001ce671784 _Block_release + 188 (runtime.cpp:176)
5   libdispatch.dylib             	0x0000000185afb280 _dispatch_client_callout + 16 (object.m:559)
6   libdispatch.dylib             	0x0000000185add5b0 _dispatch_main_queue_callback_4CF$VARIANT$armv81 + 856 (inline_internal.h:2548)

did you solve this problem?


Update the documentation of configure_optimizers()

Explain the default value for scheduler

Before submitting

[x] Was this discussed/approved via a Github issue? (no need for typos and docs improvements)
[x] Did you read the contributor guideline, Pull Request section?
[x] Did you make sure to update the docs?
[x] Did you write any new necessary tests? (N/A)
[x] If you made a notable change (that affects users), did you update the CHANGELOG? (N/A)

What does this PR do?
Update the documentation as described in #2056 .
PR review
Anyone in the community is free to review the PR once the tests have passed.
If we didn't discuss your PR in Github issues there's a high chance it will not be merged.
Did you have fun?
Absolutely.

Hello @DKandrew! Thanks for opening this PR.

In the file pytorch_lightning/core/lightning.py:

Line 1012:111: E501 line too long (114 > 110 characters)
Line 1013:111: E501 line too long (137 > 110 characters)

Do see the Hitchhiker's guide to code style


Hotfix hover

Needs a fix actually, navigates to what was first selected

Look into touchend registering when trying to scroll

@jakedcolbert I can't remember what this was supposed to fix (no description provided).  Can you remember or close?

@chrisvire fixes #284


Expose method shorthands for Request constructor

In Surf creating new requests and responses is really straightforward. It'd be nice if we were able to expose shorthands from http-types as well.
// current
let req = Request::new(Method::Get, Url::parse("https://foo.biz").unwrap());

// with this proposal
let req = Request::get(Url::parse("https://foo.biz").unwrap());

// once the TryFrom patch on the url crate is published
let req = Request::get("https://foo.biz");

The downside is that this will add more methods to the Request type. But we already have many methods, and these feel fairly natural as constructors. I would propose we add them.
Marking as "good first issue" because this should be fairly straightforward. The bounds should be copied from the Request::new method, forwarding to Request::new internally. Thanks!

Hello,
thank you for opening and labelling good-first-issues; I would be glad to propose a very simple approach to your suggestion and extend the test suite with examples as well .


Root-Offences: Slight inaccuracy in docs

The root doesn't have to be the sudo.

Closed in favor of #12451


it doesn't converge

at first I removed findMaxUpdateNorm. After a 5 iterations, it goes into inf. energy. Shouldn't the energy be decreasing? And then it crashes at the next data term estimation.

Or if I run the code with findMaxNorm enable, it will crash at 3rd iteration at findMaxNorm
**

**

what data are you running it on? how come regularisation energy isn't 0 at the first iteration of the solver?

I tried disabling the reg-term but it's still not good. Cuda error is at "findMaxUpdatesNorm"

you didn’t answer either of my questions
the cost decreases from iteration 1 to 2, so the solver is working correctly. my guess is that you set the gradient descent step size too high

I'm not so sure why reg term does not start at 0.  2. I'm using my own depth data but it's similar to the umbrella in the dataset you provided.

iter. no. 1
data energy + w_reg * reg energy = 12355 + 0.2 * 3.14573e+06 = 641501
max. update norm 3.13565 at voxel (112, 87, 33)
iter. no. 2
data energy + w_reg * reg energy = 2846.8 + 0.2 * 2.93951e+06 = 590749
max. update norm 10.5572 at voxel (83, 11, 68)
iter. no. 3
data energy + w_reg * reg energy = 10325.1 + 0.2 * 2.8413e+06 = 578586
max. update norm 27.3268 at voxel (112, 87, 33)
iter. no. 4
data energy + w_reg * reg energy = 17751.4 + 0.2 * 4.45358e+06 = 908468
max. update norm 91.7509 at voxel (119, 44, 47)
iter. no. 5
data energy + w_reg * reg energy = 33923.5 + 0.2 * 3.43105e+07 = 6.89602e+06
max. update norm 323.303 at voxel (119, 44, 47)
iter. no. 6
data energy + w_reg * reg energy = 57503.8 + 0.2 * 5.32352e+08 = 1.06528e+08
max. update norm 1173.61 at voxel (119, 44, 47)
iter. no. 7
data energy + w_reg * reg energy = 83736.2 + 0.2 * 9.09062e+09 = 1.81821e+09
max. update norm 4440.86 at voxel (105, 52, 13)
iter. no. 8
data energy + w_reg * reg energy = 108864 + 0.2 * 1.54833e+11 = 3.09666e+10
max. update norm 17723.9 at voxel (105, 52, 13)
iter. no. 9
data energy + w_reg * reg energy = 133528 + 0.2 * 2.74806e+12 = 5.49612e+11
max. update norm 71077.2 at voxel (105, 52, 13)
iter. no. 10
data energy + w_reg * reg energy = 154007 + 0.2 * 4.28178e+13 = 8.56356e+12
max. update norm 286391 at voxel (105, 52, 13)
iter. no. 11
data energy + w_reg * reg energy = 173631 + 0.2 * 6.83484e+14 = 1.36697e+14
max. update norm 1.1595e+06 at voxel (105, 52, 13)
iter. no. 12
data energy + w_reg * reg energy = 194519 + 0.2 * 1.00227e+16 = 2.00454e+15
max. update norm 4.71705e+06 at voxel (105, 52, 13)
iter. no. 13
data energy + w_reg * reg energy = 211990 + 0.2 * 1.55085e+17 = 3.1017e+16
max. update norm 1.92819e+07 at voxel (105, 52, 13)
iter. no. 14
data energy + w_reg * reg energy = 230502 + 0.2 * 3.06763e+18 = 6.13525e+17
max. update norm 7.91902e+07 at voxel (105, 52, 13)
iter. no. 15
data energy + w_reg * reg energy = 247412 + 0.2 * 4.6454e+19 = 9.29081e+18
max. update norm 3.2673e+08 at voxel (105, 52, 13)
iter. no. 16
data energy + w_reg * reg energy = 261627 + 0.2 * 7.67631e+20 = 1.53526e+20
max. update norm 1.35406e+09 at voxel (105, 52, 13)
iter. no. 17
data energy + w_reg * reg energy = 275253 + 0.2 * 1.20509e+22 = 2.41019e+21
max. update norm 5.664e+09 at voxel (106, 73, 22)
iter. no. 18
data energy + w_reg * reg energy = 287839 + 0.2 * 2.18832e+23 = 4.37665e+22
max. update norm 2.42147e+10 at voxel (105, 73, 22)
iter. no. 19
data energy + w_reg * reg energy = 298999 + 0.2 * 3.02187e+24 = 6.04373e+23
max. update norm 1.04449e+11 at voxel (105, 73, 22)
iter. no. 20
data energy + w_reg * reg energy = 308830 + 0.2 * 4.65163e+25 = 9.30325e+24
max. update norm 4.51059e+11 at voxel (105, 73, 22)
iter. no. 21
data energy + w_reg * reg energy = 317291 + 0.2 * 7.84344e+26 = 1.56869e+26
max. update norm 1.95012e+12 at voxel (105, 73, 22)
iter. no. 22
data energy + w_reg * reg energy = 324390 + 0.2 * 1.29555e+28 = 2.59109e+27
max. update norm 8.44058e+12 at voxel (105, 73, 22)
iter. no. 23
data energy + w_reg * reg energy = 331482 + 0.2 * 2.53677e+29 = 5.07354e+28
max. update norm 3.65725e+13 at voxel (105, 73, 22)
iter. no. 24
data energy + w_reg * reg energy = 336983 + 0.2 * 4.86435e+30 = 9.7287e+29
max. update norm 1.58633e+14 at voxel (105, 73, 22)
iter. no. 25
data energy + w_reg * reg energy = 342614 + 0.2 * 7.78954e+31 = 1.55791e+31
max. update norm 6.88772e+14 at voxel (105, 73, 22)
iter. no. 26
data energy + w_reg * reg energy = 347383 + 0.2 * 1.31987e+33 = 2.63973e+32
max. update norm 2.99354e+15 at voxel (105, 73, 22)
iter. no. 27
data energy + w_reg * reg energy = 352114 + 0.2 * 2.75272e+34 = 5.50543e+33
max. update norm 1.30228e+16 at voxel (105, 73, 22)
iter. no. 28
data energy + w_reg * reg energy = 356551 + 0.2 * 4.67512e+35 = 9.35024e+34
max. update norm 5.67053e+16 at voxel (105, 73, 22)
iter. no. 29
data energy + w_reg * reg energy = 360826 + 0.2 * 8.78008e+36 = 1.75602e+36
max. update norm 2.47129e+17 at voxel (105, 73, 22)
iter. no. 30
data energy + w_reg * reg energy = 364962 + 0.2 * 1.55501e+38 = 3.11002e+37
max. update norm 1.07794e+18 at voxel (105, 73, 22)
iter. no. 31
data energy + w_reg * reg energy = 368937 + 0.2 * inf = inf
max. update norm 4.70561e+18 at voxel (105, 73, 22)
iter. no. 32
data energy + w_reg * reg energy = 372318 + 0.2 * inf = inf
max. update norm inf at voxel (114, 56, 72)
iter. no. 33
data energy + w_reg * reg energy = 375664 + 0.2 * inf = inf
max. update norm inf at voxel (112, 2, 94)
iter. no. 34
data energy + w_reg * reg energy = 378907 + 0.2 * inf = inf
max. update norm inf at voxel (42, 1, 79)
iter. no. 35
data energy + w_reg * reg energy = 382125 + 0.2 * inf = inf
max. update norm inf at voxel (112, 0, 94)
iter. no. 36
data energy + w_reg * reg energy = 384678 + 0.2 * inf = inf
max. update norm inf at voxel (40, 0, 79)
iter. no. 37
data energy + w_reg * reg energy = 387447 + 0.2 * inf = inf
max. update norm inf at voxel (40, 0, 71)
iter. no. 38
data energy + w_reg * reg energy = 390090 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 71)
iter. no. 39
data energy + w_reg * reg energy = 392660 + 0.2 * inf = inf
max. update norm inf at voxel (64, 0, 62)
iter. no. 40
data energy + w_reg * reg energy = 394503 + 0.2 * inf = inf
max. update norm inf at voxel (64, 0, 60)
iter. no. 41
data energy + w_reg * reg energy = 396286 + 0.2 * inf = inf
max. update norm inf at voxel (52, 0, 54)
iter. no. 42
data energy + w_reg * reg energy = 398015 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 54)
iter. no. 43
data energy + w_reg * reg energy = 399843 + 0.2 * inf = inf
max. update norm inf at voxel (64, 0, 55)
iter. no. 44
data energy + w_reg * reg energy = 401061 + 0.2 * inf = inf
max. update norm inf at voxel (64, 0, 54)
iter. no. 45
data energy + w_reg * reg energy = 402347 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 47)
iter. no. 46
data energy + w_reg * reg energy = 403479 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 46)
iter. no. 47
data energy + w_reg * reg energy = 404906 + 0.2 * inf = inf
max. update norm inf at voxel (64, 0, 46)
iter. no. 48
data energy + w_reg * reg energy = 405697 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 39)
iter. no. 49
data energy + w_reg * reg energy = 406501 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 38)
iter. no. 50
data energy + w_reg * reg energy = 407438 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 36)
iter. no. 51
data energy + w_reg * reg energy = 408518 + 0.2 * inf = inf
max. update norm inf at voxel (56, 0, 31)
iter. no. 52
data energy + w_reg * reg energy = 409035 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 31)
iter. no. 53
data energy + w_reg * reg energy = 409687 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 28)
iter. no. 54
data energy + w_reg * reg energy = 410371 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 28)
iter. no. 55
data energy + w_reg * reg energy = 411106 + 0.2 * inf = inf
max. update norm inf at voxel (64, 0, 31)
iter. no. 56
data energy + w_reg * reg energy = 411418 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 22)
iter. no. 57
data energy + w_reg * reg energy = 412115 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 20)
iter. no. 58
data energy + w_reg * reg energy = 412765 + 0.2 * inf = inf
max. update norm inf at voxel (56, 0, 15)
iter. no. 59
data energy + w_reg * reg energy = 413206 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 15)
iter. no. 60
data energy + w_reg * reg energy = 413333 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 14)
iter. no. 61
data energy + w_reg * reg energy = 413853 + 0.2 * inf = inf
max. update norm inf at voxel (48, 0, 12)
iter. no. 62
data energy + w_reg * reg energy = 414369 + 0.2 * inf = inf
max. update norm inf at voxel (64, 0, 13)
iter. no. 63
data energy + w_reg * reg energy = 415245 + 0.2 * nan = nan
max. update norm inf at voxel (52, 0, 6)
iter. no. 64
data energy + w_reg * reg energy = 431115 + 0.2 * nan = nan
max. update norm inf at voxel (48, 0, 7)
iter. no. 65
data energy + w_reg * reg energy = 440933 + 0.2 * nan = nan
max. update norm inf at voxel (48, 0, 6)
iter. no. 66
data energy + w_reg * reg energy = 441940 + 0.2 * nan = nan
max. update norm inf at voxel (96, 0, 6)
iter. no. 67
data energy + w_reg * reg energy = 436376 + 0.2 * nan = nan
max. update norm inf at voxel (64, 0, 6)
iter. no. 68
data energy + w_reg * reg energy = 426454 + 0.2 * nan = nan
max. update norm inf at voxel (64, 0, 4)
iter. no. 69
data energy + w_reg * reg energy = 416319 + 0.2 * nan = nan
max. update norm inf at voxel (64, 0, 4)
iter. no. 70
data energy + w_reg * reg energy = 405488 + 0.2 * nan = nan
max. update norm inf at voxel (64, 0, 0)
iter. no. 71
data energy + w_reg * reg energy = 395403 + 0.2 * nan = nan
max. update norm inf at voxel (64, 0, 0)
iter. no. 72
data energy + w_reg * reg energy = 387692 + 0.2 * nan = nan
max. update norm inf at voxel (64, 0, 0)
iter. no. 73
data energy + w_reg * reg energy = 382318 + 0.2 * nan = nan
max. update norm inf at voxel (64, 0, 0)
iter. no. 74
data energy + w_reg * reg energy = 378076 + 0.2 * nan = nan
max. update norm inf at voxel (32, 0, 3)
iter. no. 75
data energy + w_reg * reg energy = 374349 + 0.2 * nan = nan
max. update norm inf at voxel (16, 0, 1)
iter. no. 76
data energy + w_reg * reg energy = 371157 + 0.2 * nan = nan
max. update norm inf at voxel (25, 0, 0)
iter. no. 77
data energy + w_reg * reg energy = 368693 + 0.2 * nan = nan
max. update norm inf at voxel (64, 85, 127)
iter. no. 78
data energy + w_reg * reg energy = 366832 + 0.2 * nan = nan
max. update norm inf at voxel (64, 89, 127)
iter. no. 79
data energy + w_reg * reg energy = 365523 + 0.2 * nan = nan
max. update norm inf at voxel (64, 93, 127)
iter. no. 80
data energy + w_reg * reg energy = 364832 + 0.2 * nan = nan
max. update norm inf at voxel (64, 97, 127)
iter. no. 81
data energy + w_reg * reg energy = 364427 + 0.2 * nan = nan
max. update norm inf at voxel (64, 101, 127)
iter. no. 82
data energy + w_reg * reg energy = 364236 + 0.2 * nan = nan
max. update norm inf at voxel (64, 105, 127)
iter. no. 83
data energy + w_reg * reg energy = 364127 + 0.2 * nan = nan
max. update norm inf at voxel (64, 109, 127)
iter. no. 84
data energy + w_reg * reg energy = 364078 + 0.2 * nan = nan
max. update norm inf at voxel (64, 113, 127)
iter. no. 85
data energy + w_reg * reg energy = 364053 + 0.2 * nan = nan
max. update norm inf at voxel (64, 117, 127)
iter. no. 86
data energy + w_reg * reg energy = 364033 + 0.2 * nan = nan
max. update norm inf at voxel (64, 121, 127)
iter. no. 87
data energy + w_reg * reg energy = 364015 + 0.2 * nan = nan
max. update norm inf at voxel (64, 125, 127)
iter. no. 88
data energy + w_reg * reg energy = 364005 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 88 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 363982 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 363958 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)

iter. no. 1
data energy + w_reg * reg energy = 10222.9 + 0.2 * 0 = 10222.9
max. update norm 3.35202 at voxel (87, 44, 45)
iter. no. 2
data energy + w_reg * reg energy = 2447.48 + 0.2 * 375334 = 77514.3
max. update norm 10.1361 at voxel (87, 44, 45)
iter. no. 3
data energy + w_reg * reg energy = 9299.74 + 0.2 * 531798 = 115659
max. update norm 27.9019 at voxel (80, 40, 49)
iter. no. 4
data energy + w_reg * reg energy = 15562.2 + 0.2 * 1.94987e+06 = 405536
max. update norm 85.4234 at voxel (19, 16, 95)
iter. no. 5
data energy + w_reg * reg energy = 29695.3 + 0.2 * 2.46834e+07 = 4.96638e+06
max. update norm 307.358 at voxel (120, 26, 38)
iter. no. 6
data energy + w_reg * reg energy = 48237.6 + 0.2 * 3.67564e+08 = 7.3561e+07
max. update norm 1173.8 at voxel (120, 26, 38)
iter. no. 7
data energy + w_reg * reg energy = 68222.3 + 0.2 * 5.51173e+09 = 1.10241e+09
max. update norm 4538.48 at voxel (120, 26, 38)
iter. no. 8
data energy + w_reg * reg energy = 86719 + 0.2 * 8.21909e+10 = 1.64383e+10
max. update norm 17747.3 at voxel (120, 26, 38)
iter. no. 9
data energy + w_reg * reg energy = 103749 + 0.2 * 1.10435e+12 = 2.20871e+11
max. update norm 70107.1 at voxel (120, 26, 38)
iter. no. 10
data energy + w_reg * reg energy = 117855 + 0.2 * 1.95521e+13 = 3.91042e+12
max. update norm 279432 at voxel (120, 26, 38)
iter. no. 11
data energy + w_reg * reg energy = 131514 + 0.2 * 2.88998e+14 = 5.77997e+13
max. update norm 1.1225e+06 at voxel (120, 26, 38)
iter. no. 12
data energy + w_reg * reg energy = 145413 + 0.2 * 4.04371e+15 = 8.08743e+14
max. update norm 4.55397e+06 at voxel (123, 24, 44)
iter. no. 13
data energy + w_reg * reg energy = 157055 + 0.2 * 6.35808e+16 = 1.27162e+16
max. update norm 1.88948e+07 at voxel (107, 35, 11)
iter. no. 14
data energy + w_reg * reg energy = 168362 + 0.2 * 1.07992e+18 = 2.15984e+17
max. update norm 7.9032e+07 at voxel (107, 35, 11)
iter. no. 15
data energy + w_reg * reg energy = 179012 + 0.2 * 2.13169e+19 = 4.26338e+18
max. update norm 3.31857e+08 at voxel (107, 35, 11)
iter. no. 16
data energy + w_reg * reg energy = 188100 + 0.2 * 3.47635e+20 = 6.95271e+19
max. update norm 1.39818e+09 at voxel (107, 35, 11)
iter. no. 17
data energy + w_reg * reg energy = 196720 + 0.2 * 6.10953e+21 = 1.22191e+21
max. update norm 5.90835e+09 at voxel (107, 35, 11)
iter. no. 18
data energy + w_reg * reg energy = 204445 + 0.2 * 2.84179e+23 = 5.68358e+22
max. update norm 2.50334e+10 at voxel (107, 35, 11)
iter. no. 19
data energy + w_reg * reg energy = 211427 + 0.2 * 1.96771e+24 = 3.93542e+23
max. update norm 1.06318e+11 at voxel (107, 35, 11)
iter. no. 20
data energy + w_reg * reg energy = 218175 + 0.2 * 4.13511e+25 = 8.27023e+24
max. update norm 4.52517e+11 at voxel (107, 35, 11)
iter. no. 21
data energy + w_reg * reg energy = 224183 + 0.2 * 6.44772e+26 = 1.28954e+26
max. update norm 1.94179e+12 at voxel (121, 23, 42)
iter. no. 22
data energy + w_reg * reg energy = 228862 + 0.2 * 9.50533e+27 = 1.90107e+27
max. update norm 8.39297e+12 at voxel (121, 23, 42)
iter. no. 23
data energy + w_reg * reg energy = 233676 + 0.2 * 1.89768e+29 = 3.79535e+28
max. update norm 3.63258e+13 at voxel (121, 23, 42)
iter. no. 24
data energy + w_reg * reg energy = 238023 + 0.2 * 7.2216e+30 = 1.44432e+30
max. update norm 1.57417e+14 at voxel (121, 23, 42)
iter. no. 25
data energy + w_reg * reg energy = 242335 + 0.2 * 1.03496e+32 = 2.06992e+31
max. update norm 6.82931e+14 at voxel (121, 23, 42)
iter. no. 26
data energy + w_reg * reg energy = 245876 + 0.2 * 9.88842e+32 = 1.97768e+32
max. update norm 2.9659e+15 at voxel (121, 23, 42)
iter. no. 27
data energy + w_reg * reg energy = 249858 + 0.2 * 1.90974e+34 = 3.81948e+33
max. update norm 1.2893e+16 at voxel (121, 23, 42)
iter. no. 28
data energy + w_reg * reg energy = 253136 + 0.2 * 3.92671e+35 = 7.85341e+34
max. update norm 5.60976e+16 at voxel (121, 23, 42)
iter. no. 29
data energy + w_reg * reg energy = 256465 + 0.2 * 6.12704e+36 = 1.22541e+36
max. update norm 2.44578e+17 at voxel (23, 62, 45)
iter. no. 30
data energy + w_reg * reg energy = 259880 + 0.2 * 1.1242e+38 = 2.2484e+37
max. update norm 1.07354e+18 at voxel (23, 62, 45)
iter. no. 31
data energy + w_reg * reg energy = 263908 + 0.2 * inf = inf
max. update norm 4.7153e+18 at voxel (23, 62, 45)
iter. no. 32
data energy + w_reg * reg energy = 266927 + 0.2 * inf = inf
max. update norm inf at voxel (121, 22, 42)
iter. no. 33
data energy + w_reg * reg energy = 269795 + 0.2 * inf = inf
max. update norm inf at voxel (123, 2, 79)
iter. no. 34
data energy + w_reg * reg energy = 272617 + 0.2 * inf = inf
max. update norm inf at voxel (88, 1, 76)
iter. no. 35
data energy + w_reg * reg energy = 275895 + 0.2 * inf = inf
max. update norm inf at voxel (90, 0, 99)
iter. no. 36
data energy + w_reg * reg energy = 278522 + 0.2 * inf = inf
max. update norm inf at voxel (88, 0, 72)
iter. no. 37
data energy + w_reg * reg energy = 280951 + 0.2 * inf = inf
max. update norm inf at voxel (24, 0, 71)
iter. no. 38
data energy + w_reg * reg energy = 283373 + 0.2 * inf = inf
max. update norm inf at voxel (24, 0, 70)
iter. no. 39
data energy + w_reg * reg energy = 286047 + 0.2 * inf = inf
max. update norm inf at voxel (88, 0, 62)
iter. no. 40
data energy + w_reg * reg energy = 287986 + 0.2 * inf = inf
max. update norm inf at voxel (88, 0, 60)
iter. no. 41
data energy + w_reg * reg energy = 290457 + 0.2 * inf = inf
max. update norm inf at voxel (84, 0, 55)
iter. no. 42
data energy + w_reg * reg energy = 292240 + 0.2 * inf = inf
max. update norm inf at voxel (112, 0, 54)
iter. no. 43
data energy + w_reg * reg energy = 294355 + 0.2 * inf = inf
max. update norm inf at voxel (80, 0, 54)
iter. no. 44
data energy + w_reg * reg energy = 296044 + 0.2 * inf = inf
max. update norm inf at voxel (84, 0, 47)
iter. no. 45
data energy + w_reg * reg energy = 297869 + 0.2 * inf = inf
max. update norm inf at voxel (32, 0, 47)
iter. no. 46
data energy + w_reg * reg energy = 299458 + 0.2 * inf = inf
max. update norm inf at voxel (32, 0, 46)
iter. no. 47
data energy + w_reg * reg energy = 301252 + 0.2 * inf = inf
max. update norm inf at voxel (120, 0, 39)
iter. no. 48
data energy + w_reg * reg energy = 302694 + 0.2 * inf = inf
max. update norm inf at voxel (80, 0, 38)
iter. no. 49
data energy + w_reg * reg energy = 304377 + 0.2 * inf = inf
max. update norm inf at voxel (80, 0, 36)
iter. no. 50
data energy + w_reg * reg energy = 305687 + 0.2 * inf = inf
max. update norm inf at voxel (120, 0, 31)
iter. no. 51
data energy + w_reg * reg energy = 307222 + 0.2 * inf = inf
max. update norm inf at voxel (80, 0, 31)
iter. no. 52
data energy + w_reg * reg energy = 308840 + 0.2 * inf = inf
max. update norm inf at voxel (80, 0, 30)
iter. no. 53
data energy + w_reg * reg energy = 310143 + 0.2 * inf = inf
max. update norm inf at voxel (64, 0, 28)
iter. no. 54
data energy + w_reg * reg energy = 311437 + 0.2 * inf = inf
max. update norm inf at voxel (0, 0, 30)
iter. no. 55
data energy + w_reg * reg energy = 312847 + 0.2 * inf = inf
max. update norm inf at voxel (112, 0, 23)
iter. no. 56
data energy + w_reg * reg energy = 314566 + 0.2 * inf = inf
max. update norm inf at voxel (64, 0, 22)
iter. no. 57
data energy + w_reg * reg energy = 315822 + 0.2 * inf = inf
max. update norm inf at voxel (64, 0, 20)
iter. no. 58
data energy + w_reg * reg energy = 316791 + 0.2 * inf = inf
max. update norm inf at voxel (80, 0, 15)
iter. no. 59
data energy + w_reg * reg energy = 318088 + 0.2 * inf = inf
max. update norm inf at voxel (96, 0, 14)
iter. no. 60
data energy + w_reg * reg energy = 319471 + 0.2 * inf = inf
max. update norm inf at voxel (64, 0, 14)
iter. no. 61
data energy + w_reg * reg energy = 320833 + 0.2 * inf = inf
max. update norm inf at voxel (108, 0, 7)
iter. no. 62
data energy + w_reg * reg energy = 321640 + 0.2 * inf = inf
max. update norm inf at voxel (96, 0, 7)
iter. no. 63
data energy + w_reg * reg energy = 322734 + 0.2 * nan = nan
max. update norm inf at voxel (96, 0, 4)
iter. no. 64
data energy + w_reg * reg energy = 332497 + 0.2 * nan = nan
max. update norm inf at voxel (96, 0, 4)
iter. no. 65
data energy + w_reg * reg energy = 333903 + 0.2 * nan = nan
max. update norm inf at voxel (96, 0, 4)
iter. no. 66
data energy + w_reg * reg energy = 328076 + 0.2 * nan = nan
max. update norm inf at voxel (64, 0, 7)
iter. no. 67
data energy + w_reg * reg energy = 318285 + 0.2 * nan = nan
max. update norm inf at voxel (64, 0, 4)
iter. no. 68
data energy + w_reg * reg energy = 306239 + 0.2 * nan = nan
max. update norm inf at voxel (64, 0, 4)
iter. no. 69
data energy + w_reg * reg energy = 293887 + 0.2 * nan = nan
max. update norm inf at voxel (64, 0, 4)
iter. no. 70
data energy + w_reg * reg energy = 282426 + 0.2 * nan = nan
max. update norm inf at voxel (0, 0, 7)
iter. no. 71
data energy + w_reg * reg energy = 272761 + 0.2 * nan = nan
max. update norm inf at voxel (0, 0, 6)
iter. no. 72
data energy + w_reg * reg energy = 265252 + 0.2 * nan = nan
max. update norm inf at voxel (0, 0, 4)
iter. no. 73
data energy + w_reg * reg energy = 259166 + 0.2 * nan = nan
max. update norm inf at voxel (0, 0, 4)
iter. no. 74
data energy + w_reg * reg energy = 253958 + 0.2 * nan = nan
max. update norm inf at voxel (0, 0, 4)
iter. no. 75
data energy + w_reg * reg energy = 249339 + 0.2 * nan = nan
max. update norm inf at voxel (124, 0, 0)
iter. no. 76
data energy + w_reg * reg energy = 244889 + 0.2 * nan = nan
max. update norm inf at voxel (61, 55, 127)
iter. no. 77
data energy + w_reg * reg energy = 240725 + 0.2 * nan = nan
max. update norm inf at voxel (61, 59, 127)
iter. no. 78
data energy + w_reg * reg energy = 236770 + 0.2 * nan = nan
max. update norm inf at voxel (61, 63, 127)
iter. no. 79
data energy + w_reg * reg energy = 233355 + 0.2 * nan = nan
max. update norm inf at voxel (61, 67, 127)
iter. no. 80
data energy + w_reg * reg energy = 231061 + 0.2 * nan = nan
max. update norm inf at voxel (61, 71, 127)
iter. no. 81
data energy + w_reg * reg energy = 229643 + 0.2 * nan = nan
max. update norm inf at voxel (61, 75, 127)
iter. no. 82
data energy + w_reg * reg energy = 229061 + 0.2 * nan = nan
max. update norm inf at voxel (61, 79, 127)
iter. no. 83
data energy + w_reg * reg energy = 228699 + 0.2 * nan = nan
max. update norm inf at voxel (61, 83, 127)
iter. no. 84
data energy + w_reg * reg energy = 228404 + 0.2 * nan = nan
max. update norm inf at voxel (61, 87, 127)
iter. no. 85
data energy + w_reg * reg energy = 228214 + 0.2 * nan = nan
max. update norm inf at voxel (61, 91, 127)
iter. no. 86
data energy + w_reg * reg energy = 228064 + 0.2 * nan = nan
max. update norm inf at voxel (61, 95, 127)
iter. no. 87
data energy + w_reg * reg energy = 227910 + 0.2 * nan = nan
max. update norm inf at voxel (61, 99, 127)
iter. no. 88
data energy + w_reg * reg energy = 227781 + 0.2 * nan = nan
max. update norm inf at voxel (61, 103, 127)
iter. no. 89
data energy + w_reg * reg energy = 227649 + 0.2 * nan = nan
max. update norm inf at voxel (61, 107, 127)
iter. no. 90
data energy + w_reg * reg energy = 227539 + 0.2 * nan = nan
max. update norm inf at voxel (61, 111, 127)
iter. no. 91
data energy + w_reg * reg energy = 227459 + 0.2 * nan = nan
max. update norm inf at voxel (61, 115, 127)
iter. no. 92
data energy + w_reg * reg energy = 227404 + 0.2 * nan = nan
max. update norm inf at voxel (61, 119, 127)
iter. no. 93
data energy + w_reg * reg energy = 227374 + 0.2 * nan = nan
max. update norm inf at voxel (61, 123, 127)
iter. no. 94
data energy + w_reg * reg energy = 227361 + 0.2 * nan = nan
max. update norm inf at voxel (61, 127, 127)
iter. no. 95
data energy + w_reg * reg energy = 227361 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 95 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227347 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227333 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227318 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227304 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227291 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227276 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227262 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227248 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227234 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227220 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227206 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227192 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227177 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227163 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227149 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227135 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227121 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227107 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227093 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227079 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227064 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227050 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227036 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227022 + 0.2 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 227008 + 0.2 * nan = nan
max. update norm 0 at voxel (0

I tried reducing step size.  the reg-term is still not good.
INFO: GL Window and Context created.
iter. no. 1
data energy + w_reg * reg energy = 12455.6 + 0.6 * 0 = 12455.6
max. update norm 3.53527 at voxel (90, 18, 52)
iter. no. 2
data energy + w_reg * reg energy = 2792.36 + 0.6 * 404943 = 245758
max. update norm 31.3926 at voxel (90, 18, 52)
iter. no. 3
data energy + w_reg * reg energy = 16057.1 + 0.6 * 5.23157e+06 = 3.155e+06
max. update norm 296.429 at voxel (92, 26, 62)
iter. no. 4
data energy + w_reg * reg energy = 44832.2 + 0.6 * 2.95903e+09 = 1.77546e+09
max. update norm 3724.51 at voxel (92, 26, 62)
iter. no. 5
data energy + w_reg * reg energy = 78913.7 + 0.6 * 2.44267e+12 = 1.4656e+12
max. update norm 47125.4 at voxel (92, 26, 62)
iter. no. 6
data energy + w_reg * reg energy = 105822 + 0.6 * 5.41628e+14 = 3.24977e+14
max. update norm 601730 at voxel (92, 26, 62)
iter. no. 7
data energy + w_reg * reg energy = 131891 + 0.6 * 2.13533e+17 = 1.2812e+17
max. update norm 7.76651e+06 at voxel (92, 26, 62)
iter. no. 8
data energy + w_reg * reg energy = 158201 + 0.6 * 2.85342e+19 = 1.71205e+19
max. update norm 1.01374e+08 at voxel (92, 26, 62)
iter. no. 9
data energy + w_reg * reg energy = 179852 + 0.6 * 4.66335e+21 = 2.79801e+21
max. update norm 1.33765e+09 at voxel (92, 26, 62)
iter. no. 10
data energy + w_reg * reg energy = 197666 + 0.6 * 3.24054e+23 = 1.94432e+23
max. update norm 1.85624e+10 at voxel (11, 42, 46)
iter. no. 11
data energy + w_reg * reg energy = 215594 + 0.6 * 4.21127e+25 = 2.52676e+25
max. update norm 2.65658e+11 at voxel (11, 42, 46)
iter. no. 12
data energy + w_reg * reg energy = 228909 + 0.6 * 3.48118e+27 = 2.08871e+27
max. update norm 3.82054e+12 at voxel (11, 42, 46)
iter. no. 13
data energy + w_reg * reg energy = 240239 + 0.6 * 1.2692e+30 = 7.61518e+29
max. update norm 5.51827e+13 at voxel (11, 42, 46)
iter. no. 14
data energy + w_reg * reg energy = 250531 + 0.6 * 6.74105e+31 = 4.04463e+31
max. update norm 8.00116e+14 at voxel (11, 42, 46)
iter. no. 15
data energy + w_reg * reg energy = 259947 + 0.6 * 1.83475e+34 = 1.10085e+34
max. update norm 1.16664e+16 at voxel (12, 42, 46)
iter. no. 16
data energy + w_reg * reg energy = 267476 + 0.6 * 1.96981e+36 = 1.18188e+36
max. update norm 1.70623e+17 at voxel (12, 42, 46)
iter. no. 17
data energy + w_reg * reg energy = 275144 + 0.6 * inf = inf
max. update norm 2.50053e+18 at voxel (12, 42, 46)
iter. no. 18
data energy + w_reg * reg energy = 282176 + 0.6 * inf = inf
max. update norm inf at voxel (125, 4, 90)
iter. no. 19
data energy + w_reg * reg energy = 289411 + 0.6 * inf = inf
max. update norm inf at voxel (96, 1, 76)
iter. no. 20
data energy + w_reg * reg energy = 294975 + 0.6 * inf = inf
max. update norm inf at voxel (96, 0, 76)
iter. no. 21
data energy + w_reg * reg energy = 300812 + 0.6 * inf = inf
max. update norm inf at voxel (96, 0, 70)
iter. no. 22
data energy + w_reg * reg energy = 306555 + 0.6 * inf = inf
max. update norm inf at voxel (96, 0, 68)
iter. no. 23
data energy + w_reg * reg energy = 311854 + 0.6 * inf = inf
max. update norm inf at voxel (96, 0, 63)
iter. no. 24
data energy + w_reg * reg energy = 316339 + 0.6 * inf = inf
max. update norm inf at voxel (96, 0, 62)
iter. no. 25
data energy + w_reg * reg energy = 320656 + 0.6 * inf = inf
max. update norm inf at voxel (114, 0, 55)
iter. no. 26
data energy + w_reg * reg energy = 324741 + 0.6 * inf = inf
max. update norm inf at voxel (96, 0, 55)
iter. no. 27
data energy + w_reg * reg energy = 327797 + 0.6 * inf = inf
max. update norm inf at voxel (96, 0, 52)
iter. no. 28
data energy + w_reg * reg energy = 330706 + 0.6 * inf = inf
max. update norm inf at voxel (112, 0, 46)
iter. no. 29
data energy + w_reg * reg energy = 333600 + 0.6 * inf = inf
max. update norm inf at voxel (96, 0, 47)
iter. no. 30
data energy + w_reg * reg energy = 335931 + 0.6 * inf = inf
max. update norm inf at voxel (88, 0, 38)
iter. no. 31
data energy + w_reg * reg energy = 338058 + 0.6 * inf = inf
max. update norm inf at voxel (64, 0, 36)
iter. no. 32
data energy + w_reg * reg energy = 339976 + 0.6 * inf = inf
max. update norm inf at voxel (88, 0, 31)
iter. no. 33
data energy + w_reg * reg energy = 342128 + 0.6 * inf = inf
max. update norm inf at voxel (48, 0, 30)
iter. no. 34
data energy + w_reg * reg energy = 343672 + 0.6 * inf = inf
max. update norm inf at voxel (0, 0, 30)
iter. no. 35
data energy + w_reg * reg energy = 345196 + 0.6 * inf = inf
max. update norm inf at voxel (104, 0, 22)
iter. no. 36
data energy + w_reg * reg energy = 349969 + 0.6 * nan = nan
max. update norm inf at voxel (80, 0, 23)
iter. no. 37
data energy + w_reg * reg energy = 357394 + 0.6 * nan = nan
max. update norm inf at voxel (112, 0, 15)
iter. no. 38
data energy + w_reg * reg energy = 355638 + 0.6 * nan = nan
max. update norm inf at voxel (96, 0, 12)
iter. no. 39
data energy + w_reg * reg energy = 347921 + 0.6 * nan = nan
max. update norm inf at voxel (96, 0, 12)
iter. no. 40
data energy + w_reg * reg energy = 338367 + 0.6 * nan = nan
max. update norm inf at voxel (96, 0, 6)
iter. no. 41
data energy + w_reg * reg energy = 328294 + 0.6 * nan = nan
max. update norm inf at voxel (96, 0, 6)
iter. no. 42
data energy + w_reg * reg energy = 318822 + 0.6 * nan = nan
max. update norm inf at voxel (96, 0, 4)
iter. no. 43
data energy + w_reg * reg energy = 310674 + 0.6 * nan = nan
max. update norm inf at voxel (96, 0, 0)
iter. no. 44
data energy + w_reg * reg energy = 304076 + 0.6 * nan = nan
max. update norm inf at voxel (16, 0, 3)
iter. no. 45
data energy + w_reg * reg energy = 298878 + 0.6 * nan = nan
max. update norm inf at voxel (64, 0, 6)
iter. no. 46
data energy + w_reg * reg energy = 294499 + 0.6 * nan = nan
max. update norm inf at voxel (0, 0, 6)
iter. no. 47
data energy + w_reg * reg energy = 290800 + 0.6 * nan = nan
max. update norm inf at voxel (124, 0, 1)
iter. no. 48
data energy + w_reg * reg energy = 287504 + 0.6 * nan = nan
max. update norm inf at voxel (127, 0, 0)
iter. no. 49
data energy + w_reg * reg energy = 284854 + 0.6 * nan = nan
max. update norm inf at voxel (66, 66, 127)
iter. no. 50
data energy + w_reg * reg energy = 282347 + 0.6 * nan = nan
max. update norm inf at voxel (66, 70, 127)
iter. no. 51
data energy + w_reg * reg energy = 280738 + 0.6 * nan = nan
max. update norm inf at voxel (66, 74, 127)
iter. no. 52
data energy + w_reg * reg energy = 279760 + 0.6 * nan = nan
max. update norm inf at voxel (66, 78, 127)
iter. no. 53
data energy + w_reg * reg energy = 278724 + 0.6 * nan = nan
max. update norm inf at voxel (66, 82, 127)
iter. no. 54
data energy + w_reg * reg energy = 278233 + 0.6 * nan = nan
max. update norm inf at voxel (66, 86, 127)
iter. no. 55
data energy + w_reg * reg energy = 277874 + 0.6 * nan = nan
max. update norm inf at voxel (66, 90, 127)
iter. no. 56
data energy + w_reg * reg energy = 277368 + 0.6 * nan = nan
max. update norm inf at voxel (66, 94, 127)
iter. no. 57
data energy + w_reg * reg energy = 277051 + 0.6 * nan = nan
max. update norm inf at voxel (66, 98, 127)
iter. no. 58
data energy + w_reg * reg energy = 276998 + 0.6 * nan = nan
max. update norm inf at voxel (66, 102, 127)
iter. no. 59
data energy + w_reg * reg energy = 277006 + 0.6 * nan = nan
max. update norm inf at voxel (66, 106, 127)
iter. no. 60
data energy + w_reg * reg energy = 276953 + 0.6 * nan = nan
max. update norm inf at voxel (66, 110, 127)
iter. no. 61
data energy + w_reg * reg energy = 276897 + 0.6 * nan = nan
max. update norm inf at voxel (66, 114, 127)
iter. no. 62
data energy + w_reg * reg energy = 276885 + 0.6 * nan = nan
max. update norm inf at voxel (66, 118, 127)
iter. no. 63
data energy + w_reg * reg energy = 276877 + 0.6 * nan = nan
max. update norm inf at voxel (66, 122, 127)
iter. no. 64
data energy + w_reg * reg energy = 276874 + 0.6 * nan = nan
max. update norm inf at voxel (66, 126, 127)
iter. no. 65
data energy + w_reg * reg energy = 276874 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 65 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276856 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276839 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276822 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276805 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276788 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276771 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276753 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276736 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276719 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276701 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276684 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276667 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276650 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276633 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276616 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276598 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276581 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276564 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276547 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276529 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276512 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276495 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276478 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276461 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276444 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276426 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276409 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276392 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276375 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276357 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
iter. no. 1
data energy + w_reg * reg energy = 276341 + 0.6 * nan = nan
max. update norm 0 at voxel (0, 0, 0)
SOLVER CONVERGED AFTER 1 ITERATIONS
INFO: Program quit after 7279 ticks
INFO: GL Window Destoryed.

I want to use your solver in my code to achieve dynamic-fusion like result. So fa,  I have implemented a static TSDF library with ICP. I forgot to initialize the Jacobian matrix while porting your code to my implementation. That's why it did not start at 0. Thank you for pointing that out.
Right now I'm testing your code solely with the depth data captured by myself. However, it never converge even after 2048 iterations at first frame. I tried many configurations including the alpha size and the recommended ones in the paper that you pointed out in your previous response.
I suspect it might be relevant to the noise generated by the depth sensor, but interestingly it does not affect my static fusion.

Interesting... Even though it never converges, the tracking somehow is good enough when there is no more than translations in the data(like you said the solver does work.). The canonical volume can even accumulate in a meaningful way only when it does not contain rotations in the data.
I also tried other step sizes from 0.01 to 0.3.  Solver stops working at 0.4
Any suggestions?
I'm using a 128, 128, 128 grid with 4-10 mm per voxel.
Alpha is 0.05 - 0.1
Filter size is 7
lambda is 0.1
weight 0.2
Log:
iter. no. 1
data energy + w_reg * reg energy = 7646.78 + 0.2 * 0 = 7646.78
max. update norm 0.350222 at voxel (87, 48, 61)
iter. no. 50
data energy + w_reg * reg energy = 2797.01 + 0.2 * 1.05463e+06 = 213722
max. update norm 0.0398565 at voxel (127, 0, 112)
iter. no. 100
data energy + w_reg * reg energy = 2656.16 + 0.2 * 1.30884e+06 = 264424
max. update norm 0.0311408 at voxel (127, 0, 111)
iter. no. 150
data energy + w_reg * reg energy = 2599.94 + 0.2 * 1.46987e+06 = 296575
max. update norm 0.0289678 at voxel (127, 0, 110)
iter. no. 200
data energy + w_reg * reg energy = 2568.47 + 0.2 * 1.5869e+06 = 319948
max. update norm 0.0297711 at voxel (127, 0, 109)
iter. no. 250
data energy + w_reg * reg energy = 2546.59 + 0.2 * 1.67322e+06 = 337190
max. update norm 0.0220492 at voxel (127, 0, 109)
iter. no. 300
data energy + w_reg * reg energy = 2530.55 + 0.2 * 1.73912e+06 = 350354
max. update norm 0.0247185 at voxel (127, 0, 108)
iter. no. 350
data energy + w_reg * reg energy = 2518.33 + 0.2 * 1.79112e+06 = 360743
max. update norm 0.0193914 at voxel (127, 0, 108)
iter. no. 400
data energy + w_reg * reg energy = 2508.63 + 0.2 * 1.83303e+06 = 369114
max. update norm 0.0230706 at voxel (127, 0, 107)
iter. no. 450
data energy + w_reg * reg energy = 2500.57 + 0.2 * 1.86783e+06 = 376067
max. update norm 0.0184403 at voxel (127, 0, 107)
iter. no. 500
data energy + w_reg * reg energy = 2493.79 + 0.2 * 1.89636e+06 = 381766
max. update norm 0.0155475 at voxel (127, 0, 107)
iter. no. 550
data energy + w_reg * reg energy = 2487.84 + 0.2 * 1.92082e+06 = 386651
max. update norm 0.0117325 at voxel (127, 2, 103)
iter. no. 600
data energy + w_reg * reg energy = 2483.23 + 0.2 * 1.94245e+06 = 390973
max. update norm 0.0098311 at voxel (127, 2, 103)
iter. no. 650
data energy + w_reg * reg energy = 2479.33 + 0.2 * 1.96136e+06 = 394752
max. update norm 0.00923391 at voxel (127, 2, 102)
iter. no. 700
data energy + w_reg * reg energy = 2475.37 + 0.2 * 1.97828e+06 = 398130
max. update norm 0.00981192 at voxel (127, 2, 102)
iter. no. 750
data energy + w_reg * reg energy = 2471.89 + 0.2 * 1.99309e+06 = 401089
max. update norm 0.00664955 at voxel (127, 2, 102)
iter. no. 800
data energy + w_reg * reg energy = 2468.92 + 0.2 * 2.00564e+06 = 403596
max. update norm 0.00483364 at voxel (127, 2, 102)
iter. no. 850
data energy + w_reg * reg energy = 2466.35 + 0.2 * 2.01632e+06 = 405731
max. update norm 0.00396784 at voxel (127, 2, 102)
iter. no. 900
data energy + w_reg * reg energy = 2464.05 + 0.2 * 2.02548e+06 = 407559
max. update norm 0.00362555 at voxel (127, 2, 102)
iter. no. 950
data energy + w_reg * reg energy = 2461.94 + 0.2 * 2.03336e+06 = 409135
max. update norm 0.0032354 at voxel (127, 2, 102)
iter. no. 1000
data energy + w_reg * reg energy = 2460.08 + 0.2 * 2.04022e+06 = 410504
max. update norm 0.00412488 at voxel (127, 3, 101)
SOLVER REACHED MAX. NO. OF ITERATIONS WITHOUT CONVERGING
iter. no. 1
data energy + w_reg * reg energy = 3550.65 + 0.2 * 2.04039e+06 = 411629
max. update norm 0.283898 at voxel (85, 41, 61)
iter. no. 50
data energy + w_reg * reg energy = 2231.8 + 0.2 * 2.0562e+06 = 413471
max. update norm 0.0406142 at voxel (127, 0, 104)
iter. no. 100
data energy + w_reg * reg energy = 2198.59 + 0.2 * 2.06222e+06 = 414643
max. update norm 0.0362966 at voxel (127, 0, 105)
iter. no. 150
data energy + w_reg * reg energy = 2185.54 + 0.2 * 2.06657e+06 = 415499
max. update norm 0.0380663 at voxel (127, 0, 106)
iter. no. 200
data energy + w_reg * reg energy = 2177.17 + 0.2 * 2.07041e+06 = 416259
max. update norm 0.0247796 at voxel (127, 0, 107)
iter. no. 250
data energy + w_reg * reg energy = 2171.46 + 0.2 * 2.0736e+06 = 416891
max. update norm 0.0132635 at voxel (127, 0, 109)
iter. no. 300
data energy + w_reg * reg energy = 2166.9 + 0.2 * 2.07631e+06 = 417429
max. update norm 0.00937067 at voxel (127, 0, 110)
iter. no. 350
data energy + w_reg * reg energy = 2163.27 + 0.2 * 2.07877e+06 = 417917
max. update norm 0.00749873 at voxel (127, 4, 108)
iter. no. 400
data energy + w_reg * reg energy = 2160.23 + 0.2 * 2.08057e+06 = 418274
max. update norm 0.00592503 at voxel (127, 0, 111)
iter. no. 450
data energy + w_reg * reg energy = 2157.65 + 0.2 * 2.08197e+06 = 418551
max. update norm 0.00498483 at voxel (127, 5, 107)
iter. no. 500
data energy + w_reg * reg energy = 2155.44 + 0.2 * 2.08312e+06 = 418779
max. update norm 0.00444591 at voxel (127, 5, 107)
iter. no. 550
data energy + w_reg * reg energy = 2153.42 + 0.2 * 2.08412e+06 = 418978
max. update norm 0.00403678 at voxel (127, 5, 107)
iter. no. 600
data energy + w_reg * reg energy = 2151.44 + 0.2 * 2.08464e+06 = 419080
max. update norm 0.00387362 at voxel (127, 4, 109)
iter. no. 650
data energy + w_reg * reg energy = 2149.45 + 0.2 * 2.08471e+06 = 419091
max. update norm 0.00376256 at voxel (127, 4, 109)
iter. no. 700
data energy + w_reg * reg energy = 2147.63 + 0.2 * 2.08478e+06 = 419103
max. update norm 0.0033257 at voxel (127, 4, 109)
iter. no. 750
data energy + w_reg * reg energy = 2146.04 + 0.2 * 2.08474e+06 = 419093
max. update norm 0.00286596 at voxel (127, 4, 109)
iter. no. 800
data energy + w_reg * reg energy = 2144.6 + 0.2 * 2.08459e+06 = 419062
max. update norm 0.00256356 at voxel (127, 4, 109)
iter. no. 850
data energy + w_reg * reg energy = 2143.31 + 0.2 * 2.08465e+06 = 419073
max. update norm 0.00232556 at voxel (127, 4, 109)
iter. no. 900
data energy + w_reg * reg energy = 2142.09 + 0.2 * 2.08484e+06 = 419110
max. update norm 0.00211953 at voxel (127, 5, 108)
iter. no. 950
data energy + w_reg * reg energy = 2140.93 + 0.2 * 2.08484e+06 = 419108
max. update norm 0.00199594 at voxel (127, 5, 108)
iter. no. 1000
data energy + w_reg * reg energy = 2139.8 + 0.2 * 2.08468e+06 = 419076
max. update norm 0.00183652 at voxel (127, 5, 108)
SOLVER REACHED MAX. NO. OF ITERATIONS WITHOUT CONVERGING
iter. no. 1
data energy + w_reg * reg energy = 6906.06 + 0.2 * 2.08467e+06 = 423839
max. update norm 0.510061 at voxel (88, 46, 63)
iter. no. 50
data energy + w_reg * reg energy = 2941.66 + 0.2 * 2.08882e+06 = 420706
max. update norm 0.0442168 at voxel (41, 78, 120)
iter. no. 100
data energy + w_reg * reg energy = 2714.22 + 0.2 * 2.08955e+06 = 420625
max. update norm 0.0231331 at voxel (39, 78, 127)
iter. no. 150
data energy + w_reg * reg energy = 2639.57 + 0.2 * 2.0898e+06 = 420599
max. update norm 0.0112255 at voxel (127, 2, 110)
iter. no. 200
data energy + w_reg * reg energy = 2600.44 + 0.2 * 2.08997e+06 = 420594
max. update norm 0.0100529 at voxel (127, 0, 110)
iter. no. 250
data energy + w_reg * reg energy = 2576.55 + 0.2 * 2.0899e+06 = 420556
max. update norm 0.01044 at voxel (127, 0, 110)
iter. no. 300
data energy + w_reg * reg energy = 2559.94 + 0.2 * 2.09032e+06 = 420623
max. update norm 0.00768468 at voxel (127, 0, 109)

alpha >= 0.1 will definitely be too large. the reconstructions on youtube were run with a step size of the order of 1e-4. for more on convergence see the discussion in #2
re translation/rotation the problem with rotations would largely be due to the fact that, in the presence of rotation, the canonical tsdf is too different from the live projective sdf. the entire deformation field is estimated starting at frame 0, meaning that for parts of the volume that only come into view later on, the field will be very inaccurate, which it's impossible to fix, and the problem only gets worse at subsequent frames. you can see the same issue in the snoopy video on youtube


forward velocity of commands in combine3

at the moment combine3 forwards the note on events' velocities from the score, but the triggering commands' velocities should be applied to the note on events returned by the function instead

should be addressed (among other things) by #3

#3 has been merged, there could be architectural improvements but the API should remain the same, so closing this now.


manual cherry-pick for conf tests timeouts and parallelism

Changes

:bug: manual cherry-pick for conf tests timeouts and parallelism for tests to pass

/kind cleanup

/lgtm


Fetch pool data from camelot

Create a function to fetch liquidity details for ODG and OD. This will be used for the stats page

[ ] Fetch pool data from camelot https://docs.camelot.exchange/
[ ] Add addresses for existing pools. Later we will update the address to our own pools

a stablecoin pool for OD
any token pool for ODG

[ ] Fetch both price and liquidity data

Create a function to fetch liquidity details for ODG and OD. This will be used for the stats page
* [ ]  Fetch pool data from camelot https://docs.camelot.exchange/

* [ ]  Add addresses for existing pools. Later we will update the address to our own pools

  * a stablecoin pool for OD
  * any token pool for ODG

* [ ]  Fetch both price and liquidity data

@pi0neerpat I found two example pools to use:
Stablecoin V2 pair: https://arbiscan.io/address/0x87425d8812f44726091831a9a109f4bdc3ea34b4#readContract
Concentrated liquidity V3 pair: https://arbiscan.io/address/0x8cc8093218bcac8b1896a1eed4d925f6f6ab289f#readContract
Price data V3:
I found that we can get price data for V3 by querying globalState which returns a unint160 "price" value according to these docs: https://docs.quickswap.exchange/reference/smart-contracts/v3/pool/
Liquidity data V3:
I'm not sure about getting liquidity for V3--there's a a liquidity function but it "has no relationship to the total liquidity across all ticks" and returns a uint128 According to the analytics dashboard the current liquidity for GRAIL-USDC is 7 million https://info.camelot.exchange/pair/v3/0x8cc8093218bcac8b1896a1eed4d925f6f6ab289f but I'm not sure yet how this is related to the total liquidity in USD--I'll try to see if the SDK has this logic
Price data V2:
Seems like people usually rely on SDK methods to calculate the price because the contract itself doesn't have this as a read function like in V3--see info in getReserves (I know we aren't using quickswap but same idea): https://docs.quickswap.exchange/reference/smart-contracts/v2/pair
Liquidity data V2:
This info isn't on the contract either and will require some more research
I'm going to ask around in the Camelot Discord to get info on calculating liquidity/price data (I'm hoping their analytics app is open source but seems it's not because I couldn't find it in their GitHub)

Focusing just on OD for now
contract systemCoinOracle.priceSource() returns UniV3Relayer
contract UniV3Relayer.uniV3Pool()
systemCoin.balanceOf(uniV3PoolAddress)
WETH.balanceOf(uniV3PoolAddress)
Total liquidity for the pool
WETH balance price of WETH
OD balance = 1$
Sum (OD balance, WETH balance)


Can't go can't back to the game after alt tabbing.

Hey, I appreciate all the work that you've put into this tool, i've been using this since the moment you introduced it and always use it in every new windows install but lately i've been having this issue where after i would run the tool any fullscreen exclusive game and alt+tab but going back to the game won't work as it will stay on the taskbar, the only workaround i've found so far is pressing lalt+enter after clicking the game on taskbar, i'd appreciate if there is any idea into fixing this :)

Hey, I appreciate all the work that you've put into this tool, i've been using this since the moment you introduced it and always use it in every new windows install but lately i've been having this issue where after i would run the tool any fullscreen exclusive game and alt+tab but going back to the game won't work as it will stay on the taskbar, the only workaround i've found so far is pressing lalt+enter after clicking the game on taskbar, i'd appreciate if there is any idea into fixing this :)

i fix that by making a new user

After running the tool on another fresh windows 10 install the issue isn't happening anymore but i'll keep that in mind if the issue occurs again, thanks for the suggestion :)

Thanks for the issue, Feel free to reopen this one or make a new one if it pops back up.


Running instructions

Hi @alexander-rakhlin  it seems like a great work for sentence classification. Can you please provide details about how to use/run the system? And also kindly provide the link to the publication related to the system (if any).
Thanks

You have closed the issue without answering the question......


feat: Add pact-axios tag

Closes #48 without last point:

get URL path from axios usage

as path is often not a static value but is computed during runtime and there is no possibility to get its value in such case.
Extracted part of the logic to classes for better encapsulation and readability.

In case of url handling, what if we just take them from axios calls anyway and just replace any existing parameters with default values: 1 for number, 'string-value' for string?


Add a join Slack button on the OCM io homepage

Signed-off-by: Mike Ng<EMAIL_ADDRESS>For https://github.com/open-cluster-management-io/open-cluster-management-io.github.io/issues/264

/approve
/lgtm


Added book and chapter overview for tN

Added book and chapter overview for tN #295

@vipinpaul, This PR can be merged.
Suggestions:

Could you freeze the notes tabs while scrolling
After scrolling the resources, while clicking the next verse the resource does not go to the initial state. If the resources start from the beginning it will be good.
Note: translationNotes is working as suggested. This recommendation for other resources, except Bibles and tNotes


Can it be made Bower and RequireJS compatible?

Currently, we can install this by Bower, but the Bower package contains everything need in it. It's great to one-click demonstration, but it also cause RequireJS optimisation failure, just because it contains everything as well, not by a package dependency structure.
Now we have to copy the required css and js manually to the development project.
If it can follow the dependency structure, it would be much better for automatic project dependency management and to CI.

Hey @DieterLi, check out my pull request.
Hope you'll be satisfied :)
https://github.com/almasaeed2010/AdminLTE/pull/857


chore(test): merge deno runtime coverage

A re-creation of #3456 in a new branch.
The author should do the following, if applicable

[ ] Add tests
[ ] Run tests
[ ] bun run format:fix && bun run lint:fix to format the code
[ ] Add TSDoc/JSDoc to document the code

@yusukebe
There are some minor additions due to the output results for each coverage tool, but I don't think there will be any major problems.
And we can see that the code coverage for deno is now being measured.
How about merging this content?

Hi @usualoma

How about merging this content?

This is good! Merging now. Thanks!


Fatal warning when running make/build

Stacktrace for reference:
fatal: No names found, cannot describe anything.

This is caused because there is no git tag available in the project. This will be fixed as we make first release.


feat: Add new cat gif

I want to add a cat gif to this project.
Please assign this issue to me and add the Hacktoberfest label to this issue.

Hi! Feel free to add the gif. The repo actually has the Hacktoberfest label.


Subject lost space when  parse from raw email content

hi thanks for 8bit fix and i had use the lastest version
but when i use the repo to get the header i still encounter the error
The correct header :
Safebook Gửi link tham dự Hội thảo thuế online ngày 18/03
After using your repo to get email subject i got this header
SafebookGửi link thamdự Hội thảo thuế onlinengày 18/03
Its lost space between character
Here is the full email content notepad
Here is the subject that cause error
Subject: Safebook =?utf-8?Q?G=E1=BB=ADi?= link tham
 =?utf-8?Q?d=E1=BB=B1_H=E1=BB=99i_th=E1=BA=A3o_?=
 =?utf-8?Q?thu=E1=BA=BF?= online =?utf-8?Q?ng=C3=A0y?= 18/03

Can you check the error? Thanks

Fixed, please check master branch


Add project list page with live websocket support.

This PR adds live web socket events to project sync within the awx projects list.

Cypress e2e tests:
Running:  awx/resources/projects.cy.ts

  projects
    ✓ can render the projects list page (20657ms)
    ✓ can navigate to project details tab (4860ms)
    ✓ can navigate to project access tab (4380ms)
    ✓ can navigate to project job templates tab (4339ms)
    ✓ can navigate to project notifications tab (5710ms)
    ✓ can navigate to project schedules tab (4263ms)
    ✓ can copy project from project details page (6399ms)
    ✓ can delete project from project details page (9450ms)
    ✓ can sync project from project details page (6292ms)
    ✓ can sync project from projects list table row kebab menu (7699ms)
    ✓ can cancel project sync from projects list table row kebab menu (12200ms)
    ✓ can copy project from projects list table row kebab menu (9338ms)
    ✓ can delete project from projects list table row kebab menu (12152ms)
    ✓ can delete project from projects list toolbar  (7336ms)
    ✓ can cancel project sync from projects list toolbar  (8309ms)

  15 passing (2m)

  (Results)

  ┌────────────────────────────────────────────────────────────────────────────────────────────────┐
  │ Tests:        15                                                                               │
  │ Passing:      15                                                                               │
  │ Failing:      0                                                                                │
  │ Pending:      0                                                                                │
  │ Skipped:      0                                                                                │
  │ Screenshots:  0                                                                                │
  │ Video:        false                                                                            │
  │ Duration:     2 minutes, 25 seconds                                                            │
  │ Spec Ran:     awx/resources/projects.cy.ts                                                     │
  └────────────────────────────────────────────────────────────────────────────────────────────────┘

Cypress unit tests:
Running:  resources/projects/Projects.cy.tsx
   projects.cy.ts
     Non-empty list
       ✓ Projects list renders (796ms)
       ✓ Projects list has filters for Name, Description, Type, Created By, and Modified By (1604ms)
       ✓ Filter projects by name (4349ms)
       ✓ Filter projects by description (4119ms)
       ✓ Filter projects by created by (3943ms)
       ✓ Filter projects by modified by (3935ms)
       ✓ Filter projects by Type > Git (5088ms)
       ✓ Filter projects by Type > Subversion (4609ms)
       ✓ Filter projects by Type > Insights (4773ms)
       ✓ Filter projects by Type > Manual (4729ms)
       ✓ Filter projects by Type > Remote Archive (4892ms)
       ✓ Sync project calls API /update endpoint (1984ms)
       ✓ Create Project button is disabled if the user does not have permission to create projects (477ms)
       ✓ Cancel project sync toolbar button shows error dialog if project sync is not running (5258ms)
       ✓ Cancel project sync toolbar button shows error dialog if user has insufficient permissions (5065ms)
       ✓ Sync, Copy, Edit, Delete Project button is disabled if the user does not have permission(s) (2949ms)
       ✓ Cancel project sync kebab button is visible for project with active sync status and is hidden for project with non active sync status (1517ms)
       ✓ Cancel project sync row button is disabled for user with insufficient permissions (876ms)
       ✓ Create Project button is enabled if the user has permission to create projects (331ms)
       ✓ Displays error if projects are not successfully loaded (1302ms)
     Empty list
       ✓ Empty state is displayed correctly for user with permission to create projects (839ms)
       ✓ Empty state is displayed correctly for user without permission to create projects (483ms)

   22 passing (1m)

   (Results)

   ┌────────────────────────────────────────────────────────────────────────────────────────────────┐
   │ Tests:        22                                                                               │
   │ Passing:      22                                                                               │
   │ Failing:      0                                                                                │
   │ Pending:      0                                                                                │
   │ Skipped:      0                                                                                │
   │ Screenshots:  0                                                                                │
   │ Video:        false                                                                            │
   │ Duration:     1 minute, 15 seconds                                                             │
   │ Spec Ran:     resources/projects/Projects.cy.tsx                                               │
   └────────────────────────────────────────────────────────────────────────────────────────────────┘

@vidyanambiar thank you for taking a look. I added a cancel button to the row item kebab as well as the project list toolbar (we now have bulk cancel (!)) and reworked some of the e2e tests. I think this is ready for a re-review. I believe we'll have to peel off the expandable row work (plus the work to show the last used and execution env. fields) into a separate ticket while we wait for guidance from UXD on which columns to keep.

The bulk action dialog issues mentioned above are happening elsewhere and should be addressed as a separate part of this PR. Project sync is now disabled if a project has an active sync status and there is now a string for translation to handle singular and plural bulk project sync cancel.

@kialam I see this commit in the commit history for disabling the sync when it is progress but I suspect some following commit is undoing that change 🤔 because it's not in the final set of file changes and the Sync button remains enabled when a sync is in progress.


Crashes when Clicking on Profiles

Whenever the plugin is turned on, clicking on someone's profile will crash discord. Turning it off and back on will create the ability to click on profiles without it crashing, however pronouns are not able to be changed.

This seem to be an issue with a plugin for a Discord client mod, which is separate from the main repository. You should report this issue to the appropriate place, on the repository of the plugin you're using.


[Feature Request] automatically .setgame when playing music.

When playing music, automatically set the currently playing game to the song's title. (Normally done with the .setgame command)

That's already a feature. "!m setgame"

@kongslien "!m setgame" does nothing, is it in a newer build?
.ropl and .adpl %playing%  did the trick though.

"!m setgame" is the old option i guess. Don't know why i even still think it works, my bad.


docs: decision to recommend FCM for image handling

Complete each step to get your pull request merged in. Learn more about the workflow this project uses.

[ ] Assign members of your team to review the pull request.
[ ] Wait for pull request status checks to complete. If there are problems, fix them until you see that all status checks are passing.
[ ] Wait until the pull request has been reviewed and approved by a teammate
[ ] After pull request is approved, and you determine it's ready add the label "Ready to merge" to the pull request and it will automatically be merged.

Pull request title looks good 👍. If this pull request gets merged, it will not cause a new release of the software.
Example: If this project's latest release version is 1.0.0. If this pull request gets merged in, the next release of this project will be 1.0.0.
To merge this pull request, add the label Ready to merge to this pull request and I'll merge it for you.

Blocked until this pr is merged to fix lint errors.

:tada: This PR is included in version 3.3.0-beta.2 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


⚠ Bofrost.at has degraded performance

In 69a238a, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 2398 ms

Resolved: Bofrost.at performance has improved in 2f874cd.


PointLight2D acting as fully occluded at Compatibility rendering mode on android

Godot version
4.0
System information
Honor 10, android 10,mali-G72
Issue description
The scene has pointLight2d with the shadow enabled (in the example it is green) and lightoccluder2d, entering the range of pointlight2d. In any mode on the PC and in Forward plus and mobile modes on the smartphone, everything works as it should.

But in compatibility mode on android, the shadow completely covers the light, no matter what I do.

Steps to reproduce
Create node2d, add pointlight2d and lightoccluder2d to it so that pointlight2d can cast a shadow, enable the shadow, try it on different render modes on android.
Minimal reproduction project
asd.zip

Now I tested with the same rendering mode on another device - xiaomi mi note 10, and there shadows work fine. I also noticed that on mi there is always a freeze before displaying a previously not displayed shader (maybe compiling?), on honor this does not happen.

Didn't seem to work on powerVR as well

Godot v4.4.dev3 - Android - Single-window, 1 monitor - OpenGL ES 3 (Compatibility) - PowerVR Rogue GE8320 -  (8 threads)


Changes to improve reliability of token monitor

Description

We've seen a few issues where it looks like our token monitor isn't spotting that the token changes. This is meant to try to improve the reliability of the monitor by:

Monitoring files direcly, in addition to the directory
Adding a backstop in the form of a periodic resync.

Related issues/PRs

Related to https://github.com/projectcalico/calico/issues/4857
Todos

[ ] Tests
[ ] Documentation
[ ] Release note

Release Note

Improve reliability of token monitor

This improvement was released？
I hit the problem. I'm using two environment which build by the same ansible scripts.

one installation, calico/node has logs about token refresh,
the other one has no logs, so after 24 hours, the token was invalidated, I have to delete the pods(calico/node), it work again.
I have no idea about how to solved it. and try to set CALICO_MANAGE_CNI=true.

My way to install calico is

https://projectcalico.docs.tigera.io/getting-started/kubernetes/self-managed-onprem/onpremises
kubectl apply manifests file: https://raw.githubusercontent.com/projectcalico/calico/v3.24.5/manifests/calico.yaml
That's it.
Everything is fine, except the token monitor doesn't work.

We ended up going a different direction so the changes in this PR weren't needed. I'd recommend opening an issue to track discussion of the problems you're seeing in your cluster


Markdown content not being rendered as markdown html in short bio

@rithviknishad is this still an issue?

Oh my bad, duplicate of #186 which was already completed


Packages used to build base ubuntu 16.04 AMI

Is there a list of packages that are installed on the base cfncluster AMI for ubuntu 16.04? I am looking for all the apt-get  or apt steps done.
Appreciate your help!

See https://github.com/awslabs/cfncluster-cookbook/blob/develop/attributes/default.rb#L105
All the distro's are in there.

Thanks, @sean-smith!


Plugin - Access BufPlane of newly created tab

I'm having trouble to use plugin API and and fill buffer of newly created tab with some text.
The bp:AddTab() method does exactly what I'm after - adds and updates the current tab - but I can't find any method to access BufPlane of the new tab.
The bp:OpenBuffer(mybuffer) works but populates the buffer in the previous tab (which used to be the current before executing the my plugin).
Is there any reference example how work with tabs in Lua?

Ok, I think I get what I was after:
function myfun(bp)
    -- adding makes the tab active
    bp:AddTab()
    local buf,err  = buffer.NewBuffer("ABC", "")
    ...
    micro.CurPane():OpenBuffer(buf)
    ...
end


Getting  x509: certificate signed by unknown authority while creating eks cluster.

Description
I'm trying to collect more information and possibly find out what I'm doing wrong here. I've been getting a certificate signed by unknown authority error from the http.wait_for_cluster data source while trying to create an EKS cluster.
│ Error: Error making request: Get "https://<cluster_endpoint>/healthz": x509: certificate signed by unknown authority
│
│   with module.eks.data.http.wait_for_cluster[0],
│   on external-modules/terraform-aws-eks/cluster.tf line 68, in data "http" "wait_for_cluster":
│   68: data "http" "wait_for_cluster" {

This is how my code looks like.
module "eks" {
  source     = "./external-modules/terraform-aws-eks"
  depends_on = [data.aws_vpc_endpoint.sts, aws_vpc_endpoint.s3, aws_vpc_endpoint.logs, aws_vpc_endpoint.ecr_dkr, aws_vpc_endpoint.ecr_api, aws_vpc_endpoint.ec2, aws_route53_resolver_rule_association.test]
  cluster_name                    = local.cluster_name
  cluster_version                 = var.cluster_version
  subnets                         = var.subnets
  vpc_id                          = var.vpc_id
  cluster_endpoint_private_access = true
  #To be removed after fixing EKS local access
  cluster_endpoint_public_access = true
  node_groups = {
    example = {
      desired_capacity = var.desired_capacity
      max_capacity     = var.max_capacity
      min_capacity     = var.min_capacity

      launch_template_id      = aws_launch_template.default.id
      launch_template_version = aws_launch_template.default.default_version

      additional_tags = var.additional_tags
    }
  }
}

Versions

Terraform:  0.15
Provider(s):

+ provider registry.terraform.io/hashicorp/aws v3.42.0
+ provider registry.terraform.io/hashicorp/cloudinit v2.2.0
+ provider registry.terraform.io/hashicorp/helm v2.1.2
+ provider registry.terraform.io/hashicorp/kubernetes v2.2.0
+ provider registry.terraform.io/hashicorp/local v2.1.0
+ provider registry.terraform.io/hashicorp/null v3.1.0
+ provider registry.terraform.io/hashicorp/random v3.1.0
+ provider registry.terraform.io/hashicorp/template v2.2.0
+ provider registry.terraform.io/terraform-aws-modules/http v2.4.1

Module:

Reproduction

I've been using a local copy of this module and using it to create a private EKS cluster. The terraform code is run from a CI tool and this runs behind a corporate proxy.
Expected behavior

EKS Cluster gets created and worked nodes join the cluster.
Actual behavior

Fails to create EKS cluster.
Terminal Output Screenshot(s)

Additional context

Normally, the http provider follows proxy specifications.
Did you set http_proxy/https_proxy environment variables ?

Yes, Those are set as part of the jenkins step.
steps {
        script {
          withEnv([
            "http_proxy=http://<proxy>:80",
            "https_proxy=http://<proxy>:80",
            "no_proxy=localhost,<IP_ADDRESS>,<IP_ADDRESS>",
            "AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID}",
            "AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}",
            "AWS_DEFAULT_REGION=${AWS_DEFAULT_REGION}",
          ])

https://github.com/terraform-aws-modules/terraform-provider-http/blob/main/internal/provider/data_source.go#L116

Humm, just did some tests from our private network where we can go through internet without using our corporate proxy.
My configuration
terraform {
  required_providers {
    http = {
      source = "terraform-aws-modules/http"
    }
  }
}

data "http" "example" {
  url = "https://httpstat.us/200"

  request_headers = {
    Accept = "application/json"
  }
}

output "example" {
  value = data.http.example.body
}

Test without proxy
➜  tf-tests env | grep proxy
➜  tf-tests tf apply

Error: Error making request: Get "https://httpstat.us/200": dial tcp: lookup httpstat.us on <IP_ADDRESS>:53: no such host

  on test.tf line 14, in data "http" "example":
  14: data "http" "example" {

Test with proxy (in CAPITAL and in lowercase)
➜  tf-tests env | grep proxy
http_proxy=http://<proxy>:8080/
https_proxy=http://<proxy>:8080/
HTTP_PROXY=http://<proxy>:8080/
HTTPS_PROXY=http://<proxy>:8080/
➜  tf-tests tf apply

Apply complete! Resources: 0 added, 0 changed, 0 destroyed.

Outputs:

example = "{\"code\": 200, \"description\": \"OK\"}"
➜  tf-tests unset HTTPS_PROXY
➜  tf-tests unset HTTP_PROXY
➜  tf-tests tf apply

Apply complete! Resources: 0 added, 0 changed, 0 destroyed.

Outputs:

example = "{\"code\": 200, \"description\": \"OK\"}"
➜  tf-tests prx
➜  tf-tests unset http_proxy
➜  tf-tests unset https_proxy
➜  tf-tests tf apply

Apply complete! Resources: 0 added, 0 changed, 0 destroyed.

Outputs:

example = "{\"code\": 200, \"description\": \"OK\"}"

Also did the same tests on a private EKS endpoint with custom CA, and everything is working as expected.
Do you have this problem with curl ?
Is this happens once or every run ?
What is your module version ? I've noticed that you're using a local version "./external-modules/terraform-aws-eks".
Is this work without your depends_on in the module section ? Just wondering if this is not a bug in dependencies in TF 0.15. Can you please upgrade to latest version of Terraform 0.15 ?

https://github.com/terraform-aws-modules/terraform-provider-http/blob/main/internal/provider/data_source.go#L116

What you want me to see ?

Thank you for checking this out. I should've mentioned that I'm using this http module
https://github.com/terraform-aws-modules/terraform-provider-http

Do you have this problem with curl ? Nope. Curl returns 200.
Is this happens once or every run ? Yes
What is your module version ? I've noticed that you're using a local version "./external-modules/terraform-aws-eks". - I need to check. I'll upgrade to the latest version and check.
The terraform-aws-modules/http provider version is 2.4.1.
Is this work without your depends_on in the module section ? Just wondering if this is not a bug in dependencies in TF 0.15. Can you please upgrade to latest version of Terraform 0.15 ? I'm using 0.15.4 now.

Do you have this problem with curl ? Nope. Curl returns 200.

Did you just skip TLS validation with curl or you used the CA provided by the EKS cluster ?

Is this work without your depends_on in the module section ? Just wondering if this is not a bug in dependencies in TF 0.15. Can you please upgrade to latest version of Terraform 0.15 ? I'm using 0.15.4 now.

I'll say, it worth for testing only, to remove your depends_on.
Is this simple configuration work for you ?
terraform {
  required_providers {
    http = {
      source = "terraform-aws-modules/http"
    }
  }
}

data "http" "example" {
  url = "https://<your-endpoint>/healthz"

  ca_certificate = base64decode("you-base64-encoded-CA-from-AWS-console")
}

output "example" {
  value = data.http.example.body
}

Just an update on the earlier comment, I updated to the latest version of the terraform-aws-eks module. This is part where it errors out -
https://github.com/terraform-aws-modules/terraform-aws-eks/blob/master/data.tf#L89-L100
data "http" "wait_for_cluster" {
  count          = var.create_eks && var.manage_aws_auth ? 1 : 0
  url            = format("%s/healthz", aws_eks_cluster.this[0].endpoint)
  ca_certificate = base64decode(coalescelist(aws_eks_cluster.this[*].certificate_authority[0].data, [""])[0])
  timeout        = var.wait_for_cluster_timeout

  depends_on = [
    aws_eks_cluster.this,
    aws_security_group_rule.cluster_private_access_sg_source,
    aws_security_group_rule.cluster_private_access_cidrs_source,
  ]
}

I'll say, it worth for testing only, to remove your depends_on.

Testing without depends_on now.

This is configuration I'm using now. Still fails.
data "http" "wait_for_cluster" {
  url            = "https://ABCDEFGHIJN789065.gr7.ap-southeast-2.eks.amazonaws.com/healthz"
  ca_certificate = base64decode("base64-encoded-CA-from-AWS-console")
}

Also a correction on my earlier statement, curl doesn't work. The 200 I got was from the proxy.
* TLSv1.3 (OUT), TLS handshake, Client hello (1):
* CONNECT phase completed!
* CONNECT phase completed!
* OpenSSL SSL_connect: SSL_ERROR_SYSCALL in connection to ABCDEFGHIJN789065.gr7.ap-southeast-2.eks.amazonaws.com:443
* stopped the pause stream!
* Closing connection 0
curl: (35) OpenSSL SSL_connect: SSL_ERROR_SYSCALL in connection to ABCDEFGHIJN789065.gr7.ap-southeast-2.eks.amazonaws.com:443

I tried setting the insecure flag for the http provider to true. I got a 503 now.
│ Error: HTTP request error. Response code: 503
│
│   with module.eks_cluster.module.eks-cluster.data.http.wait_for_cluster[0],
│   on external-modules/terraform-aws-eks/data.tf line 89, in data "http" "wait_for_cluster":
│   89: data "http" "wait_for_cluster" {
│

Please see with admins why your proxy is returning that error. See your proxy logs.

Thanks @barryib

I have faced same problem. I solved it by adding ap-southeast-2.eks.amazonaws.com to "no_proxy".

this is related to your proxy or  corporate setup which we cannot help here beside what was already posted. Closing this issue

atlantis plan