Confused about number of steps

Hi, I saw your training curve for Gemma 9b SimPO here: https://wandb.ai/yumeng0818/simpo/runs/4w25j650?nw=nwuseryumeng0818.
How is it that there's only 92 steps? At 128 batch size, that would only be 11k total examples seen, but there's ~60k in the dataset.
Thanks.

Hi @cinjon did you figure it out? It's confusing. Also the actual batch size seems to be 256 (2 * 8 * 16), so there should be about 232 steps for 1 epoch.

Still confused but our training runs are reasonable, so I gave up trying to guess theirs.
Yeah I was confused if it was 128 or 256.
I'm also confused about their eval templates and scores on Gemma.

@cinjon I tried to use TRL's implementation (https://huggingface.co/docs/trl/cpo_trainer#simple-preference-optimization-simpo) for training runs, but I cannot reproduce their Gemma2-9B-SimPO model. The resulting model after 1 epoch on the dataset is so much worse. I noticed there is another PR by the authors to create a separate SimPOTrainer with TRL: https://github.com/huggingface/trl/pull/1725 I hope that can fix the issues.


Create sk.js

Hey, I´ve just created this little document translated to SLOVAK language.
Matus

Thank you very much @matoweb!

Not problem at all guys.


Support fetching annotations and populating them in TimelineChart model

Signed-off-by: Patrick Tasse<EMAIL_ADDRESS>

If this patch requires changes to other libraries, could you point to them here please?


Cannot tune sequential model given get different results for each run

Click to expand!
Issue Type
Bug
Have you reproduced the bug with TF nightly?
No
Source
binary
Tensorflow Version
2.12
Custom Code
No
OS Platform and Distribution
No response
Mobile device
No response
Python version
No response
Bazel version
No response
GCC/Compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
No response
Current Behaviour?
I am trying to tune a sequential model. But if I rerun my tuning code, I get a different result for "best parameters" each time. I am not using GPUs. I have seeds set to a constant.
My tuning code ran fine under an earlier tf version. But when I updated to latest, it stopped producing replicable results.
Did a specific version give up on replicability? Is there a workaround for tuning?
Standalone code to reproduce the issue
https://colab.research.google.com/drive/1wxa5PCf7kQhTKrDFlbehq-k8MGAQpwkK?usp=sharing

Relevant log output
No response

It is common for the results of a machine learning model to vary slightly between runs, even when setting random seeds to a constant. While setting random seeds can help control for some sources of randomness and make your results more consistent between runs, it is still possible for the results to vary slightly. This is normal and to be expected. also the weights of a machine learning model will not be exactly the same after each run. The weights are initialized randomly at the beginning of training and are updated during training based on the data and the optimization algorithm used. As a result, the final weights of the model can vary slightly between runs.
I can see that the results you got were not changing significantly.
Hopefully this was helpful

Still a bit concerned about tuning. When I ran simple tuning algorithm on a Sequential model, I came out with different architectures as best on every rerun, i.e., different number of layers and different nodes in each layer. It is kind of hard to average architectures across reruns.
My conjecture is this will also affect sklearn tuning algorithms, e.g., RandomSearch and HalvingSearch. They will not produce consistent "best parameters" on rerun. I plan to test this out in next couple days. I feel I am missing something because I would expect a hue and cry from the community if tuning libraries stopped working as expected and I have not seen any complaints.
Also, it still seems something changed in a version update. As I said, I would get consistent results with early versions of 2, but an update to latest 2 version changed things.

Calling tf.keras.utils.set_random_seed sets the Python seed, the NumPy seed, and the TensorFlow seed. Setting these seeds is necessary to ensure any random numbers your program generates are also deterministic.
I tried to execute the code with the alternative approach by using tf.keras.utils.set_random_seed, and I was getting the same result while executing the mentioned code. Kindly find the gist of it here.
Could you please have a look at this official document for reference.
https://www.tensorflow.org/api_docs/python/tf/config/experimental/enable_op_determinism
Thank you!


@GenClient cannot expand method named in reserved word properly

val definition = Protocol.empty.codec[String].specify1("type", Field.strict[String]("foo"), Type[String])

@GenClient(definition)
object FooClient

this throws compile error at
https://github.com/oncue/remotely/blob/master/core/src/main/scala/GenClient.scala#L46
since type is a reserved word.
easiest solution could be using backtick to surround the variable name, like this,
  val signatures : Set[Tree] = s.signatures.map { sig =>
      c.parse(s"""val `${sig.name}` = Remote.ref[${sig.typeString}]("${sig.name}")""")
  }

Closed by https://github.com/oncue/remotely/commit/21edf825880e2727ccab436b28de9441d7ff3070


3.0.x changelog

[ ] Object-oriented design
[ ] Support external Aplayer.js resource, see #24
[ ] Support external lyric resource, see #23
[ ] Support Meting API, see #21
[ ] Fix duplicate Aplayer.js loading, see #22
[ ] Configurable in _config.yml

Cool, let's make hexo-tag-aplayer great again.


Fix iOS 11 Navigation Issue

The steps described in #16 end up in a blank unresponsive page. These changes should prevent the unresponsive state in iOS 11 when the Photos permission is denied.
An additional PHAuthorizationStatus check before presenting Pickle.ImagePickerController is still required until the system permission denied message can be properly displayed in iOS 11.

Shall I merge and create a release with this fix? We need to ship it in next release :D

Sure, let me update the README first, thanks!


check_tree: crashes if no start-node defined

Describe the bug
The check_tree fct crashes if no start-node is defined in the tree.
To Reproduce
Steps to reproduce the behavior:

Create new tree and add a node (atm start-nodes can't be set in the UI)
Click "Export tree"

Additional context
Make the first node created the start node and offer option to change start node.

Fixed, first node in tree is automatically set as start-node.


Push container image should be an option in func build

While working on the Tekton Pipelines for onCluster builds I found that the push functionality is defined inside the func deploy command and that func build only does the building of the image. func deploy does the push if it is instructed to build the image as part of the deploy procedure.
My recommendation would be to:

Move the push functionality to build, with an optional parameter to do so
If func deploy wants to call func build it can do it and it can specify the push parameter there.

This will allow us to clearly define the functionality for both func build and func deploy.

@lance @zroubalik I need some consensus on this.. do you see any issue with this proposed change? I am happy to do the work around this.. but I am not sure who else needs to be included in the discussion.

Reference: https://github.com/salaboy/func-oncluster-build-experiments/blob/main/README.md

@salaboy makes sense +1 from me

Just note, func build should by default keep the current behaviour (ie. don't push)

@zroubalik so.. the idea is to add push as an optional parameter to fund build and remove the push code from func deploy? right? @lance are you ok with this change? @lkingland do you have any opinions on this change?

/assign

the idea is to add push as an optional parameter to fund build and remove the push code from func deploy? right? @lance are you ok with this change?

Conceptually, we think of deployment as a single act which may comprise multiple steps, one of which is a push to a registry. Truthfully, this push should be an implementation detail that the function developer should not have to think about. But of course we are not there yet.
Personally, I think this is fine. Although it would be worth talking with Luke about it. A pull request of his last year removed the --push flag from build. There is a lot of discussion in the PR comments about that decision. Although, now I think that some of that reasoning may be aged to the point where we can revisit it.

We should at least do this change internally in the API and not expose to CLI.

/assign @shinigambit

I think this was fixed in https://github.com/knative-sandbox/kn-plugin-func/pull/681
Closing as resolved


Stop crash when a scene has the tool keyword and _exit_tree() method

Fix for https://github.com/godotengine/godot/issues/34959

Not sure how to handle this. Closing the tab will now memory leak.

@vnen Can you look into this. I don't like this patch, but maybe you can fix this another way.

That's too Jacky, Node should not have any code from editor/.


Error creating a simple Database object in Snowflake

Terraform CLI and Provider Versions
provider[registry.terraform.io/snowflake-labs/snowflake] ~> 0.76
Terraform v1.0.11
on linux_amd64

provider registry.terraform.io/snowflake-labs/snowflake v0.81.0

Terraform Configuration
terraform {
  required_providers {
    snowflake = {
      source  = "Snowflake-Labs/snowflake"
      version = "~> 0.76"
    }
  }
}

provider "snowflake" {
  role = "SYSADMIN"
}

resource "snowflake_database" "db1" {
 name = "TF_DEMO1"
}

Expected Behavior
Create the simple Database in Snowflake
Actual Behavior
Error: Provider produced invalid plan
│
│ Provider "registry.terraform.io/snowflake-labs/snowflake" planned an invalid value for snowflake_database.db1.data_retention_time_in_days:
│ planned value cty.NumberIntVal(1) for a non-computed attribute.
│
│ This is a bug in the provider, which should be reported in the provider's own issue tracker.
╵
╷
│ Error: Provider produced invalid plan
│
│ Provider "registry.terraform.io/snowflake-labs/snowflake" planned an invalid value for snowflake_database.db1.is_transient: planned value
│ cty.False for a non-computed attribute.
│
│ This is a bug in the provider, which should be reported in the provider's own issue tracker.
Steps to Reproduce

terraform apply

How much impact is this issue causing?
High
Logs
No response
Additional Information
No response

Hey @ankitsr92. Thanks for reporting the issue.
Please bump Terraform version to 1.1.5 (at least; preferrable is the newest version). It should solve the problem. Please let me know if that helps.

@ankitsr92 hey! Did you have a chance to try it out?

Hey @ankitsr92, I will close this issue; please open a new one if you are experiencing this problem after bumping Terraform to 1.1.5.


Added date validation for birth date

Used regex and html5 pattern attribute

Yep yours is more succinct! I was trying to make the validation more stringent by making sure that dd cannot be more than 31 and mm cannot be more than 12 but didn't quite achieve that exactly

Thank you very much for your contribution.
I like the idea of doing a vanity check for the input data on top of the date format check. However, doing numeric range checks with regular expression is not possible, just string range checks (see regular-expressions.info).
I suggest the following improvements on top of your commit:

Add some more boilerplate HTML code around to be able to test the regular expression (Wicket will only use what is in the panel tag.)
Allow users to enter single digit numbers for the date and month
Further restrict the year to start with "1" or "2", instead of also a "0".

https://github.com/kwyoke/ksch-workflows/pull/1

Regarding the proposal from @ankurjha21 , I have asked a question for clarification here:
https://github.com/ksch-workflows/ksch-workflows/pull/23#issuecomment-434669822

resolve #21


Sunrise/set not being shown in 24h format and missing wind direction

Describe the bug
Sunrise and sunset is shown as AM/PM (12 hour format) despite use_12hour_format being set to "false"
Wind direction/bearing is being show as degrees and not text. Also arrow is missing
To Reproduce
Steps to reproduce the behavior:
Enable the following options:
use_12hour_format: false
winddir:
Expected behavior
Would expect sunrise/sunset being shown in 24H format, instead of AM/PM, when use_12hour_format  is set to false
Would expect winddirection being shown as text (for instance NW, instead of 315) - also an arrow being shown, indicating the direction. I am not sure why this not work as all screenshots in the examples looks correct
Screenshots
If applicable, add screenshots to help explain your problem.

Desktop (please complete the following information):

WEATHER-CHART-CARD VERSION: 2.2.6 (latest in HACS)
HOME ASSISTANT VERSION AND INSTALLATION TYPE (e.g.  2024.2.0 - was also broken in latest 2024.1.x)
OS: [e.g. 10.3, venv, etc.]. HomeAssistant OS 11.5
Browser [e.g. chrome, safari]: Chrome
Version [e.g. 22]: 121.0.6167.139

Additional context
Weather station data is coming from the Ecowitt integration in HA, using a GW2000 gateway and WS90 weather station
Weather forecast data is using met.no integration in HA

The use_12hour_format is part of the forecast setting, not for the attributes. The sunset and sunrise are now showing the time based on the language settings. If you have you general HA language on English I would like to propose to use English (GB) if you would like to have 24h format.
The windir alternate sensor in degrees I can reproduce and will provide a fix in a next release.

Thanks. I can confirm that updating the language settings does fix the 24h timeformat issue

I think the time and date format better follow the time and date formats as configured in the user profile.
In my case, I use time (24h) and date (ddmmyyyy) formats as used in most European countries (except the UK) while my language is English.

@erkr I will look for the option to change the forecast setting to a global setting, then it is fully controlled within the card.

Global flag for 12h works great, thanks


Add managed instance icon

Duplicate of https://github.com/microsoft/azuredatastudio/pull/21720 - CLA check isn't completing there for some reason so hoping this fixes it...
Did a small bit of cleanup while I was here
@nemanja-milovancevic

I'm still having issues with connecting to an actual MI server (following up offline about that...) but in the meantime I verified this at least can show the icon correctly by just hardcoding it for all servers.


Wrong variable referenced in MemoryCAcheItemPool.php

On line https://github.com/google/google-auth-library-php/blob/master/src/Cache/MemoryCacheItemPool.php#L77 it sets $this->deferred = []; when it should be setting $this->deferredItems = [];

Good catch! Thank you.


Add max batch size limit to BatchEventProcessor

Add an optional maxBatchSize parameter to BatchEventProcessor.
Defaults to Integer.MAX_VALUE.
Limits the amount of events that will be processed before updating the sequence in the BatchEventProcessor.
Closes #438

This changes the behaviour of the call on onBatchStart().  Previously it would receive notification of the entire count of pending events, now it receives the size of the batch that is going to be processed.  That does fit with the javadoc for the method, but the old value was useful for monitoring purposes - it is useful the know the size of the pending queue of events.

In my view, BatchEventProcessor is almost an implementation detail for many disruptor users. The processor is often instantiated through the DSL API. Is there a plan to expose the max batch size in the DSL API? It could be added as a default member in EventHandler<T>.


Outputs from background threads not displayed

Current main

Previous stable release (stable vs code & stable extension)

Looks like weird bug
here's the output you get when you run it a few times

Looks like we're getting the outputs, but we're not sending it correctly to VS Code or something wrong in vs code.

Works 100% reliably for me

Absolutely no idea, but this was not working earlier. No changes since then.

So it works for you now? If you still repro an issue we can try to debug on your machine


Make OEIUPAC optional for normalize_molecule, cut release

Also fixed typo in the error messages for OEIUPAC which incorrectly told the user it was missing OEOmega
This is actually a critical bugfix for some users who have everything needed but IUPAC and its inhibiting some packages which depend on this package.

@jchodera do you think you can update the OpenEye License on here? I think it expired based on the logs.

Will do!

Thanks!


Fix disable statement not working

Fix

[ ] Add a unit test to verify that the fix works.
[x] Explain briefly why the bug exists and how to fix it.

This bug was introduced through @arugal 's https://github.com/apache/skywalking/pull/4748. As we changed the loading priority and sequence of the OAL scripts, it did make sure disable statements could be found before loading hardcoded metric/record/...
I add a new disable.oal, and give it the highest priority. All disable statements have to be put in there.

[x] If this pull request closes/resolves/fixes an existing issue, replace the issue number. Closes #6662.
[x] Update the CHANGES log.

@nisiyong Please take a look.

👍I try it tomorrow.


Allow chaining of methods

Hey,
Would you mind returning this from use and useAfter helpers of network interface? It would make it easier to chain use calls. Maybe it's worth considering on other methods and classes as well.

Definitely! Do you have a proposal for a design? If we agree on something we'll definitely accept a PR adding this.


Support showLineNumbers option

resolve #114

This already has a PR (#116), but can you post a screenshot of your changes?

Sorry, I saw just when I created this PR.
But anyways, here is the screenshot:

LGTM.

Hey @guilhermefloriani thanks so much for the effort, but like @yeskunall said, #116 beat you to it 😄
Closing.


[Discussion Space] Support LaTeX and AsciiMath via MathJax on excalidraw.com

Even #5311 is starting to get cluttered with Vercel deployments left over after periodic force-pushes.  So, I'm opening this issue as a tidier place for discussion related to MathJax support in Excalidraw.
For those who have requested LaTeX support in Excalidraw, the plan is for that to go in @excalidraw/plugins once we create that package.  (That will take a bit of time.)
@baptiste @jcezarms @mcaruel @ad1992 @dwelle

See #5265 instead.


Refactor to better model multiple work graphs for in build tree

Fixes #?
Context
In some cases Gradle may run more than one set of tasks and other work during a build invocation, for example to build some local plugins in an included build prior to configuring the main build, or to build buildSrc or source dependency outputs prior to use. This PR models this situation more clearly by separating the "execution plan" from the "task graph" for a build in the tree, where multiple plans can be created, populated and executed for a build. Currently, a particular build may only have a single plan in use at a given time.
Contributor Checklist

[ ] Review Contribution Guidelines
[ ] Make sure that all commits are signed off to indicate that you agree to the terms of Developer Certificate of Origin.
[ ] Make sure all contributed code can be distributed under the terms of the Apache License 2.0, e.g. the code was written by yourself or the original code is licensed under a license compatible to Apache License 2.0.
[ ] Check "Allow edit from maintainers" option in pull request so that additional changes can be pushed by Gradle team
[ ] Provide integration tests (under <subproject>/src/integTest) to verify changes from a user perspective
[ ] Provide unit tests (under <subproject>/src/test) to verify logic
[ ] Update User Guide, DSL Reference, and Javadoc for public-facing changes
[ ] Ensure that tests pass sanity check: ./gradlew sanityCheck
[ ] Ensure that tests pass locally: ./gradlew <changed-subproject>:quickTest

Gradle Core Team Checklist

[ ] Verify design and implementation
[ ] Verify test coverage and CI build status
[ ] Verify documentation
[ ] Recognize contributor in release notes

@bot-gradle test and merge

OK, I've already triggered a build for you.


Feature request: Global search box

I think one of the the main benefits of having global assets database is to be able to instantly locate them, but at the moment using search functionality is a bit tedious: I need to know what exactly type/class (device, rack, circuit, device type, etc) the thing I am looking for belongs to and then I have to navigate to the very specific place where search for the particular class is possible (like Devices -> Device Type).
It would be amazing to have always visible, 'global' search box at the top of the page, please see my quick mockup:

Possible use scenarios would be as follows:

I want to locate some particular Exchange server, but I don't exactly remember how is it called or where it is. In such case I can just type 'exch' in the globlal search box. This would match all the servers containing name 'exch', but additionally all device roles like 'Exchange Server' as well as VLANs, etc with the name containing 'exch' string  - which I can explore further to locate my box.

I just type serial number / asset tag (or part of it) of the device in global search box - and it instantly comes up with the pieces of equipment that match the pattern.

Same thing - I paste IP address there and it comes up with the matching subnet objects - as well as devices assigned with the particular address.

I want to locate all Cisco 3850 devices in the datacenter - I just type 3850 in the global search box, and it comes up with the 3850 device type + all the devices that belong to it.

Etc etc.

Strongly seconded.
When I am searching for a device I don't know if the text is in the description of an IP address object, or the name of a device, or the description of the interface.

Dupe of #159 ?

Yes, this is a duplicate of #159.


Add emergency=fire_service_inlet

Maybe there is a better icon for this.

I don't know how to solve the conflicts. Can you tell me, what's missing?
https://wiki.openstreetmap.org/wiki/Tag:emergency%3Dfire_service_inlet#Tagging

PS: For reference: The tag was quite recently "approved" (see https://wiki.openstreetmap.org/w/index.php?oldid=2483791)

I think it should be fine now.


Categorical: don't sort the categoricals if Categorical(..., ordered=False)

In https://github.com/mwaskom/seaborn/issues/361 it was discussed that lexicographical sorting the categories is only appropiate if an order is specified/implied. If this is explicitly not done, e.g. with Categorical(..., ordered=False) then the order should be taken from the order of appearance, similar to the current Series.unique() implementation.

Note this should only be taken if Series.unique() is kept as it is now (https://github.com/pydata/pandas/issues/9346)
I'm also not so sure what is best here: if a categorical is changed from ordered==True to ordered=False, the order of the categories should not change, which means that in the following case the two categroeical datas are not equal:
cat1 = Series(Categorical(["a","c","b"], ordered=False))
cat2 = Series(Categorical(["a","c","b"]))
cat2.ordered=False

IMO ordered is effectively part of the dtype and should be immutable.

@shoyer: can you elaborate? :-) This is models after R's factor which lets you set this (but of course this will produce a new factor, not an inplace operation like we have it here)

@shoyer the more I think about it, the more sense it makes to not let s.cat.order be changeable (only readable). In R that's implicitly there, as every change creates a new factor,
If thats desireable, we need a change_ordered(new_order) method which returns a new copy of the categorical. And remove the setter...
@jreback @jorisvandenbossche any comments?

I don't think we necessarily need a change ordered method; it's straightforward enough to use Categorical.from_codes(orig.codes, orig.categories, ordered=False) or even just Categorical(orig, orig.categories, ordered=False).
By "part of the dtype" I'm referring to categorical data as it's defined, e.g., in dynd -- everything that's not the specific values of an array is part of the dtype. From a simplicity perspective, it's nice if that cannot change.

But right now it can change, as it is "only inplace", as it is a setter: s.cat.ordered = False. It's actually the only part of the s.cat-API, which does inplace by default (and only), all others are methods with a default of inplace=False.
E.g.
df["cat"] = ...
df.cat.cat.ordered = False

will change the dataframe itself
For all else, you have to assign again or use inplace=True:
df["cat"] = df.cat.cat.reorder_categories([...])
df.cat.cat.reorder_categories([...], inplace=True)

The current method to change the order is not friendly and requires more knowledge than most users would probably have.  Of course, many people would just use
ordered = pd.Categorical(['a','b','c']),
unordered = pd.Categorical(ordered, ordered=False)

which is a little wasteful but simple.  I could see something like
unordered = ordered.swap_ordering()

or
ordered.swap_ordering(inplace=True)

making it more obvious how to remove (or add) ordering.
One of the dangers of the current approach to ordering is
unordered = pd.Categorical(['a','c','d','b'], ordered=False)
unordered.ordered=True

which seems to work but only by accident.

actually we tried to hide pd.Categorical() and promoted s.astype("category") and s.cat instead, so I don't think that's a good option...

@JanSchulz I think this PR is fine.
separate issue is whether to change what ordered does now (e.g. make it a immutable property). (so let's open a new one for that).

@JanSchulz pls add a release note (API section, maybe add a small example to be clear).

As a comparison, R does lexicographical sort the categories for unordered factors (but that is the default).
And apart from that, I don't know if I find it more logical or not to sort the categories or not. @JanSchulz As you said in another discussion (about the sorting I think), that often 'the order of appearance' in a dataset does not really mean something. So I don't know if I find it worth changing.

@JanSchulz can you add a release note (and maybe a short example of the behavior change to 0.16.0)

@JanSchulz can you add a release note explaining this change? otherwise looks gtg.

@jreback @JanSchulz I am not really sure I think this is a good idea. I think having it sorted lexicographically is more logical, as there is no inherent order in the categories. But you still want to have this somewhat consistent. In that way, sorting it lexicographically makes the most sense I think.
This is also what R does (but there the default is unordered), and I think also what dynd does in factor_categorical (although I don't know if dynd has the distinction between ordered and unordered)

In [33]: pd.Categorical(["a", "c", "b", "a"], categories=['a','c','b'], ordered=None)
Out[33]:
[a, c, b, a]
Categories (3, object): [a < c < b]

In [34]: pd.Categorical(["a", "c", "b", "a"], categories=['a','c','b'], ordered=True)
Out[34]:
[a, c, b, a]
Categories (3, object): [a < c < b]

In [35]: pd.Categorical(["a", "c", "b", "a"], categories=['a','c','b'], ordered=False)
Out[35]:
[a, c, b, a]
Categories (3, object): [a, c, b]

In [36]: pd.Categorical(["a", "c", "b", "a"], ordered=None)
Out[36]:
[a, c, b, a]
Categories (3, object): [a < b < c]

In [37]: pd.Categorical(["a", "c", "b", "a"], ordered=True)
Out[37]:
[a, c, b, a]
Categories (3, object): [a < b < c]

In [38]: pd.Categorical(["a", "c", "b", "a"], ordered=False)
Out[38]:
[a, c, b, a]
Categories (3, object): [a, b, c]

So think the intent is to have the 2nd section (where no ordering is specified explicity) be turned into the first section by default (for all cases). They will still be ordered/unordered as a Categorical type as indicated by the ordered attribute.
This will effectively remove the default ordering from lexiographic to the discovery order (which is how .factorize() works).
a couple of options I see

leave this alone
make the default as I describe above, e.g. to the order of appearance
require categories to be specified when ordered=True (e.g. force the user to say the actual ordering)
leave this alone, but make ordered=None -> ordered=False, e.g. if you don't specify an ordering they your ordering is lexographic but you are not considered ordered (this is the same as 1), but we don't default the order

aside from this, I think we need for #9190
def set_order(self, ordered, inplace=False):
    Parameters
    ----------------
    ordered : boolean
       set the ordered attribute for this Categorical to be the passed ordered
    inplace : boolean, default False
        modify the categorical inplace

and then raise on cat.ordered = value (or could deprecate and suggest set_order)
I think 4) is the most logical here. Basically turning default Categoricals to unordered. The ordering still remains lexographic, unless otherwise overriden.

Yes, I also wanted to raise the idea to have unordered as a default (wanted to make an issue for that, but started with reraising in this issue). Do we discuss that here or open a new one?
I also think ordered=False as a default makes more sense:

It is more in line with the distinction of 'categorical' vs 'ordinal' variable (eg http://www.ats.ucla.edu/stat/mult_pkg/whatstat/nominal_ordinal_interval.htm), where we provide both in pandas through Categorical, but with the 'categorical' meaning as default.
Many common examples, saying gender (F, M), country, color, etc have no intrinsic order. So to say that defaulting to unordered makes as much sense I think.
In line with the default of R

I can life with making it unordered as default.
Regarding the default order on the categories: I actually don't mind much, if you want to have it ordered in most of the case you have to reorder anyway... i would lean slightly to let it be as it is now (lexi sorting and not order of appearance). Someone who is willing to make a decision should do it by either pulling this PR or closing it :-)
-> In line with option 4 above (default to unordered but lexi-sort the categories)
Regarding the method which changes the "ordered" property: maybe a s.cat.as_[un]ordered(inplace=False)' or s.cat.as_nominal/ordinal(inplace=False)would be more clear.set_ordercan mean both setting a specificly ordered categories or setting theorder` property.
Not sure about deprecation or not. If deprecation, just one cycle?

closing in favor of #9611


remove-toggle-height

removed toggle height and removed code around managing it in favor of pure css. converted some longer class names to shorter ones
https://github.com/AugurProject/augur/issues/1719

This pull request introduces 1 alert and fixes 2 when merging d89c776b738cffe6ece41abdfe702b807f6228c4 into 282bf1678ca9ef0c42f27f129ccd8b3d028083d2 - view on LGTM.com
new alerts:

1 for Potentially inconsistent state update

fixed alerts:

2 for Potentially inconsistent state update

Comment posted by LGTM.com

This pull request fixes 2 alerts when merging e4e124a19c6a65318ae70e7bb898aa7b1493df3e into 282bf1678ca9ef0c42f27f129ccd8b3d028083d2 - view on LGTM.com
fixed alerts:

2 for Potentially inconsistent state update

Comment posted by LGTM.com


46 Add rooted-paths sample scans

This set of commits replaces the existing scan files in the samples folder with five rooted-paths scans and modifies the README file (removes spaces between [] and () for several links and lists the new scan files).

Addressed by pull request #51, which has been merged into the develop branch.


Godot: Add support for .x86_32 extension for Linux x86 32-bit

SteamDB app page links to a few games using this
None yet, it's future proofing for Godot 4.0.
Brief explanation of the change
The extension changed from .x86 to .x86_32 in Godot 4.0.
Ref. https://github.com/godotengine/godot/pull/59394

Can you add test filenames for it please (and in the other PR)

Yes. We just need filenames that would actually match these rules.

I added some tests for a generic export for each platform, let me know if that's how it should be done.


N20: Bevy Engine

Sorry for missing the soft deadline. I focused too much on the Bevy release yesterday and let this slip. Hope we're not too late!
Part of #351

Merged, thanks for the PR!

It's a little bit longer than 1000 chars but I guess it's ok in this case

Thanks for the heads up. I'll consolidate even more next time


Brevity; Link to docs of abstractions over ACR / AKS integration

A summary of the operations described at [aks/cluster-container-registry-integration](https://docs.microsoft.com/en-us/azure/aks/cluster-container-registry-integration]
should be added at the top of this page.
The 'How-To' details integration from new / existing AKS / ACRs through
the --attach-acr and --detach--acr option flags; this abstraction simplifies
the process for new users and those with less granular subscription and/or
security configurations.
Example commands for abstractions over ServicePrincipal creation and ACRPull role configuration:
# create new ACR, AKS, and integrate the services
az acr create -n myContainerRegistry -g myContainerRegistryResourceGroup --sku basic
az aks create -n myAKSCluster -g myResourceGroup --attach-acr <acrName | acr-resource-id>

# existing AKS, attach ACR
az aks update -n myAKSCluster -g myResourceGroup --attach-acr <acrName | acr-resource-id>
# existing AKS, detach ACR
az aks update -n myAKSCluster -g myResourceGroup --detach-acr <acrName | acr-resource-id>

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

ID: d4af71a4-648e-580f-7e86-94ce05196de5
Version Independent ID: 134b8ba0-b085-076a-d2e1-16d0ddff5586
Content: Kubernetes on Azure tutorial - Deploy a cluster
Content Source: articles/aks/tutorial-kubernetes-deploy-cluster.md
Service: container-service
GitHub Login: @mlearned
Microsoft Alias: mlearned

Thanks for the feedback! We are currently investigating and will update you shortly.

@qzdl thanks for submitting a PR. Can you @ me directly in that PR and I can request to have it reviewed by the content authors.
I will close this and we can work off that PR request.


Naming convention, adding data from website, and CsI test

Sorry for the late response. I will get on it and make sure your suggestions will be used. I updated the file names to system-owner.dat. And all files are from the tutorial, excluding one that we cannot post there should be no need to worry on that end.


As a user, I want to see the identity related business

Statescan will support relay chain business. The main explorer will be separated by businesses. Identity is one popular feature of kusama/polkadot, and user may want following features:

[ ] Check my account identity history, basic info, sub-identities, parent-identity, etc
[ ] Check my identity registration/judgement status
[ ] See registrars
[ ] Search accounts by identity info
[ ] Do identity related operations

[ ] Registration
[ ] Request judgement
[ ] Add sub ids
[ ] Cancel request

@hyifeng will be the master of this story, @wliyongfeng and @Popoulosss will also help. We design the user features first, then discuss with @Popoulosss for the design.
I hope this feature will be one of our bounty program.


[$250] Payment option doesn't update unless refresh or reopen IOU details page reported by @thesahindia

If you haven’t already, check out our contributing guidelines for onboarding and email<EMAIL_ADDRESS>to request to join our Slack channel!

Action Performed:

Login with account A
Search for account B and request money
Open another browser > Login with account B
Go to chat with account A
Tap on pay button
Verify that you don't see the option Pay with PayPal.me at the button in iou details page
Close the modal
Go to account A
Go to settings > Payments > Add payment method
Click on PayPal.me > Add Paypal account
Go to account B again and click on pay button
Verify that you still don't see the option to Pay with PayPal.me
Refresh the page/ close and reopen the IOU details modal
Check if you see it now

Expected Result:
You payment options should update at the step 12
Actual Result:
The payment options doesn't update without refreshing or closing and re-opening the iou details page
Workaround:
unknown
Platform:

Where is this issue occurring?

Web
iOS
Android
Desktop App
Mobile Web

Version Number: 1.2.21-4
Reproducible in staging?: y
Reproducible in production?: y
Email or phone of affected tester (no customers):
Logs: https://stackoverflow.com/c/expensify/questions/4856
Notes/Photos/Videos:
https://user-images.githubusercontent.com/43996225/198913299-f0272dd6-1db6-46a1-b7e7-22788a1d73ea.mp4
https://user-images.githubusercontent.com/43996225/198913319-4a89ce03-5f83-4957-83d3-72598f9cb85e.mov
Expensify/Expensify Issue URL:
Issue reported by: @thesahindia
Slack conversation: https://expensify.slack.com/archives/C01GTK53T8Q/p1667080453236989
View all open jobs on GitHub

Proposal
The payment options are set at the state and when the option paypal is removed the old value is being used
https://github.com/Expensify/App/blob/62ff507162d7712c2aa76b5eb96141f83ec2dd91/src/components/SettlementButton.js#L43-L71
key can be used to fix this. Now it will re render if the paypal address changes
key={lodashGet(this.props, 'iouReport.submitterPayPalMeAddress')}
https://github.com/Expensify/App/blob/62ff507162d7712c2aa76b5eb96141f83ec2dd91/src/pages/iou/IOUDetailsModal.js#L140

I confirmed that the Paypal payment option does not show up until I refresh the page. Adding the external label.

Internal Upwork post: https://www.upwork.com/ab/applicants/1587687358672089088/job-details
External Upwork post: https://www.upwork.com/jobs/~016bc1d3a553815351

looks like we're still waiting for proposals on this one, not overdue

This seems to be relatively edge-casey, gonna mark it as a Weekly while we wait for proposals.

Bumped back to daily per our new BugZero process, internal Slack thread with deets

Thanks for the proposal @daraksha-dk. I am not sure I follow your proposal. I don't see why/where would we need to add a key?
Also why do e need to update it with submitterPayPalMeAddress ? How does it handle refresh problem?

Still open for proposals.

Proposal:
It looks like the issue is creating "buttonOptions" on the construction. So "buttonOptions" not changed on prop change.
https://github.com/Expensify/App/blob/dc0bb5db6dd835279dfb916e8b7b3ebd0703404f/src/components/SettlementButton.js#L43-L73
Solution:
Making a method to create "buttonOptions" so it will be changed if the prop changes.
-    constructor(props) {
-        super(props);
-
-        const buttonOptions = [];
-
-        if (props.currency === CONST.CURRENCY.USD && Permissions.canUsePayWithExpensify(props.betas) && Permissions.canUseWallet(props.betas)) {
-            buttonOptions.push({
-                text: props.translate('iou.settleExpensify'),
-                icon: Expensicons.Wallet,
-                value: CONST.IOU.PAYMENT_TYPE.EXPENSIFY,
-            });
-        }
-
-        if (props.shouldShowPaypal) {
-            buttonOptions.push({
-                text: props.translate('iou.settlePaypalMe'),
-                icon: Expensicons.PayPal,
-                value: CONST.IOU.PAYMENT_TYPE.PAYPAL_ME,
-            });
-        }
-
-        buttonOptions.push({
-            text: props.translate('iou.settleElsewhere'),
-            icon: Expensicons.Cash,
-            value: CONST.IOU.PAYMENT_TYPE.ELSEWHERE,
-        });
-
-        this.state = {
-            buttonOptions,
-        };
-    }
-
+getButtonOptionsFromProps() {
+  const buttonOptions = [];
+
+  if (this.props.currency === CONST.CURRENCY.USD && Permissions.canUsePayWithExpensify(this.props.betas) && Permissions.canUseWallet(this.props.betas)) {
+      buttonOptions.push({
+          text: this.props.translate('iou.settleExpensify'),
+          icon: Expensicons.Wallet,
+          value: CONST.IOU.PAYMENT_TYPE.EXPENSIFY,
+      });
+  }

+  if (this.props.shouldShowPaypal) {
+      buttonOptions.push({
+          text: this.props.translate('iou.settlePaypalMe'),
+          icon: Expensicons.PayPal,
+          value: CONST.IOU.PAYMENT_TYPE.PAYPAL_ME,
+      });
+  }

+  buttonOptions.push({
+      text: this.props.translate('iou.settleElsewhere'),
+      icon: Expensicons.Cash,
+      value: CONST.IOU.PAYMENT_TYPE.ELSEWHERE,
+  });

+  return buttonOptions;
+}

                             this.props.onPress(iouPaymentType);
                         }}
-                        options={this.state.buttonOptions}
+                        options={this.getButtonOptionsFromProps()}

The button is not updating because we are showing the previous options we need to re-render when the prop (PayPalMe address) changes
On passing key={lodashGet(this.props, 'iouReport.submitterPayPalMeAddress')} at SettlementButton the button will re-render with the latest option
https://github.com/Expensify/App/blob/62ff507162d7712c2aa76b5eb96141f83ec2dd91/src/pages/iou/IOUDetailsModal.js#L140

I like @daraksha-dk proposal, simple and takes advantage of the existing React component lifecycle.
Can you try your solution and post a screen recording of it working since it's so simple? Once that happens I'll accept the proposal.

@Delgee I like your proposal and I think it should work, let's go with it!

External Upwork post: https://www.upwork.com/jobs/~016bc1d3a553815351

@daraksha-dk thank you for your proposal, but I don't think your solution would work, because the SettlementButton sets its button styles in the constructor, and the constructor isn't invoked when props change.

@daraksha-dk thank you for your proposal, but I don't think your solution would work, because the SettlementButton sets its button styles in the constructor, and the constructor isn't invoked when props change.

My solution is to use key which will re-render the SettlementButton if the key value( submitterPayPalMeAddress ) changes so constructor will be invoked. You can see this article https://medium.com/@albertogasparin/forcing-state-reset-on-a-react-component-by-using-the-key-prop-14b36cd7448e

@jasperhuangg PR is ready for review. And created a proposal for Upwork.

@jasperhuangg @sakluger The last I could trace the changes was creation of SettlementButton in this PR. We've set buttonOptions in the constructor since the beginning and hence it wouldn't have refreshed the code. Now I am not sure if we had this code in some other component before this.
@jasperhuangg do you have the information on this?

Hmm it looks like that PR creates the settlement button using the constructor, it didn't necessarily introduce the bug, we just weren't aware of the bug when that PR went out and didn't know that was something we needed to test for. That being said, since that's the only PR that's related let's use that one. @mananjadhav

@sakluger If you comment on the PR, just make sure you mention something about how we should sure that all reusable components react accordingly to any prop updates.

it didn't necessarily introduce the bug, we just weren't aware of the bug when that PR went out

Honestly, this has been my dilemma for a few issues. Thanks for helping out here.

This PR was deployed to production 5 days ago, but it's payment date wasn't updated. @sakluger This due in 2 days.

@mananjadhav which PR were you talking about in this comment? It looks like the linked PR was deployed to production 6 days ago and should be paid out tomorrow.

@sakluger My bad, I am not sure why I saw 5 days ago! Thanks for clarifying.

@sakluger Quick note this is eligible for 50% bonus as it was merged within 3 business days.

see if there are any other reusable components that don't update to props like this one. Better to fix them all in one go vs. letting them become discovered down the road as bugs and go through triage

Cool thanks for the explanation, but just to confirm, are you suggesting we should do an audit of all of our components and fix something about them?

@marcaaron yep, or at least do a quick search to see if there are any other components that are written in the same way. I haven't really had the chance to see if there are any that are like this, I was more just thinking off the top of my head. The more I think about it now it's an easy fix, so we don't really need to do anything here.

do a quick search to see if there are any other components that are written in the same way

Sorry, what way is that? What is it that you think we need to fix about the components?

Honestly, the more I think about it now it's an easy fix, so we don't really need to do anything here.

No need, I was just saying we could maybe go to see if other components are written by accessing props in the constructor. But let's just do nothing for now.

@jasperhuangg @sakluger Quick bump on the payout here.

Hi all, just got back from a long weekend for Thanksgiving holiday and am paying out today.

Thanks @sakluger. Hope you enjoyed the holidays!

Thanks @mananjadhav!
Everyone has now been paid, the contract has been completed, and the Upwork post has been closed.


Extension: error message

@ocots according to the weak dep. in Project.toml, using OrdinaryDiffEq.jl (lighter than DifferentialEquations.jl) is enough. Am I missing sth? If not, can you please update the message below?

I have made the modification.

See
https://github.com/control-toolbox/CTFlows.jl/blob/072356af88a52ff9f4210793cdb703563b4448a2/src/CTFlows.jl#L26


10/23/2018 17:51 : Create Pull Request for branch master -> prTesting1_2018102317

:white_check_mark: Validation status: passed

File
Status
Preview URL
Details
Dependent Files

split/updateTestRef1.md
:white_check_mark:Succeeded

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


Use LLAMA3 On Replicate

Support using LLAMA3 on Replicate as the AI.

How do we want to handle Configuration for specifying the model to use?
There are two different concepts

LLM Provider

e.g. OpenAI, Anthropic, Replicate

Model

GPT4 , EmbeddingSmall

We don't want to duplicate LLMProvider settings
We want to specify LLMProvider settings like BaseURL and APIKey once
So one option would be to have an llm provider section
type ModelProvider {
     OpenAI OpenAIConfig
     Anthropic AnthropicConfig
     Replicate ReplicateConifg
}

We could then configure models by specifying the provider and parameters
type Model {
   OpenAIModel OpenAIModelConfig
   AnthropicModel AnthorpricModelConfig
}

Should it be a single model or should we have different structures for different classes of models; e.g.
type LLMConfig {
   OpenAILLM
   AnthropicLLM
}

type EmbeddingConfig {
    OpenAIEmbedding
    AnthropicEmbbedding
}

For the LLM
I don't think we need to introduce additional LLM parameters quite yet. The model name is sufficient for now.
For RAG we could use a provider. Although really only OpenAI is support right now because embeddings on Replicate are too slow.


[Bug]: Report captcha need update

Version of the software
0.1.26
Operating system
Windows 10
Browser / Native
Chrome  92
What happened?
On report captcha block in recaptchas returns
Could not report the solution of task 654305535 to the service: Captcha not found or expired
something in apiside must change here https://anti-captcha.com/apidoc/methods/reportIncorrectRecaptcha they have report options
also be aware your account might be banned
https://ruri.please-fuck.me/5dOoNS9Rv
Relevant LoliCode if needed
No response

and exclude report captcha in settings for capmonster.

and exclude report captcha in settings for capmonster.

Just use SAFE mode so even if it fails it doesn't matter at all and the config continues as normal.

and exclude report captcha in settings for capmonster.

Just use SAFE mode so even if it fails it doesn't matter at all and the config continues as normal.

ok don't change anything...

Just tried it with recap (v2)
Report goes to https://api.anti-captcha.com/reportIncorrectImageCaptcha
According to Api docu it should be
https://api.anti-captcha.com/reportIncorrectRecaptcha

Thanks @meinname can you open this in the CaptchaSharp repo please? Thanks


[ResultBuilders] Make sure that case body variables get types

Solution application needs to set interface types for variables
declared in a case statement, otherwise this would lead to crashes
in SILGen.

@swift-ci please test

@swift-ci please test Windows platform

@swift-ci please test Windows platform

@swift-ci please test Windows platform


docs(zh): sync update to e008551

Range: c3d3bc0...e008551

BTW @posva may I have the permission of this repo in order to create and maintain the docs-sync-zh branch as the translation checkpoint? Thanks.

Added


Support for @> and <@ operators when working with full-text-search

Problem
Prisma docs/full-text-search state that Prisma Client supports operators that Postgres supports.

When I tried executing a query using the @> or <@, Prisma Client returned the following error:
{ query: 'tom <@ sawyer' } // not related to the Prisma client error
{
  error: PrismaClientUnknownRequestError:
  Invalid `prisma.book.findMany()` invocation:

    Error occurred during query execution:
  ConnectorError(ConnectorError { user_facing_error: None, kind: QueryError(Error { kind: Db, cause: Some(DbError { severity: "ERROR", parsed_severity: Some(Error), code: SqlState("42601"), message: "syntax error in tsquery: \"tom sawyer\"", detail: None, hint: None, position: None, where_: None, schema: None, table: None, column: None, datatype: None, constraint: None, file: Some("tsquery.c"), line: Some(689), routine: Some("makepol") }) }) })
      at cb (/Users/ruheni/Documents/repos/work/prisma/projects/prisma-fulltextsearch/node_modules/@prisma/client/runtime/index.js:38692:17)
      at async handler (webpack-internal:///./pages/api/search.ts:40:29)
      at async Object.apiResolver (/Users/ruheni/Documents/repos/work/prisma/projects/prisma-fulltextsearch/node_modules/next/dist/server/api-utils.js:102:9)
      at async DevServer.handleApiRequest (/Users/ruheni/Documents/repos/work/prisma/projects/prisma-fulltextsearch/node_modules/next/dist/server/next-server.js:1064:9)
      at async Object.fn (/Users/ruheni/Documents/repos/work/prisma/projects/prisma-fulltextsearch/node_modules/next/dist/server/next-server.js:951:37)
      at async Router.execute (/Users/ruheni/Documents/repos/work/prisma/projects/prisma-fulltextsearch/node_modules/next/dist/server/router.js:222:32)
      at async DevServer.run (/Users/ruheni/Documents/repos/work/prisma/projects/prisma-fulltextsearch/node_modules/next/dist/server/next-server.js:1135:29)
      at async DevServer.run (/Users/ruheni/Documents/repos/work/prisma/projects/prisma-fulltextsearch/node_modules/next/dist/server/dev/next-dev-server.js:445:20)
      at async DevServer.handleRequest (/Users/ruheni/Documents/repos/work/prisma/projects/prisma-fulltextsearch/node_modules/next/dist/server/next-server.js:325:20) {
    clientVersion: '3.7.0'
  }
}

Suggested solution
It would be worth noting explicitly the operators Prisma client supports in the docs or provide more concrete examples of how it works/ use it.

The operators you're mentioning are Postgres operators, not query operators. The link provided in the documentation is misleading.
Below are the query operators Postgres supports, with the addition of <-> that I couldn't find documented anywhere:

This is more of a documentation issue. I, unfortunately, couldn't find any proper documentation on all the supported query operators.
I'll leave it open and hand it over to the docs team.

I think the link on https://www.prisma.io/docs/concepts/components/prisma-client/full-text-search#querying-the-database has been fixed. Can you confirm @ruheni?

Yes


Template provider clarification

A fix pr to https://github.com/stratum-mining/stratum/issues/1261

Hey @Arshia-r-m, since both PRs you opened (this one and #236) are touching the same instructions related to TP, why don't you just unify them into a single one? Up to you which one to leave.

We can close this one, the other one is updater ✌


Kill phantom process

Phatom itself doesn't seem to leak memory for me, however, when I close the screenshot stream, it seems like about ~40mb of data get left behind resulting in a serious memory leak.
I'm assuming that phantom is leaving something hanging around on its end, or not exiting?
It happens every time the node server throws Error: ECONNRESET.

I only write this as an issue here since I've attached an on('error') to every stream in my server, yet memory continues to leak. Perhaps a stream is getting left behind in index.js`?
This one, maybe: https://github.com/kevva/screenshot-stream/blob/master/index.js#L56

Not much we can do based on this information, but you could probably use node --inspect in latest Node.js version to inspect memory usage using DevTools and see where it's coming from.


check the value of ge_set_xquad everywhere in -zkp modules

cc @real-or-random @jonasnick

utACK.
This is rather for a second PR:
Currently, the parse functions promise to succeed if the bytestring contains a "valid" generator / commitment. That's not quite right. It's kind of safe, because the user is forced to use the generators and commitments through our API functions, which check that the point is actually valid. I say "kind of" because our API promises that parsed objects can be memcmp'd, so the user could memcmp invalid points.
I think it will be less surprising, less error-prone, and more efficient to check full validity at parse time. This will also be consistent with the pubkey_parse function, which checks everything and then the pubkey_load merely does a memcpy. Probably we should just steal from there; the only difference is that it accepts uncompressed encoding and uses a different prefix.
If you agree, I can create a PR for that (or you do it here).
If not, we should clarify in the documentation what "valid" means.

I don't understand. What further validity checks are needed?
I see that we should check the `x' coordinate for overflow, which we currently don't, because that's a malleability vector, but it's fairly benign.
Also we should not be telling users they can memcmp generators that have been parsed.

Sorry, maybe my comment was confusing. I'm not saying that more checks are needed. (Except that you're right, we should check for x-overflow.)
I'm proposing to move the checks from the generator_load functions to the generator_parse functions (and the same for commitments) Advantages are

We fail earlier, so there is less room for internal functions and users to work with invalid points, e.g., memcmp them as we explain here: https://github.com/ElementsProject/secp256k1-zkp/blob/secp256k1-zkp/include/secp256k1_generator.h#L20
We perform the checks only once instead of every time we load a point.
We are consistent with the corresponding functions for pubkeys. Here, the _parse function performs all the validation and does not postpone it to the _load function: https://github.com/ElementsProject/secp256k1-zkp/blob/secp256k1-zkp/src/eckey_impl.h#L17

Ah! Yes, you're right.

@real-or-random  I completely rewrote the PR.

utACK


Compilation failed due to ENABLE_PY2 not defined

I can't compile pyflame successfully. My environment gets Py2.7 and the develop files are installed. See the configure log:

checking for PY26... yes
checking for PY34... no
checking for PY34... no
configure: WARNING: Building without Python 3.4/3.5 support
checking for PY36... no
configure: WARNING: Building without Python 3.6 support

But the compilation still fails:

pyflame.cc:40:1: 错误：static assertion failed: Need Python2 or Python3 support to build
static_assert(false, "Need Python2 or Python3 support to build");

Looks to me only ENABLE_PY26 is defined but not ENABLE_PY2. I temporarily change it to ENABLE_PY26 and the build succeeds.

Thanks for the report. Yes you're right -- the code should have said ENABLE_PY26. I have made this change in master, and released it as Pyflame 1.4.4.

Thanks.


Support ingesting data from existing S3 buckets

We often tout the capabilities of this project as being a tool for cataloging data across cloud storage solutions, but we currently do not have a way to import/ingest data from existing S3 buckets... this is at odds with our messaging.
We need a way to ingest/point to data in any existing s3 bucket. This issue will be a place to outline how to do that
(likely needed for #160)

After talking with @brianhelba, we have converged on a path forward for this.
First, we will implement a basic solution for working with public data on S3 (or any source actually) through https:// URLs to the resource. To do this, we will abstract the file-holding models to all have a foreign-key to the ChecksumFile model (and deprecate the ArbitraryFile model). Then we will add a new TextField next to the current usage of S3FileField and add a CheckConstraint to make sure one and only one of the two fields are set (we will need to make both fields nullable). This gives us the advantage of managing all file resources through a single model (cc @mcovalt, this should simplify the permissions work).
Once we have that, we will add internal helper methods on ChecksumFile to fetch the file to a temporary place on disk: perhaps via a method on the model called get_local_path() or another for getting a file-like object. This helper method will handle the details of downloading files from the specified URL (eventually handling S3 credentials down the road) or calling field_file_to_local_path like we currently do for S3FileField. Then all of the ETL routines that access the file model will call the method for retrieving the file for use rather than the fields. Down the road, we can improve that file access by implementing #237 under the hood for these access methods.

After talking with @brianhelba, we have converged on a path forward for this.
First, we will implement a basic solution for working with public data on S3 (or any source actually) through https:// URLs to the resource. To do this, we will abstract the file-holding models to all have a foreign-key to the ChecksumFile model (and deprecate the ArbitraryFile model). Then we will add a new TextField next to the current usage of S3FileField and add a CheckConstraint to make sure one and only one of the two fields are set (we will need to make both fields nullable). This gives us the advantage of managing all file resources through a single model (cc @mcovalt, this should simplify the permissions work).
Once we have that, we will add internal helper methods on ChecksumFile to fetch the file to a temporary place on disk: perhaps via a method on the model called get_local_path() or another for getting a file-like object. This helper method will handle the details of downloading files from the specified URL (eventually handling S3 credentials down the road) or calling field_file_to_local_path like we currently do for S3FileField. Then all of the ETL routines that access the file model will call the method for retrieving the file for use rather than the fields. Down the road, we can improve that file access by implementing #237 under the hood for these access methods.

I will start with some example data from https://docs.opendata.aws/landsat-pds/readme.html (though I believe this will not be available after July 2021)

I will start with some example data from https://docs.opendata.aws/landsat-pds/readme.html (though I believe this will not be available after July 2021)

FYI I found this sentinel open data bucket that is free to access (no requester pays and not going offline like the landsat bucket): https://registry.opendata.aws/sentinel-2-l2a-cogs/

FYI I found this sentinel open data bucket that is free to access (no requester pays and not going offline like the landsat bucket): https://registry.opendata.aws/sentinel-2-l2a-cogs/


⚠ Bofrost.es has degraded performance

In 0577e80, Bofrost.es (https://www.bofrost.es) experienced degraded performance:

HTTP code: 200
Response time: 1162 ms

Resolved: Bofrost.es performance has improved in 3dcdbe3 after 313 days, 8 hours, 54 minutes.


Speeding up environment initialization

As I'm running a test program on miniF2F, a runtime bottleneck was observed for LeanDoJo's environment initialization from this operation with Dojo(theorem) as (dojo, init_state): , which essentially calls the "__enter__" method from DoJo class. The time spent on this initialization was about 10x more than the time spent on neural network inference.
So I tried to parallelize this operation. First by mutli-threading, but I got the following error saying that signal only works in main thread.
/bask/projects/j/jlxi8926-auto-sum/dongwei/miniconda/envs/dojo/lib/python3.10/threading.py", line 1016, in _bootstrap_inner
    self.old_sigint = signal.signal(signal.SIGINT, self._exit_gracefully)
  File "/bask/projects/j/jlxi8926-auto-sum/dongwei/miniconda/envs/dojo/lib/python3.10/signal.py", line 56, in signal
    self.run()
ValueError: signal only works in main thread of the main interpreter
    self.old_sigint = signal.signal(signal.SIGINT, self._exit_gracefully)
  File "/bask/projects/j/jlxi8926-auto-sum/dongwei/miniconda/envs/dojo/lib/python3.10/signal.py", line 56, in signal
    self.run()
    self.run()

Then I tried multi-processing, which gave me this error message saying there's an object being shared between processes that contains a lock or similar resource.
Traceback (most recent call last):
  File "/bask/projects/j/jlxi8926-auto-sum/dongwei/miniconda/envs/dojo/lib/python3.10/multiprocessing/process.py", line 314, in _bootstrap
    self.run()
  File "/bask/projects/j/jlxi8926-auto-sum/dongwei/miniconda/envs/dojo/lib/python3.10/multiprocessing/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "/bask/projects/j/jlxi8926-auto-sum/dongwei/LeanDojo/test_interact_multi.py", line 55, in worker
    return_dict[theorem_name] = result
  File "<string>", line 2, in __setitem__
  File "/bask/projects/j/jlxi8926-auto-sum/dongwei/miniconda/envs/dojo/lib/python3.10/multiprocessing/managers.py", line 817, in _callmethod
    conn.send((self._id, methodname, args, kwds))
  File "/bask/projects/j/jlxi8926-auto-sum/dongwei/miniconda/envs/dojo/lib/python3.10/multiprocessing/connection.py", line 206, in send
    self._send_bytes(_ForkingPickler.dumps(obj))
  File "/bask/projects/j/jlxi8926-auto-sum/dongwei/miniconda/envs/dojo/lib/python3.10/multiprocessing/reduction.py", line 51, in dumps
    cls(buf, protocol).dump(obj)
TypeError: cannot pickle '_thread.lock' object

So I'm wondering is there a solution that can speed up the environment initialization?

Do you have an estimate of how long __enter__ takes?
I'm not sure about how you were trying to use multithreading/multiprocessing. However, it should be possible to use it with multiple processes. Please see DistributedProver.

On my setup, I've found the __enter__ method to be a bit time-consuming, averaging around 3 minutes per run. Given that miniF2F comprises over 200 theorems, the overall run time extends quite a bit. I was wondering if your team experienced similar timelines when running experiments on miniF2F?
The multiprocessing code I wrote is pretty standard
from lean_dojo import *
import time
import json
from model_inference import inference, init_model
import threading
from multiprocessing import Process, Manager

def init_env(repo_name, commit_id, file_path, repo_type="miniF2F"):
    repo = LeanGitRepo(repo_name, commit_id)
    theorem_list = []
    if repo_type == "miniF2F":
        with open(file_path, "r") as f:
            for line in f.readlines():
                if line.startswith("theorem"):
                    theorem_list.append(line.split()[1])
    return repo, theorem_list

def worker(repo, file_path, theorem_name, return_dict):
    theorem = Theorem(repo, file_path, theorem_name)
    dojo, init_state = Dojo(theorem).__enter__()
    result = (theorem_name, dojo, init_state)
    return_dict[theorem_name] = result

if __name__ == "__main__":
    repo, theorem_list = init_env("https://github.com/openai/miniF2F", "4e433ff5cadff23f9911a2bb5bbab2d351ce5554", "/bask/projects/j/jlxi8926-auto-sum/dongwei/LeanDojo/traced_miniF2F/miniF2F/lean/src/valid.lean", "miniF2F")
    model, tokenizer, generation_config, inference_args = init_model()

    with Manager() as manager:
        # create a shared dictionary to store the results
        return_dict = manager.dict()

        processes = []
        for theorem in theorem_list:
            p = Process(target=worker, args=(repo, "lean/src/valid.lean", theorem, return_dict))
            p.start()
            processes.append(p)

        # Wait for all processes to finish
        for p in processes:
            p.join()

        # convert the shared dict to normal dict for further usage
        results = dict(return_dict)

I did attempt to use Ray for multiprocessing following your advice, but unfortunately, I kept stumbling into the same error message. Although I've not delved too deeply into ReProvers code, my understanding is that it may not involve an instance of multiprocessing that calls the enter method. This leads me to believe the situation might not be directly applicable to my case.

3 minutes is definitely possible. There might be some room for improving the initialization time. It wasn't our priority, since the wall time limit for evaluating the prover does not include the time for initialization.
I'm not sure if the Dojo object can be passed between different processes. What we did was distributing the testing theorems to different workers. Each worker launches Dojo, perform proof search, destroy Dojo, and returns the result of proof search.

Thanks for the information! I'm closing this issue for now, will reopen it when/if I have more updates.

Related discussion: https://github.com/lean-dojo/LeanDojo/discussions/50


bugfix: 修复外部企业版微信端查看详情链接错误的问题

Codecov Report

Merging #910 (0287bcf) into v2.6.x_develop (4c95e64) will not change coverage.
The diff coverage is 100.00%.

@@               Coverage Diff               @@
##           v2.6.x_develop     #910   +/-   ##
===============================================
  Coverage           60.82%   60.82%
===============================================
  Files                 466      466
  Lines               29713    29713
===============================================
  Hits                18073    18073
  Misses              11640    11640

Impacted Files
Coverage Δ

itsm/component/notify.py
46.51% <100.00%> (ø)

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.


Auto login after registering

Solves issue #15
Also solves issue #25
After register, redirects to "profile/username"

looks good to me! one thing though is to maybe redirect a user to the site's homepage instead of their profile page?

Thanks! Just fixed it :)


Influx 0.9.2 is not capable of handling fields like 0_foo

During tests, I created a measurement with fields named like 0_foo, 1_foo...
While the data are correctly saved, doing a
SELECT * FROM bar

fails with found _foo, expected FROM at line 1, char 10.
Doing foo_0 does not crash.
The interpreter should either accept the form 0_foo, or reject the user input at write time, claiming that fields must start with a non-digit character, like some programming languages do.

Afterwards, the application crashed when trying to make a query, but I don't know if this is related.
Here are the logs:
http://pastebin.com/KjB9MhyJ
This is the full log since influxdb was set up this morning with default config. All operations are related to this measurement.
before [14/Aug/2015:14:10:07 +0000] : trying to send data with 0_foo,0_bar,1_foo,1_bar... (number ranges from 0 to 18). After this point, field names were flipped.

The problem with queries failing on select * should be fixed on the nightly build. Could you try out that version and see if it works?

@jeremyVignelles Closing issue as it seems to be resolved in 0.9.3
``> insert bar 0_foo=1,1_foo=1

select * from bar
name: bar

time				0_foo	1_foo
2015-08-19T23:49:39.521320959Z	1	1

Thanks for your replies. Tested in 0.9.3-rc1 and it worked.


D415 got stuck/frooze in wait_for_frame() after unplug-replug

Required Info

Camera Model
D415

Firmware Version
5.13   just updated today  successfully

Operating System & Version
Win 10

Platform
PC

SDK Version
updated to latest 2.50.x

Language
c++

Segment
Robot

Issue Description
D415 got stuck  in wait_for_frame() after unplug-replug about 45 seconds occasionally.  I just updated everything today but it still happend in my code.  So I copied demo code, still got stuck. I need know it's normal situation or exception. In the image, I unplugged and replugged immediately.

Hi @LLY13  It is possible for a program to become unresponsive after the camera is disconnected by some means (such as physically unplugging it from the USB port).  RealSense users have typically created workaround mechanisms when frames stop arriving, such as automatically resetting the camera with the hardware_reset() instruction.  A C++ case that discusses the issue is at https://github.com/IntelRealSense/librealsense/issues/10084

I have tried use hardware_reset() before this I posted this issue, seemed like useless.  I'd just try to not unplug it.

When you unplug, how long on average do you wait before re-inserting?  Upon disconnection, the pipeline should be able to resume streaming if the camera is reconnected within 5 seconds, otherwise the connection time-outs.

less than 1 seconds. yep most time reconnected in 5 seconds. but somtimes 15s even 45s+

I would recommend trying a wait period of 2 seconds before re-inserting to give the computer time to properly register the removal of the device from the USB system and see whether that reduces the occurrences of the long time-out events.

Hi @LLY13  Do you require further assistance with this case, please?  Thanks!

no thx

Thanks very much @LLY13 for the update.  As you do not require further assistance, I will close this case.  Thanks again!


bluetooth: tester: Add TBS server tests

Adding support for TBS server tests.

@Thalley updated  overlay-le-audio.conf with CONFIG_BT_TBS_MAX_CALLS=10. This is needed for group of test that require updating characteristic with oversized values.

@jhedberg Please review.


Windows 10 Show Its Boot Screen But Dis Not Boot

Maybe It Must Be My Copy Of Windows 10 Because I Got It Off The A Youtuber Website And That Youtuber Name Is Enderman And He Dis Windows Stuff

how do you know it doesn't boot win10, maybe it works but takes hours to start (iirc android did that)
Under linux emulation, the latest kernel is arch linux, kernel 4.40. My laptop run 5.90.
Windows 10 isn't abandonware, you can't put it up.
Why do you expect so much from a browser-based virtual machine? Just use proper solutions like QEMU.

how do you know it doesn't boot win10, maybe it works but takes hours to start (iirc android did that)
Under linux emulation, the latest kernel is arch linux, kernel 4.40. My laptop run 5.90.This does not indicate support for the latest software.
Windows 10 isn't abandonware, you can't put it up.
Why do you expect so much from a browser-based virtual machine? Just use proper solutions like QEMU.

I totally agree with you

Closing as v86 is very unlikely to support W10 at any point.

k

Here i Got Screenshots

#378

Boom

That was fixes for win98.
On Wed 2 Dec 2020, 22:54 #Wifi Got Minecraft<EMAIL_ADDRESS>wrote:

[image: Screenshot 2020-11-23 at 7 33 36 PM]
https://user-images.githubusercontent.com/64691261/100941230-ee37d880-34be-11eb-8e13-1cdb8db726d0.png
Boom
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/copy/v86/issues/376#issuecomment-737544868, or
unsubscribe
https://github.com/notifications/unsubscribe-auth/AJ3IJSJX6Y64OZFY6CDJ423SS3AQ3ANCNFSM4UAMKHAQ
.

Boom

did it works?

Boom

did it works?

windows 10 is never going to work on this as it requres a proper setup that cant be built in a browser


feat: default function with bin flag

I have a package with two binaries, one for a local server and another for lambda deployment. Setting the --bin flag in watch mode still deploys to .../lambda-url/, citing that there are "multiple available functions" even though I specified the binary; which to me doesn't make much sense.
(I'm aware that, as per the docs, I can just split the package into two and specify the package to achieve the same result, but I really prefer having a single package with two binaries)

You can use the --package flag to indicate which package to watch, which should give you the routes without the prefix. It might make sense to use the same behavior for the --bin flag as you point out.

I'll add this to the release I'm doing this afternoon.

👋 I've just released version 1.6.2 with these changes. Check out the release notes: https://github.com/cargo-lambda/cargo-lambda/releases/tag/v1.6.2


issue/9: fix for initial form of letters in safari

directly including unicode character seemed to work.

change looks good, thank you!


bug

What version of Wallet are you using?
fuel
What is happening?
I couldn't use send button.my wallet adress is fuel1cwlaqupmwsmu42km2l8l6s7w3ef76v4kxzuraszc3t28w4v0035sut2qdh
steps to reproduce

How it should behave?

What os are you seeing the problem on?
Windows Desktop
What browser?
Other
What is your browser version?
microsoft edge the last version

As the prompt window says, the send feature is not yet available. With the upgrade, there will be more and more features, you can check the features currently available for the wallet here. https://github.com/FuelLabs/fuels-wallet#features


update expected test results

@jonmv  maybe the proper fix is changing the output, keeping the test, I leave it to you to decide


Drone CI Gitea-Release 404 not found

Gitea version (or commit ref): 1.13.0 (system package)
Git version: 2.26.2
Operating system: Alpine Linux PPC64le
Database (use [x]):

[x] PostgreSQL
[ ] MySQL
[ ] MSSQL
[ ] SQLite

Can you reproduce the bug at https://try.gitea.io:

[ ] Yes (provide example URL)
[x] No

Log gist:

[Macaron] 2020-12-08 13:51:16: Started GET /api/v1/version for <ip>
[Macaron] 2020-12-08 13:51:16: Completed GET /api/v1/version 200 OK in 2.357098ms
[Macaron] 2020-12-08 13:51:16: Started GET /api/v1/repos/trufflepig/minion/releases?limit=0&page=0 for <ip>
[Macaron] 2020-12-08 13:51:16: Completed GET /api/v1/repos/trufflepig/minion/releases?limit=0&page=0 404 Not Found in 3.216813ms
[Macaron] 2020-12-08 13:51:16: Started POST /api/v1/repos/trufflepig/minion/releases for <ip>
[Macaron] 2020-12-08 13:51:16: Completed POST /api/v1/repos/trufflepig/minion/releases 404 Not Found in 3.33654ms

I did not find any other logs related to this problem.
Description
Hi folks!
We're using Drone CI and since we've updated Gitea to 1.13.0 the Gitea release plugin gives us a 404 when trying to upload artifacts from Drone.
The only change I found that seems somewhat relevant is #12933 but I don't think it causes the 404.
I'd appreciate any help, sorry for not being able to provide more (helpful) information.
Cheers

Ok, there were actually 2 issues:
after updating Gitea, we had to:

regenerate the API key
refresh the oauth2 client secret

both were necessary to get drone properly working again.

Unfortunately we are unable to offer debugging for third party software (specifically the drone plugin). I recommend opening up an issue at: https://github.com/drone-plugins/drone-gitea-release for the plugin itself.
I suspect that since you've regenerated the API Key and the oauth2 client secret and don't run into this issue anymore we won't be able to debug it.
As for providing logs in these issues please read: https://docs.gitea.io/en-us/logging-configuration/#debugging-problems as right now we can only see that some routes gave a 404, but by following that then gitea will provide debugging information. Also in the future providing additional details also is helpful, for example what version of drone are you using, what version of Gitea did you upgrade from, etc... and to keep separate issues in separate threads.
Since your drone install is working again I will close this.


Add a simple remote debug logger via gun

Visit /log.html to see all the logs, it replaces the current log directly once you put
<script src="assets/js/gunlogger.js"></script>
in the one that should report

Please check here
https://meething-qvdev.herokuapp.com/
double test if you hear yourself so try wit other particpants

Maybe wrap this into the event emitter- pattern - I think it's still valid concearn

Yes, I’ve been thinking about passing debug around so you only have to put debug true once...?

Not needed at the moment


Changing Service type or ports does not trigger ServiceUpdate event

To reproduce:

Create ClusterIP service foo.
Patch foo with kubectl edit svc foo to change its type to NodePort.
No Kubernetes service definition changed log entries (level=debug) = no updates in the LB BPF maps to reflect the change.

A user reported that changing the ports does not trigger the service update too.


Is there a example on how to use quantization-aware training ?

Is there a example on how to use quantization-aware training ?

Yes, there are a few under [examples/quantization/quant_aware_train].(https://github.com/NervanaSystems/distiller/tree/master/examples/quantization/quant_aware_train)

Closing this, feel free to re-open if there are any more questions

@guyjacob would like to know, if we can ues "distiller.file_config" and "distiller.file_config" to load the .yaml config file and run quantization aware training?

I'm not sure what you refer to by "distiller.file_config". Can you clarify?

@guyjacob
i am sorry to have made a typo, it should be "distiller.CompressionScheduler" and "distiller.file_config"
for example, i saved my training settings in "train_config.yaml", then i run my training code like this:
compression_scheduler = distiller.CompressionScheduler(model)      compression_scheduler = distiller.file_config(model, optimizer,                                      '/home/username/distiller/workingdir/train_config.yaml',                                      compression_scheduler)     for epoch in range(total_epoch):         compression_scheduler.on_epoch_begin(epoch)         for train_step, (inputs, target) in enumerate(train_loader):             total_iter += 1             inputs, target = inputs.cuda().float(), target.cuda().float()             compression_scheduler.on_minibatch_begin(epoch, train_step,                                                      num_iter, optimizer)             output = model(inputs)             loss = criterion(output, target)             agg_loss = compression_scheduler.before_backward_pass(epoch, train_step,                                                          num_iter, loss, optimizer, True)             loss = agg_loss.overall_loss             optimizer.zero_grad()             loss.backward()             optimizer.step()             compression_scheduler.on_minibatch_end(epoch, train_step,                                                  num_iter, optimizer)

Oh OK, I understand. So yes - that is the way to create a scheduler for quantization aware training.

@guyjacob  thank you so much for your kind help!


Myth Cape Rack (construction)

Adds the mythical cape (mounted) to the list of constructables. Ensures the user needs the relevant skills for ds2 along with the quest points. It then finally checks they have a myth cape in their bank or on them as they would need one. Closes #4181

[x] I have tested all my changes thoroughly.

xp/hr?

Wiki says Players can gain up to around 430,000 experience per hour with maximum efficiency., this is 100k less per hour? I wouldnt expect it to be 100% tick-perfect efficiency, but If its 100k less xp/hr, it seems really off the xprate?

Wiki says Players can gain up to around 430,000 experience per hour with maximum efficiency., this is 100k less per hour? I wouldnt expect it to be 100% tick-perfect efficiency, but If its 100k less xp/hr, it seems really off the xprate?

I noticed that but teak garden benches are 700k xp/hr according to the wiki, and in game rates are 498k xp/hr that's 202k xp/hr less... so think construction as an overall would need looking into and reviewing on this matter?


proposal: math/big: Rat.SetUint64

Please consider adding Rat.SetUint64 in addition to Rat.SetInt64 as there is currently no way of setting by uint64 integers. This is similar to Int.SetInt64 and Int.SetUint64.

Thank you!


vector_graphics package should be more careful about forced compositing

currently dnfield/vector_graphics will unconditionally create a repaint boundary and use multiple explicit layers for painting. We should instead try to compress this into a single picture to avoid the current flutter issues of repeated raster caching.
Second, we should try to estimate the rough complexity of the picture and entirely elide the repaint boundary for these.
This was determined by investigating the performance of the customer: money application.

This is done


Rename stopId

🚀 Feature request
Components' property stopId should be renamed into something more meaningful and semantically correct.
Motivation
For me stopId is something terminal, inactive or closed. And reading the docs I has been dropping it out of my attention as something secondary or unnecessary.
Possible implementations
In my opinion there are more suitable names for this property:

aimId,
innerId,
myId,
ownId,
scopeId
selfId,
targetId.

"Stop" in this context refers to "tab stop", but I agree that it may not be too obvious. And in some components it may not make much sense, such as TabPanel.
We're in the process of creating an alternative to Rover (which implements the stopId prop and is used by the other modules that have the same prop), so we have some opportunity to think about a better prop name. stopId won't go away though, but we can deprecate it if we find something better.
My current idea is to use just id where it's really used as the id attribute (Tab, MenuItem, ToolbarItem, Radio) and create an idref prop (which is another XML standard) on components that refers to another element's id (TabPanel).
What do you think? @rumkin

By the way, using just id is already supported in all components except TabPanel.

Seems like I need to dig into this a little bit deeper, because stopId seems overloaded and I'm not sure if I understand all the use-cases. For example tabs have stopId which refers to corresponding panel's stopId, and the Reakit code makes them work together using tab state. In the same time stopId affects regular html id and if I overwrite id with a custom value the Tab component doesn't work anymore.
I think it's better to use panelId for tabs to specify target panel and allow several tabs to refer to a single panel, for example if I want to duplicate tabs in the bottom of the tab panel.
This is how I think it should work with innerId instead of stopId :
() => {
  const tabs = useTabState()

  return (
    <TabList>
      <Tab {...tabs} innerId="tab1" panelId="panel1" />
    </TabList>
    <TabPanel {...tabs} innerId="panel1" />
  )
}

Property name idref have intersection with the ref prop of react and I'd suggest to use it carefully due to this intersection. I think it will be named refId according to the project name convention, but anyway developers could understand this wrong. While I like the idea of reusing existing standards, there are some tradeoffs. I will dig into the Rover to be helpful there.

I will read Rover component code to understand how it works. Also I have some thoughts on the name and id usage for creating nested components and to make them accessible programmatically from the top level and it seems that Reakit is very close to the concept I have in min. I'm about to create an example of how it could work together to solve issues like this and then I will send you the code to review when it will be ready. I think it will make the discussion more useful and productive.

As of v1.0.0-rc.0, stopId is deprecated in favor of just id (or tabId on TabPanel). Going to close this for now, but we can continue talking about that if needed.


Optimize Trigger Trigger Player collision checks

The player collide hook in trigger triggers is extremely inefficient as it is called once for each collidable entity in a room every frame. This PR keeps a separate list of trigger triggers currently in the level to reduce the number of calls to GetEntities.
The PR also changes the entitiesTouched and entitiesInside Lists into HashSets as the order isn't needed for either, greatly improving performance of calls such as Add. Furthermore, the number of calls to entitiesTouched per iteration has been cut in half. In one particularly large room, this alone reduced the time Player.Update took from 3.65ms down to 2.95ms.
I do not know how safe it is to keep a separate list of trigger triggers in a static field like this. If there is a better way to do it, feel free to change it.

I just realized there had already been performance improvements made to this exact part of trigger triggers, but those got reverted a week ago. What was wrong with that version?

Looks like the old patch is back, even better.


Is proxy setting allowed for langchain.llm LLM like openai.proxy=os.getenv(HTTP_PROXY) ? please add if possible.

Is proxy setting allowed for LLM like openai.proxy = os.getenv(HTTP_PROXY) ? please add if possible.
openai-python api  has a attribute openai.proxy, which is very convenient for HTTP/WS proxy setting as :
import openai
import os

openai.proxy = os.getenv(HTTP_PROXY)  # HTTP_PROXY="your proxy server:port" is put in local .env file

How to set the attribute in langchain LLM instance? Give me a hint, thanks.

I am handling one the issue myself and will submit a PR request today to solve it. I made testing locally and solved the proxy setting.

https://github.com/hwchase17/langchain/pull/1453  PR is submitted to solve the issue #1423. Please review it, thanks.

is there documentation on openAIs side about when/why to do this?

is there documentation on openAIs side about when/why to do this?

openai documentation error code doesnt explicitly indicate the reason to set openai.proxy for APIConnectionError, while I noticed that chat-langchain client-side failed to make WebSocket connection if the client browser was behind a firewall (company or others) in async mode + streaming mode (without **"in-code"**proxy setup). However, it works smoothly in sync mode(with "out-code" normal proxy).
To use lang-server tracing and prototype verification in Jupyter notebook, it was figured out that aiohttp package is the reason. Check the aiohttp documentation about proxy support, which explains HTTP_PROXY or WS_PROXY setup in environment "in-code".
async with aiohttp.ClientSession() as session:
        async with session.get("http://python.org",
                           proxy="http://proxy.com") as resp:
        print(resp.status)

After "think step by step" trick😄, the simple solution is to "in-code" assign openai.proxy attribute as HTTP_PROXY variable from .env file.
I could move the block to function-build_extra from func-validate_environment if you think the implementation in PR is not elegant since it might not be a popular situation for the common users.

It seems that I finally figured out the How-to solve the issue. AzureOpenAI sample seems not the answer since not all of attributes are extracted from env setting in "openai/openai-python/init.py"
However, langchain/ecosystem/Helicone docs show a valid example, which is straight and cool.
Tried in Juypter, it worked. I will withdraw my PR after a while.

Hi @peter65374
I have this same problem, have you found a resolution yet?
Retrying langchain.embeddings.openai.embed_with_retry.<locals>._embed_with_retry in 4.0 seconds as it raised APIConnectionError: Error communicating with OpenAI: HTTPSConnectionPool(host='api.openai.com', port=443): Max retries exceeded with url: /v1/engines/text-embedding-ada-002/embeddings (Caused by ProxyError('Cannot connect to proxy.', RemoteDisconnected('Remote end closed connection without response'))).

@youngfreeFJS hello ,请问你的问题解决了吗？我也遇到这个情况了。谢谢啦


An Issue on Reproducing Streamingllm

Congratulations on your excellent work! I attempted to run bash scripts/run_streamingllm_lm.sh to reproduce the results of streaming_llm, but I encountered the following error:
TypeError: llama_pos_shift_attention_forward() got an unexpected keyword argument 'padding_mask'

It seems that the transformers library version needs to be below 4.34.0, but this project requires version 4.34.1. Have you encountered the same issue? If so, do you have any solutions? Thank you very much!

Thank you for your interest in our work :)
I did run into a similar issue, apologies for not including the fixes in the original repo. To fix this issue, I applied a patch on top of the original streaming_llm repo. To apply the fix:

clone the original repo
replace the file streaming_llm/pos_shift/modify_llama.py with this file; the only changes I made to this file is adding the padding_mask argument to the pos_shift forward function, and also added supported for FlashAttention2.
Install this version of the streaming_llm from source via python setup.py develop in the base directory. Alternatively, you can also just add this new version to your path (in case you don't want to go through the installation process).

This should work with transformers==4.34.1, which is what I tested it on. There are other libraries (e.g., AttentionSink) that also implement this, but I cannot speak to how they perform compared to the original repo. If you do get a chance to check them out, please let me know how they go.
Please let me know if you have any other questions :)


Output metadata for each word set

Word-set metrics:

number of words
true packing value (not upper-bound)
mean word length <-- very important
mean pairwise overlaps
total pairwise overlaps <-- very important

Solution-board metrics:

number of horiz/vert/diag/fwb/bwd words
number & % of overlapping letters
number & % of rows/columns with overlapping letters

Code now returns word-set metrics. Still need to return solution-board metrics.

Updated in https://github.com/jonadsimon/wonder-words-generator/commit/d552718972e50019104df16d003796a30a59e575
Still don't have overlap counts, but good enough


chore(availability): adding subset of US states for Ramp

Description
Adding ability to cash-in from the US with Ramp
Other changes
n/a
Tested
unit tests for ramp's availability in each US state in providerAvailability
How others should test
yarn test
Related issues
cc #1604
Backwards compatibility
no API change

Closing to avoid confusion with the private repo version of this code.

....and re-open if it makes sense!


Attachments with .log .txt and .xls are not downloaded properly Office365

Are there any related issues?
Not exact match. I found xls related but not txt and log extension.
What operating system are you using?
$ uname -a
Linux tel-box 4.8.0-51-generic #54~16.04.1-Ubuntu SMP Wed Apr 26 16:00:28 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux
What version of Nylas Mail are you using?
cat /usr/share/nylas-mail/version
v1.4.15
Bug?
Do you have any third-party plugins installed? If so, which ones?
No
Is the issue related to a specific email provider (Gmail, Exchange, etc.)?
I've only one account that is office365
Is the issue reproducible with a particular attachment, message, signature, etc?
all .xls, .log and .txt extension files are not downloaded. 0bytes.
Other extensions pdf and .doc are downloaded and opened properly
--
Feature Request?
Does this feature exist in another mail client or tool you use?
Big Yes

I've around 40K messages in office365 account and I configured my office365 nearly 48hrs ago still syncing is going on.
$ date ; find .nylas-mail/messages/ -type f | wc -l; du -sh .nylas-mail
Thu May  4 17:25:11 PDT 2017
16447
910M	.nylas-mail

$ date ; find .nylas-mail/messages/ -type f | wc -l; du -sh .nylas-mail; pgrep nylas
Fri May  5 10:06:17 PDT 2017
25742
1.6G	.nylas-mail

$ ps -eo "%c - %a - %C - %t - %x" | grep -i nylas
nylas           - /usr/share/nylas-mail/nylas -  4.0 -    22:00:33 - 00:53:36
nylas           - /usr/share/nylas-mail/nylas -  0.0 -    22:00:31 - 00:00:00
nylas           - /usr/share/nylas-mail/nylas -  4.5 -    22:00:28 - 01:00:13
Nylas Mail defa - Nylas Mail default          -  6.2 -    22:00:27 - 01:23:04
Nylas Mail work - Nylas Mail work             -  5.7 -    05:23:44 - 00:18:40
grep            - grep --color=auto -i nylas  -  0.0 -       00:00 - 00:00:00
nylas           - /usr/share/nylas-mail/nylas -  0.0 -    14:48:42 - 00:00:00
Nylas Mail empt - Nylas Mail emptyWindow      -  0.0 -    11:20:12 - 00:00:23

I really wanted to give a try because of it UI. I'll wait till my sync completes and see attachments are opening fine.
Without xls, log and txt file I can't continue to use this


SerializationContext.Default UnpackSingleObject failure on Unity 3D iOS Device build

deserializing LoginRP error:System.ExecutionEngineException: Attempting to JIT compile method 'MsgPack.Serialization.SerializationContext:GetSerializer (object)' while running with --aot-only.
---> System.Reflection.TargetInvocationException: Exception has been thrown by the target of an invocation. ---> System.ExecutionEngineException: Attempting to JIT compile method 'MsgPack.Serialization.SerializationContext:GetSerializer (object)' while running with --aot-only.
at System.Reflection.MonoMethod.Invoke (System.Object obj, BindingFlags invokeAttr, System.Reflection.Binder binder, System.Object[] parameters, System.Globalization.CultureInfo culture) [0x00000] in :0
at System.Reflection.MethodBase.Invoke (System.Object obj, System.Object[] parameters) [0x00000] in :0
at MsgPack.Serialization.ReflectionExtensions.InvokePreservingExceptionType (System.Reflection.MethodInfo source, System.Object instance, System.Object[] parameters) [0x00000] in :0
at MsgPack.Serialization.SerializationContext+SerializerGetter.Get (MsgPack.Serialization.SerializationContext context, System.Type targetType, System.Object providerParameter) [0x00000] in :0
at MsgPack.Serialization.SerializationContext.GetSerializer (System.Type targetType, System.Object providerParameter) [0x00000] in :0
at MsgPack.Serialization.ReflectionSerializers.ReflectionSerializerHelper.GetMetadata (IList1 members, MsgPack.Serialization.SerializationContext context, System.Func2[]& getters, System.Action2[]& setters, System.Reflection.MemberInfo[]& memberInfos, MsgPack.Serialization.DataMemberContract[]& contracts, MsgPack.Serialization.IMessagePackSerializer[]& serializers) [0x00000] in <filename unknown>:0    at MsgPack.Serialization.ReflectionSerializers.ReflectionObjectMessagePackSerializer1[Assets.LoginRP]..ctor (MsgPack.Serialization.SerializationContext context) [0x00000] in :0
at MsgPack.Serialization.MessagePackSerializer.CreateReflectionInternal[LoginRP] (MsgPack.Serialization.SerializationContext context, System.Type concreteType, MsgPack.Serialization.PolymorphismSchema schema) [0x00000] in :0
at MsgPack.Serialization.SerializationContext.GetSerializer[LoginRP] (System.Object providerParameter) [0x00000] in :0
at MsgPack.Serialization.SerializationContext.GetSerializer[LoginRP] () [0x00000] in :0
at Assets.SerializerHelper.Deserialize[LoginRP] (System.Byte[] data) [0x00000] in :0
======================
it work fine on iOS simulator
i use MsgPack.Cli.0.6.0-Beta2

Thank you for reporting!
It looks general AOT issue, so the issue should depend on the structure of LoginRP type. Does it have generic value type like KeyValuePair<TKey, TValue> ?

Is there any progress?

Please reopen or post new issue when any problems occur.


Now transpiles for estimator and sampler

Without transpilation, you can't run Estimators and Samplers using Qiskit 1.0. This is a simple change that just transpiles circuits so that it can be submitted to a real hardware backend. Tested on a local notebook that access to the device works as intended and the answers seem reasonable (other than some formatting issues that a different PR is addressing).

[sc-62928]

Can hold off on this one while we decide on if we are going to change to using V2 primitives instead.

This is just a few lines of code so I merged it into #539 as without the transpilation none of the code works 😅


[Oracle] Include filters for databases are case sensitive, but exclude filters are case-insensitive.

System information:

Operating system (distribution) and version win10
DBeaver version 21.3.0

Connection specification:

Database name and version Oracle

Describe the problem you're observing:
Include filters for databases are case sensitive, but exclude filters are case-insensitive.
Existing databases:

Exclude filter:

Include filter:

Verified


Add support for bn254

move methods to a trait
implement trait for goldilocks and bn254
change AbstractNumberType to BigUint

currently fails in pilcom, probably something to do with biguint arithmetics in the bit constraints

In the riscv zkVM there are lots of assumptions on GL

In the riscv zkVM there are lots of assumptions on GL

Once we expose both GL and Bn we can make the riscv crate use GoldilocksField directly instead of being generic over F: FieldElementTrait

In the riscv zkVM there are lots of assumptions on GL

Once we expose both GL and Bn we can make the riscv crate use GoldilocksField directly instead of being generic over F: FieldElementTrait

So what's missing currently?

In the riscv zkVM there are lots of assumptions on GL

Once we expose both GL and Bn we can make the riscv crate use GoldilocksField directly instead of being generic over F: FieldElementTrait

So what's missing currently?

In this PR? Fixing the tests and figuring out what to use for bigint. This PR does not make the whole codebase generic, it only introduces the trait, everything still uses GL.

There are more additions to these traits in #256 but maybe it's worth merging this first.


[Search-bar] The input placeholder is shown even if the query is not empty

Current behaviour
Even if there is a 'query' the placeholder is shown.

Expected behaviour
Hide the placeholder if there is a query.
Versions
Focus-core: 0.14.0
Focus-components: 0.14.1

@GuenoleK Is it a material problem?

Yes it's a material design problem @JoanaDalmeida & @pierr . The placeholder is not updated.
We  should update input/text component this way :

waiting to be merged in #1144

@pierr @GuenoleK what do we do ????

Cannot reproduce the bug