proposal: Go 2: change len, cap to return untyped ints if result is constant

Reminder issue.
Can we change len, cap, etc. to return an untyped value rather than an int if they are constant expressions? Investigate if this is possible in a backward-compatible way.

And unsafe.Sizeof etc.

Yes,  this meets every use case that has frustrated me in code.

It turns out that per the spec, unsafe.Sizeof (and its siblings unsafe.Offsetof, unsafe.Alignof) return a uintptr rather than an int, which makes it impossible to change these in a backward-compatible way: even though they always return a constant, if that were an untyped int it would not default to uintptr. A place where this is causing problems is for instance in file https://golang.org/src/cmd/vendor/golang.org/x/sys/unix/syscall_darwin.go on line 353 where n is supposed to be of type uintptr.
But we should be able to do it for len and cap without problems - and indeed there aren't any in the stdlib as a type-checking it via a modified type checker shows (apply CL 179184 and run go test go/types which will run the go/types over all packages of the std lib, among other tests).

As an aside, changing len and cap as described is in the spirit of the built-ins complex, real and imag which also return an untyped result if the argument(s) are untyped.

Rather than make cap and len only evaluate to untyped when their arguments are constant, why not just always make them untyped?
Non-constant comparisons are still untyped bool when their operands are typed.

It turns out that per the spec, unsafe.Sizeof (and its siblings unsafe.Offsetof, unsafe.Alignof) return a uintptr rather than an int, which makes it impossible to change these in a backward-compatible way: even though they always return a constant, if that were an untyped int it would not default to uintptr.

We could make them evaluate to "untyped uintptr" lol.

I concur (consistently untyped for Go 2) but I may be overlooking potential
problems.
On Sat, Sep 7, 2019 at 10:32 AM Matthew Dempsky<EMAIL_ADDRESS>wrote:

Rather than make cap and len only evaluate to untyped when their
arguments are constant, why not just always make them untyped?
Non-constant comparisons are still untyped bool when their operands are
typed.
It turns out that per the spec, unsafe.Sizeof (and its siblings
unsafe.Offsetof, unsafe.Alignof) return a uintptr rather than an int, which
makes it impossible to change these in a backward-compatible way: even
though they always return a constant, if that were an untyped int it would
not default to uintptr.
We could make them evaluate to "untyped uintptr" lol.
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@mdempsky As you noted, the problem with making len always untyped is the size of the result. For booleans (and also strings) the size is known, no matter what kind of boolean (or string).

Will this change allow const X = len("Go") + 2i and complex(len("Go"), 2)?

yes

I am not sure the costs here are worth the benefit. Today there is a simple rule: len(x) has type int. Changing the type to depend on what x is will interact in non-orthogonal ways with various code changes. For example, under the proposed semantics, this code compiles:
const x string = "hello"
func f(uintptr)
...
f(len(x))

but suppose then someone comes along and wants to be able to modify x for testing or something like that, so they s/const/var/. That's usually fairly safe, but now the f(len(x)) call fails to type-check, and it will be mysterious why it ever worked.
This change seems like it might add more rough edges than it removes.

Agreeing with @rsc here. While this seems like an easy win at first glance, it's not clear that the corner cases are worth the extra complexity. I am retracting this proposal.


Allow generic @imports

Wouldn't it make sense to simply allow something like @import theme(colors)? We rely on postcss-css-variables and we don't need postcss-modules-values, so we'd simply like this plugin to inject the correct theme folder path.
This is the error
Error:
@import 'theme(colors)';
^
      File to import not found or unreadable: theme(colors)

Any thoughts?

Hi @pierlo-upitup. I think the problem is only related to the apostrophes.
Have you tried @import theme(colors);?

Error:
@import theme(colors);
^
      @import directive requires a url or quoted path

I believe the problem is postcss-theme is run after sass in my case. I will double-check.

Yeah, that would explain the issue 😉
Worst case: You need to run PostCSS before and after SASS.

@pierlo-upitup Any updates on this?


Change image of pressed bubble item index?

How to change the image of the pressed item?

Are you referring to the on touch down of a bubble? There is no way to do that. What you could do is fork the repo and send through a pull request.
What you would need to do is allow the menu to be initialized with another array of UIImages for the pressed state. Then add an additional target in the createButtonWithImage function to another function that changes the image!

Yeah I thought so.. Just wanted to confirm if this is in the library already or not.. sigh. Thanks @lvandyk


Data Shift detection over time with Resemblance Model

One way to measure at which point in time we can observe a data shift.
One idea would be to split data into multiple folds based on time e.g. 10. Then one could train a resemblance model taking:

1st fold as class 0 and 9 other folds as class 1
2 first folds as class 0 and 8 other as class 1
...
By measuring the AUC over different split time, we could observe whether data significantly changes at any point in time,  and we could monitor, which features contribute to that.
One drawback is the first and last iteration would lead to high AUC, due to small sample size of one of the classes.

Another idea would be to again split the data into folds based on time. However, in this case we would perform cross-validation, where at each iteration only one fold belongs to class 1. This way we could point to e.g. months that significantly differ from other months in the past and the future.
This feature could be part of sample_similarity, and the user could specify which resemblance model to use: permutation or shap based (default could be SHAP).
The init should take as arguments the clf and resemblance_model type, and fit should take X dataset, and indication of number of bins, or split dates, and date column name.
The output of compute should be the report presenting the validation AUC for each iteration of the process, the information about current time split date and top feature of the resemblance model (top_n parameter?)
In the plot method we could plot the AUC over time, but also user should be able to plot resemblance model plots for a specific iteration, to analyse it.

I see how training a resemblance model could help detect seasonality in the data. I think there should be more context provided before offering a tool like this:

Can this seasonality be detected in the target instead of the training data? Can the target data be used?
Why and when would you want to detect (multivariate) seasonality in the data? If it is somewhat present, how would you migitate it?
What others methods / approaches exist to detect this seasonality, and when would you use which? Some literature context might help there.

Hmm, I see this throwing confusing outputs. There are two potential flaws
Let me explain:

If you want to detect seasonality, maybe a better approach is to map your folds to a repetitive pattern. For example, if you have 3 years of data, why not define a fold mapping based on quarters?
In that way, you train your resemblance on Q1,Q2 and Q3 folds, and test on Q4, and then you repeat for every shuffle.

I see the approach you propose hard to interpret. let me explain:
assume the that you have a linear shift in your features with time. If you train on folds 1234 and 6789 and evaluate on fold 5, probably you would not detect anything, cause you are exactly on the average shift. A better approach might be to do a "rolling" fold, where you train on 123 and estimate on 4, and then you train on 234 and estimate on 5... this might be more complicated to implement, but I would expect this to yield better results.

Addressing your comments:
@timvink

I think the target data can be used as well, since the shift could also appear there. This can be quite simply done by adding the label to the X, and providing it to the resemblance model. This way we can also see if the label's properties change over time
Example use case:  Let's say that you are trying to determine whether your data is stable over time. There are many tools that allow you to look at this from univariate perspective, but if you look at multivariate using resemblance model, you can detect that in given time of the data, there is a shift in relations between features. If you use Logistic regression model and there is multivariate data shift, but on the univariate level the trends remain, this is probably not a problem. But the more advanced model you use, the model relies more on the multivariate relations.  Such analysis would crucial to determine
- how you split the data into train and OOT Test,
- why OOT Test scores are lower than Train,
- How much of the data early months of data in Train to remove remove.
Based on discussion with Artur, it seems like this would not be focused on seasonality, because we don't catch repeating patterns, but rather data shift. Indeed diving deeper into other packages and literature could help, I will do this when i have more time.

@sbjelogr

Indeed we would need to find a convenient way to use the time domain. This would be the first time we do it in probatus, so it would require some thought
The two variants i proposed would detect different things:

Class 0: folds 1, 2, 4, 5, class 1 fold 3 - tells you how this time is different from all the others. Imagine that in december people spend more money due to christmas this would be a good indication. It would be a good ground to further research seasonal patterns there.
Class 0: folds 1, 2, 3, class 1: folds 4, 5 - tells you how data changed from a given point in time. This would e.g. catch the impact of Covid-19 on the dataset.

What do you think?

This blogpost identifies different types of datashift and provides some ways of tackling it.
TD;LR:
There are 3 types of data shifts possible  :

Co-variate shift :

The features between the train and test samples, but the target relation remains the the same.
Solution :
* Univariate or Multivariate resemblance model to identify which features are shifting between the train and test sets.
* SHAP feature importance

Prior Probability Shift :

The feature distributions remain the same but the target changes .
Solution :
*  Visual : Plot the histogram of the target variable.
*  Statistical tests of mean difference (t-test,ANOVA)

Concept Drift :

A concept drift happens where the relations between the input and output variables change. So we are not anymore only focusing on X variables or only the Y variable but on the relations between them e.g situations with seasonality.
Solution :

De-trend the time-series data and work with the stationary part of it.
Use time-series cross validation . Which is what @sbjelogr is mentioning as well .

In terms of Probatus implementation this can form a module, datashift which produces a data shift report . The report covers the above 3 aspects.

Co-variate shift : Identify the columns that have shifted the most and can be dropped.
Prior Probability Shift : Identify the shift and report the statistical results.
Concept Drift : Plot and report the results. We can also plot the target distribution so see both side by side.

@anilkumarpanda That is a great proposal.
It seems like a very large feature though. If we split it into the tree parts and tackle each one separately, and then try to combine using some wrapper that would be doable. For the first point, most can be done using components already available in probatus. For the rest, we would need to use other libraries.
In order to work on it we would probably need involvement of multiple collaborators, and set a more structured way of working on it. Who would like to contribute to that?

I agree with the above points. The feature is a large one and needs to be separated. I will create a separate issues for this one. Linking them to this master issue. sample_similarity module would be the obvious place for implementing this functionality. I can start with the Prior Probability shift.


Use build flag -mod=vendor instead of GO111MODULE=off

Closes #281
Closes #280

@sashayakovtseva
Just to verify, you'd like me to check that:
go1.11 and go1.12 built in $GOPATH works
go1.11 and go1.12 built in $HOME works
Is this correct?

@jscook2345 Yes, that would be great. I checked 1.12, pretty sure 1.11 will work the same, so I downgraded Go version on go.mod file.

ERRO Running error: context loading failed: failed to load program with go/packages: go [list -e -json -compiled=true -test=true -export=false -deps=true -find=false -mod=vendor -- ./...]: exit status 1: build golang.org/x/crypto/openpgp/errors: cannot find module for path golang.org/x/crypto/openpgp/errors

make: *** [lint] Error 3

[vagrant@localhost singularity-cri]$ make
 GO bin/sycri
GOOS=linux go build -mod vendor -tags "selinux seccomp" -o ./bin/sycri ./cmd/server
build golang.org/x/crypto/openpgp/errors: cannot find module for path golang.org/x/crypto/openpgp/errors
make: *** [bin/sycri] Error 1

This required creating a config file so that golangci-lint would use the vendor directory. It also required a newer golangci-lint to use that option in the config (1.17.1)
[vagrant@localhost singularity-cri]$ cat .golangci.yml
run:
  modules-download-mode: vendor

So it looks like that one module is problematic for the build here. It appears in the replace() section of go.mod, but not in the require section. Is that the problem maybe?

@jscook2345 Found this in modules doc:

The go1.11 builds worked for me! Great catch with that module fix.

The go1.12 builds worked as well. Still had to set GO111MODULE=on in $GOPATH.


feat/retain md image links

Unstructured doesn't currently retain markdown image links (like this format). User wants to do document loading through Langchain with Unstructured and keep markdown image links.

+1. It is beneficial to extract the src and alt attributes of an image in Markdown to metadata in certain scenarios. Hope Unstructured can support this.


Repeatedly adding the same node

Description

Fixes #1581

added node checks for TransparencyLogService::remove_authorized_node method
made TransparencyLogService::write_transparency_log method private
extended TransparencyLogService::add_artifact to insert a log record to the database
added according tests

Screenshots (optional)
PR Checklist

[x] I've read the contributing guidelines.
[x] I've read "What is a Good PR?"
[x] I've included a good title and brief description along with how to review them.
[x] I've linked any associated an issue.

Code Contributions

[x] I've run pre-commit.sh (pre-commit.bat) successfully.
[ ] I've run the integrations tests
on the PR branch and all tests passes.

Changes Unknown when pulling 708c4abe274448d11f834d6fa6d9e2d6ed61b09b on dgarus:1581 into ** on pyrsia:main**.

coverage: 49.742% (+0.1%) from 49.645%
when pulling 7e60ecd0859a7acbc0262c61b73b216351cb5f43 on dgarus:1581
into 69ed9324e9a9a51de1a1802ce8b6fe241fd13c9c on pyrsia:main.


tests/input/txt/test_txt.py test_text_to_jpeg fail with wand and imconvert backend.

Related to #113 (read first).
Wand and imconvert are telling they support plain text, but it looks like they don't.
  Wait for command to complete.  If
        the exit code was zero then return, otherwise raise
        CalledProcessError.  The CalledProcessError object will have the
        return code in the returncode attribute.

        The arguments are the same as for the call function.  Example:

        check_call(["ls", "-l"])
        """
        retcode = call(*popenargs, **kwargs)
        if retcode:
            cmd = kwargs.get("args")
            if cmd is None:
                cmd = popenargs[0]
>           raise CalledProcessError(retcode, cmd)
E           subprocess.CalledProcessError: Command '['convert', '/home/mdk/clones/preview-generator/tests/input/txt/the_text.txt', '-layers', 'merge', '/tmp/61d29d63-c745-4b64-bdfa-be883fd1d411.png']' returned non-zero exit status 1.

../../.local/lib/python3.8/subprocess.py:364: CalledProcessError
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> entering PDB >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>

>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> PDB post_mortem (IO-capturing turned off) >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
> /home/mdk/.local/lib/python3.8/subprocess.py(364)check_call()
-> raise CalledProcessError(retcode, cmd)

@JulienPalard Look like part of the problem is related to imagemagick lib tel it support txt file, pdf, and other non-image type but cannot handle them properly.
We may think about making those builder be able to handle those type of file, but as we have clearly better builder for those mimetype, i don't think it's really useful (we may have many bug like encrypted pdf, etc...).
So i suggest first, to fix supported file by imagemagick to remove non-image type that can't be processed same way as other (although imagemagick support them at some point).

created a pr with idea exposed here #153

As imconvert backend is deprecated in favor of wand, we will not solve theses issues.


chore: get rid of todos in locale

Summary

Please summarize your changes, describing what they are and why they were made.

Need to remove the TODO locales
Changelog
- Remove TODO locales

Relevant Issues

Please list any related issues using development keywords.

Closes #4565
Testing
Platforms

Please select any platforms where your changes have been tested.

Desktop

[ ] MacOS
[x] Linux
[ ] Windows

Mobile

[ ] iOS
[ ] Android

Checklist

Please tick all of the following boxes that are relevant to your changes.

[ ] I have followed the contribution guidelines for this project
[ ] I have performed a self-review of my own code
[ ] I have commented my code, particularly in hard-to-understand areas
[ ] I have added or modified tests that prove my changes work as intended
[ ] I have verified that new and existing unit tests pass locally with my changes
[ ] I have verified that my latest changes pass CI workflows for testing and linting
[ ] I have made corresponding changes to the documentation

@nicole-obrien @Tuditi @jvegis Potentially we'll need some more text here to replace the UI:


MM-794: returning proper JSON response from APIs

Summary
returning proper JSON response from APIs
Screenshots

Created a PR on mattermost remote with all these changes hence closing this one


[Bug] With the manual world optimization chunk deletion, structures at chunk edges will have blocks cut off

Like this:

It could (handily?) be mitigated if there was logic to maintain the save flag for the neighboring chunks in a radius, of edited/player visited chunks.
Regardless of feasibility, the mod is still great as is. Thank you!

Interesting bug, thanks for reporting it, and also thanks for suggesting how it could be fixed.
Tho, I am having a bit of a hard time trying to figure out what exactly happened here and what caused it. Usually when a chunk is discarded, it is supposed to be re-generated in the same way it was generated prior to being discarded, so having a cut-off tree appear does confuse me a bit.
Also, I was thinking about a similar thing and worrying it might be an issue when it comes larger strustures like fortresses. Specifically, what if the player puts the "save flag" on one half of a structure, and then discards the other half with the mod. But even in that case, the other half should just re-generate with no issues as far as I know.
So how that tree managed to get cut-off instead of re-generated properly does confuse me. If it is because the tree structure refused to generate its other half in a player-modified chunk, then the leaves in that player-modified chunk should have remained from the previous generation unless they got removed manually?
I guess will try to figure out what the issue could be. In the meantime, you could also let me know how you think this took place and what you did to replicate the issue.
Thanks again and have a great day!

Bad report, it's not affecting structures. That was a poor assumption based on the trees. Just trees.
While this was my original assumption:
I'd guess it would be due to the tree (analogy to a sapling) belonging to the player edited chunk, and while the structure leaves/blocks may happen to go outside the chunk, the root tree place/coordinate is still at the flagged chunk.
Therefore, it won't re-generate the leaves because the origin tree of these leaves hasn't been deleted and thus won't generate itself and thus the leaves for the deleted chunk.

After just trying it on a new 1.19.2 world, no mods, latest forge, it seems to be "randomly" picking chunks and doing something with the tree blocks generation, even if the nearby chunks were left untouched, which is mildly concerning. So maybe forget my fix suggestion because it appears to be a whole other issue now..
*Doesn't happen with the mods auto chunk unflagging, only manual blast?
https://user-images.githubusercontent.com/67803583/226160947-2b73f10e-2db8-4f4a-bf31-5474174e0411.mp4

I will now pin this issue in case anyone else encounters it
If anyone's interested in why it happens, here's why (please click here).
Unfortunately this bug is un-resolvable from my end.
Basically, when Minecraft generates trees at chunk edges next to un-loaded and non-existing chunks, it stores the coordinates and information about those "unfinished' trees on the physical hard drive. The next time you walk close enough to the non-existing chunks next to those trees, the game will retrieve the data about the "unfinished" trees from the hard drive, after which it will "finish" them whenever possible.
The problem is, when removing already previously generated chunks, the trees will go back to being "unfinished", but this time, since they were already generated before, nothing will keep track of them again, resulting in them remaining "unfinished" and "cut-off" after removing unused chunks that are next to them.
This unfortunately, is not possible to fix.


Bug in gffread when indexing fasta files with empty lines

Empty lines between fasta entries in file provided via the -g switch throws error at line 117 in GFastaIndex.cpp
Workaround is either to pre-index file with samtools - handles blank lines fine - or remove blank line in fasta file.

I'm not on the dev team but I suspect they might want to know more about the structure of the input files.
Do they have multiple empty lines in a sequence or just one empty line between entries?

or is the a gap between the label and the sequence (within the bounds of a single entry)

The entries have valid sequence in them, but there is an additional blank space between the end of one entry and the start of the next e.g.
>Seq1
CACTCTACTACTATCATCTTCAACGA

>Seq2
CCGTCATCGTAGTGATGCTAGCTAGCTGTAGCTGA

It's arguable whether that's a valid fasta file, but I think the code could be better written to not assume that two adjacent lines of unequal length is an error, which is essentially what the error in GFastaIndex.cpp is reporting.

Agreed - I'll fix this.

Great. Thanks.

usually if I write custom fasta parsers i just have an early check for lines that are blank (or completely composed of whitespace) and just flat out ignore all blank lines. Its fairly permissive, but it sidesteps problems like this.

The whitespace highlighted a more general issue about line length which is the problem here.


[FormRecognizer] Simplify the samples to get poller results

as we can get the results from pollUntilDone()

Fixes #9475


Fix mutable dataclass defaults

Prevents a ValueError on py3.12

@shahules786 @jjmachan

thanks a lot @yasyf ❤

Hey @yasyf Very interesting & curious at the same time to see you were quick to try out experimental test generation ( we haven't made announcement yet) . Would love to chat and learn more about your interest in it https://cal.com/shahul-ragas/30min

@shahules786 still havent got it working actually, hit a few more bugs that I didn't have time to dive into. ya happy to chat!


ci: add xorgproto dep to Arch build

Arch Linux maintainers are still figuring out whether they should ask
people to explicitely install it or make it a dependency of xcb again.
In the meantime, add it as an explicit dependency. I'll revert this
patch if they decide otherwise.

Thanks!


REG-1710: Add handling of sad path scenarios

Add tests for sad path cases

Potential sad paths:

400 - invalid JSON
404 - unit not found
409 - edit conflict
422 - unprocessable entity (POST JSON does not comply with our model)
500 - internal server error

I have added tests for the mapping of EditStatus -> HTTP Status here and unit tests for patchJson have been added here.


[stable/oauth2-proxy] Update oauth2-proxy image to v3.2.0

What this PR does / why we need it:
Update oauth2-proxy image to v3.2.0
Which issue this PR fixes
(optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close that issue when PR gets merged)

fixes #

Special notes for your reviewer:
Checklist
[Place an '[x]' (no spaces) in all applicable fields. Please remove unrelated fields.]

[x] DCO signed
[x] Chart Version bumped
[x] Variables are documented in the README.md
[x] Title of the PR starts with chart name (e.g. [stable/chart])

/ok-to-test

/lgtm

/lgtm


KE-18993 revert ae skew release r51

What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Please review http://spark.apache.org/contributing.html before opening a pull request.

retest this please


[DispatchCreation] Run preprocessing before elementwise fusion

I think it makes sense to run FusionPreprocessingPass before ElementwiseOpFusionPass because it helps put the IR in a better state for fusion (e.g. interchanging linalg.generic indexing maps). But also, reshapes have been propagated to the edges of the program, which allows the GatherFusionPattern to be more effective.
Fixes compilation error from https://github.com/iree-org/iree/issues/17226#issuecomment-2441200369.

This is the state of the IR (from the linked issue) before reshape propagation:
  %2 = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, affine_map<(d0, d1) -> (d0, d1)>], iterator_types = ["parallel", "parallel"]} ins(%cst : tensor<30522x128xf16>) outs(%1 : tensor<30522x128xf32>) {
  ^bb0(%in: f16, %out: f32):
    %8 = arith.extf %in : f16 to f32
    linalg.yield %8 : f32
  } -> tensor<30522x128xf32>
  %expanded = tensor.expand_shape %2 [[0, 1], [2]] output_shape [1, 30522, 128] : tensor<30522x128xf32> into tensor<1x30522x128xf32>
  %collapsed = tensor.collapse_shape %0 [[0, 1]] : tensor<1x128xi32> into tensor<128xi32>
  %3 = tensor.empty() : tensor<128x128xf32>
  %4 = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0)>, affine_map<(d0, d1) -> (d0, d1)>], iterator_types = ["parallel", "parallel"]} ins(%collapsed : tensor<128xi32>) outs(%3 : tensor<128x128xf32>) {
  ^bb0(%in: i32, %out: f32):
    %8 = arith.index_cast %in : i32 to index
    %9 = linalg.index 1 : index
    %extracted = tensor.extract %expanded[%c0, %8, %9] : tensor<1x30522x128xf32>
    linalg.yield %extracted : f32
  } -> tensor<128x128xf32>

Note that %expanded blocks GatherFusionPattern

It makes sense to me. Just one question, I think it is a prerequisite for element-wise fusion. Perhaps we should also delete the below passes (which are run right before addDispatchRegionCreationPreprocessingPasses), because they are moved into the preprocessing passes. What do you think?
(You probably want to run canonicalizer and cse at the beginning of the pipeline.)
https://github.com/iree-org/iree/blob/e66171aa4c928727a589ad016134f009140c8a03/compiler/src/iree/compiler/DispatchCreation/Passes.cpp#L297-L301

That makes sense to me, I'll move them inside and delete the extra preprocessing

@c-rhodes this should fix the problem you were encountering on https://github.com/iree-org/iree/issues/17226#issuecomment-2441630461

there's a regression in amdgpu_rocm_mi300_gfx942 but I can see this in other PRs so I think it's safe to say it's not because of this PR. I'll go ahead and land the fix, cheers!

This might have regressed VAE decode time on MI250.

Time before was around 317ms: https://github.com/iree-org/iree/actions/runs/11567948617/job/32199348505#step:8:56
Time after is 338ms https://github.com/iree-org/iree/actions/runs/11569362382/job/32227054297#step:8:128

That was also reported in the checks on the PR: https://github.com/iree-org/iree/actions/runs/11561437104/job/32180922269#step:8:128

This might have regressed VAE decode time on MI250.
* Time before was around 317ms: [iree-org/iree/actions/runs/11567948617/job/32199348505#step:8:56](https://github.com/iree-org/iree/actions/runs/11567948617/job/32199348505#step:8:56)

* Time after is 338ms [iree-org/iree/actions/runs/11569362382/job/32227054297#step:8:128](https://github.com/iree-org/iree/actions/runs/11569362382/job/32227054297#step:8:128)

That was also reported in the checks on the PR: iree-org/iree/actions/runs/11561437104/job/32180922269#step:8:128

@ScottTodd thank you for the comment, I didn't realize this was merged. I was going to look into the regressions before merging but don't have a fix yet. This may cause issues for other's PRs so I'll open a revert and re-land once the regressions have been resolved.
I looked into this a bit yesterday and I'm a bit confused why this is causing runtime regressions but no change to dispatch count.

apologies for jumping the gun and landing this one! I noticed the regression but thought I saw the same one on other PRs and disregarded it.

apologies for jumping the gun and landing this one! I noticed the regression but thought I saw the same one on other PRs and disregarded it.

No worries, I also thought it was just being flaky at first :)


pip install issues

Could not find a version that satisfies the requirement jaxlib (from tensor2tensor) (from versions: )
No matching distribution found for jaxlib (from tensor2tensor)
Windows

Tensor2Tensor appears to have a dependency on Jax, which does not currently support Windows.  You can try using the Magenta development environment as described here; unless you're using Transformer you won't need the Tensor2Tensor dependency.


[DOC] : Comments on the different sections

[ ] @rohaan2614  : In the section The Data, subsection Demographic Health Surveys, it would be good to mention the specific datasets(which csv files) that was used to create the bar  graphs or the box plots helps with reproducibility when someone else is reading the doc/code.
[ ] @cmougan : In the section The Data, subsection Night Time Light Data, I have so far not used GEE at all but implemented data download with MODAPS client. Just to clarify was GEE indeed used for some analysis?

@cmougan @rohaan2614 :
Had a quick read of the ReadMe and it looks pretty great! I have opened rest of the issues related to data preparation and I will be working on today and would be coordinating with @GvdDool
My two cents here :
I would also think of the problem as a regression problem and not a classification problem. Previous to using machine learning techniques in this field deterministic spatial interpolation was being used to find the approximation of the function to best predict socio economic index.

@cmougan @GvdDool @rohaan2614  : For the data sections I have added information about the python modules. So you can give your feedback.

Suggestion Night Time Light Data:
After conversion, from hdr (native format) to GeoTIFF, the daily NTL intensity tiles are available for processing. The project area (Continental India) is covered by 7 (or 8) tiles of 10x10 degrees, or 2400x2400 cells. To match the temporal window of the project (2013-2017, 2 years around the DHS 2015 census for India) the total NTL data repository would be more than 1825 data layers (4MB per HDR / 10MB per GeoTiff images). The difference in disk size between HDR and GeoTIFF is the compression and data type, HDR files are optimised for storage, and will contain besides the light intensity values also the data quality flags. The spatial resolution of the data is 500m, and similar to the techniques used to match the OSM data to DHS clusters, a method will have to developed to aggregate the NTL to the appropriate DHS cluster. It would be recomended to use the same weighted vonoroi polygons when doing the "Zonal Statistics"; a spatial operation designed to retrieve key statistics by area (polygons) from raster images.

@GvdDool feel free to add it to the Readme!

OSM data:
Clusters, not shared by both dataset - could please explain, it is not clear why a DHS cluster should be removed, they are based on the DHS data.

OSM data:
Clusters, not shared by both dataset - could please explain, it is not clear why a DHS cluster should be removed, they are based on the DHS data.

@cmougan : This is something perhaps added by you.

@GvdDool feel free to add it to the Readme!

@cmougan I rather not add/edit directly in the readme - normally I work in a gdoc with comments, which makes collaboration easier.

Suggestion Night Time Light Data:
After conversion, from hdr (native format) to GeoTIFF, the daily NTL intensity tiles are available for processing. The project area (Continental India) is covered by 7 (or 8) tiles of 10x10 degrees, or 2400x2400 cells. To match the temporal window of the project (2013-2017, 2 years around the DHS 2015 census for India) the total NTL data repository would be more than 1825 data layers (4MB per HDR / 10MB per GeoTiff images). The difference in disk size between HDR and GeoTIFF is the compression and data type, HDR files are optimised for storage, and will contain besides the light intensity values also the data quality flags. The spatial resolution of the data is 500m, and similar to the techniques used to match the OSM data to DHS clusters, a method will have to developed to aggregate the NTL to the appropriate DHS cluster. It would be recomended to use the same weighted vonoroi polygons when doing the "Zonal Statistics"; a spatial operation designed to retrieve key statistics by area (polygons) from raster images.

@GvdDool : Thanks, I will incorporate this change. The bit on aggregating NTL to appropriate DHS cluster, I will introduce in the Data Preparation sub-section since this is where I would introduce the voronoi / weighted voronoi approach for the first time.

OSM data:
Clusters, not shared by both dataset - could please explain, it is not clear why a DHS cluster should be removed, they are based on the DHS data.

I did not, it needs to be updated

Suggestion Night Time Light Data:
After conversion, from hdr (native format) to GeoTIFF, the daily NTL intensity tiles are available for processing. The project area (Continental India) is covered by 7 (or 8) tiles of 10x10 degrees, or 2400x2400 cells. To match the temporal window of the project (2013-2017, 2 years around the DHS 2015 census for India) the total NTL data repository would be more than 1825 data layers (4MB per HDR / 10MB per GeoTiff images). The difference in disk size between HDR and GeoTIFF is the compression and data type, HDR files are optimised for storage, and will contain besides the light intensity values also the data quality flags. The spatial resolution of the data is 500m, and similar to the techniques used to match the OSM data to DHS clusters, a method will have to developed to aggregate the NTL to the appropriate DHS cluster. It would be recomended to use the same weighted vonoroi polygons when doing the "Zonal Statistics"; a spatial operation designed to retrieve key statistics by area (polygons) from raster images.

@GvdDool : Thanks, I will incorporate this change. The bit on aggregating NTL to appropriate DHS cluster, I will introduce in the Data Preparation sub-section since this is where I would introduce the voronoi / weighted voronoi approach for the first time. Hope this is alright

Sure, that would be the perfect place to link the sections and methods.

OSM data:
Clusters, not shared by both dataset - could please explain, it is not clear why a DHS cluster should be removed, they are based on the DHS data.

@cmougan : This is something perhaps added by you.

I added that. It was misunderstanding. Feel free to edit.

[ ]  @rohaan2614  : In the section The Data, subsection Demographic Health Surveys, it would be good to mention the specific datasets(which csv files) that was used to create the bar  graphs or the box plots helps with reproducibility when someone else is reading the doc/code.
[ ]  @cmougan : In the section The Data, subsection Night Time Light Data, I have so far not used GEE at all but implemented data download with MODAPS client. Just to clarify was GEE indeed used for some analysis?

Its just a file and that's DHS_CLEAN.csv.
I have mentioned and copied the notebook in the repo so I hope there won't be reproducibility issues.

[x]   @rohaan2614  : In the section The Data, subsection Demographic Health Surveys, it would be good to mention the specific datasets(which csv files) that was used to create the bar  graphs or the box plots helps with reproducibility when someone else is reading the doc/code.
[ ]   @cmougan : In the section The Data, subsection Night Time Light Data, I have so far not used GEE at all but implemented data download with MODAPS client. Just to clarify was GEE indeed used for some analysis?

Its just a file and that's DHS_CLEAN.csv.
I have mentioned and copied the notebook in the repo so I hope there won't be reproducibility issues.

But this DHS_CLEAN.csv is not present in this repository and neither is the procedure on how this was obtained.

[x]    @rohaan2614  : In the section The Data, subsection Demographic Health Surveys, it would be good to mention the specific datasets(which csv files) that was used to create the bar  graphs or the box plots helps with reproducibility when someone else is reading the doc/code.
[ ]    @cmougan : In the section The Data, subsection Night Time Light Data, I have so far not used GEE at all but implemented data download with MODAPS client. Just to clarify was GEE indeed used for some analysis?

Its just a file and that's DHS_CLEAN.csv.
I have mentioned and copied the notebook in the repo so I hope there won't be reproducibility issues.

But this DHS_CLEAN.csv is not present in this repository and neither is the procedure on how this was obtained.
https://drive.google.com/file/d/1IL47jJQeILo_1AElKHOS-ULfRB-7-Y5k/view

I went back to the slack discussions and found the following thread:
Rong Fang  1:47 AM
Hi, I had went through the notebooks of the coding pipeline. I had some questions, most are about data preparation and aggregation. I appreciate it if someone in charge could answer the questions.
Rong Fang  2:10 AM
Data sources:
What are Census (scraped_india_census2011_housing.csv) and DHS (DHS-PROCESSED-CLEAN.csv) datasets? How are they connected? Are they from different sources? What are the spatial scales of them correspondingly?
I saw the original file (IAGC72FL.csv) is at household level (2869043 houses), where was the file acquired? How is this IAGC72FL.csv file connected with the census file scraped_india_census2011_housing.csv?
Data label and aggregation:
I didn’t see the census dataset (processed_census_2011.csv) was used in the deep learning modeling process, so what is the purpose of labeling it using k-mean clustering? Or was it used in another modeling process?
As the size, population and number of households vary in different districts, should some features (e.g. materials of the roof, cooking facilities in processed_census_2011.csv) used in the k-mean clustering be averaged by the district size, number of households or whatever the units the features represent?
How was data (IAGC72FL.csv) aggregated from the household level (2869043 houses) to the household cluster level (28524 clusters)? By the variable dhs_house['hv001']? How was the variable 'hv001' coded?
Does the geo-coordinate in file (DHS-PROCESSED-CLEAN.csv) mark the centers of the household clusters? Whether all the household clusters have the similar area? If so, how big the area is?
Whether each household cluster (DHS-PROCESSED-CLEAN.csv) is only connected with one satellite image by the geo coordinate? If the image resolution is 10m X 10m, does each image cover the entire are of household cluster?
Within each household cluster (A row in DHS-PROCESSED-CLEAN.csv), whether all the households have the same Toilet Facility, Roof Material, Electricity, Cooking Fuel, Drinking Water as they were labeled?
Please let me know if the questions are clear enough? They are important for us to understand the whole process and to justify the methods. Thank you. :smiley:
Rehab Emam  5:44 AM
Please Rong, have some time to understand the project or read reports because all the answers are already written there and are also in code.

Census Was used in first phase as a ground truth with landsat images. DHS is used in second phase as ground truth to sentinel images.
They were chose like that after research and reasons behind that are in Appendix of the report.
And if you Google them, you'd find they are not related at all as they are surveys done by different organizations.
Also they were not used together in the same code.
There is no estimation of area of a household in DHS data, where did you find that?
Also census was done in 2011 and DHS was done in 2015, they can't be used together in the same estimation.
The files you mentioned with clusters are the files provided by the organizations on their websites. We have done some data wrangling and cleaning to get the final clean csv files. The code is in github. And why we chose those metrics was done after reading a huge number of papers suggesting those metrics to estimate economic well-being, like Stanford paper and quality of life, they are in references section, please have a look.
The geo data are the center of households, there is no area given if you look at the data.
The resolution of sentinel images is 10x10 m, means a Pixel corresponds to an area of 10m squared, it has nothing to do with the area we chose to get our images, which is 4x4 km as you can see in the code.
The metrics like toilet facility or roof material  are categorical, there are many categories out there, there is a dashboard in the report and presentation showing all categories of the metrics and of course not all households have the same category but some households have gasoline as a cooking fuel and some have wood as cooking fuel, etc.
Thank you

@GvdDool : Thank you, in the meanwhile I also looked into Omdena's code and found the python notebook which does the cleaning. In this case I had few questions and concerns for the whole team :

We cannot put the DHS_CLEANED.csv on the git repository due to the data sharing restriction we had to sign on to when downloading this csv file.
Moreover if we use this file in this repository we should ask Omdena's permission for this. I will also check at my side through my commits if I am using this file somewhere.

@GvdDool : Thank you, in the meanwhile I also looked into Omdena's code and found the python notebook which does the cleaning. In this case I had few questions and concerns for the whole team :

We cannot put the DHS_CLEANED.csv on the git repository due to the data sharing restriction we had to sign on to when downloading this csv file.
Moreover if we use this file in this repository we should ask Omdena's permission for this. I will also check at my side through my commits if I am using this file somewhere.

#sharing restriction: I am almost 99% sure you are correct, access to the original DHS data was protected with a non-distribute agreement, and regarding your second point, Omdena is working for WRI (which holds the IP), so we should ask WRI if we can use the file. My recommendation would be to add a link to the DHS site and don't mention the cleaning (especially because we were not sure this was done correctly).

@GvdDool : Thank you, in the meanwhile I also looked into Omdena's code and found the python notebook which does the cleaning. In this case I had few questions and concerns for the whole team :

We cannot put the DHS_CLEANED.csv on the git repository due to the data sharing restriction we had to sign on to when downloading this csv file.
Moreover if we use this file in this repository we should ask Omdena's permission for this. I will also check at my side through my commits if I am using this file somewhere.

#sharing restriction: I am almost 99% sure you are correct, access to the original DHS data was protected with a non-distribute agreement, and regarding your second point, Omdena is working for WRI (which holds the IP), so we should ask WRI if we can use the file. My recommendation would be to add a link to the DHS site and don't mention the cleaning (especially because we were not sure this was done correctly).

Just putting this on the table in case this helps:
I got myself direct access to raw DHS data from DHS themselves back in February but it would have need a lot of work to reach the clean data stage so we took this short cut.
WRI does not have direct access to the raw data. Omdena acquired it on their behalf and the non-distribute agreement exitts between Omdena and DHS.

@GvdDool : Thank you, in the meanwhile I also looked into Omdena's code and found the python notebook which does the cleaning. In this case I had few questions and concerns for the whole team :

We cannot put the DHS_CLEANED.csv on the git repository due to the data sharing restriction we had to sign on to when downloading this csv file.
Moreover if we use this file in this repository we should ask Omdena's permission for this. I will also check at my side through my commits if I am using this file somewhere.

#sharing restriction: I am almost 99% sure you are correct, access to the original DHS data was protected with a non-distribute agreement, and regarding your second point, Omdena is working for WRI (which holds the IP), so we should ask WRI if we can use the file. My recommendation would be to add a link to the DHS site and don't mention the cleaning (especially because we were not sure this was done correctly).

So this is what I will do then. I will scan through the repository a little later today, to fix this issue.

@GvdDool : Thank you, in the meanwhile I also looked into Omdena's code and found the python notebook which does the cleaning. In this case I had few questions and concerns for the whole team :

We cannot put the DHS_CLEANED.csv on the git repository due to the data sharing restriction we had to sign on to when downloading this csv file.
Moreover if we use this file in this repository we should ask Omdena's permission for this. I will also check at my side through my commits if I am using this file somewhere.

#sharing restriction: I am almost 99% sure you are correct, access to the original DHS data was protected with a non-distribute agreement, and regarding your second point, Omdena is working for WRI (which holds the IP), so we should ask WRI if we can use the file. My recommendation would be to add a link to the DHS site and don't mention the cleaning (especially because we were not sure this was done correctly).

Just putting this on the table in case this helps:
I got myself direct access to raw DHS data from DHS themselves back in February but it would have need a lot of work to reach the clean data stage so we took this short cut.
WRI does not have direct access to the raw data. Omdena acquired it on their behalf and the non-distribute agreement exitts between Omdena and DHS.

ok. then we just refer to that.

[ ]  @rohaan2614  : In the section The Data, subsection Demographic Health Surveys, it would be good to mention the specific datasets(which csv files) that was used to create the bar  graphs or the box plots helps with reproducibility when someone else is reading the doc/code.
[x]  @cmougan : In the section The Data, subsection Night Time Light Data, I have so far not used GEE at all but implemented data download with MODAPS client. Just to clarify was GEE indeed used for some analysis?

We only have what you did here

@GvdDool : Thank you, in the meanwhile I also looked into Omdena's code and found the python notebook which does the cleaning. In this case I had few questions and concerns for the whole team :

We cannot put the DHS_CLEANED.csv on the git repository due to the data sharing restriction we had to sign on to when downloading this csv file.
Moreover if we use this file in this repository we should ask Omdena's permission for this. I will also check at my side through my commits if I am using this file somewhere.

#sharing restriction: I am almost 99% sure you are correct, access to the original DHS data was protected with a non-distribute agreement, and regarding your second point, Omdena is working for WRI (which holds the IP), so we should ask WRI if we can use the file. My recommendation would be to add a link to the DHS site and don't mention the cleaning (especially because we were not sure this was done correctly).

Just putting this on the table in case this helps:
I got myself direct access to raw DHS data from DHS themselves back in February but it would have need a lot of work to reach the clean data stage so we took this short cut.
WRI does not have direct access to the raw data. Omdena acquired it on their behalf and the non-distribute agreement exitts between Omdena and DHS.

ok. then we just refer to that.

Thought about this again: anyone whose reproducing our work will need the DHS_CLEAN.csv so what do we do about that?
A suggestion comes to mind: we could clone their notebook and rewrite the code but it doesn't seem very 'neat'.

@GvdDool : Thank you, in the meanwhile I also looked into Omdena's code and found the python notebook which does the cleaning. In this case I had few questions and concerns for the whole team :

We cannot put the DHS_CLEANED.csv on the git repository due to the data sharing restriction we had to sign on to when downloading this csv file.
Moreover if we use this file in this repository we should ask Omdena's permission for this. I will also check at my side through my commits if I am using this file somewhere.

#sharing restriction: I am almost 99% sure you are correct, access to the original DHS data was protected with a non-distribute agreement, and regarding your second point, Omdena is working for WRI (which holds the IP), so we should ask WRI if we can use the file. My recommendation would be to add a link to the DHS site and don't mention the cleaning (especially because we were not sure this was done correctly).

Just putting this on the table in case this helps:
I got myself direct access to raw DHS data from DHS themselves back in February but it would have need a lot of work to reach the clean data stage so we took this short cut.
WRI does not have direct access to the raw data. Omdena acquired it on their behalf and the non-distribute agreement exitts between Omdena and DHS.

ok. then we just refer to that.

Thought about this again: anyone whose reproducing our work will need the DHS_CLEAN.csv so what do we do about that?
A suggestion comes to mind: we could clone their notebook and rewrite the code but it doesn't seem very 'neat'.

The reproduction will be difficult, even for us, when trying to recreate the DHS_CLEAN file, because rewriting the code doesn't guarantee identical results. @cmougan, how important is this in the report, would a simple flow diagram be enough (if there is still time to produce a diagram)?


Fixes in flutter framework code to address the mixin issue raised in Dart issue 31984

Addresses the flutter framework part of the issue raised in https://github.com/dart-lang/sdk/issues/31984.
This pulls all the relevant changes from https://github.com/flutter/flutter/pull/14327 without the generic type changes at the mixin application sites.


Basic Lstm cell giving NAN loss and 0 acuraccy.

Environment info
Operating System: Ubuntu 14.04
Installed version of CUDA and cuDNN:  7.5 cudnnv4.0
(please attach the output of ls -l /path/to/cuda/lib/libcud*):
-rw-r--r-- 1 root root 189170 Mär 29 12:20 /usr/local/cuda/lib/libcudadevrt.a
lrwxrwxrwx 1 root root     16 Mär 29 12:20 /usr/local/cuda/lib/libcudart.so -> libcudart.so.7.5
lrwxrwxrwx 1 root root     19 Mär 29 12:20 /usr/local/cuda/lib/libcudart.so.7.5 -> libcudart.so.7.5.18
-rwxr-xr-x 1 root root 311596 Mär 29 12:20 /usr/local/cuda/lib/libcudart.so.7.5.18
-rw-r--r-- 1 root root 558020 Mär 29 12:20 /usr/local/cuda/lib/libcudart_static.a

If installed from binary pip package, provide:

Which pip package you installed. sudo pip install --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.7.1-cp27-none-linux_x86_64.whl
The output from python -c "import tensorflow; print(tensorflow.version)".

I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcurand.so locally
0.7.1

Hi,
I had modified this code to accept an input 4096 vector with 16 time steps.
and changed very little.
The loss is always nan and acuraccy 0.
I have tried several combinations of Learningrate/batchsize/optimizers with no change.
Here Is my code.
Output
Iter 640, Minibatch Loss= nan, Training Accuracy= 0.75000
Testing Accuracy: 0.75
Iter 1280, Minibatch Loss= nan, Training Accuracy= 0.75000
Testing Accuracy: 0.0
Iter 1920, Minibatch Loss= nan, Training Accuracy= 0.00000
Testing Accuracy: 0.0
Iter 2560, Minibatch Loss= nan, Training Accuracy= 0.01562
Testing Accuracy: 0.0
Iter 3200, Minibatch Loss= nan, Training Accuracy= 0.01562
Testing Accuracy: 0.0
Iter 3840, Minibatch Loss= nan, Training Accuracy= 0.00000
Testing Accuracy: 0.0
Iter 4480, Minibatch Loss= nan, Training Accuracy= 0.03125
Testing Accuracy: 0.0
I tensorflow/core/common_runtime/gpu/pool_allocator.cc:244] PoolAllocator: After 4696 get requests, put_count=4701 evicted_count=1000 eviction_rate=0.212721 and unsatisfied allocation rate=0.21678
I tensorflow/core/common_runtime/gpu/pool_allocator.cc:256] Raising pool_size_limit_ from 256 to 281
Iter 5120, Minibatch Loss= nan, Training Accuracy= 0.00000
Testing Accuracy: 0.0
Iter 5760, Minibatch Loss= nan, Training Accuracy= 0.00000
Testing Accuracy: 0.0
Iter 6400, Minibatch Loss= nan, Training Accuracy= 0.00000
Testing Accuracy: 0.015625
Iter 7040, Minibatch Loss= nan, Training Accuracy= 0.00000
Testing Accuracy: 0.0
Iter 7680, Minibatch Loss= nan, Training Accuracy= 0.00000
Testing Accuracy: 0.015625
Iter 8320, Minibatch Loss= nan, Training Accuracy= 0.00000

Any ideas on y this is happening?

not a real issue.. Fixed the problem
closing

How did you end up fixing this? I'm having be same issue

The issue was caused because I initialized the one hot classes as np.array() and didnt fill a few of them with 0 or 1. And as they are randomly initialized. A few of them turned out to be nan.
Just debug your input data to the N/W.


improving footer design and alignments

I would like to contribute to the repo by improving the footer design and alignments to make the ui-ux of the website more readable and apprehensive.
Please assign me this issue under hactoberfest @Karamraj

Hey @Karamraj ,please assign me this issue.


[docs] SliverList named constructor docs mention SliverGrid instead of SliverList

Steps to reproduce

View the docs on SliverList.builder() and SliverList.separated()
See that they reference SliverGrid

Expected results
Both the SliverList.builder() and SliverList.separated() should only mention SliverList.
Actual results
  /// A sliver that places multiple box children in a linear array along the main
  /// axis.
  ///
  /// This constructor is appropriate for sliver lists with a large (or
  /// infinite) number of children because the builder is called only for those
  /// children that are actually visible.
  ///
  /// Providing a non-null `itemCount` improves the ability of the [SliverGrid]
  /// to estimate the maximum scroll extent.
  ///
  /// `itemBuilder` will be called only with indices greater than or equal to
  /// zero and less than `itemCount`.
  ///
  /// {@macro flutter.widgets.ListView.builder.itemBuilder}
  ///
  /// {@macro flutter.widgets.PageView.findChildIndexCallback}
  ///
  /// The `addAutomaticKeepAlives` argument corresponds to the
  /// [SliverChildBuilderDelegate.addAutomaticKeepAlives] property. The
  /// `addRepaintBoundaries` argument corresponds to the
  /// [SliverChildBuilderDelegate.addRepaintBoundaries] property. The
  /// `addSemanticIndexes` argument corresponds to the
  /// [SliverChildBuilderDelegate.addSemanticIndexes] property.
  ///
  /// {@tool snippet}
  /// This example, which would be provided in [CustomScrollView.slivers],
  /// shows an infinite number of items in varying shades of blue:
  ///
  /// ```dart
  /// SliverList.builder(
  ///   itemBuilder: (BuildContext context, int index) {
  ///     return Container(
  ///       alignment: Alignment.center,
  ///       color: Colors.lightBlue[100 * (index % 9)],
  ///       child: Text('list item $index'),
  ///     );
  ///   },
  /// )
  /// ```
  /// {@end-tool}
  SliverList.builder({
   // ...
  });

Code sample
Code sample
[Paste your code here]

Screenshots or Video

Screenshots / Video demonstration
[Upload media here]

Logs
Logs
[Paste your logs here]

Flutter Doctor output
Doctor output
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    • Upstream repository git@github.com:navaronbracke/flutter.git
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    • Framework revision 5874a72aa4 (12 days ago), 2024-08-20 16:46:00 -0500
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      Studio.app/Contents/jbr/Contents/Home/bin/java
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    • Xcode at /Applications/Xcode.app/Contents/Developer
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      🔨 https://plugins.jetbrains.com/plugin/6351-dart
    • Java version OpenJDK Runtime Environment (build
      17.0.10+0-17.0.10b1087.21-11572160)

[✓] VS Code (version 1.92.2)
    • VS Code at /Applications/Visual Studio Code.app/Contents
    • Flutter extension version 3.94.0

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    • iPhone Xs (mobile) • A1C65549-1101-4825-B9ED-41E7C098ACD5 • ios
      • com.apple.CoreSimulator.SimRuntime.iOS-17-5 (simulator)
    • macOS (desktop)    • macos                                • darwin-x64
      • macOS 14.6.1 23G93 darwin-x64
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      • Google Chrome 128.0.6613.113

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• No issues found!

Similar issue exists for SliverFixedExtentList.builder & SliverVariedExtentList.builder as well. Shall we track them here only @danagbemava-nc or a new issue?


[Feature] Add a alert notice to redirect for development when unauthorized

Relevant template
refarch-frontend
Problem description (optional)
The vite dev server is not capable of handling authorization with KeyCloak (even not when proxying).
This means the developer has to navigate to the URL of the API-Gateway to get a valid SSO session and then return to the Vite dev server to start developing.
Desired solution
The problem can be improved by providing the user with a custom alert with the missing SSO session through the Vite proxy. This alert should then be able to open a new tab automatically to have the developer get a SSO session.
Considered alternatives (optional)

Additional context (optional)
No response
No duplicate

[X] I confirm that this issue is not a duplicate

Code of Conduct

[X] I agree to follow this project's Code of Conduct

https://github.com/it-at-m/refarch/issues/99 needs to be done first before this issue can be implemented. Setting to Blocked until resolved.


wip: untangling asm package

@ethersproject/asm doesn't bundle for browsers due to some use of path and other node-specific packages, for functionality we don't need.
Plan right now is to vendor a minimal subset (probably just opcode definitions, unless I end up regenerating them from elsewhere) and do the disassembling manually, which we can build lookups on the opcodes whatsabi actually needs.

Obsoleted by #5


Class timing conflict bug

When a student gets deleted, the available time slots does not get updated.
ie:
edit 2 dt/2022-10-12 1300-1400
delete 2
edit 1 dt/2022-10-12 1300-1400

will yield There is a conflict between the class timings when in reality there shouldn't be after 2's deletion.

Overriden by #113


Clean up ports in .gitpod.yml

The Problem/Issue/Bug:
Many ports belong to previous setup that is no longer needed in current ddev workspace in Gitpod.
Each port that is defined in .gitpod.yml, is added to the list of ports, and can be confusing for users -

How this PR Solves The Problem:
Manual Testing Instructions:
Automated Testing Overview:

Related Issue Link(s):
Release/Deployment notes:

I opened this by mistake, here's the correct PR - https://github.com/rfay/ddev/pull/13


gocd-server VOLUME /var/go makes no sense

TL;DR
Remove /etc/go/ and /var/go from gocd-server Dockerfile.gocd-server as in it's current state it doesn't allow use of gocd/gocd-server as a base image which can be configured (e.g., cruise-config.xml, ssh keys for go user, etc.)
I imagine the sorts of files one would put into /var/go would be configuration related. For example, I am using the GoCD SCM plugin for GitHub. For GoCD to pull code from GitHub you have to have a private key in the gocd-server Docker container. As the server is running as the unix go user the logical location is /var/go/.ssh/id_rsa with the public half of the key pair in GitHub. The typical ways you would get the private key into the gocd-server docker image or container are as follows:

docker run -d -v id_rsa:/var/go/.ssh/id_rsa gocd/gocd-server
Build a custom image FROM gocd/gocd-server with the private key copied into position

Option one will not work as the owner of /var/go/.ssh/id_rsa will be root. Option two gives us the flexibility of changing the id_rsa owner and permission (i.e, go user owned and 600) so SSH works correctly. But this line from Dockerfile.gocd-server is causing issues:
VOLUME ["/var/lib/go-server", "/var/log/go-server", "/etc/go", "/go-addons", "/var/go"]

Docker data volumes are intended for data not configs which often need to be dynamically modified. Here is an example of what happens if you try to use gocd/gocd-server as a base image and modify /var/go
FROM gocd/gocd-server:16.1.0

RUN mkdir /var/go/.ssh \
    && ls -al

$ docker version
Client:
 Version:      1.8.3
 API version:  1.20
 Go version:   go1.4.2
 Git commit:   cedd534-dirty
 Built:        Tue Feb  2 13:28:10 UTC 2016
 OS/Arch:      linux/amd64

Server:
 Version:      1.8.3
 API version:  1.20
 Go version:   go1.4.2
 Git commit:   cedd534-dirty
 Built:        Tue Feb  2 13:28:10 UTC 2016
 OS/Arch:      linux/amd64

$ docker build -t foo .
Sending build context to Docker daemon 10.24 kB
Step 1 : FROM gocd/gocd-server:16.1.0
 ---> f9088466c94b
Step 2 : RUN mkdir /var/go/.ssh     && ls -al /var/go/
 ---> Running in 07ccb25529ea
total 48
drwxr-xr-x.  3 go   go   4096 Feb 13 00:07 .
drwxr-xr-x. 12 root root 4096 Feb 12 22:52 ..
-rw-r--r--.  1 go   go    220 Apr  9  2014 .bash_logout
-rw-r--r--.  1 go   go   3637 Apr  9  2014 .bashrc
-rw-r--r--.  1 go   go    675 Apr  9  2014 .profile
drwxr-xr-x.  2 root root 4096 Feb 13 00:07 .ssh
 ---> 829bb624192e
Removing intermediate container 07ccb25529ea
Successfully built 829bb624192e

$ docker run -it --rm foo bash
root@70e85e684ff2:/tmp# ls -al /var/go/
total 40
drwxr-xr-x.  2 go   go   4096 Feb 13 00:07 .
drwxr-xr-x. 12 root root 4096 Feb 12 22:52 ..
-rw-r--r--.  1 go   go    220 Apr  9  2014 .bash_logout
-rw-r--r--.  1 go   go   3637 Apr  9  2014 .bashrc
-rw-r--r--.  1 go   go    675 Apr  9  2014 .profile

Docker issue #3639 pinpoints this problem. From the sound of things in the issue VOLUME is behaving correctly.
To repeat, directories used for configs such as /etc/go and /var/go should not be declared in a base image with VOLUME as they can not be modified by another Dockerfile that inherits from the base image as instructions like RUN (e.g., RUN mkdir /var/go/.ssh) will have no affect.

#24 submitted

Any update on this issue from the Thought Works folks?

+1

+1

I'm also having an issue that "/var/go" is exposed as a VOLUME and I cannot easily copy my ssh keys or change any configuration in there.
👍

Closing. This has changed significantly over time. Also, there is no VOLUME definition now.


Make it compatible with the Experimental gamemode

Would you be able to get it working/optimised  the the Experimental game mode please http://www.agarioguide.com/game-mode-experimental/

I'm not sure what you want, you already can join that mode with the bot.

Yet, but I was wanting it more optimised for that game mode, e.g tends to stay more around the red spikes to get bigger faster and push other players into bigger players, all that sort of thing

It sounds like you want me to write a completely new bot and then maintain both his one and the new one.

His one? Im a bit confused. All im asking is can you add in a option so if the "Experimental" game mode is selected, the bot will run around until it finds a spiky red ball and then hover around that area collecting the dots it spits out

I'd rather just focus on FFA. Everything in experimental mode will just get changed anyway. If I do that, I'll just end up writing code that becomes obsolete everything the mode changes.

Fair enough


matrix_client/client.py: Remove room from rooms dict on leave event

I guess this doesn't include everything we should do on leave events, but at least it makes join and leave flows more symmetric and have a more updated rooms status.
When receiving a leave event, we should remove the room from our rooms
dictionary since it is no longer meaningful for us.
This fix also makes join and leave events more symmetric.

Signed-off-by: Gal Pressman<EMAIL_ADDRESS>

Ok to test

LGTM


feat: Vmix preset actions

What kind of change does this PR introduce? (Bug fix, feature, docs update, ...)
Feature

What is the current behavior? (You can also link to an open issue here)
No Vmix preset control

What is the new behavior (if this is a feature change)?
Vmix presets can be loaded and saved via TSR actions

Other information:

Codecov Report
Patch coverage: 100.00% and project coverage change: +69.29 :tada:

Comparison is base (7bb78ed) 30.70% compared to head (cd01787) 100.00%.

:mega: This organization is not using Codecov’s GitHub App Integration. We recommend you install it so Codecov can continue to function properly for your repositories. Learn more
Additional details and impacted files
@@               Coverage Diff               @@
##           release49      #247       +/-   ##
===============================================
+ Coverage      30.70%   100.00%   +69.29%
===============================================
  Files             70        30       -40
  Lines           8713       569     -8144
  Branches        2206        62     -2144
===============================================
- Hits            2675       569     -2106
+ Misses          5506         0     -5506
+ Partials         532         0      -532

Impacted Files
Coverage Δ

...meline-state-resolver-types/src/generated/index.ts
100.00% <100.00%> (ø)

...imeline-state-resolver-types/src/generated/vmix.ts
100.00% <100.00%> (ø)

packages/timeline-state-resolver-types/src/vmix.ts
100.00% <100.00%> (ø)

...state-resolver/src/integrations/vmix/connection.ts

...line-state-resolver/src/integrations/vmix/index.ts

...e-state-resolver/src/integrations/shotoku/index.ts

...ate-resolver/src/integrations/telemetrics/index.ts

...lver/src/integrations/multiOsc/deviceConnection.ts

...-state-resolver/src/integrations/abstract/index.ts

...ages/timeline-state-resolver/src/devices/device.ts

... and 34 more

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(1.11) Docker gc log fix

High-level description
This is a 1.11 backport of #3710.
Corresponding DC/OS tickets (obligatory)
These DC/OS JIRA ticket(s) must be updated (ideally closed) in the moment this PR lands:

DCOS_OSS-4469 Backport docker-gc log fix

Related tickets (optional)
Other tickets related to this change:
N/A
Checklist for all PRs

[x] Added a comprehensible changelog entry to CHANGES.md or explain why this is not a user-facing change:
[x] Included a test which will fail if code is reverted but test is not. If there is no test please explain here: This makes logs more verbose, which doesn't need a test.
[x] Read the DC/OS contributing guidelines
[x] Followed relevant code rules Rules for Packages and Systemd

Checklist for component/package updates:
If you are changing components or packages in DC/OS (e.g. you are bumping the sha or ref of anything underneath packages), then in addition to the above please also include:

[ ] Change log from the last version integrated (this should be a link to commits for easy verification and review): example
[ ] Test Results: [link to CI job test results for component]
[ ] Code Coverage (if available): [link to code coverage report]

@mesosphere-mergebot bump-ee

@mesosphere-mergebot label ready for review

@gracedo I think that's OK, we use merge trains to make sure that PRs work with the latest changes on the target branch.

@mesosphere-mergebot sync-status

@mesosphere-mergebot label shipit


Fixes Sneakers::Utils#parse_workers for scoped classes. (Fixes #158)

Your solution looks like a better solution, can you include a test example where the existing implementation failed for you? i would like to document that
Thanks!

Ofc. Will do it as soon as I can :+1:

Btw this pattern may be common, i just found this as well https://github.com/cinchrb/cinch/blob/master/lib/cinch/utilities/kernel.rb

I can check those too. The method does work unless the class is scoped.

@AfonsoTsukamoto I think I understand the difference Ruby 2.0 makes your solution better, the solution was made to support 1.9. But since this series of Sneakers no longer supports 1.9 -- you are completely right with locating this change!
Happily accepting this, thanks! :)

Awesome! Still, think there should be a test so the bug doesn't come back. Hope I get some time soon for it :+1:


Download mismatch error when installing esp-idf

After cloning the repo, during ./install.sh esp32, seeing this error WARNING: file size mismatch for ..., expected x, got <x
+ ./install.sh esp32
Detecting the Python interpreter
Checking "python3" ...
Python 3.10.12
"python3" has been detected
Checking Python compatibility
Installing ESP-IDF tools
Current system platform: linux-amd64
Selected targets are: esp32
Installing tools: xtensa-esp-elf-gdb, xtensa-esp32-elf, esp32ulp-elf, openocd-esp32, esp-rom-elfs
Skipping<EMAIL_ADDRESS>(already installed)
Installing<EMAIL_ADDRESS>Downloading https://github.com/espressif/crosstool-NG/releases/download/esp-12.2.0_20230208/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz
Destination: /home/user1/.espressif/dist/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz.tmp
99%WARNING: file size mismatch for /home/user1/.espressif/dist/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz.tmp, expected 67006496, got 66673920
WARNING: Download failure: <urlopen error retrieval incomplete: got only 66673920 out of 67006496 bytes>
WARNING: Failed to download https://github.com/espressif/crosstool-NG/releases/download/esp-12.2.0_20230208/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz to /home/user1/.espressif/dist/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz.tmp
Downloading https://github.com/espressif/crosstool-NG/releases/download/esp-12.2.0_20230208/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz
Destination: /home/user1/.espressif/dist/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz.tmp
99%WARNING: file size mismatch for /home/user1/.espressif/dist/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz.tmp, expected 67006496, got 66685248
WARNING: Download failure: <urlopen error retrieval incomplete: got only 66685248 out of 67006496 bytes>
WARNING: Failed to download https://github.com/espressif/crosstool-NG/releases/download/esp-12.2.0_20230208/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz to /home/user1/.espressif/dist/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz.tmp
Downloading https://github.com/espressif/crosstool-NG/releases/download/esp-12.2.0_20230208/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz
Destination: /home/user1/.espressif/dist/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz.tmp
99%WARNING: file size mismatch for /home/user1/.espressif/dist/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz.tmp, expected 67006496, got 66794880
WARNING: Download failure: <urlopen error retrieval incomplete: got only 66794880 out of 67006496 bytes>
WARNING: Failed to download https://github.com/espressif/crosstool-NG/releases/download/esp-12.2.0_20230208/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz to /home/user1/.espressif/dist/xtensa-esp32-elf-12.2.0_20230208-x86_64-linux-gnu.tar.xz.tmp
ERROR: Failed to download, and retry count has expired
Please make sure you have a working Internet connection.
+ cleanup
+ rm -rf -- /home/user1/Downloads/diy_jade/temp
+ '[' Linux == Linux ']'
+ '[' -n '' ']'

I do indeed have a working internet connection. Need to understand if this is an upstream bug or something to do with my local environment..
67006496 vs 66794880 is 0.32% less than expected file size.

https://github.com/espressif/esp-idf/issues/11157

I saw this error after reinstalling Ubuntu and installing system updates with dist-upgrade


Aggregated city data has study region name 'City' while grid data has 'study_region'

When preparing a formal data dictionary to address #230 I noticed an inconsistency in variable naming, with the study region (or city) data having a variable 'City' for the study region name while the grid data has the same variable but instead called 'study_region'.
To make things simple and consistent, the same name should be used; I think most appropriate is 'study_region' because technically a user could apply the tool to analyse a single neighbourhood or other area if they had appropriate data to support the analysis.
So, just a small thing, but we should amend the _09_urban_covariates script where these city level summaries are constructed that ultimately propagate to the export of the city data to retain the same variable name.
https://github.com/global-healthy-liveable-cities/global-indicators/blob/e642a00b1acc6880c68064f395c302b2dcbce162/process/subprocesses/_09_urban_covariates.py#L72

My only doubt about this is that the 'nice' formatting idea is nice (e.g. using "Study region" instead of "study_region") - but to make that change for the grid data would involve more coding.  Rather than do that, I think i'd sooner just amend the above line to not rename to 'City' so attention can be focused on priorities (metadata, data dictionary, and validation reporting).


Some files are missing in the File Explorer

VSCode Version: 1.37.1
OS Version: MacOS 10.15.6

Steps to Reproduce:
I can't tell the specific steps for now, but I see it after a sequence similar to this one:

Open some project with Git repository.
Move, add, or rename some file (may be, move it into an another project subdir).
Switch to an another branch
See one of the files moved missing in that branch (even though does exist there).

I'll try to put together a more definite set of steps to reproduce in the meantime.

I can not reproduce. Can you reproduce with vscode insiders?
https://code.visualstudio.com/insiders/
Also nice steps would be great. Thanks


Calculate Stake-Weighted Servicer Rewards per PIP-22

Following the guidance in the PIP-22 spec, this PR updates how rewards are calculated:
https://forum.pokt.network/t/pip-22-stake-weighted-servicer-rewards/3101#proof-lifecycle-validation-rewards-calculation-7

@itsnoproblem i will look into what has been done and try making an update


Update README for different Spark/Runner2 product IDs and clarify unprivileged udev/usb setup a little

Thanks. That's great. Do you think it would be worthwhile to change the udev rule to include all the product IDs? Three nearly identical lines should do it.

Yes - I think so. I'll make a PR tomorrow.

I decided I'd just do it. I've checked in a rules file that includes all three lines, so I'll update the README.md file to match and mention the file.

I've updated the README.md file and also added a new rule to Makefile to automate the udev rule and usb group creation.


Using images with different sizes

Describe the bug
It seems in #868 that nerfstudio now supports training nerf with images of different sizes. Still, the following error popped up when I was trying to train nerf on the Waymo Open dataset (with images of size 1920x1080 and 1920x886).
To Reproduce
Steps to reproduce the behavior:
here is my transforms.json:
{
    "camera_model": "OPENCV",
    "k1": 0,
    "k2": 0,
    "p1": 0,
    "p2": 0,
    "frames": [
        {
            "transform_matrix": [
                [ 0.9867326702177505, -0.07891035227867108, 0.14188655266868724, -1220.8189424581687 ],
                [ 0.0712640838307024, 0.9957584074065905, 0.058194711399413526, 10554.48731853961 ],
                [ -0.14587689289506664, -0.04731120778786397, 0.9881708261919773, 16.831 ],
                [ 0.0, 0.0, 0.0, 1.0 ]
            ],
            "./image_0/0000000.png",
            "fl_x": 2059.612,
            "fl_y": 2059.612,
            "cx": 952.4122,
            "cy": 634.5872,
            "w": 1920,
            "h": 1280
        },
        ...
     ]
}

Expected behavior
A clear and concise description of what you expected to happen.
RuntimeError: stack expects each tensor to be equal size, but got [886, 1920, 3] at entry 0 and [1280, 1920, 3] at entry 3

Screenshots
If applicable, add screenshots to help explain your problem.

Any chance you can send me the command you're using to do this? I ask because right now, the only ns-train method that supports multiple camera sizes is the phototourism method, since the collate function we use is specified by the datamanager, with the VariableResDataManagerConfig being the only variation of the vanilla configuration with the collate function that will concatenate images by putting them in a list instead of stacking the raw tensors.
If you're just using the vanilla datamanager, a quick hack to get this to work rn would be to go into the method_configs.py file, and define your own method that is the same as nerfacto or whatever you're planning on using, except you replace the VanillaDataManagerConfig with a VariableResDataManagerConfig (which is simply a subclassed version of the VanillaDataManagerConfig, but with again a collate that will collate by putting images in a list).

I am using the vanilla DataManager. I will try with the configs. Thank you very much!

Party! Let me know if you have any issues with the variable res config, make sure to look at the phototourism method in the method_configs.py file for reference

Replace  the line 107 in nerfstudio/data/utils/nerfstudio_collate.py with return batch seems work well on variable size images.

将nerfstudio/data/utils/nerfstudio_collate.py 中的第 107 行替换 为return batch似乎在可变大小图像上运行良好。

It really works, thank you!


Fix: TF 1.6+ deprecation warnings on fogg generated s3 backend config

TF 1.6 onwards deprecated role_arn in s3 backend config and s3 remote state config blocks:
Potentially affected fogg code:

(not applicable) Generates AWS Provider block (already uses assume_role nested block)
aws_provider.tmpl
which is called here:
https://github.com/vincenthsh/fogg/blob/afa0608fbd5935f9d4be871cef0b9426044eeb8a/templates/templates/component/terraform/fogg.tf.tmpl#L3-L7

(Affected) Fogg code that generates Backend block
https://github.com/vincenthsh/fogg/blob/44abc0f1fe523ec6ec2be7e9a9e1b1f8b3ad0d21/templates/templates/common/backends.tmpl#L10
which is called here:
https://github.com/vincenthsh/fogg/blob/afa0608fbd5935f9d4be871cef0b9426044eeb8a/templates/templates/component/terraform/fogg.tf.tmpl#L64

(Affected) Fogg code that generates Remote State data lookups
https://github.com/vincenthsh/fogg/blob/44abc0f1fe523ec6ec2be7e9a9e1b1f8b3ad0d21/templates/templates/common/backends.tmpl#L28
which is called here:
https://github.com/vincenthsh/fogg/blob/44abc0f1fe523ec6ec2be7e9a9e1b1f8b3ad0d21/templates/templates/component/terraform/remote-states.tf.tmpl#L21

Thanks a lot!


feedback nova resource issue

Feedback index and detail view shows email object instead of just the email address for participant field.

https://github.com/tipoff/bookings/pull/98


Restore version with StaticArrays for concurrent Julia

@Moelf @MasonProtter
50% faster on my machine

I think it can be merged


Is it possible to remove the logo and reduce the container size?

Wonder if the top-left logo is there by designed?

Is it possible to remove it and adjust the width?
It would be nice to be:

Thank you!

They are limited by Teams Message Extension (currently only support Cards)

Teams build-in emoji will add features like this app in the future version.


compute hota from mot challenge 2d in line

Hi, I would like to bring my contribution at Trackeval, this PR has 2 features

I setup a package for Trackeval so it can be imported as import trackeval . It needs to be installed previously, there are two possible ways. The numpy and scipy depencies are embedded :

git clone the repo and run python setup.py install
use pip install git+https://github.com/ATrackerLearner/TrackEval , if the PR is accepted the command line would be pip install git+https://github.com/JonathonLuiten/TrackEval.git .

I implemented a sub-directory compute in order to shorten evaluation method for specific use. Most of time we use HOTA on MOT Challenge 2D file. The use of functions from compute directory are very convenient for people who want to test their tracking system on a specific/private dataset. There is an actual example to run in a script or live interpreter :

>> from trackeval.compute from compute_hota_from_mot_challenge_2d
>> gt_path_list = ['/path1/to/gt1.txt','/path2/to/gt2.txt']
>> sequence_path_list = ['/path3/to/seq_1.txt','/path4/to/seq_2']
>> d  = compute_hota_from_mot_challenge_2d(gt_path_list, sequence_path_list)

gt1.txt and gt2.txt respectively are ground file relative to seq_1.txt and seq_2.txt
.txt file must be MOT Challenge 2D format.
d is the dictionnary given by evaluate function, nothing has been modified.
compute_hota_from_mot_challenge_2d makes all folders and files required to run the trackeval.
Once compute_hota_from_mot_challenge_2d has been executed, it removes the data folder. Also, it still removes the data folder in case of error (see _data_remover decorator in compute_hota_from_mot_challenge_2d.py) .
If the PR is ok, I guess there is a need to add a section in readme.md to indicate how to use quickly HOTA from MOT Challenge 2D format. I believe this script is useful for most of cases since the HOTA is the recommended metric from now. Also a lot of trackers use MOT  Challenge 2D format. I admit, the script from compute are different from what trackeval means to be i.e. a tool to evaluate large amount of trackers on different databases. But I believe this additionnal feature are also very important  for a lot of researchers or engineers in this field.
Ideas for later implementation: I guess the compute folder can be appended by quick script as compute_hota_from_kit_challenge for example. If so, it would need an additionnal utils.py in compute to avoid redondance between different compute_XXX_from_YYY scripts.
For example, the first steps in compute_hota_from_mot_challenge_2d which checks that list are same length or making directory of data/gt/dataset... will be the same regardless of compute_XXX_from_YYY scripts.
Also this PR doesn't modify any files in trackeval - expect the add subdirectory compute, obviously. So it is easily maintenable and is built entire on your trackeval work.
Please contact me at<EMAIL_ADDRESS>if you want to have a long discussion about this PR or anything else. Of course you can review me by github PR tool, also.
Thank you for your attention,
Mathias Réus.

Super awesome stuff!! Thanks a lot for contributing!
I don't have lots of time to dig into all of this now, but hopefully I will next week.
For now here's a few thoughts.
In general I feel this should be 2 PR's because it's contributing 2x different features (having 2 will keep it easier to track changes etc).
Also, for the setup.py stuff, what is the difference between what has been done in #15 from @jvlmdr??
Could you and Jack (@jvlmdr) discuss what's there and then merge the two contributions together, into one PR for this stuff.
I haven't accepted Jack's one yet just because I didn't think it was a priority for people, but if two of you want it then I am happy to accept it in as soon as the two of you agree how it should be and I get a chance to look over it.
In terms of the other contribution (the .compute). I am a little confused by this. What I see is that you would like something that wraps the functionality in scripts/run_mot_challenge_2D_box, but not as a separate script but as a function within trackeval that you can run after installing the package?
This makes sense to me to do, e.g. to abstract most of the stuff from the 'scripts' into a method that can be called.
I do feel thought that this should be 'cleaner' somehow. E.g. instead of
compute_hota_for_motcha(gt_dir, tracker_dir)
maybe it is cleaner if it is
eval_single(dataset, metric, tracker_dir, gt_dir=None)
where the last parameter could just default to the dataset default gt dir.
This to me seems much more clean (then one doesn't need a lot of these such function).
Anyway, let me think on that and I will get back to you next week.
Thanks again for contributing!
Jonathon

Wow thanks for your detailed reply. I agree that your approach might be much cleaner, I will also think about it. If you have any more ideas / details, I'm up!
Yes, I just quickly saw PR #15 and I will take a look on Monday. I'd gladly discuss about it with Jack!

Hi @JonathonLuiten !
This is my final review / commit about the eval_once feature ! I am up to discuss about it.
Have a nice day!
eval_once feature
eval_once.py is a standalone scripts that allows you to use trackeval module in order to eval few files quickly without implementing all directories for the test. User using this script must have write access to the local directory in order to execute eval_once since the script creates any directories needed

Do with this feature

Evaluate few trackers score with different metrics available from trackeval according to dataset type
Evaluate tracker's performances based on few different files

Do not do with this feature

Evaluate a large amount of files by making a long pair_path_list (see below)
Evaluate multiple benchmarks

How it works
User side
eval_once has 3 input args :
- dataset (str): dataset string input. Must be one of the following: KITTI_2D_BOX, KITTI_MOTS, MOT_CHALLENGE_2D, MOTS_CHALLENGE, BDD_100K, DAVIS, TAO, YOUTUBE_VIS.

- metric_list (List[str]): A list of desired strings metric to eval. String should be included into the following set of metrics : HOTA, CLEAR, IDENTITY, COUNT, JANDF, TRACKMAP, VACE.

- pair_path_list (List[List[str, str]]): A list of pair of path to ground truth / tracker result. A pair is a list of two strings. Within each pair, tracker result will be evaluated by trackeval by comparing to corresponding grount truth file.

Execution example
An example would be like this : we evaluate with HOTA, CLEAR and IDF1 metrics 3 pairs of (gt, results) from 3 different sequence from 1 tracker.
from trackeval import eval_once
eval_once(
    "MOT_CHALLENGE_2D",
    ["HOTA", "CLEAR", "IDENTITY"],
    [
        [
            "/path/to/gt1.txt",
            "/path/to/tracker_result1.txt"
        ],
        [
            "/path/to/gt2.txt",
            "/path/to/tracker_result2.txt"
        ],
        [
            "/path/to/gt3.txt",
            "/path/to/tracker_result3.txt"
        ]
    ]

)

In this example, files are in .txt extension, you can replace it by any required extension.
Script Execution
Also there is a data-test.zip to copy in root folder in order to run scripts/run_eval_once.py. This a leightweigted version of data.zip. There are no seqmaps included.
Currently there are some problems with JAndF metric and MOTS format (warning), also TrackMap metric with YouTube_VIS (error). I do not think it's due to eval_once because JAndF works DAVIS format and TrackMap works with TAO.
Also, in order to run the script you need to have all packages including in requirements.txt expect pytest. Also numpy >= 1.20.1 since I got some problems with version below to execute existing scripts / evaluation (see PR #38). Basically this script is not meant to stay on the repo, I wrote it to test eval_once myself and provide a quick way to test for other.
eval_once side
Generate directories and files
eval_once is just a convenient way to make the necessary files. This hierarchy might be cumbersome for few files or in a production chain. eval_once has two advantages : First one line evaluation, second all files and folders are cleaned right after.
Into details we have a custom eval_config file and dataset_config. The eval_config file is the same in any case. The dataset_config is set to match default eval_config from _BaseDataset objects from trackeval.datasets. Then, the script creates everything that needs to exist to build the data folder. Finally, the environnement is evaluated by trackeval
A cleaner way?
The current implementation is okay according to user side. It has a major drawback: it needs write access to current directories, also it calls the OS for writing / editing / removing files. A better way would be to implement eval_once at a deeper level. I mean, directly run the evaluation function without the needs of making folder. It would be faster (no I/O) and mucher cleaner. I do not know if it's possible with current trackeval, also I cannot look at this soon.


Log request and response

Hi!
I want to log every request and response of a connector.
To just log the request I could use something like in the example, but at that early stage there is no response.
Do we have any hook or event that can be used to log request, response and maybe even more information from guzzle (e.g. request time) in one method?

You could use debugRequest and debugResponse methods on a connector I think: https://docs.saloon.dev/digging-deeper/debugging

My understanding of those methods is, that they are more or less a wrapper for the onRequest/onResponse middleware methods. So in this case I would again only be able to log just the request or just the response.
Or am I wrong?
It would be enough to have information about the request somewhere in "onResponse", I would say. But it seems it's not there.

the $response parameter you receive in debugResponse closure is a saloon response class and that class has getRequest()/getPendingRequest()/getPsrRequest() methods

That was way easier than expected.
Thanks a lot! 👍

Thanks for the response @gdebrauwer! Yep this is a good way of logging.


Add note to yujitach-menumeters

To avoid problems akin to https://github.com/caskroom/homebrew-cask/pull/27953#issuecomment-269032440 in the future

Thank you, but an isolated incident does not warrant a comment. Especially since we know by experience that most people won’t read this.

@vitorgalvao Ok, your call


readOnly demo does not work

the demo for readOnly still allows users to edit the date range.

I am unable to edit the range by typing in the input. What browser are you using?

Chrome
Version 69.0.3497.100 (Official Build) (64-bit)

Can you provide a gif? I'm on the same version and am unable to reproduce.

Same issue in my project, readOnly is not working properly in SingleDatePicker.
I tried in two different browsers:

Chrome Version 69.0.3497.100 (Official Build) (64-bit)
Safari Version 12.0 (146<IP_ADDRESS>.9)

I think there may be confusion about what readOnly means. We're treating it as you cannot type in a date, but not that you cannot change it via the calendar. If you want to prevent the user from changing the value, I would use the disabled prop. You could also simply not update the focusedInput prop to accomplish the same thing.

@majapw Yes, I was confused, that's why I deleted mi comment, would be a nice idea to add more documentation about it, I couldn't find any, I inferred it later.

Not a bad idea! :)

This property name is pretty confusing!!


SauceLabs widget in README is not working

Describe the bug
Saucelabs widget in README is not being displayed correctly it should be investigated and updated

Sauce Labs browser matrix seems to be not working, and other frameworks seems to abandon the widget.
Updated README.md to not have it.


Ghosttapping during dialogue

Describe your bug here.
I've used the template dialogue lua script, but during the dialogue, it's still possible to ghost tap and die, thus crashing the game.
Command Prompt/Terminal logs (if existing)
None available

Are you modding a build from source or with Lua?
Lua
What is your build target?
Windows
Did you edit anything in this build? If so, mention or summarize your changes.
Nothing has been changed.

setProperty('inCutscene', true); before starting the dialogue.


Find the source of the mystery ALTO files

Discovered while working on #4189 and #4215: there are ALTO files in the storage service that don't match LIB_WDL_DDS_METS or the S3 sync. Where did they come from? What's their canonical origin?
This also affects https://github.com/wellcometrust/platform/issues/4187, because we can't clean them up if we can't find them!

Another example: b21461375_0001.
This time the storage service has the older file:
        <processingDateTime>2015-12-08T11:50:17</processingDateTime>

and the S3 sync has the newer file:
        <processingDateTime>2016-03-22T02:28:42</processingDateTime>

Closing.


Add a flag for disabling doom-themes' org fixes.

I want a more vanilla doom experience so I really need this module flag to prevent the default org settings from being overwritten.
As you can see, this is my first patch of doom :tada: Please let me know if there is anything else this PR needs.

Thanks for the PR, but I cannot accept it. I am resistant to adding new flags for trivial configuration. i.e. this could be accomplished with a single line of code:
(remove-hook 'doom-load-theme-hook #'doom-themes-org-config)

I also want to avoid setting a precedent where we have flags for similarly trivial configuration. i.e. This could invite PRs for +disable-neotree-config and +disable-treemacs-config flags.

to prevent the default org settings from being overwritten

How are you configuring org? Your private settings should have precedence unless you're applying them before doom-themes (or org) is loaded. i.e. Wrap them in (after! org ...) and ensure you aren't eagerly loading org at startup.

I am resistant to adding new flags for trivial configuration. i.e. this could be accomplished with a single line of code:

This makes sense and in retrospect I agree completely.

(remove-hook 'doom-load-theme-hook #'doom-themes-org-config)

Oh, I see: I can add this in .doom.d/config.el to remove the hook before I load anything. Makes sense.

How are you configuring org?

I have no org configuration: in particular I do not load the org module or execute any org-related code at all (I started my doom conversion by disabling absolutely everything I could).
Thanks for the help!


Why is this password box on easygui showing the characters before anythings typed?

Here is my code, it is supposed to produce a password box for the user to enter their password with hidden characters showing instead of letters. When I run it, the hidden characters are showing even before I've typed anything.
import easygui as eg

message="Enter Password"
title="New User"
fieldNames=["Enter Password"]
fieldVals=eg.passwordbox(message,title,fieldNames)

from:
http://stackoverflow.com/questions/27800574/why-is-this-password-box-on-easygui-showing-the-characters-before-anythings-type

It turns out, this is just a bit of user error.  The default password is shown in asterisks.  Everything seems to be OK


Remove quantity field from SelectItemsView

Description of changes
Fixes #246 by removing the quantity field from the ProductItemsGrid in the SelectItemsView

Good Idea! Thanks :)