fix: Pass schema to chunked parquet reads

Feature or Bugfix

Bugfix

Detail

Passing the schema allows to avoid StopIteration in pyarrow's pa.Table.from_batches(chunks) when reading files with no rows. This will create an empty table using the schema and loading partition columns.

Relates

https://github.com/aws/aws-sdk-pandas/issues/2394

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

AWS CodeBuild CI Report

CodeBuild project: GitHubCodeBuild8756EF16-4rfo0GHQ0u9a
Commit ID: 34dd8ebefea638731ba5d6a59f837573f6664bae
Result: SUCCEEDED
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Reset messages for each mine separately

I created this Pull Request because one of the users requested it. I think the code is not the best and should be improved in the future. I will create a translation for the messages in silent subcommand in a separate Pull Request soon. Everything has been tested by me and I have not noticed any problems.

The saved property isn't being loaded when the mine is loaded at startup.


Downloading the project results in an error

Describe the bug
Downloading the project using the suggested command resulted in an error:
! could not find commit hash for master
To Reproduce
npx degit github:e0ipso/adr-website-example adr
The local version of git is 2.32
Expected behavior
No error
Additional context
The workaround is to specifically point to the main branch in the degit command:
npx degit github:e0ipso/adr-website-example#main .
The degit documentation states that master is the default branch.

According to this commit https://github.com/Rich-Harris/degit/commit/02d3d56d273bf8a5ce7e2bc59c1de17f54976bcc it should have worked. Nonetheless I will update the docs.
Thanks!

https://github.com/Lullabot/gatsby-theme-adr/commit/cfeb507b48173e8b84659ede81a9c5f8ef44dfb3 fixed this.
Thanks again for your contribution :heart:


Fix base class check to allow 'object' type

Fixes #13805.
This PR also changes the apparent type of object to be the empty object type {} instead of the Object type declared in lib.d.ts. It should have been this way in the first place.

👍


Improve failure message: "Expected subject to be %@, not nil"

How to reproduce:
SPEC_BEGIN(OutputSpec)

it(@"could output a better failure message", ^{
    id octocat = nil;
    [[octocat should] equal:@"Octocat is cool."];
});

SPEC_END

Current behavior (output is using 2.0.6):
CouldOutputABetterFailureMessage (OutputSpec) failed:
' could output a better failure message' [FAILED],
expected subject not to be nil

It would be great if the failure message included what the subject was expected to be, i.e.:
CouldOutputABetterFailureMessage (OutputSpec) failed:
' could output a better failure message' [FAILED],
expected subject not to be "Octocat is cool", not nil

Let me know what you think!

Closing this as a "would've been nice to have". :)


All TPU cores create tensorboard logs

🐛 Bug
With TPUs, TestTubeLogger writes many empty tensorboard logs, one log per TPU core except one. This confuses tensorboard and prevents it from updating. This is happening because the logger is created before spawning processes then the logger is replicated in each process.
To Reproduce
Train any model with ptl.Trainer(logger=TestTubeLogger(), num_tpu_cores=8) then check the tf directory, you will find 1 file with real log and 7 empty files.
Expected behavior
Only the main process creates a tensorboard log.
Environment
pytorch-lightning==0.8.5

@lezwon mind have look?

WIll do :]

@ibeltagy mind check it with the latest master?

@Borda, couldn't test it because it appears that master is broken. It runs for a few steps then crashes with the following error. The only thing I changed is switching from release v0.8.5 to master, everything else is the same.
Epoch 1:   1%|█▏                                                                                | 10/1066 [02:07<3:45:12, 12.80s/it, loss=1.645, v_num=0]
Traceback (most recent call last):
  File "scripts/pretrain.py", line 488, in <module>
    main(args)
  File "scripts/pretrain.py", line 482, in main
    trainer.fit(pretrainer)
  File "/home/beltagy/pytorch-lightning/pytorch_lightning/trainer/states.py", line 34, in wrapped_fn
    result = fn(self, *args, **kwargs)
  File "/home/beltagy/pytorch-lightning/pytorch_lightning/trainer/trainer.py", line 1059, in fit
    self.accelerator_backend.train(model)
  File "/home/beltagy/pytorch-lightning/pytorch_lightning/accelerators/tpu_backend.py", line 87, in train
    start_method=self.start_method
  File "/anaconda3/envs/torch-xla-nightly/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 387, in spawn
    _start_fn(0, pf_cfg, fn, args)
  File "/anaconda3/envs/torch-xla-nightly/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 324, in _start_fn
    fn(gindex, *args)
  File "/home/beltagy/pytorch-lightning/pytorch_lightning/accelerators/tpu_backend.py", line 118, in tpu_train_in_process
    trainer.transfer_distrib_spawn_state_on_fit_end(model, mp_queue, results)
  File "/home/beltagy/pytorch-lightning/pytorch_lightning/trainer/distrib_data_parallel.py", line 417, in transfer_distrib_spawn_state_on_fit_end
    if self.distributed_backend.lower() not in ['ddp_spawn', 'ddp_cpu', 'tpu']:
AttributeError: 'NoneType' object has no attribute 'lower'

trying to reproduce with colab tests, but actually I have a problem installing XLA, @zcain117 ?
https://colab.research.google.com/drive/15E3oo3vPsSvLVufU4I6AK2thcXcg2mdW#scrollTo=BHBz1_AnamN_

@lezwon mind taking a look?

I haven't been able to reproduce this issue. Maybe if @ibeltagy could share a notebook I could look into it. :)

Are you testing with num_tpu_cores=8? do you get a single file under the tf directory?

the test is here, but not counting files
https://github.com/PyTorchLightning/pytorch-lightning/blob/c94c0a2b1ee6b444ab1ecf58059e922229d44436/tests/models/test_tpu.py#L74-L88

The test looks good but it is not capturing the issue that multiple tensorboard log files are created and that these files confuse tensoboard

Are you testing with num_tpu_cores=8? do you get a single file under the tf directory?

Yea. I didn't see multiple files.

@ibeltagy mind share a notebook so we can try to reproduce? or see if this issue is still happening on master?

closing this issue for now. Feel free to reopen with an example so we can reproduce!


Bump up version to 0.17.6

Description

Release new minor version of Kedro
Development notes

Checklist

[ ] Read the contributing guidelines
[ ] Opened this PR as a 'Draft Pull Request' if it is work-in-progress
[ ] Updated the documentation to reflect the code changes
[ ] Added a description of this change in the RELEASE.md file
[ ] Added tests to cover my changes


Adding checkboxes

Hi,
I almost completed the checkboxes feature and I wanted your opinion (to see if there any necessary changes I should do.)
I'm still experiencing some difficulties with implementing the Indeterminated state of a checkbox. However I wanted to start the merge process to see that everything else is fine.
As soon as you give me the O.K. I will add tests and documentation.
Thanks,
TMaster.

Hi @rychkog  the PR seems to still have conflicts although I resolved the conflicts.
Can you help please.
Thanks

@TMaster Cool, thanks! I don't have a chance to dive into this feature during these weekends but I'll start looking at it on Monday and give you my feedback ASAP.

HI @rychkog
I finished the indeterminate feature for the tree, you can check it out.
However there is still a little problem and I'm  not sure about my solution.
While developing the feature I needed to check for a parent if one of it's children are checked, and validated it using the node id's. After a while I realized the node doesn't have to have an id which make a crazy behavior when checking a node with no id.
I temporary overcame this problem by checking if the node has a defined id, and if it doesn't I send a message to the console.
How do you recommend to solve this problem?
Thanks,
TMaster
And again, . . I'll add my tests after you approve the feature.

@TMaster Sorry for being silent so long - has lots of work without a chance to dedicate some time to open-source.

I hope you still believe in a bright future of this project :)

@TMaster Had a quick look and overall it is cool - will review in a bit more holistic manner today evening (my time - Eastern European Time (Standard Time))

@TMaster I've added tests, fixed some issues in here https://github.com/valor-software/ng2-tree/pull/211. So will close this one.

Thanks a lot @rychkog .
Sorry about the delay, I have some things I have to close at work. no time for open source :(

No worries - same stuff on my side :)


Non dependent requests into a single JSON file

Also look at #170, if both can be clubbed 👍
Problem Statement
@santhoshTpixler requested for:
Scenarios should be kept as it is. I am looking for a way to place my non dependent requests into a single JSON file. They should not be executed like scenario. They should be executed regardless of the previous test result
{
    "scenarioName": "Do some tasks which are related, but not dependent on each other",
    "ignoreStepFailures": true,
    "steps": [
        {
            "name": "task_1",
            "url": "/api/v1/optics",
            "operation": "POST",
            "request": {
                "headers": {
                    "Authorization": "EONLY",
                    "content-type": "multipart/form-data"
                },
                "queryParams": {
                },
                "body": {
                    "files": [
                        "queryFile:test-data/ocr/xxyy.png"
                    ],
                    "modelType": "crop"
                }
            },
            "assertions": {
                "status": 200
            }
        },
        {
            "name": "task_2",
            "url": "/api/v1/optics",
            "operation": "POST",
            "request": {
                "headers": {
                    "Authorization": "XONLY",
                    "content-type": "multipart/form-data"
                },
                "queryParams": {
                },
                "body": {
                    "files": [
                        "queryFile:test-data/ocr/hello2.png"
                    ],
                    "modelType": "strict"
                }
            },
            "assertions": {
                "status": 200
            }
        },
        {
            "name": "task_3",
            "url": "/api/v1/optics",
            "operation": "POST",
            "request": {
                "headers": {
                    "Authorization": "YONLY",
                    "content-type": "multipart/form-data"
                },
                "queryParams": {
                },
                "body": {
                    "files": [
                        "queryFile:test-data/ocr/hello3.png"
                    ],
                    "modelType": "ocr"
                }
            },
            "assertions": {
                "status": 200
            }
        }
    ]
}

Why it is useful?
In the above example, there are few requests to test the various functions of the same endpoint. They are not dependent on each other, but they should be placed in same JSON for better maintainability. The issue I am facing is, now I can place only scenarios in JSON. I should not place them as scenario, instead they should be like unit tests in a same file

Also, they need not support passing variables from previous response because they are not dependent on each other.

PR https://github.com/authorjapps/zerocode/pull/171 under review.

Feature:

This flag will be applicable only for this JSON scenario file
It will also notify the step failure, but it will go to the next steps and execute
Report will have as usual Failed and Passed report.
You can still use JSON path as usual

If the previous response is not proper, then JSON path might not work as the pointer will be invalid
Well, this is not due to this feature impl, this is usual when we mention an invalid path.

Implemented in the following version.
<dependency>
  <groupId>org.jsmart</groupId>
  <artifactId>zerocode-rest-bdd</artifactId>
  <version>1.2.16</version>
</dependency>


SAK-31011 Small fixes for hidden sites

Could you squash them into a single commit?

Just done!  Thanks :)


Pseudonyms should be treated as passwords

This issue has been raised from discussions in https://github.com/folkehelseinstituttet/Fhi.Smittestopp.Documentation/pull/2
Comment from related PR in docs repo:
The solution with hash and shared salt could be not secure enough.
If we leak the hash and shared salt then it could be pretty easy to crack the input pseudonym.
I'd suggest changing it from HMACSHA256 to one of password hashing algorithms like PBKDF2

One core challenge to this issue is that we will need to be able to detect pseudonyms that has performed multiple verifications within a certain timeframe.
If we were to treat the pseudonyms as passwords we should generate a unique salt for each entry, however this makes it difficult to fullfill the purpose of storing these pseudonyms in the first place.
To be able to detect repeated verifications from the same pseudonym, we need to be able to match hashes created from the same pseudonym at different points in time. If we were to create a new unique salt per verification record, we would need to hash a pseudonym with all salts available in the dataset, as we do not have any way if identifying the relevant salt(s) for a pseudonym. This is not scalable. In a username+password login, you can use the username to identity the correct salt for the hash, in this case we do not have this option.


Partitions cannot be created on columns of type ENUM

Fixes https://github.com/cockroachdb/docs/issues/8646.

This change is

Online preview: http://cockroach-docs-review.s3-website-us-east-1.amazonaws.com/6ca29cb34891a977b325a56e947a622a9d915ecc/
Edited pages:

v20.2/enum.md
v20.2/known-limitations.md

@vy-ton Friendly ping on review

Closing in favor of https://github.com/cockroachdb/docs/pull/8784.


[v3.3.1] Release PR

Release PR for v3.3.1

I have released and once the last two jobs are green then we are good to go. Then this can be merged in.


Add 384x384 in12k pretrain and finetune for convnext_nano

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.


{‘error_code: ‘403025’, ‘message’: ‘Profile is not valid’}

I keep getting this error for all the functions in the Analytics Class.
{‘error_code: ‘403025’, ‘message’: ‘Profile is not valid’}
I have the developer and admin rights for the Analytics Product.
Note: I am able to retrieve the JWT Authentication access token.
Please share how to resolve this

Hello
It seems to me that you are not connecting the correct Product Profile to the API service in the console.adobe.io. Every time I heard this issue raising, it was a problem with the console.adobe.io setup. It may require some times as well. Check again now or on Monday.
If not working, I would recommend to create a product profile attached to the API.
In any case, it is not related to the python module, so I close this issue.


added unit tests for mrkl output_parser.py

Description: added unit tests for mrkl output_parser.py,
Tag maintainer: @hinthornw
Twitter handle: EdenEmarco177

awesome stuff! like you said, next would be great to add a check in output parser (and corresponding unit test) for multiple actions being returned


update tvOS16 offline resources

update tvOS16 offline resources

Yes yes yes !
Thanks a lot, merging now!


fix: use TCP as default protocol

Fixes #373
I don't know how I missed this behaviour when I added npipe to go-mssqldb.

package sqlcmd

see line 16

In reply to:<PHONE_NUMBER>

Refers to: pkg/sqlcmd/sqlcmd_windows_amd64.go:1 in 248d889. [](commit_id = 248d889293edd118f21813e6a6850975f1a40b69, deletion_comment = False)

package sqlcmd

it's another argument for writing our own named pipes dialer in go-mssqldb

In reply to:<PHONE_NUMBER>

Refers to: pkg/sqlcmd/sqlcmd_windows_amd64.go:1 in 248d889. [](commit_id = 248d889293edd118f21813e6a6850975f1a40b69, deletion_comment = False)


CTCSS/DCS squelch being on makes RX drop out every second for a split-second

Like the title says.
Repro steps:

Enable RX CTCSS/DCS
Tune into a continuous signal
Notice that any signal opens it regardless of CTCSS tone / DCS code (another bug)
Notice that squelch cuts out every second for a split-second
This does not happen if monitor mode is on, or if RX CTCSS/DCS is off

Seems fixed. Closing.


Update Transformers to 4.35 and fix pad_to_multiple_of

What type of PR is this? (check all applicable)

[ ] Refactor
[ ] Feature
[X] Bug Fix
[X] Optimization
[ ] Documentation Update
[ ] Community Node Submission

Have you discussed this change with the InvokeAI team?

[X] Yes, with @blessedcoolant
[ ] No, because:

Have you updated all relevant documentation?

[ ] Yes
[ ] No

Description
This PR updates Transformers to the most recent version and fixes the value pad_to_multiple_of for text_encoder.resize_token_embeddings which was introduced with https://github.com/huggingface/transformers/pull/25088 in Transformers 4.32.0.
According to the Nvidia Documentation, Performance is better when equivalent matrix dimensions M, N, and K are aligned to multiples of 8 bytes (or 64 bytes on A100) for FP16
This fixes the following error that was popping up before every invocation starting with Transformers 4.32.0
You are resizing the embedding layer without providing a pad_to_multiple_of parameter. This means that the new embedding dimension will be None. This might induce some performance reduction as Tensor Cores will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
This is my first "real" fix PR, so I hope this is fine. Please inform me if there is anything wrong with this. I am glad to help.
Have a nice day and thank you!
Related Tickets & Documents

Related Issue: https://github.com/huggingface/transformers/issues/26303
Related Discord discussion: https://discord.com/channels/1020123559063990373/1154152783579197571
Closes #

QA Instructions, Screenshots, Recordings

Added/updated tests?

[ ] Yes
[ ] No : please replace this line with details on why tests
have not been included

[optional] Are there any post deployment tasks we need to perform?

I haven't messed with this adding-tokens code myself. From my experience with the outputs of the text encoder, I can imagine that adding that extra padding either:

increases memory usage by a relatively small amount, and then has absolutely zero impact on the results.
or maybe the padding isn't invisible to the following operations and this makes the results different (in a way that probably isn't better because the padding is neither matching up with the model's training nor containing any new information).

Do we have any tests that could tell us which?
Automated unit tests are always preferred -- but this is in the middle of some LoRA-loading code, and we don't have a test suite that contains a full model and LoRA. If we can't figure out how to factor out that code to an easily-testable function, some manual tests would be reassuring.

I think this should probably be exposed to the user. We set the default to 8 but otherwise provide the option to the user to change it as per their card.
In this particular case we are setting a custom value for the A100 as per the docs but when there are other card families that require different settings, then we'll need to constantly keep this updated and a user will have to wait on us to support it.
So maybe it should be exposed like @psychedelicious suggested. Chuck it in advanced settings in the UI.

then we'll need to constantly keep this updated and a user will have to wait on us to support it.

I too would like this to be more resilient than a substring check of the device name. Ideally pytorch would expose some torch.cuda.tensor_core_alignment_size number or something like that and we'd use that. But since we don't have that, and reading through the referenced nvidia docs didn't give me any bright ideas about how to come up with it...
I have some sympathy for the "this will be a maintenance burden and people will have to wait for a new release" argument. But practically speaking, this is proposing adding a configuration setting for the hypothetical benefit of someone who's just bought a bleeding-edge $10,000 GPU, for the sake of some small performance optimization during text encoding -- at the expense of everyone else in the world whose Settings screen just got that much longer with an option that's going to be hard to document in a way that means anything to the kind of people who aren't buying new bleeding-edge server hardware.
I'm afraid the support burden of answering all the "hey what's this setting can I change it to make my GTX 1660 go faster" would outweigh that hypothetical maintenance burden.
Anyone who is dropping that kind of money on server hardware is probably either already running their own fork, or can afford to sponsor a release.
[There's a hole in my argument if someone suddenly comes out with a new CUDA-capable GPU that's budget-priced and needs that number to be something other than 8, but I don't see that happening anytime soon.]

If we feel this value won't change for the majority of the cards in the near future, I'd prefer just hardcoding it too. It's a difficult setting for people to know what the right value should be anyway.
But if we do expose it, I think it lives in the UI because if it goes in the config file, changing it would mean restarting the backend which in this case is not necessary.

Hardcode it now, re-assess in the future?

I personally think this is a good fix for now, as a lot of stuff will likely get reworked in the future anyway.
I tested it on my RTX 3060 with 8, 16 and 64 and tbh the performance different was negligible.
The results I got were: 1.24it/s on 8, 1.25it/s on 16 and 1.25it/s on 64. (I used a big resolution to see differences better)
So I don't know if that might be different for other professional cards, but I assume from my non-representive self testing that this hardcore fix works fine for now.

Until proven otherwise, this seems like a thing where there is a correct value for your system. Not something you'd want to change regularly. So it makes sense to set it once in the config, requiring a restart.
FWIW, there are many other config settings that can be changed at runtime, but which we don't expose in the UI.

I would love to meet the user that's running Invoke with an A100.
@Malrama would you be able to make the updates @psychedelicious and then we can get this in as hardcoded optimizations for now with an eye to revisit in the future?

I would love to meet the user that's running Invoke with an A100.
@Malrama would you be able to make the updates @psychedelicious and then we can get this in as hardcoded optimizations for now with an eye to revisit in the future?

I will try. I have to figure out how I am suppose to do it because Github is really new Land for me and I get quiet confused. Give me a little time. I assume I should only change the comment but we keep it hardcoded like this?

@Millu Did I do it right?

Alright, sorry for the multiple commits. I think I'm done now unless I did something wrong or more changes need to be done.

@RyanJDick I'm not confident hardcoding this in case some other GPU platform needs a different value. Can you please review the nvidia/transformers docs and advise?
It's straightforward to make the setting configurable. Should we do that in this PR or is it not a big deal either way?

@RyanJDick I'm not confident hardcoding this in case some other GPU platform needs a different value. Can you please review the nvidia/transformers docs and advise?
It's straightforward to make the setting configurable. Should we do that in this PR or is it not a big deal either way?

Just did my best to catch up on this whole conversation. It feels very hand-wavy right now. There is guidance that suggests that setting the right padding value could improve performance, but there is still lots of uncertainty because we haven't actually profiled it on multiple cards. Questions I still have:

How much speedup does this provide?
Does the optimal setting depend on other factors than the card (e.g. driver version or dtype)?
Does the time cost of padding counteract the benefit in some cases?

Given all of this confusion, I'd propose:

Set it to 8 in all cases.
Include a comment summarizing all of this confusion.
Only add device-specific configs once we can clearly prove that they are better. (Otherwise we just end up with hard-coded values that people are afraid to change/break in the future.)

Updated the PR with taking @RyanJDick points into account.

Is there any benchmarking data for no padding vs padding=8 and other values? It seems like we're arguing over hypotheticals.

@lstein

Is there any benchmarking data for no padding vs padding=8 and other values? It seems like we're arguing over hypotheticals.

Well, that's the thing - we just want a value that works on all platforms. It looks like 8 is that number for now.


Feat/rebass

[ ] Image component
[ ] Link component? I checked the next link, but didn't change much
[ ] Figure out if we are going to extend rebass components or theme them in theme or componentsTheme
[ ] Update readme
[ ] Check why @types/rebass isn't working T_T
[ ] Remove system in lib
[ ] aaaaa just found an error in button
[ ] sleep

[ ] Image component
[ ] Link component? I checked the next link, but didn't change much
[ ] Figure out if we are going to extend rebass components or theme them in theme or componentsTheme
[ ] Update readme
[ ] Check why @types/rebass isn't working T_T
[ ] Remove system in lib
[ ] aaaaa just found an error in button
[ ] sleep


You can not select disabled devices when using Enable Device

What version of Spook are you using?
3.0.1
What version of Home Assistant are you using?
2024.6.1
The problem

When choosing the enable device service, you can not select disabled devices in the developer tools. See the image.
Anything in the logs? Paste it here!
No response

This is, unfortunately, not an problem with Spook, but a limitation of Home Assistant. The service call / action would remain the same / working, but the UI elements currently are not able to provide them.


Tests

This app needs tests!

Tests for:

[ ] Command line interface
[ ] Database operations
[ ] Web frontend
[ ] JSON frontend


feat: Reject tuple input with direct relationship if not allowed instead of writing

Currently, a WriteCommand (ref: server/commands/write.go) with a tupleset that is not valid because of attempting to write a DirectUserset (ref: openfga/v1/authzmodel.proto in openfga/api) is not rejected as invalid.  This tupleset does not cause an invalid authorization check (which is great), but it does create two potential pain points with users:

Services that write tuples to an fga store that violate this condition will not receive an error and assume that they provided a semantically valid tuple (they are already syntactically validated with the provided regex patterns); and,
fga admins (global or store) may get complaints of authorization checks failing that a service believes should be valid and, upon investigating see the invalid direct relationship, assume there is a deeper or more complex issue than simply violation of the indirect only relationship

Looking through server/commands/write.go, we do not currently pull in the AuthorizationModel (like in server/commands/read_authzmodel.go; though we do have the StoreId and AuthorizationModelId in the req input for Execute and should be able to fetch it), but if we did we would have access to the TypeDefinitions and should be able to then check if the TypeDefinition.relations map contains a DirectUserset or not

.

I am hoping to try and implement the resolution to this (even just to get more hands on if not accepted), but am not against this being picked up by someone more comfortable with the openfga code base.

@adriantam - I think I've got my plan in order and will begin tomorrow, but wanted to put the idea down here to get any feedback or cautions.
As I see it, there are 4 scenarios in which direct assignment should be permitted

this:{}
When this:{} is on side of a difference (originally I thought this should be base only, but if it is in the subtract it still means that it could be directly assigned, only that would mean it will be interpreted by check and any other expansions as not actually the relation)
When this:{} is anywhere in an intersection
When this:{} is anywhere in a union

Thus, I plan to create a new function (would love suggestions on where to put it, whether that be in write.go or a utils/... or other) called isDirectRelation which takes in a *openfgapb.Userset and determines if it matches one of the above criteria.  If so, it will return true, if not it will return false (and a possibly nil error, ofc), which we can then use in validateTuplesets to determine if we should write the tuple or return error.
What are your thoughts on this, given the more concrete details?

@adriantam @rhamzeh - hey all, apologies it has been a couple of weeks.  I finally had some time today and added in the changes to my branch in my fork.  Everything except for unit tests has been completed (I've done extensive testing via the local playground and all appears to be in order).
When I ran go test ./... from root, I see this response for the server/tests set

@dblclik The server tests are in server/server_test.go. The server/test package defines shared tests (not test functions) that can be used for different storage implementations and they are publicly exported tests that can be used externally for services that embed OpenFGA as a server.
If you just want to run the server tests directly you can run the following command go test -v ./server/.... Or, to test OpenFGA for a specific storage engine, you can run commands such as:
go test -v ./server/... -run TestOpenFGAServer/TestPostgresDatastore
go test -v ./server/... -run TestOpenFGAServer/TestMemoryDatastore

@jon-whit - perfect, thank you, that seems to work (and means my earlier run of go test ./... included it 🙌 ).
I will work on adding tests for the new functionality, but can at least confirm that my additions have not broken anything prior :phew:

@jon-whit @adriantam - hey all, I (finally) opened up PR 114.  I signed the CLA after opening it, so there's a mark in the PR history that it wasn't in place.  It should be good, but the license check workflow can't run until launched by an owner (like the other workflows).  Feel free to fire away with any/all comments and thoughts 🦖


Feature encoding enhancements

[This continues the discussion in #12.]
Both the transducer and the pointer-generator treat features in architecture-specific ways; issue #12 deals with their ideal treatment in the transducer, since the Makarov/Clematide mechanism of treating them as one-hot embeddings appears to be ineffectual. In contrast, they are just concatenated by the LSTM and transformer models. My proposal is that we should, in attentive LSTM and transformer, have separate (LSTM and transformer, respectively) encoders for features and these encoders should then be lengthwise concatenated. To be more explicit, imagine the source tensor is of size batch_size x hidden_size x source_length and the feature tensor is of size batch_size x hidden_size x feature_length. Then I propose that we concatenate these to form a tensor of size batch_size x hidden_size x (source_length + feature_length), and attention operates over that larger tensor.
As a result, we can use the features column to do multi-source translation in general. Furthermore, the dataset getter is no longer is conditioned on architecture: it just has features and no-feature variants, which makes things a bit simpler.
(Note that this will not work for the inattentive LSTM; something else will have to be done or we can just dump it.)
A distant enhancement is that it would be possible, in theory, to have different encoders for source and feature (LSTM vs. GRU vs. transformer); an even more distant enhancement would be to allow these to have different dimensionalities and use linear projection to map the feature encoding back onto the source encoding. I do not actually think we should do either of these, but it's a thing we could do...

My proposal is that we should, in attentive LSTM and transformer, have separate (LSTM and transformer, respectively) encoders for features and these encoders should then be lengthwise concatenated.

That sounds great. I do think we should keep the option to do it the current way for 1) reproducibility of papers that do it that way (though I suspect it was often done this way out of convenience for using popular MT libraries in the past :D), and 2) perhaps to make comparisons wrt runtime?
Another note: then in the FeatureInvariantTransformer, we'd only need to embed the character embeddings with positional encodings, and would not need to track the feature idx in the vocab.

My proposal is that we should, in attentive LSTM and transformer, have separate (LSTM and transformer, respectively) encoders for features and these encoders should then be lengthwise concatenated.

That sounds great. I do think we should keep the option to do it the current way for 1) reproducibility of papers that do it that way (though I suspect it was often done this way out of convenience for using popular MT libraries in the past :D), and 2) perhaps to make comparisons wrt runtime?

One thought I've had is maybe we should have a vintage, waxed mustache, penny-farthing-style fork that contains all the old methods, for that kind of work.

Another note: then in the FeatureInvariantTransformer, we'd only need to embed the character embeddings with positional encodings, and would not need to track the feature idx in the vocab.

Yes, that'd be a big improvement to readability etc. Good point.

Howdy y'all, I've emerged from dissertation land and can return to this. Looking over the modules, here are my thoughts (pr to follow after some coffee runs):

It looks like this is most cleanly managed by having a features.py module that just maintains encoders to be imported by individual architectures.
In this case, we might as well just allow swapping out encoders (since they'll all be there) and just use a factory like we do for modules.
Since we can swap out encoder architectures, we can actually have it both ways and have a default function of just combining embeddings with a FFN. This should make it compatible with most penny farthing approaches.

Will share later this evening/tomorrow for criticism and stone throwing.

So this is what I currently have design wise:

The encoder for the features are specified at run-time. Currently the options are: LSTM, Transformer, and Linear projection (which is just the embeddings).
If features are included at run-time but no encoder is specified, we're just adding the features to the source string. Then source string and features are projected through the same embedding encoder and decoding is model specific.
If features and an encoder are specified at run time, architecture specific decoding is done. For attention based decoders, this is a concatenation of the projected
If the decoder is LSTM based, my thoughts are that we do what we were thinking of for transducer: average all feature into a single time step and append to all timesteps in source encoding. Then decoding is done as normal for LSTM.

I can throw stuff into a design document, but don't have a preferred template.

I don't see how this design would work with pointer-generators, so that needs to be clarified. (You may want to chat with @Adamits about this later---there's a subtlety we discussed recently.)
I don't really care about the template for design doc (pure Google Docs, with typewriter text for code, is what I usually use) but I think this is complicated enough that your design should provide proposed interfaces (e.g., typed Python function signatures) and also propose changes to the command-line interface.

proposal.pdf

Thanks for the doc. A couple thoughts:

I don't love it but I'd probably prefer a run-time if/else check (do I need to use a feature encoder or not right now?)...I think that's slightly different than what you're calling "aliasing"---but easier to understand.
In your (6), I think you're saying the user should decide whether or not to have a separate feature encoder, right? That's one possibility: the other is that we should figure out the right answer for each architecture and just do it automatically.
I think the encoder factory should be a static method not a function.

Before you go ahead I would like to see the exact design for the new CLI flags to accomodate the proposed change.

* I don't love it but I'd probably prefer a run-time if/else check (do I need to use a feature encoder or not right now?)...I think that's slightly different than what you're calling "aliasing"---but easier to understand.

That works too. I think that was used before we separated models into NoFeature vs. Feature duals so thought it would rankle feathers.  More specifically the 'aliasing' idea would be like:
def _forward_with_features...
def forward....
if feature_encoder
    forward = _forward_with_features

Not sure if the most pythonic, but I've seen in some not dumpster fire code.

* In your (6), I think you're saying the user should decide whether or not to have a separate feature encoder, right? That's one possibility: the other is that we should figure out the right answer for each architecture and just do it automatically.

Oh I meant automatically. The seaparate_features would be an architecture specific flag that train would check to see if a feature_encoder is legal. My idea was that down the line it could be extended so that you could specify a feature_encoder even with models that collate the source and feature strings together so you could do stuff like - run the base lstm but instead of embedded features you encode the features with their own lstm.

* I think the encoder factory should be a static method not a function.

Sure, was just thinking function to keep consistent with all other factories.

Before you go ahead I would like to see the exact design for the new CLI flags to accomodate the proposed change.

As in just write them down as a sample script run or would want to see how they'd be pass in the code?

That works too. I think that was used before we separated models into NoFeature vs. Feature duals so thought it would rankle feathers. More specifically the 'aliasing' idea would be like:
def _forward_with_features...
def forward....
if feature_encoder
    forward = _forward_with_features

Not sure if the most pythonic, but I've seen in some not dumpster fire code.

I am just saying I don't like that stylistically. It certainly works but I think it's extremely hard to read and reason about.

Oh I meant automatically. The seaparate_features would be an architecture specific flag that train would check to see if a feature_encoder is legal. My idea was that down the line it could be extended so that you could specify a feature_encoder even with models that collate the source and feature strings together so you could do stuff like - run the base lstm but instead of embedded features you encode the features with their own lstm.

Okay, if the "flag" here is outside of user control I have no objection, thanks for clarification.

* I think the encoder factory should be a static method not a function.

Sure, was just thinking function to keep consistent with all other factories.

I was thinking it could be like Adam's embedding initialization stuff.

Before you go ahead I would like to see the exact design for the new CLI flags to accomodate the proposed change.

As in just write them down as a sample script run or would want to see how they'd be pass in the code?

I think I would want to see flag names, doc strings, etc.---I trust how they'd get passed around is something you'd have no trouble with.

I am just saying I don't like that stylistically. It certainly works but I think it's extremely hard to read and reason about.

Fair enough, it's easier to code anyhows.

I was thinking it could be like Adam's embedding initialization stuff.

Will co-opt that then.

I think I would want to see flag names, doc strings, etc.---I trust how they'd get passed around is something you'd have no trouble with.

Okie doke, let me draft that up in a separate comment.

Sample CLI:  sample_run.txt
Docstrings for Base:  base.txt
Docstrings for Encoder: encoder.txt
Lemme know where further detail would help.

Variable update suggestions (and paper idea) accepted. I"ll start working on the PR sometime next week.

Now that #72 is in what else of this bug remains @bonham79?

Only thing to fix would be to extend feature_encoder to all model types. So like: transformer can now have a feature_encoder flag like pointer_generator and transducer. But this seems like an idea that should be needed first

Only thing to fix would be to extend feature_encoder to all model types. So like: transformer can now have a feature_encoder flag like pointer_generator and transducer. But this seems like an idea that should be needed first

Okay, definitely not urgent. I would do this as a way of testing out whether feature-invariance is really a contribution...


Styling and content improvements

The front page has been edited to display only next steps and partners:

The next blob, partners, looks like:

Based on https://inveniosoftware.org/products/rdm/

Note: rows are different, but that depends on the framework and we will work on CSS separately. This is just to update logos.
Signup, login and lost password pages have been styled accordingly:

Closes: https://github.com/inveniosoftware/demo-inveniordm/issues/4
Closes: https://github.com/inveniosoftware/invenio-app-rdm/issues/92

All fixed, thanks!

The signup page should say "Sign up for an InvenioRDM account".

Had to overwrite the template but it is fixed :)


Fallback to conda-web when artifact download fails

Some CDN copies are buggy, corrupted or missing. When that happens, we can try to go to the non-CDN copy, which is hopefully ok. We do that without the retry decorator so we don't spam too much.
This should alleviate those 404 problems in https://github.com/channel-mirrors/mirrormirror/issues/11

Great! We will have better data than upstream anaconda :)


Storybook drawer component

Notes for Reviewers
This PR fixes #
Signed commits

[x] Yes, I signed my commits.

@senali-d  Let's discuss this on Meshery Dev call. Please add this as an agenda item in the meeting minutes if you would. :)

But please check why End-to-end tests check is failing 🤔


pgf option doesn't work in conjunction with \usepackage pgfplots

Hello,
When I use this package as follows (\usepackage[pgf]{bodeplot}) in conjunction with \usepackage{pgfplots} I get the following output:

But when I exclude \usepackage[pgf]{bodeplot} I get the intended output:

In your package, there is some interference with pgfplots

This package already loads pgfplots package with compat=1.18. You do not need to load it separately using \usepackage.
I am afraid it might have to do with your \usepackage{pgfplots} command overriding the compat=1.18 compatibility setting. If that is the case, there is nothing I can do. The bodeplot package needs pgfplots 1.18 or newer.
That being said, I will look into the issue if you can tell me the exact commands you are using to generate the plots above.


Generate compilation database for workspace

Since .ycm_extra_conf.py is calling bazel print_action directly, generate_compilation_database.sh is only called by clang_tidy.sh and this  call is broken as clang_tidy does not pass a certain file path to generate_compilation_database.sh.
This PR fixes this by making generate_compilation_database.sh generate the compilation database for the project workspace and not require a file as input.

/gcbrun

Thanks @justbuchanan, I see that one of the checks is failing but I do not have permission to see the details of the failure.

Here's the relevant snippet from the logs:
Step #1: shellcheck...............................................................Failed
Step #1: - hook id: shellcheck
Step #1: - exit code: 1
Step #1:
Step #1: In tools/cpp/generate_compilation_database.sh line 13:
Step #1:   $(bazel query 'kind(cc_.*, //...) - attr(tags, manual, //...)') > /dev/null
Step #1:   ^-- SC2046: Quote this to prevent word splitting.
Step #1:
Step #1: For more information:
Step #1:   https://www.shellcheck.net/wiki/SC2046 -- Quote this to prevent word splitt...

Since you actually want word splitting to happen here, my preferred approach for that is to use a bash array:
TARGETS=($(bazel query ....))
bazel build ... "${TARGETS[@]}"

/gcbrun

Sigh; shellcheck doesn't like that and suggests using mapfile, which would look like:
mapfile -t TARGETS < <(bazel query ...)

Hopefully I remember this the next time it comes up. Thanks!


fix: Add several c8s fixes for missing deps and decorators

fix: Add cache decorator for older python versions.

fix(mrack.spec): Missing dependency in c8s for beaker-client

c8s run is now green: https://dashboard.packit.dev/results/testing-farm/153647

Should I remove temp commits? @pvoborni

I will remove the 4 commits from other PR then it should be fine do you agree? and I will rebase #226 on top of this one.


IntegrationServiceEnvironmentClient, Delete wait for delete completion

Feature Request

Currently the SDK has only non blocking Delete operation in IntegrationServiceEnvironmentClient.
The call Delete correctly deletes ISE in async mode but next get operation for status returns immediately NotFound so not possible to check for delete completion.
Please provide the workaround/example how to wait for delete completion of ISE with existing SDK or provide
IntegrationServiceEnvironmentDeleteFuture structure so we can call WaitForCompletionRef to wait for delete completion.

Hi @jbinko thanks for the issue!
Actually the implementation of the deletion of ISE is sync - which should be blocking. But based on your description, this deletion should be async. To resolve this, we will have to first modify the corresponding swagger to mark this operation as long-running-operation and usually this should be done by the service team.
In the meantime, could you please provide the response of the delete request (including the status code and the headers)? I have tried to create one first but it seems to take forever to complete... Typically, if the request is truly a long-running-operation, it should first give you the status code 201 or 202 and there should be a URL for polling the async result in the header (could be Location or AsyncOperation depending on the implementation of the service).

Basically this call:
resp, err := client.Delete(ctx, id.ResourceGroup, id.Name)
initiates deletion process and returns quickly like in 5 seconds (it is OK) but real deletion of ISE can take 1-2 hours and is in progress in the background. I need to have mechanism to be blocked somehow until the real deletion really finishes. Reason is ISE is occupying my VNET resource and VNET cannot be deleted until real unprovisioning of ISE finishes. It is Azure Terraform related blocker.

@jbinko based on what I am seeing in the response and the status code, this request is not a long-running-operation. Therefore we cannot introduce a Future struct for this function.
It interested me that if after the delete call returns, a immediate get request returns 404, does this mean the delete has been completed? This behaviour sounds very reasonable to me. Or is there any other context?

Correct and this is the challenge I'm referring to. You call delete, it takes 5 seconds to successfully finish with status code 200. The ISE resource disappears from Azure (even from Portal) and you cannot control it/polling it. However the delete operation is still in progress for like next 60 minutes and is still effectively occupying your VNET and you cannot delete VNET until the ISE is truly deleted. How can I detect ISE is truly deleted so we can unblock TF workflow and continue with deletion of VNET which is not containing ISE anymore? E.g. Can we initiate change and ask for Long running Operations?

@ArcturusZhang any updates?


different types of authentication

How does the scanner handle different types of authentication mechanisms when testing APIs?

The current implementation does not handle authentication mechanisms. To address this, you should extend the scanner to support different authentication types such as OAuth, API keys, and JWT. Implement mechanisms to inject authentication tokens into requests, and handle authentication flows based on the API’s requirements.

What are the limitations of using static payloads for vulnerability testing in an API scanner?

Static payloads can miss complex or obfuscated attack vectors and may not account for all possible input variations. They are also limited by their predefined nature and do not adapt to new or evolving attack patterns. To improve, consider using dynamic payload generation and integrating with external vulnerability databases for more comprehensive coverage.

How does the scanner ensure it does not negatively impact the target API during testing?

To minimize impact, implement rate limiting and error handling in the scanner. Ensure that requests are made at a controlled rate and implement retries with exponential backoff. Also, consider adding a configuration to adjust the intensity of the scans based on the target API’s capacity and requirements.

What are the benefits and challenges of integrating Swagger/OpenAPI specifications into the scanner?

Benefits: Integration allows for dynamic discovery of endpoints and parameters, ensuring that the scanner tests all relevant parts of the API. It also supports automated testing based on the API’s actual documentation.
Challenges: Swagger/OpenAPI specifications can be complex, and different APIs may use varying formats or versions. Ensuring accurate parsing and handling of different specifications requires robust parsing logic and thorough testing. Additionally, not all APIs have up-to-date or complete documentation.


[SPARK-12665][CORE][GRAPHX] Remove deprecated and unused classes

Whole code of Vector.scala and GraphKryoRegistrator  are no longer used so it's time to remove them in Spark 2.0.

Test build #48832 has started for PR 10613 at commit 3914311.

Test build #48832 has finished for PR 10613 at commit 3914311.

This patch fails MiMa tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test FAILed.

Test FAILed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/48832/
Test FAILed.

Test build #48844 has started for PR 10613 at commit 99029db.

LGTM

I'd update the title to just say the classes you are removing, since there are only 3.

Thanks for your suggestion. I've update the title and corresponding JIRA.

Test build #48844 has finished for PR 10613 at commit 99029db.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/48844/
Test PASSed.

Merged build finished. Test PASSed.

I've merged this.


Bugfix: Restore failed when two or more full backups were created

This PR fixes #2 .

Thanks a lot for your PR!
I've adjusted the code after merging this one, to allow any backup to be restored, not just the last.

That's strange. I was testing the code with several full backups and
incremental backups between them. I was selecting different backups to
restore, not just the latest.
Anyway it looks like your adjustments are doing the same. I'll wait for
nuget package 2.2.0 and upgrade :)
Thanks for your effort in creating and keeping the repo. You saved
plenty of my time.
On 19.06.2017 23:18, loekd wrote:

Thanks a lot for your PR!
I've adjusted the code after merging this one, to allow any backup to
be restored, not just the last.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/loekd/ServiceFabric.BackupRestore/pull/3#issuecomment-309561775,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AcGPCfG385xsn9OzgOnuaI5vJigBeItfks5sFtemgaJpZM4N7iks.

After looking at it a second time, I think you're right. Sorry about that. I'll try to release the package asap, after I investigate the StartPartitionDataLossAsync issue.


Fix core scss files permissions

Before this, the installed files in a project were executables with a
775 permissions.
This commit chmod the files to 644.

👍
@whmii Want to merge this and cut a release?

Thanks, @mehlah! Merged as a1a0ca9188d63596a67379fd07ae8053aed0e653.


How to traffic-shift tracing collector clusters?

Title: How to traffic-shift tracing collector clusters?
Description:
We are in the process of migrating from one tracing collector cluster to another for our Lightstep-tracing setup:
...
    "tracing": {
     "http": {
      "name": "envoy.lightstep",
      "typed_config": {
       "@type": "type.googleapis.com/envoy.config.trace.v3.LightstepConfig",
       "collector_cluster": "OLDCLUSTER",
       "access_token": {
        "filename": "/path/to/token"
       }
      }
     }
    },
...

We are trying to change the collector_cluster field from OLDCLUSTER to NEWCLUSTER in a gradual way, similar to the strategy defined in Traffic Shifting/Splitting. However, that traffic shifting only works within the context of routes, and not in a field where we're expected to provide a collector_cluster: string. We'd ideally be able to ramp up traffic to the NEWCLUSTER with some runtime configuration, rather than have to redeploy and static-template in some traffic-diversion strategy.
I see a couple of potential options/leads:

AggregateCluster seems like we could independently define a cluster that abstracts around two underlying clusters, and use that cluster name in the collector_cluster config. However, I don't see a great way to use a runtime-knob to ramp up traffic to the new cluster, as its moreso based around failover logic.
We could modify the lightstep-tracing config to take in more than just a string-field, and provide some bespoke weighted traffic-splitting options in there.

I think in my ideal world, I could define a new cluster type called MultiCluster that lets users define a list of clusters: [] which they could toggle weightings via some runtime_key.
Also very possible there's some other obvious way of doing this that I'm missing. Would appreciate any advice!

Got it, I think we might just do some allowlist/gradual rollout via templated static config for now. Thanks!


dashboard - automatic rui setup/update

mechanism for installing and updating the correct rui file according to the desired version

dashboard is on! check https://github.com/compas-dev/compas_dashboard


Closing Cluster Log Collection Manually Deletes Cattle-Logging and Reopens Invalid

**What kind of request is this (question/bug/enhancement/feature request):bug
**Steps to reproduce (least amount of steps as possible):

Creating Cluster Log Collection

Configure Kafka Click Save

Check that cattle-logging has a corresponding pod

Delete cattle-logging project and close cluster log collection:None

Save in reconfiguration Kafka to see if cattle-logging is not creating the corresponding fluentd-anent
**Result:
No corresponding fluentd-anent is created under cattle-logging
Other details that may be helpful:

Environment information

Rancher version (rancher/rancher/rancher/server image tag or shown bottom left in the UI):v2.2.2
Installation option (single install/HA):HA

Cluster information

Cluster type (Hosted/Infrastructure Provider/Custom/Imported):Custom
Machine type (cloud/VM/metal) and specifications (CPU/memory):cloud 4 vCPU 8 GiB
Kubernetes version (use kubectl version):

Client Version: version.Info{Major:"1", Minor:"13", GitVersion:"v1.13.5", GitCommit:"2166946f41b36dea2c4626f90a77706f426cdea2", GitTreeState:"clean", BuildDate:"2019-03-25T15:26:52Z", GoVersion:"go1.11.5", Compiler:"gc", Platform:"linux/amd64"}
Server Version: version.Info{Major:"1", Minor:"13", GitVersion:"v1.13.5", GitCommit:"2166946f41b36dea2c4626f90a77706f426cdea2", GitTreeState:"clean", BuildDate:"2019-03-25T15:19:22Z", GoVersion:"go1.11.5", Compiler:"gc", Platform:"linux/amd64"}

Docker version (use docker version):

Docker version 17.03.2-ce, build f5ec1e2

@Hwting I couldn't reproduce. Could you try the latest version?


fix: upgraded some dependencies and added .node-version files

Thanks for this really fun library.
I did some upgrades to make the automatic security scanning robots happy!
Let me know if you want any tweaks and I'll get to 'em as soon as I can.

:tada: This PR is included in version 1.0.3 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:

Wow the semantic-release worked! ☝

PS thanks for the pull request. Glad you're finding this useful (or at least fun) 💛

You are most welcome! I used this fun repo in an example application that deploys a Node.js Lambda to AWS.  Just switched back to installing from you instead of my fork and all seems good.
https://blog.testdouble.com/posts/2019-11-26-from-noops-to-allops/

Nice! Thanks for sharing.


Password Exposure

Unless I'm doing something wrong, if you use the -Password flag there doesn't appear to be a way to either enter the password securely or pass a credentials variable. It looks like I'm being asked to enter the plaintext password with the cmdlet.

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

ID: a28e55f1-0862-f421-d8f9-d21793b9a88c
Version Independent ID: 684f76eb-0b8c-3fbb-4f0c-1e12ccf1405d
Content: New-SmbMapping (smbshare)
Content Source: docset/windows/smbshare/new-smbmapping.md
Product: w10
Technology: powershell-windows
GitHub Login: @coreyp-at-msft
Microsoft Alias: coreyp

Hello, @MWRobertson
The issues section of this repository is intended for documentation problems only.
Please consider checking any relevant resources and asking the community regarding your problem via the following link.
PowerShell Community
If you feel that this document can also be updated with information related to your request, please comment and re-open this issue we would love to to follow-up with documentation updates.
Thank you for getting in touch.

@officedocsbot assign @e0i

@officedocsbot close


reformat HGVS records

@jeromekelleher - I see what you mean - I've removed the redundant comments. It would be cumbersome to describe HGVS in great detail here, so I've added a link to the recomendation. What do you reckon?

Looks good to me @sarahhunt, +1

+1 on the hgvs change.  Linking to canonical external
documentation, when it exists, is far better that writing
a condensed `reader's digest' version
Sarah Hunt<EMAIL_ADDRESS>writes:

@jeromekelleher - I see what you mean - I've removed the redundant comments. It
would be cumbersome to describe HGVS in great detail here, so I've added a link
to the recomendation. What do you reckon?
—
Reply to this email directly or view it on GitHub.*


Optional function param in interface allows implemented class to define function without the param being optional

Bug Report
The following way of declaring a function in an interface allows the class that implements the interface to declare an optional function parameter as not optional. This is not caught at compile time as I would expect but causes a runtime error.
interface TestType {
    val: number;
}

interface IClass {
    foo(param?: TestType): void
    //fooWithProperChecking: (param?: TestType) => void
}

class MyClass implements IClass {
    public id = ""
    constructor() {

    }

    public foo(param: TestType): void {
        console.log(`foo val(${param.val})`)  // Compiles but throws exception because param is undefined
    }

    public fooWithProperChecking(param: TestType): void {
        console.log(`fooWithProperChecking val(${param.val})`)
    }
}

const myObj = new MyClass()
const myInterfaceRef: IClass = myObj
myInterfaceRef.foo()  // Fails with [ERR]: undefined is not an object (evaluating 'param.val')

Note that uncommenting the function declaration using the style of fooWithProperChecking will cause a compile error as expected.

You forgot to fill out the issue template for bug reports.
This is working as intended. Methods are checked bivariantly. See also: https://github.com/microsoft/TypeScript/issues/53353#issuecomment-1475309343

Apologies on the template. I think I had an incorrect paste that made me delete the template below my paste when I tried to delete just the paste.  In any case, thanks for the reference on the behavior. I see there is a lint option I can explore to enforce one method signature style over another: https://typescript-eslint.io/rules/method-signature-style/


Different Errors while trying to install

I followed the instructions on the main page,
to make my first test simple I put the audio and wav in the root directory to make a short path:
python3 inference.py --face 1.mp4 --audio 1.wav --outfile 1_1.mp4
After installing the cuda and requirements as explained,
I had a lot of different errors of missing modules so tried to install them by myself
But the last error I'm stuck on I can't get rid of:
D:\Video_Retalking>python3 inference.py --face 1.mp4 --audio 1.wav --outfile 1_1.mp4
No CUDA runtime is found, using CUDA_HOME='C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.3'
C:\Users\Alon\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\torchvision\transforms\functional_tensor.py:5: UserWarning: The torchvision.transforms.functional_tensor module is deprecated in 0.15 and will be **removed in 0.17**. Please don't rely on it. You probably just need to use APIs in torchvision.transforms.functional or in torchvision.transforms.v2.functional.
  warnings.warn(
Traceback (most recent call last):
  File "D:\Video_Retalking\inference.py", line 19, in <module>
    from utils.ffhq_preprocess import Croper
  File "D:\Video_Retalking\utils\ffhq_preprocess.py", line 31, in <module>
    import dlib
  File "C:\Users\Alon\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\dlib\__init__.py", line 19, in <module>
    from _dlib_pybind11 import *
ImportError: DLL load failed while importing _dlib_pybind11: The specified module could not be found.

I tried pip install it, pip3 install and even conda install but nothing solve the problem.
I also tried to re-install CUDA but I still get the same error as above.
Any idea how to fix that and make Video-Retalking run local on Anaconda?
Thanks ahead 🙏

I googled some links.
https://github.com/davisking/dlib/issues/2097
https://stackoverflow.com/questions/62255730/dlib-importerror-in-windows-10-on-line-dlib-pybind11-import-dll-load-failed
Hope that helps~

I have the same error🙋  I used Windows 10.

try python 3.7


frontend - remove 3rd party types from own type declaration

Using third party libraries is a good thing. Usually it is a good practice to protect your core business logic from these libraries by hiding them behind custom interfaces and classes. This also allows to simply exchange a library without or minimal impact to the core.
Currently we do this already with the EthereumProvider interface which we implement then for the different providers. Under the hood we use ethers.js to sign messages, interact with contracts etc. pp. Unfortunately we made the mistake to put 3rd party types into the interface definition of the EthereumProvider. This breaks the dependency protection and let 3rd party code leak into the core. This can be recognized easily when writing simple unit tests. The ethers.js types for JsonRpcProvider and JsonRpcSigner are quite complex. Thereby it also becomes an issue to easily mock them. The same goes also for simpler types like Block.
We should aim to remove these leaks. We simply need to define our own interfaces with just the exact boundaries we need. Here we should think from the perspective of the core using these objects. Not how ethers.js types look like and what we need from them. So we should define our own Block type and think about what information we need to know and how we want to name them. If we need any helper methods etc. And then we provide a "hidden" utility function that maps ethers.js its Block instances to our own version.

It doesn't look like we can easy tackle this right now. We will first work on all the other refactorings we have in mind to enable new features and testability. We will always try to get rid of as much as possible of such types when editing the code. But it doesn't seem to become a standalone active task. Not right now. We have to revisit this later.

We heavily improved on this one by introducing our own TokenAmount and UInt256 types. The last  to remove ones are JsonRpcProvider and JsonRpcSigner.

We went a step back from this again. There are several places where such 3rd party types were reintroduced.
After having a quick look, places were we should eliminate these 3rd party types from our interfaces include (there is probably more!!):

Uint256 exposes a asBigNumber getter
EthereumProvider exposes a Web3Provider via getProvider
Many transaction functions rely on the JsonRpcSigner as a parameter.

For the last one, we should split our IEthereumProvider interface and move anything that is related to signing / wallet functionality into another interface (e.g. IEthereumWallet or IEthereumSigner). This new interface should extend the IEthereumProvider interface. Only our own provider and signer interfaces should be passed to the functions which interact with the contracts. This also implies that instead of passing rpc urls and creating new JsonRpcProviders in these functions, we should pass instances of our own provider interface. This will enable to solve #1443.
One challenge is decoupling the contract interaction functions from our provider and signer interfaces. Our contract interaction functions (e.g. everything inside request-manager.ts) still need to use the contract interface internally which comes from ethers and is generated by typechain. The contract instances need to connect to our own provider and signer interfaces. We used to have a connect function in our EthereumProvider, I have no idea why it was removed. It looked like this (from git history):
connectContract(contract: Contract): Contract {
    return contract.connect(this.web3Provider);
  }

The issue with that is that Contract is again an ethers interface. One solution could be to use a generic type: connectContract<T>(contract: T): T
Maybe make the generic T even extending a new Connectable interface. Maybe there is also a better solution to this.
Happy birthday to this issue btw


Empty and random transcripts after finetuning wav2vec2.

Hi @alexeib @patrickvonplaten ,
I have fine-tuned wav2vec2 models, specifically large-lv60, base, base-960h, and large-960, on Indian English data from four speakers. However, I am getting the empty or random transcripts after fine-tuning.
the below are the training arguments. I have used.
model = Wav2Vec2ForCTC.from_pretrained(model_id,
            ctc_loss_reduction = "mean",
            pad_token_id=processor.tokenizer.pad_token_id,
            vocab_size=len(processor.tokenizer))

# I have tried freezing feature extractor as well.
#model.freeze_feature_extractor()
model.freeze_feature_encoder()

training_args = TrainingArguments(
  output_dir="wav2vec2_large_5k_ckpts",
  group_by_length=False,
  per_device_train_batch_size=8,
  gradient_accumulation_steps=8,
  evaluation_strategy="steps",
  num_train_epochs=50,
  fp16=True,
  gradient_checkpointing=True,
# tried different eval, save, logging and warmup steps.
  save_steps=200,
  eval_steps=200,
  logging_steps=200,
  learning_rate=1e-5,
#   weight_decay=0.005,
  warmup_steps=200,
  save_total_limit=2,
  push_to_hub=False,
  do_train=True,
  do_eval=True,
  load_best_model_at_end=True,
  metric_for_best_model="wer",
  greater_is_better=False,
  #report_to="tensorboard",
  #seed=101,
)

trainer = Trainer(
    model=model,
    data_collator=data_collator,
    args=training_args,
    compute_metrics=compute_metrics,
    train_dataset=ds_prepared["train"],
    eval_dataset=ds_prepared["validation"],
    tokenizer=processor.feature_extractor,
    # callbacks = [EarlyStoppingCallback(early_stopping_patience=3)]
)

I have experimented with various learning rates, such as 1e-7 and 1e-9 . Additionally, I varied the dataset sizes, including 5k, 2k, 1k, and 15k data points; however, I consistently obtained the same results.
I have followed this finetuning code. https://huggingface.co/blog/fine-tune-wav2vec2-english.
Training Code for your reference.
model_training.txt
prepare_dataset.txt
prepare_tokenizer.txt

I have same issues, do you have any solutions for that?


Turn into module and lazy-load

I appreciate that the current design is much easier to maintain, but it would be nice to have lightspeed do proper on-demand loading (similarly to how old vimscript plugins did the heavy lifting in autoload functions that are not sourced unconditionally at startup).
(Basically, you want to move as much as possible into modules that are required only on executing the mappings.)

Yeah, for a while I've been thinking about that maybe it's time to explode the single source file.
On the other hand, in Lightspeed's case this might not be the most pressing thing to do. The plugin is still pretty lightweight, there's not much logic running when requiring, except for defining a bunch of highlight groups and checking/defining mappings; it's almost in the same order of magnitude than lazy-loaded plugins (currently it adds 20ms on my super-slow laptop, where the absolute bare-bone ones are around 1-3ms). And I can hardly imagine any editing session without using it, it is an even more basic tool than surround or targets.  Moreover, for any search executed, we will need pretty much the whole codebase anyway (we're processing everything ahead of time, this is the very concept), thus there's not much sense in modularizing it too much yet - for this reason, at least.
One more thing: motion plugins are kinda special in this regard, since for those even the slightest noticeable pause can be super-annoying when the loading is deferred to the actual invocation (looking at you, targets.vim).
That said, as I mentioned above, I'm thinking about this, and will probably do the big refactor sometime in the near future. (E.g. the highlight section is almost certain to get its own module.)

Yeah, I understand that completely. For me, it's about 1.3ms out of 50ms -- not at all terrible, but the largest single time for a plugin without configuration (beating even vim-fugitive), so I just thought there might be some low-hanging fruit somewhere.
I was certainly not asking to re-engineer for absolutely minimal startup time -- I agree that this makes little sense in this case if(!) there are trade-offs.

I agree with clason, it would be nice to see proper lazy-loading capabilities.
As a workaround I put the following in my packer.nvim config:
use {
    'ggandor/lightspeed.nvim',
    keys = {
        '<Plug>Lightspeed_s',
        '<Plug>Lightspeed_S',
        '<Plug>Lightspeed_x',
        '<Plug>Lightspeed_X',
        '<Plug>Lightspeed_f',
        '<Plug>Lightspeed_F',
        '<Plug>Lightspeed_t',
        '<Plug>Lightspeed_T',
    },
    setup = function()
        local default_keymaps = {
            { 'n', 's', '<Plug>Lightspeed_s' },
            { 'n', 'S', '<Plug>Lightspeed_S' },
            { 'x', 's', '<Plug>Lightspeed_s' },
            { 'x', 'S', '<Plug>Lightspeed_S' },
            { 'o', 'z', '<Plug>Lightspeed_s' },
            { 'o', 'Z', '<Plug>Lightspeed_S' },
            { 'o', 'x', '<Plug>Lightspeed_x' },
            { 'o', 'X', '<Plug>Lightspeed_X' },
            { 'n', 'f', '<Plug>Lightspeed_f' },
            { 'n', 'F', '<Plug>Lightspeed_F' },
            { 'x', 'f', '<Plug>Lightspeed_f' },
            { 'x', 'F', '<Plug>Lightspeed_F' },
            { 'o', 'f', '<Plug>Lightspeed_f' },
            { 'o', 'F', '<Plug>Lightspeed_F' },
            { 'n', 't', '<Plug>Lightspeed_t' },
            { 'n', 'T', '<Plug>Lightspeed_T' },
            { 'x', 't', '<Plug>Lightspeed_t' },
            { 'x', 'T', '<Plug>Lightspeed_T' },
            { 'o', 't', '<Plug>Lightspeed_t' },
            { 'o', 'T', '<Plug>Lightspeed_T' },
        }
        for _, m in ipairs(default_keymaps) do
            vim.api.nvim_set_keymap(m[1], m[2], m[3], { silent = true })
        end
    end,
}

This makes it so that lightspeed is loaded only on-demand, when one of the mappings is actually invoked.

@disrupted nice, thanks for sharing!

All of the mappings for Lightspeed use require'lightspeed', so if those are simply exported to a plugin/lightspeed.lua (or .vim) and the definitions could remain in lua/lightspeed.lua, I don't think anything else would need to change. Also, neovim will load plugin/*.lua files now, so the plugin/lightspeed.vim could be dropped.


fortedata package goals

Hello @ashiklom @atkinsjeff @cmgough
It was an interesting idea to provide the students with a one-stop, easy to use FoRTE R data package. Everyone seemed to have questions/difficulties with the Google Drive download step, which I can understand, and this might make it much easier.
I think it would be good to build slowly into this, i.e. do the easiest things first, test, expand, test. A proposal:
First priority: things that everyone needs and will never change:

Plot/treatment assignments
Subplot orientation
Lon/lat of plots

Second priority: data that many people need and will change only slowly:

Tree inventory data
Local climate data (from Ameriflux tower)?
...?

Third priority: student-specific data, e.g.:

Kayla's raw Licor data and collar/subplot assignments
Lisa's leaf physiology data
Max's raw diameter data

Thoughts? Thanks.

Sounds great! Are the "first priority" data already available somewhere? If so, I can take some time to work on this this week.
Some more ideas for "Second priority":

Functions to download climate reanalysis products for UMBS (for comparison/cross-calibration against local climate data)
Categorical trait data (e.g. from USDA Plants, TRY) for UMBS species. (Maybe also subsets of pubic quantitative trait data from TRY as well? Could be useful for comparison)
Functions (and/or downloads) of remote sensing data at UMBS -- definitely Landsat and MODIS, possibly older AVIRIS flights, others?

Fantastic! Jeff likely has the first priority data hat his fingertips, since he's been playing with the stem map data.
For the second priority:

Tree inventory data: it would be slick if we could apply allometries and scalers for the derivation of wood NPP since this is a key measurement of use to many.
Local climate data: could pull in flux tower data and data from forthcoming installed met stations that Jeff and I hope to install before the girdling treatment.

this week

I would like to be careful here. If we build this, and the students start to use it, that's great...but then any significant subsequent change will break their scripts. So it's worth taking a bit of time to think about design options, and try it privately (i.e. among us), before releasing it more broadly.
The simplest but almost most fundamental thing to start with might be this table:

Replicate
Plot
Longitude
Latitude
Treatment
Area_m2

This information is all (i) already known and (ii) will never change, right? @atkinsjeff ?
We also want a consistent naming scheme, e.g. this might be fd_plots. Thoughts?
The advantage of a data package is it should be dead simple to use, but we'll still want a wiki page describing how to install, load, and use it.

it's worth taking a bit of time to think about design options

Good point -- I probably jumped the gun a bit. Though I also think the sooner we have something to play with, the sooner we can get a sense of what works.

a wiki page

I agree that this should be documented, but I think it would be good if this lived inside the package itself (i.e. not as a GitHub wiki), partially in the .Rd files and partially as RMarkdown vignettes. That documentation could then be rendered as a website using pkgdown with minimal effort. A really cool idea would be to add vignettes representing real exploratory analyses using the data, especially if many of them were prepared by other FoRTE participants.

design options

Although I wouldn't necessarily recommend SQL as a storage backend for this (plain text is conceptually much simpler and easier to version-control), I do think creating an SQL-inspired "database schema" is a useful way to map out the data and their interrelationships and constraints.

Re documentation–ah, that's a much better idea, agreed.

database schema

Agreed! Plain text much simpler and perfectly adequate for our purposes, as far as I can see, but a clear schema on how things relate would be useful.

To answer @bpbond yes all those data and metadata exist. As do matching with the inventory data that @cmgough mentioned and no, they will never change. Going with the original plan we talked about earlier I would suggest
Replicate (i.e. A, B, C, D), Plot (i.e. 1,2,3,4), Subplot (i.e. E, W), Treatment (i.e. 00, 45, 65, 85), Lat, Long, Area (thought area is constant, but I can see the utility).
Also, Subplot could be changed to the bottom-up, top-down classification (i.e. B and T) and we can drop the subplot thing if desired, but saying treatment twice is confusing. Thoughts?

Looking back at older files we designated the "treatments" as "disturbance_severity" and  "disturbance_approach"

Interesting questions. Personally I would prefer to keep separate things separate (see @ashiklom 's comment above about schemas). So this would involve one plots table (mapping disturbance level to replicate/plot combination) , and one subplots table (mapping disturbance approach to plot/subplot combination).
Just committed (in c7e1fa2e909361cc2bf7c03d5c063ec86d3956b6) an example of this, along with a fd_plots() function to return it.
We could then have a fd_plots_subplots() function that would return a unified table like this (but perhaps using base R only)
fd_plots() %>%
  left_join(fd_subplots(), by = c("Replicate", "Plot"))

using base R only

base::merge!
merge(fd_plots(), fd_subplots(), by = c("Replicate", "Plot"))

@atkinsjeff Just in terms of learning–at this point you can clone the repo to your computer, open the RStudio project file, select Build->Install and Restart, and the fortedata package will be loaded.
Now type fd_plots() to see the dummy plot table, and ?fd_plots for its help page. The code for this function is in R/ and the data are in inst/extdata/.

Where do we want this .csv to go?

The .csv file lives in inst/extdata–you can see the sample one I put here: https://github.com/FoRTExperiment/fortedata/blob/master/inst/extdata/fd_plots.csv


ES6 transpilation of 'new.target' is not yet implemented.

Google closure does not support new.target. Is it possible to replace it with something else?

Meybe change new.target !== SqliteError to this.constructor.name !== "SqliteError".


filter out vendored imports, copy vendor directories

This addresses #444 partially. It only filters out imports of a package PKG which are present in $PKG/vendor because only those are definitely going to be used by go build.
Let me describe what's expected after this PR:
Say I'm at $GOPATH/src/github.com/donhcd and I have two git repos test and test2:
$ ls test
f.go
$ cat test/f.go
package test

import _ "github.com/donhcd/test2"
$ ls test2
f.go
$ cat test2/f.go
package test2

import _ "github.com/blang/semver"

Then
$ cd test
$ godep save
$ find vendor
vendor
vendor/github.com
vendor/github.com/blang
vendor/github.com/blang/semver
vendor/github.com/blang/semver/semver.go
vendor/github.com/blang/semver/sort.go
vendor/github.com/blang/semver/README.md
vendor/github.com/blang/semver/LICENSE
vendor/github.com/blang/semver/json.go
vendor/github.com/blang/semver/sql.go
vendor/github.com/donhcd
vendor/github.com/donhcd/test2
vendor/github.com/donhcd/test2/f.go
$ rm -r vendor Godeps # cleanup

which is the same behavior you would find in godep master.
However, my PR introduces new behavior if you follow this workflow:
$ cd ../test2
$ godep save
$ find vendor
vendor
vendor/github.com
vendor/github.com/blang
vendor/github.com/blang/semver
vendor/github.com/blang/semver/semver.go
vendor/github.com/blang/semver/sort.go
vendor/github.com/blang/semver/README.md
vendor/github.com/blang/semver/LICENSE
vendor/github.com/blang/semver/json.go
vendor/github.com/blang/semver/sql.go
$ cd -
$ godep save
$ find vendor
vendor
vendor/github.com
vendor/github.com/donhcd
vendor/github.com/donhcd/test2
vendor/github.com/donhcd/test2/f.go
vendor/github.com/donhcd/test2/vendor
vendor/github.com/donhcd/test2/vendor/github.com
vendor/github.com/donhcd/test2/vendor/github.com/blang
vendor/github.com/donhcd/test2/vendor/github.com/blang/semver
vendor/github.com/donhcd/test2/vendor/github.com/blang/semver/semver.go
vendor/github.com/donhcd/test2/vendor/github.com/blang/semver/sort.go
vendor/github.com/donhcd/test2/vendor/github.com/blang/semver/README.md
vendor/github.com/donhcd/test2/vendor/github.com/blang/semver/LICENSE
vendor/github.com/donhcd/test2/vendor/github.com/blang/semver/json.go
vendor/github.com/donhcd/test2/vendor/github.com/blang/semver/sql.go

In master, this would result in output identical to the first example, which causes problems if you have different dependencies using incompatible versions of semver.

ping @freeformz

godep's goal is to produce a single, top level vendor folder. See the convo in #444 as to why.


InterruptibleStdioStream error when starting container

When trying to start a container, the log will eventually show this line:

Error InterruptibleStdioStream.cpp:61: Got EOF on stdin; closing

Trying to connect to the server results in failure. Checking if the port is open, i.e. with ping.eu shows that it is closed.
I had this same error and behavior on multiple different vps servers. The same setup used to work on both of these servers in the past.
Cropped Log
factorio    |    0.020 Running in headless mode
factorio    |    0.026 Loading mod core 0.0.0 (data.lua)
factorio    |    0.145 Loading mod base 0.18.27 (data.lua)
factorio    |    0.487 Loading mod base 0.18.27 (data-updates.lua)
factorio    |    0.660 Checksum for core:<PHONE_NUMBER>
factorio    |    0.660 Checksum of base:<PHONE_NUMBER>
factorio    |    0.883 Prototype list checksum:<PHONE_NUMBER>
factorio    |    0.955 Info PlayerData.cpp:68: Local player-data.json available, timestamp<PHONE_NUMBER>
factorio    |    0.955 Info PlayerData.cpp:75: Cloud player-data.json unavailable
factorio    |    0.957 Factorio initialised
factorio    |    0.958 Info ServerSynchronizer.cpp:28: nextHeartbeatSequenceNumber(0) initialized Synchronizer nextTickClosureTick(0).
factorio    |    0.958 Info ServerMultiplayerManager.cpp:771: updateTick(4294967295) changing state from(Ready) to(PreparedToHostGame)
factorio    |    0.958 Info ServerMultiplayerManager.cpp:771: updateTick(4294967295) changing state from(PreparedToHostGame) to(CreatingGame)
factorio    |    0.962 Loading map /factorio/saves/_autosave1.zip: 6871857 bytes.
factorio    |    0.980 Loading level.dat: 20011161 bytes.
factorio    |    1.001 Info Scenario.cpp:187: Map version 0.18.14-1
factorio    |    2.586 Loading script.dat: 35249 bytes.
factorio    |    2.590 Checksum for script /factorio/temp/currently-playing/control.lua:<PHONE_NUMBER>
factorio    |    2.610 Info UDPSocket.cpp:27: Opening socket at (IP ADDR:({<IP_ADDRESS>:34197}))
factorio    |    2.611 Hosting game at IP ADDR:({<IP_ADDRESS>:34197})
factorio    |    2.611 Info ServerMultiplayerManager.cpp:771: updateTick(2080401) changing state from(CreatingGame) to(InGame)
factorio    |    2.614 Info RemoteCommandProcessor.cpp:131: Starting RCON interface at IP ADDR:({<IP_ADDRESS>:27015})
factorio    |    2.614 Info CommandLineMultiplayer.cpp:303: Maximum segment size = 100; minimum segment size = 25; maximum-segment-size peer count = 10; minimum-segment-size peer count = 20
factorio    |    2.616 Error InterruptibleStdioStream.cpp:61: Got EOF on stdin; closing

I am not sure what type of prompt this is. Can you try running docker with stdin and post what it asks for? Also the command you used to run the Image would really help me debugging this.

I think I'll add it when the question comes up again.


Potentially update BoxSpec to download objects from neutral location at server root

@CalebKendra discovered that GitHub is potentially limiting certain kinds of operations (i.e. the use of the gitit module to download content from world-additions). This is a problem. A big one. It makes certain parts of some assignments inoperable.

This was fixed in the last set of commits. The remedy is to update to a content CDN; we're using GitHub raw


Autosuggest Users

I want to be able to tag users that has access to the repo.

org members are taggable


Translate concepts/cluster-administration/kubelet-garbage-collection.md in Korean

This is a Feature Request

What would you like to be added

Translate concepts/cluster-administration/kubelet-garbage-collection view in Korean.
Why is this needed
There is no documents with concepts/cluster-administration/kubelet-garbage-collection in Korean.
Comments

https://kubernetes.io/docs/concepts/cluster-administration/kubelet-garbage-collection/

/language ko
/assign


Add forked to indicator to query

Shows where a query was forked to an from (my first time writing both django and angular: apologies if I'm not doing it right)

Add "parent_id" field to show where a query was cloned from
Add parent and forked queries to query (fiddle) screen

I was keeping this pull request open as a reminder to implement this functionality, but realized that I won't do it any time soon, and it started to become ridiculous. So with heavy heart, I'm closing this...
Sorry, @shayel.


Configuration tool

Original report by Brian Calder (Bitbucket: brian_r_calder, ).

  Some of those are a little obscure, and it would be better if there was a tool to allow the user to examine the current configuration, or set a new one.
Features might include:

Automatic generation of the unique ID for the logger
Upload and download of configuration information
Setting up processing request and additional metadata elements with appropriate formatting.

Original comment by Brian Calder (Bitbucket: brian_r_calder, ).

Resolved in release 1.3.0 of the system through DesktopUI.


fix parameter name in preprocess function; fix remote model function …

…name
Description
[Describe what this change achieves]
Issues Resolved
[List any issues this PR will resolve]
Check List

[ ] New functionality includes testing.

[ ] All tests pass

[ ] New functionality has been documented.

[ ] New functionality has javadoc added

[ ] Commits are signed per the DCO using --signoff

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

Tests are failing.


Update NEWS.md and improve consistency of MPI container fieldnames

Close #1086.

I'll just merge right now since we only got new documentation stuff in main


App crash when access to camera

Some apps like google meet and chrome will crash when access to camera. There is the log https://hastebin.com/ijoyuyicox
In previous versions vcam v2.5 it runs normally and doesn't crash, And when in v2.6 and v2.7 the app crash, I've tried disabling and enabling cam2api.

The problem has not been resolved, meet gmail and chrome still crash in version 2.8. there is the log https://hastebin.com/iletonaloh

But....I have tested on my phone (samsung a60 with Android 11)
Although Chrome will get crash when close the camera( I think it can be fixed.)， The apps runs smoothly.
because Google meet doesn't have access to local storage,  you only can see a blank preview. BUT it wouldn't get crash.

hmm.... ok, google meet in gmail app i mean. Maybe it's because I'm using a custom rom. By the way, thank you for your hard work developing vcam for android. Very useful 🙂

version of 2.9 has successfully fixed the chrome app crash
Have a try!


PostalInfo::info_type can be an enum

https://datatracker.ietf.org/doc/html/rfc5733#section-3.2.1

One or two contact:postalInfo elements that contain postal-
address information.  Two elements are provided so that address
information can be provided in both internationalized and
localized forms; a "type" attribute is used to identify the two
forms.  If an internationalized form (type="int") is provided,
element content MUST be represented in a subset of UTF-8 that can
be represented in the 7-bit US-ASCII character set.  If a
localized form (type="loc") is provided, element content MAY be
represented in unrestricted UTF-8.  The contact:postalInfo
element contains the following child elements:

Ah, that's a a good bit more complex than what we have now. So if I understand correctly:

There might be two postalInfos, not just one (as we have now)
If type = int the content must be representable in ASCII
If type = loc the content may use all of UTF-8


[Depends on #37] Add on/off ramps to highways

Once #37 is done, add the on/off ramps to the highways.

Adding on-off ramps means moving all the 2D geometry to 3D, so won't be done in the foreseeable future. Closing.


Adding new LP Rewards contract for Saddle TBTCv2 pool

New Saddle LP Token along with a new Saddle TBTCv2 pool is already on mainnet. We want to support rewards for the new Saddle pool and this contract inherits from the previous LP Saddle Rewards and from LPRewards contract.
Saddle LP token: https://etherscan.io/address/0x122Eca07139EB368245A29FB702c9ff11E9693B7
Saddle TBTCv2 Meta Pool: https://saddle.exchange/#/pools/tbtc/deposit

@dimpar Could you please also update deployment scripts? Can be in this PR or in a separate one.

@dimpar Could you please also update deployment scripts? Can be in this PR or in a separate one.

Do you mean this guy https://github.com/keep-network/keep-migrations/pull/20 or something else?


fix(TestUtils): inlcude dts file in files array

Description
Adds index.d.ts file to the files included in the published artifact for @lightningjs/ui-components-test-utils.

References

Testing

Automation

Checklist

[ ] all commented code has been removed
[ ] any new console issues have been resolved
[ ] code linter and formatter has been run
[ ] test coverage meets repo requirements
[ ] PR name matches the expected semantic-commit syntax

:tada: This PR is included in version @lightningjs/ui-components-test-utils-v1.4.1 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


InvalidChainFound - block 1738697

Hi, dash has stopped syncing at block 1738697. Same issue is with some other online services like cryptoid - see attached screenshot. Sync stopped at same block.

Log events: 2022-09-15T13:05:47Z InvalidChainFound:  current best=00000000000000362d528545b40976af8a9b5380def57d63943a30a9379a5385  height=1738697  log2_work=78.91219653  date=2022-09-15T12:39:02Z
CheckForkWarningConditions: Warning: Found invalid chain at least ~6 blocks longer than our best chain.
Any idea what is going on?

Yes, Dash's previously announced hard fork happened at block after they are stuck. This could happen if Dash Core was not updated to v18 prior to activation.
This support article describes how to get back on track.

Thank you, this solved the issue indeed. Confirmed.


ConsentCookie API changes #23 regression bug

Description
Return of ConsentCookie.get() does not contain a public variables consents with the key-value mapping of the Consents mapped by the id
Expected Behavior

Actual Behavior

Possible Fix
Make the API backwards compatible with 0.6.4
Steps to Reproduce

load the demo page
from console after ConsentCookie has been initialized: ConsentCookie.get()

Context
GTM implementation does not work properly
Your Environment
n.a.

Fixed backwards compatibility

@christianvriens Could you confirm this:
https://cdn.humanswitch.services/cc/consentcookie/app/snapshot/adc70bf05e62049cfe388fcb56b377bb8a91ebb1/consentcookie.min.js

Tested
Is solved!


Instrumentation for outbound rosetta client request/responses to track slow or failing endpoints

Is your feature request related to a problem? Please describe.
Currently, there is no instrumentation support in rosetta-cli. Adding flag to enable instrumentation should start tracing outbound requests to measure their response time, error percentages, p99, p95, p50 etc
We can add an enable-request-instrumentation flag in config.json to enable or disable instrumentation.
Describe the solution you'd like
If we can integrate some instrumentation library such as open telemetry in rosetta-cli, we can instrument request/response of rosetta endpoints.
We would be able to see slow and error requests.
Describe alternatives you've considered
Problems with current performance tooling:

check:perf
It needs to be run as a separate process and measure results for /block and /account/balance endpoint.
/account/balance is not using "address" value from blocks but is using hard-coded "address" string which is why all of requests fail due to address validation.
--block-profile
It is great to measure block pprof data but does not shows which requests failed or are slow.

Additional context
Adding instrumentation could potentially slow down the process which is why it is important to have enable/disable configuration added for it.

Fixed in #395


CORE deposit error - "No datastream could be returned" - (user Adam Pfau/SLS Papers)

Date first reported: 5/12/2022
Site: Humanities Commons
Area: CORE
Description
On Adam Pfau/SLS Papers's deposit titled "Are YouTube and Netflix One-Way Stops to Learn a Language? Language Learners’ Beliefs on Videos," the file does not appear when you click View in Browser or Download. Instead you get the message: "[DefaulAccess] No datastream could be returned. Either there is no datastream for the digital object "hc:45840" with datastream ID of "CONTENT "  OR  there are no datastreams that match the specified date/time value of "null "  ."
Further details
Deposit: https://hcommons.org/deposits/item/hc:45839/

This is a duplicate of https://github.com/MESH-Research/commons/issues/364 (which has been fixed)


⚠ Bofrost.fr has degraded performance

In 3c3c789, Bofrost.fr (https://www.bofrost.fr) experienced degraded performance:

HTTP code: 200
Response time: 818 ms

Resolved: Bofrost.fr performance has improved in cd0091d.


Lumina-T2X VAE problem

As mentioned in the openCV dalle3 paper, the channel number of VAE is critical in generating character, letters. Do you guys have any plans to upgrade the SDXL VAE to a similar VAE version similar to SD3 (16 channels).
Besides, do you guys plan to release a larger version of Lumina.NEXT, like 5B or 8B, etc?

Lumina is integrating with SD3-VAE currently. The model is expected to be released in a few weeks.

@gaopengpjlab any reason to use SD3's commercial VAE over https://huggingface.co/AuraDiffusion/16ch-vae which  matches the performance but is under a totally open license?

Lumina 目前正在与 SD3-VAE 集成。该模型预计将在几周后发布。

As far as I know, the basic license of sd3 restricts the use of any components of sd3 for other models, and stability will be held accountable if you do，


cmp.c is executable

This causes no trouble but cmp.c has permissions 755 instead of 644.

@camgunz This was closed in #28, can you close it ?

Yes, thanks


Adding an event tracking system (focus is use in M/EEG & fMRI research)

Summary of the idea
Create a tracking system that records custom events (e.g. trial start, object picked up etc.) when they happen in system time (not in relative time) so it can be accurately used to model neural data (e.g. in M/EEG & fMRI), where we need to know the exact timing of when relevant things happened because we want to relate them to the data that is saved by another system (e.g MRI-scanner).

Illustration of the idea
Detailed description
My current idea is that there is central script called EventTracker.cs  that receives bits of informations (like strings) from other scripts (e.g. a script that deals with picking up objects) and records & saves these bits to a .txt file. This system would be for relatively rare events  that don't need to be updated every frame in contrast to for instance the player position, so in my opinion this tracker system only needs to write something down when it receives information but not when nothing happens. I also think it would be useful to have this script running across trials & blocks so inforrmation about trial starts can be saved. However, I am not sure whether that conflits with how UXF is set up.
Further comments
I think this kind of functionality might be useful for neuroimaging research because it lets you use relevant information directly.  I will work on something like this for my own fMRI research so I am happy & willing to develop such functionally but it would be nice to know how it can be easily integrated with UXF and how it can be general enough so it is useful for other people.

This does sound great indeed. I will check how that work for my current project and see if there might be something that can or should be improved.


Manual clustering GUI won't open in Session

I can run the GUI straight from the command line, but not within a session. I think it's QT related, because when I run
$ phy.enable_qt()
the results is:
[W] Qt event loop not activated.
Running on OSX.
Thanks!

 Are you in IPython?

The exact commands I'm using are
$ source activate phy
$ python
$ import phy
$ phy_enable_qt()

OK; this may be fixed in the future. In the meantime, can you use ipython instead of python?

Yep, that works. Thanks!

closing in favor of #560