Edit code, ¿where?

I would like to be able to edit the code, I already have it deployed in AWS, is it possible to do so? What lambda is it located in?
function handler(event) {
var request = event.request;
var originalImagePath = request.uri;
//  validate, process and normalize the requested operations in query parameters
var normalizedOperations = {};
if (request.querystring) {
Object.keys(request.querystring).forEach(operation => {
switch (operation.toLowerCase()) {
case 'format':
var SUPPORTED_FORMATS = ['auto', 'jpeg', 'webp', 'avif', 'png', 'svg', 'gif'];
if (request.querystring[operation]['value'] && SUPPORTED_FORMATS.includes(request.querystring[operation]['value'].toLowerCase())) {
var format = request.querystring[operation]['value'].toLowerCase(); // normalize to lowercase
if (format === 'auto') {
format = 'jpeg';
if (request.headers['accept']) {
if (request.headers['accept'].value.includes("avif")) {
format = 'avif';
} else if (request.headers['accept'].value.includes("webp")) {
format = 'webp';
}

yes! you can find them in the 'functions' folder

Thank you
I have seen in functions / url rewrite but if I have already deployed everything in aws, can I can edit it?
The lambda is called ImgTransformationStack-imageoptimization? I see it is a ZIP. What files does the lambda have in this zip? To edit it and upload it again
Thank you so much

yes you can edit it. The best way is to edit the downloaded CDK code, and then deploy again. Changes will propagate.


Fix flaky DnsNameResolverTest.testTruncatedWithTcpFallback

Motivation:
testTruncatedWithTcpFallback was flacky as we may end up closing the socket before we could read all data. We should only close the socket after we succesfully read all data.
Modifications:
Move socket.close() to finally block
Result:
Fix flaky test and so make the CI more stable again.

See https://ci.netty.io/job/netty-centos6-java12-prb/951/testReport/junit/io.netty.resolver.dns/DnsNameResolverTest/testTruncatedWithTcpFallback/

Let me just merge this one...


FPS value in AnimatedSprite (2D) applied to wrong animation when switching to another

Godot version:
3.1-RC3
OS/device including version:
Windows 10
Issue description:
If you have 2 animations in a AnimatedSprite (2D) with the same FPS value, and you try to change the FPS of one of them, and then you click in the second one, then the FPS change is wrongly applied to second one.
If the animations do not have the same FPS value them the change is omitted/discarded and both animations preserve the original value.
Steps to reproduce:

Create a AnimatedSprited (2D).
Assign a new SpriteFrames.
Click on the SpriteFrames to open the panel.
Create 2 animations.
Click in the first one.
Change the FPS value. Do not press enter key.
Click in the other animation.

Minimal reproduction project:
Test.zip

Can confirm.
(psst, there is no need to submit the new project template as a MRP. Just say works from a blank project)

Can I take this on as my first issue here?
I think I'd be tweaking this function so that before reassigning edited_anim to the newly selected animation, I would check if the current edited_anim's FPS value has changed and call _animation_fps_changed with the new value if so.

I could also do anim_speed->release_focus(), but since _update_library changes anim_speed before the focus_exited signal gets processed that won't work unless I defer the call to _update_library.
Not sure which way would be better or if it makes much of a difference in the end?

I did it the first way I mentioned, without release_focus, since I wasn't sure how to defer the change of edited_anim, but if anyone thinks that'd work better, I can change it.


refactor role package

The access token feature added in this PR #56 is implemented in the role package.
It should be divided into access packages.

I think it would be good to match this to atpParams.
https://github.com/yahoojapan/athenz-authorizer/blob/930b45d7acc36c92377872b0f6597ff6d7c15c98/role/processor.go#L45-L49
https://github.com/yahoojapan/athenz-authorizer/blob/930b45d7acc36c92377872b0f6597ff6d7c15c98/option.go#L44-L47

TODO: add test cases for *Verifier := wrapper functions in func (a *authorizer) initVerifiers() error

continue in: https://github.com/AthenZ/athenz-authorizer/issues/5


Unlcear how to read results of rendering back on CPU

For implementing something like AVI logging, it would be nice to be able to read the contents of the backbuffer, or even a render target, back via the CPU.
It appears that bgfx::readTexture can accept a FrameBufferHandle, an attachment index (presumably for the texture(s) that were attached via bgfx::createFrameBuffer?), and a void pointer for the output data, but unfortunately I can't even get that far.
I've added BGFX_TEXTURE_READ_BACK to the flags that I'm already using for creating the framebuffer's texture attachments (BGFX_TEXTURE_RT and whatever filtering modes were specified by the caller). Unfortunately, when the BGFX D3D11 renderer tries to create that particular target's view with CreateRenderTargetView, it returns E_INVALIDARG, and BGFX blows up.
One post on some forum said that it might be due to format restrictions when creating a texture that supports readback on the CPU, so I tried changing from what I was using (TextureFormat::RGBA8) to the BGFX equivalent of a format that someone mentioned elsewhere on the web (TextureFormat::RGBA8U) that supports it, but I'm still getting the same issue.
I'm not sure how to get you a repro case, I could maybe check a branch into the MAME project on github, but do you have any ideas that jump to mind?

Long story short: What I'd like to do is be able to

If you just want to capture video, you can use BGFX_RESET_CAPTURE:
https://bkaradzic.github.io/bgfx/bgfx.html#_CPPv2N4bgfx5resetE8uint32_t8uint32_t8uint32_t
And implement capture callbacks:
https://bkaradzic.github.io/bgfx/bgfx.html#_CPPv2N4bgfx9CallbackI12captureBeginE8uint32_t8uint32_t8uint32_tN13TextureFormat4EnumEb
There is example how to capture video into AVI in 07-callback example:
https://github.com/bkaradzic/bgfx/blob/master/examples/07-callback/callback.cpp#L263


Feature request to chain And and Or Conditions in Where Clause

It would be great if we can add dynamic where clause chaining into specification. For example, if we need to dynamically include search values in where clause based on condition or to support advanced search scenarios; can something like this would make sense?
public class ItemFilterSpecification : Specification<ItemEntity>
{
    public ItemFilterSpecification(string? itemName, string? itemCode) : base()
    {
        if (!string.IsNullOrWhiteSpace(itemName))
        {
            Query.Where(i => i.Name == itemName);
        }

        if (!string.IsNullOrWhiteSpace(itemCode))
        {
            Query.Where(i => i.Code== itemCode); // WhereAnd or Where can be defaulted to And search
            Query.WhereOr(i => i.Code== itemCode); // WhereOr to include Or conditions in search
        }

        // Till this point if both values are not null then query should be composed like
        // Query.Where(i => i.Name == itemName && i.Code == itemCode);
        // For Or search
        // Query.Where(i => i.Name == itemName || i.Code == itemCode);
    }
}

This would add great value to the package. And help to build query for advanced search or dynamic search

Hi @fingers10,
This feature is useful, but it's out of the scope of the specifications (as implemented in this package).
In order to implement it, we need to manipulate the expressions that the user enters. We should keep track of all the conditions and then re-constructs the expressions. This will increase the complexity of the package significantly. In the current state, we just hold the expressions, and pass them to the ORM as they are.
It's not about if it's hard to implement or not (it can be done). It's the fact that the package suddenly will become something that users have to master it. Personally, I prefer it to remain useful and yet not to be struggle to use it. @ardalis any thoughts on this?
Btw, you can accomplish the functionality you want with one additional condition. It's not elegant, but it's simple.
public class ItemFilterSpecification : Specification<ItemEntity>
{
    public ItemFilterSpecification(string? itemName, string? itemCode) : base()
    {
        if (!string.IsNullOrWhiteSpace(itemName) && !string.IsNullOrWhiteSpace(itemCode))
        {
            Query.Where(c => c.Name == itemName || c.Code == itemCode);
        }
        else if(!string.IsNullOrWhiteSpace(itemName))
        {
            Query.Where(i => i.Name == itemName);
        }
        else if(!string.IsNullOrWhiteSpace(itemCode))
        {
            Query.Where(i => i.Code == itemCode);
        }
    }
}

@ardalis What's your thought on this?
If we decide to utilize expression reconstructions, then we can achieve a lot, and add quite many features (btw, we can solve #38 too).
But, on the other hand, it's kind of a rabbit hole if we go on that path. There are a lot of edge cases. We should be more carefully following .NET changes, and we should include rigorous tests for everything.

If calling code is having to AND and OR different specifications together, that's essentially query logic the caller is responsible for. I'd put that logic into a new specification so the caller doesn't need to do anything. In that new specification, it can AND and OR however it wants in its Query construction. To me giving callers the ability to combine specifications just asks for query logic to leak up the call stack.

Closing as I think this can/should be done in individual specifications to keep logic from leaking throughout the app.


Extract submver from dependencies

Instead of updating submver manually, use whatever is specified as the Submariner dependency. This avoids having to update a variable every time Submariner is released, which means we can rely on dependabot to take care of everything for us.
While we're at it, drop the Submariner CR update; it no longer specifies the version to use.

/cc @dfarrell07 @sridhargaddam @tpantelis

/lgtm and this would make https://github.com/stolostron/submariner-addon/pull/787 unnecessary once backported I assume

/approve

/cherrypick release-2.7 release-2.6

/cherrypick release-2.7

/cherrypick release-2.6


[AutoPR managedservices/resource-manager] [Hub Generated] Review request for Microsoft.ManagedServices to add version preview/2019-04-01-preview

Created to sync https://github.com/Azure/azure-rest-api-specs/pull/5947

(message created by the CI based on PR content)

Codecov Report

Merging #5248 into restapi_auto_managedservices/resource-manager will not change coverage.
The diff coverage is n/a.

@@                              Coverage Diff                               @@
##           restapi_auto_managedservices/resource-manager    #5248   +/-   ##
==============================================================================
  Coverage                                          49.51%   49.51%
==============================================================================
  Files                                               6330     6330
  Lines                                             177194   177194
==============================================================================
  Hits                                               87731    87731
  Misses                                             89463    89463

Continue to review full report at Codecov.

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evaluator: unexpected behaviour from list.Sum

What version of CUE are you using (cue version)?

$ cue version
cue version v0.10.1

go version go1.23.2
      -buildmode exe
       -compiler gc
       -trimpath true
     CGO_ENABLED 0
          GOARCH amd64
            GOOS windows
         GOAMD64 v1
cue.lang.version v0.10.1

Does this issue reproduce with the latest stable release?
Yes. Tested in playground as of today.
What did you do?

import "list"

_test: {
  one: {
    num: 2
    test: num: 6
  }
  two: {
    num: 3
    test: num: 7
  }
  three: {
    num: 4
    test: num: 8
  }
  four: {
    num: 5
    test: num: 9
  }
}

list.Sum([for key, val in _test {
  val.num + val.test
}])

Evaluate this.
What did you expect to see?
Invalid operands error (int and struct)
What did you see instead?
Evaluates to 0

works in evalv3, perhaps a non-issue

perhaps it is better to leave it to your discretion whether to close this as a non-issue or not

Thanks for reporting - good to hear that evalv3 fixes this issue. We will add a regression test to ensure our test suite covers this edge case.


[Question] Maui support with Microsoft.Maui.Graphics instead of SkiaSharp

Hi,
Is there any plan to officially support Maui, using Microsoft.Maui.Graphics instead of SkiaSharp?
Thanks

right now, no. This library is all about SkiaSharp, making a straight Maui solution would be a major undertaking that someone not me would have to do.


Init lib automatically using content provider

https://firebase.googleblog.com/2016/12/how-does-firebase-initialize-on-android.html

If it's up for debate I'd vote against it. It's a heavy handed hack in exchange for what's a line of code that'll throw an exception if missing, which can happen only once per project tops. Paper is geared towards intermediate-advanced users that'll read and understand the requirements, which is not the target audience Google intends for Firebase. The change also breaks flow for multi-process apps, and takes control away from the implementer.

Yeah, I read about all drawbacks, they don't look like showstoppers for me. For multi-process apps Paper can throw an exception like it's now so devs can init it in custom Application class. The init section is not very important for devs to pay so much attention for it. Paper.init() is only about capturing app context. And I'm so lazy to create Application classes and register it in AndroidManifest that I would use safe (!) tricks in order to provide better and more convenient API for everyone :)

Couple of months old this but... I prefer explicit initialisation to this hack. A ContentProvider should be used to provide content, it's a misuse of the API to use it to get around calling init();
I know the example is on googleblog but it seems like bad practice.

Ok, agreed with you guys. Let's close it 🎉


puzzled With Mobilenet_v3 out_indices

when out_indices is set None.
arch is small ,out_indices is (12,), while len(arch) is 11.
when arch is large, out_indices is (16,), however len(arch) is 15.

Does it mean to output classifier layer(12th layer).

there is a layer0 in the start.


NavLink no longer updates activeClassName when a parent component has componentDidMount

Version
4.2.0
Test Case
https://codesandbox.io/s/6vyol3o86n
Steps to reproduce
Make a parent component have a componentDidMount method
Expected Behavior
NavLink active state updates after link click
Actual Behavior
NavLink active state only updates on page refresh.


Part1-06 getting quite long

This chapter is getting quite long, especially if we add package manager info - @oneilsh, how would you feel about splitting it into 2?
I'm thinking a split right after the first section of exercises, still called "Installing (Bioinformatics) Software", and a second chapter maybe "Using (Bioinformatics) Software"? It would contain the headers:

Getting Data
Putting It All Together
Reproducibility with Scripts

Thoughts?

Yeah, that's one of the three "apex" chapters in each part (mentioned here in the preface). Splitting it sounds good to me, perhaps the other corresponding ones need a similar treatment.


docs: fix simple typo, quanlity -> quality

There is a small typo in docs/lpt.md.
Should read quality rather than quanlity.
Semi-automated pull request generated by
https://github.com/timgates42/meticulous/blob/master/docs/NOTE.md

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


merge caps plugins

https://github.com/metajack/strophejs-plugins/blob/master/caps/strophe.caps.js
https://github.com/flosse/strophejs-plugins/blob/master/caps/strophe.caps.coffee

I'll take a look as soon as I have some spare time :)
Writing tests would be nice, especially for testing if the version-computation is done correctly.


ERROR: read ECONNRESET

Hi, any solution with the error below ?

forgot to quit the session upon initializing.

how do you resolve it ? @nicopenaredondo


Fix repository settings form template to work with redmine 4.x

Patch from comments in issue #742
(https://github.com/jbox-web/redmine_git_hosting/issues/742#issuecomment-600840141)

Thank for merging this.
About the previous question: this patch was tested on the following setup (Debian10)
Environment:
  Redmine version                4.1.1.stable
  Ruby version                   2.5.5-p157 (2019-03-15) [arm-linux-gnueabihf]
  Rails version                  <IP_ADDRESS>
  Environment                    production
  Database adapter               Mysql2
  Mailer queue                   ActiveJob::QueueAdapters::AsyncAdapter
  Mailer delivery                smtp
SCM:
  Subversion                     1.10.4
  Git                            2.20.1
  Filesystem
  Xitolite                       2.20.1
Redmine plugins:
  additionals                    2.0.23
  redmine_bootstrap_kit          0.2.5
  redmine_code_review            1.0.0
  redmine_default_members        1.0-devel
  redmine_dmsf                   2.4.2 devel
  redmine_embedded               0.0.2
  redmine_git_hosting            4.0.1
  redmine_per_project_formatting 0.1.0


[hf inference] Add HuggingFaceTextSummarizationParser

[hf inference] Add HuggingFaceTextSummarizationParser
[hf inference] Add HuggingFaceTextSummarizationParser
Implement HuggingFaceTextSummarizationParser for running hf summarization models via inference API for gradio. Some things to note:

The summarization API doesn't support streaming, so just handle non-streaming (ignore stream flag)
Added support for user-provided api_token as part of InferenceOptions, redacting it from the logged options (though note that we are logging the object / address itself anyway ('options': <aiconfig.model_parser.InferenceOptions object at 0x16e8cb910>)

Testing:
Build/install the local hugging face package with these changes
(hf) ryanholinshead@Ryans-MacBook-Pro aiconfig % cd extensions/HuggingFace
pip3 install build && cd python && python -m build && pip3 install dist/*.whl
pip3 install -e .

Register these parsers in /Users/ryanholinshead/Projects/aiconfig/cookbooks/Gradio/hf_model_parsers.py then run aiconfig editor with the local parsers and gradio config:
aiconfig_path=/Users/ryanholinshead/Projects/aiconfig/cookbooks/Gradio/huggingface.aiconfig.json

(hf) ryanholinshead@Ryans-MacBook-Pro aiconfig % parsers_path=/Users/ryanholinshead/Projects/aiconfig/cookbooks/Gradio/hf_model_parsers.py

(hf) ryanholinshead@Ryans-MacBook-Pro aiconfig % aiconfig edit --aiconfig-path=$aiconfig_path --server-mode=debug_servers --parsers-module-path=$parsers_path

Ensure the model works in the config. Ensure changing settings works & is persisted to aiconfig.

Test setting fake model ('test') propagates expected error

Test setting invalid api_token in the InferenceOptions in run server-side propagates expected error

Set to my own key and ensure execution works

Stack created with Sapling. Best reviewed with ReviewStack.

#1006
#1005
#1004
#1003
#997
-> #993
#992

Added support for user-provided api_token as part of InferenceOptions

Sorry I remember this being mentioned and something having to do with editor client passing api_token. Could you explain why this change is needed again?

In Gradio, the server for the space will initialize parser instances in the registry and those parsers will be shared by anyone using the space. But, we want users to be able to provide their own HF api token to use for the actual inference requests, so it needs to be done at the run layer


Updated docstrings and function annotations for compute and compute_procedure

Description
closes #348
Still waiting on comment re: updating local_config -> task_config but wanted to provide these updates before I forgot.
Changelog description
Updated docstrings and function annotations for compute and compute_procedure
Status

[x ] Code base linted
[ ] Ready to go

I realized the local_config nomenclature goes one layer deeper into the get_config function. I updated these functions calls. I'm treating get_config as a more internal function and just updating it's signature and internal package calls of the function directly.  Any other changes needed let me know :)


Create a copy of a realm Object

Lets say i have an realm object stored in my db (indeed is much more complex):
class Dog: Object {
    @objc dynamic var name = ""
    @objc dynamic var age = 0
}

Now lets say i want to modify this object cause you can edit the Dog object. To verify you can actually save this object you have to call a server, and if its ok, you can save it.
The problem is that for modify the object i only have 2 options: One is importing Realm and modifying the object from the db (the option that i dont want, cause i need the object in my views and i dont want to import Realm there), and the option that im aiming for is to create a copy of the realm Object to a regular struct.
struct DogStruct {
   var name = ""
   var age = ""
}

So i can easily change those values and then if servers is ok, i can save it. There is any trick or way to do this transform? I have to manually do the transform between Dog and DogStruct and its very tedious, since Dog have nested vars and so on.

@ivangodfather we are doing something similar, in our case we wanted a detached object from Realm so we are using this:
import Realm
import RealmSwift

protocol DetachableObject: AnyObject {
  func detached() -> Self
}

extension Object: DetachableObject {
  func detached() -> Self {
    let detached = type(of: self).init()
    for property in objectSchema.properties {
      guard let value = value(forKey: property.name) else {
        continue
      }
      if let detachable = value as? DetachableObject {
        detached.setValue(detachable.detached(), forKey: property.name)
      } else { // Then it is a primitive
        detached.setValue(value, forKey: property.name)
      }
    }
    return detached
  }
}

extension List: DetachableObject {
  func detached() -> List<Element> {
    let result = List<Element>()
    forEach {
      if let detachableObject = $0 as? DetachableObject,
        let element = detachableObject.detached() as? Element {
        result.append(element)
      } else { // Then it is a primitive
        result.append($0)
      }
    }
    return result
  }
}

Then on your object (if it inherits from Object) you can just do object.detached() 👍
Hope it helps!

@robertofrontado makes a lot of sense! thx u!

As of now, Dec 2020, there is not proper solution of this issue. We have many workarounds though.
Here one I have been using, and one with less limitations in my opinion.

Make your Realm Model Object classes conform to codable

class Dog: Object, Codable{
    @objc dynamic var breed:String = "JustAnyDog"
}

Create this helper class

class RealmHelper {
    //Used to expose generic
    static func DetachedCopy<T:Codable>(of object:T) -> T?{
       do{
           let json = try JSONEncoder().encode(object)
           return try JSONDecoder().decode(T.self, from: json)
       }
       catch let error{
           print(error)
           return nil
       }
    }
}

Call this method whenever you need detached / true deep copy of your Realm Object, like this:

 //Suppose your Realm managed object: let dog:Dog = RealmDBService.shared.getFirstDog()
 guard let detachedDog = RealmHelper.DetachedCopy(of: dog) else{
    print("Could not detach Note")
    return
 }
//Change/mutate object properties as you want
 detachedDog.breed = "rottweiler"

As you can see we are piggy backing on Swift's JSONEncoder and JSONDecoder, using power of Codable, making true deep copy no matter how many nested objects are there under our realm object. Just make sure all your Realm Model Classes conform to Codable.
Though its NOT an ideal solution, but its one of the most effective workaround.

This is not working for me: I have a Company object. When I encode it, it does the _partition and the _userId fine, but any other field is coming over blank. Additionally, if there is a List in the object it just stops. Granted the List is not Codable, I figure I would see an error or at least just skip over it.
I checked my object being passed in and the name property has a value. After encoding, it becomes blank.

Is anyone using @robertofrontado's DetachableObject in Xcode 13 / Swift 5.5? It's no longer happy with the initial init() of the detached object, giving me "Constructing an object of class type 'Self' with a metatype value must use a 'required' initializer"
If anyone knows of a workaround that would let the protocol extension work as it had before, I'd appreciate it. Otherwise I think I have to duplicate the detached() function across all my realm models.

Followup: the problem ended up being my custom subclass of Realm's Object that I forgot about. Changing the code in question to be an extension of RealmSwift.Object cleared it up for me.

@ivangodfather we are doing something similar, in our case we wanted a detached object from Realm so we are using this (we do this when we read an object from Realm so we can use that instance from any thread):
[...]
Hope it helps!

Modified @ivangodfather's code to work with EmbeddedObject.
func makeDetachedObject<O: RLMObjectBase>(of object: O, with objectSchema: ObjectSchema) -> O {
    let detached = type(of: object).init()
    for property in objectSchema.properties {
        guard let value = object.value(forKey: property.name) else {
            continue
        }
        if let detachable = value as? DetachableObject {
            detached.setValue(detachable.detached(), forKey: property.name)
        } else { // Then it is a primitive
            detached.setValue(value, forKey: property.name)
        }
    }
    return detached
}

extension Object: DetachableObject {
    func detached() -> Self {
        makeDetachedObject(of: self, with: objectSchema)
    }
}

extension EmbeddedObject: DetachableObject {
    func detached() -> Self {
        makeDetachedObject(of: self, with: objectSchema)
    }
}


improve message extentions

#24 nice but here a few improvements

I agree that the extend is strange and I will fix it. I will also try to merge the approach with the IQ payload registration.
Possibly, I am thinking of avoiding to make the registry a global variable but make it par of the client structure.
Regarding the way to approach the registration, I was trying to explore registering per name space, instead of namespace + local tag name. It should make it easier to support new features, by having a single struct that support all the possibles fields / messages.
However, while it seems to make sense for the urn:xmpp:receipts namespace, having simalar data, it may be more painful to implement more complex XEP.
I need to make some test implementing it on several extensions. If some of the have very different subelements, for different tag name, then it is not a good idea. In that case, we would need to indeed stick to the approach of having a single struct per namespace + Local (which is probably going to be the case).

I updated my commit with a better registry that is shared between IQ Payload and messaging extensions.
I still need some more refactor, but I should probably merge it to master first first.
I would like to have the registry hold by the Client structure, to avoid having the registry as a global package-level variable.

It should be fixed by https://github.com/FluuxIO/go-xmpp/pull/27


Revert "Text regression"

Reverts neulab/ExplainaBoard#324
It seems that this PR doesn't have to be merged due to: https://github.com/neulab/ExplainaBoard/pull/354

I just opened a new PR merging the neulab/explainaboard branch text_regression into main: https://github.com/neulab/ExplainaBoard/pull/363
Maybe this would be sufficient to solve the issue and this PR could be closed?

@neubig  OK, I closed this PR.


be able to rewind cassette within the @use_cassette decorator

Now there is a .rewind method of the Cassette.  But since cassette is not given into the test, there is no way to rewind it upon test completion. So in the case of parametric tests (e.g. in case of nose, the same decorated with @use_cassette test yielded with different parameters to be used in consecutive runs) my tests would blow on the second run.  It would be nice to be able to provide @use_cassette with rewind option defaulting to False.

Could you please provide a code snippet or link to a toy repo to replicate the exact case you reference here?
I only have bandwidth to act as a release manager nowadays, so anyway to be able to assist the next person in closing out PRs is very welcomed.

I will try to come up with one

hm, on a minimalistic one I failed to reproduce my issue, so either things changed or it does not yet capture the same situation I was in.  I will try again later
import urllib2
from vcr import use_cassette

@use_cassette('mytape')
def _test_use_cassette(p):
    print("param %s" % p)
    response = urllib2.urlopen('http://www.iana.org/domains/reserved').read()
    assert 'Example domains' in response
    print("response: %s" % response[:10])

def test_use_cassette():
    for p in 1, 2:
        yield _test_use_cassette, p

$> python -m nose -v -s test_vcrpy.py
Beware: you are importing a development version of IPython -- no whining
trash.test_vcrpy.test_use_cassette(1,) ... param 1
response: <!doctype
ok
trash.test_vcrpy.test_use_cassette(2,) ... param 2
response: <!doctype
ok

----------------------------------------------------------------------
Ran 2 tests in 0.046s

OK


Feature request: make linguist capable of being run on non-repositories

Hi,
This tool is great, except there is one shortcomming, namely that it seems to only be able to be run on git repositories. I have source code directories locally that I'd rather not commit to a git repository, but I'd still like to get a source code composition breakdown using this tool. Presently when I run linguist on a non-repository directory I get the error:
/home/fusion809/.gem/ruby/2.1.0/gems/github-linguist-5.0.8/bin/linguist:27:in `new': Could not find repository from '.' (Rugged::RepositoryError)

Thanks for your time,
Brenton

See #3563.

I've hacked together a simple script that allows linguist to run on non repos, but it's very much a hack that temporarily creates a local repo then removes it after analysis:
https://gist.github.com/PuZZleDucK/a45fd1fac3758235ffed9fe0e8aab643

I'd like to see this too. I still keep version 2.12 installed since it has this capability.

I'm pretty sure we'd welcome a pull request to implement this if it's not too invasive (/cc @lildude for confirmation). In the meantime, creating a git repository and deleting it after the analysis as suggested by @PuZZleDucK is a quick workaround.

Closing as this is not something we need ourselves, but if anyone is interested in this feature, they're welcome to submit a pull request!


How to train the Imagnet (which has 300million images) in local machine?

I just wonder to know what is your computer hardware device, I chose the i5-12400f and RTX4080 to train the just simple Conv model, just have 5 layers, but the speed is so slow, and the training time will cost many years about 100 epochs. And I try to ues AutoDL to train this model , the cpu is 100% utilize but the gpu is just 40%, and the training speed is also very slow.

I just wonder to know what is your computer hardware device, I chose the i5-12400f and RTX4080 to train the just simple Conv model, just have 5 layers, but the speed is so slow, and the training time will cost many years about 100 epochs. And I try to ues AutoDL to train this model , the cpu is 100% utilize but the gpu is just 40%, and the training speed is also very slow.

你好！这个库里所有的实验都是在AUTODL平台上完成的。绝大多数实验的硬件配置为2卡RTX A5000(24GB显存)，30 核CPU AMD EPYC 7543 32-Core Processor，60GB内存，一些比较大的网络训练时会采用2卡/4卡RTX 4090(24GB显存) ，32 核/64核CPU AMD EPYC 9654 96-Core Processor，120GB/240GB内存的配置。如果你想知道具体的某个实验到底用了哪种显卡，可以在https://huggingface.co/zgcr654321/classification_training/tree/main/imagenet中查到。比如假设我们要看resnet50这个实验，可以在https://huggingface.co/zgcr654321/classification_training/raw/main/imagenet/resnet50/log/train.info.log.2023-03-14中找到这两行记录：

I have a new question, what is your training and testing time? I try to use
auto-dl, just single 4090 GPU, use vgg-net, the simple version, the paper E
experiment version, that have first 2 and second 3 and following the 5
layer three times, it means i have 5 vgg blocks, and every block have many
layers, this network is a little complicated, I can just get the very
slowly training speed, about 300 batches per second, batches is just the
single image processing, not the batchsize number, maybe there I make the
batches is not very precise, anyway, the training speed is very slow, i
will cost 2 weeks or more time to train this model, and i also don't know
how bad about my neural network structure, if I want to change the model, I
will cost more one week again, it's very hardly to train these big model,
what the special method your team adopt? And what is your training time
about the 3 millions images dataset and the vgg_net, using the whole
ImageNet.
On Mon, 4 Dec 2023 at 16:02, zgcr @.***> wrote:

Closed #33
https://github.com/zgcr/SimpleAICV_pytorch_training_examples/issues/33
as completed.
—
Reply to this email directly, view it on GitHub
https://github.com/zgcr/SimpleAICV_pytorch_training_examples/issues/33#event-11135379723,
or unsubscribe
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.
You are receiving this because you authored the thread.Message ID:
<zgcr/SimpleAICV_pytorch_training_examples/issue/33/issue_event/11135379723
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I'm very apologize about the question about your training time, I check out
your training log, it's really need too much time to train a huge model
with huge dataset, thank you for your answer, wish you have a nice day!
On Mon, 4 Dec 2023 at 23:42, 龙周 @.***> wrote:

I have a new question, what is your training and testing time? I try to
use auto-dl, just single 4090 GPU, use vgg-net, the simple version, the
paper E experiment version, that have first 2 and second 3 and following
the 5 layer three times, it means i have 5 vgg blocks, and every block have
many layers, this network is a little complicated, I can just get the very
slowly training speed, about 300 batches per second, batches is just the
single image processing, not the batchsize number, maybe there I make the
batches is not very precise, anyway, the training speed is very slow, i
will cost 2 weeks or more time to train this model, and i also don't know
how bad about my neural network structure, if I want to change the model, I
will cost more one week again, it's very hardly to train these big model,
what the special method your team adopt? And what is your training time
about the 3 millions images dataset and the vgg_net, using the whole
ImageNet.
On Mon, 4 Dec 2023 at 16:02, zgcr @.***> wrote:

Closed #33
https://github.com/zgcr/SimpleAICV_pytorch_training_examples/issues/33
as completed.
—
Reply to this email directly, view it on GitHub
https://github.com/zgcr/SimpleAICV_pytorch_training_examples/issues/33#event-11135379723,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AVJPQYIT477ZIL6XJMIUAF3YHV7SHAVCNFSM6AAAAABACDNPQSVHI2DSMVQWIX3LMV45UABCJFZXG5LFIV3GK3TUJZXXI2LGNFRWC5DJN5XDWMJRGEZTKMZXHE3TEMY
.
You are receiving this because you authored the thread.Message ID:
<zgcr/SimpleAICV_pytorch_training_examples/issue/33/issue_event/11135379723
@github.com>


Fix python 3 pyflakes error.

Change raw unicode literal to non-raw.  A raw unicode literal is a syntax error in python 3.  This error was detected by pyflakes in python 3 mode.

This looks good, but I realized that regular expression didn't have any tests, and in fact was totally broken since the last time Zulip changed its URL scheme for uploaded files.  So I fixed the regular expression, added tests, and then merged this fix for Python 3 compatibility (applied to the post-fix code).  Thanks @sharmaeklavya2!


Remove device capability pixel sender

Task/Issue URL: https://app.asana.com/0/488551667048375/1203337379671752/f
Description
Steps to test this PR
Feature 1

[ ]
[ ]

UI changes

Before
After

!(Upload before screenshot)
(Upload after screenshot)

Current dependencies on/for this PR:

develop

PR #2515   👈

This comment was auto-generated by Graphite.


Tests depend on experiment flag which is going to be disabled.

The tests

pkg/dartdev/test/commands/test_test.dart
pkg/dartdev/test/analytics_test.dart

both contains --enable-experiment=non-nullable in a test. That feature is now enabled by default, and the flag should not be passed.
However, removing the flag makes the test fail (because it checks something about the generated artifact which depends on the flag being passed).
These tests should either be changed to expect the non-flag behavior, or just be dropped if they are only testing behavior which doesn't happen any more.
Adding @sigurdm since you appear to have written the tests.

If the flag is removed I guess the test should be dropped.
Only we might want to use other experiments later.
Is there some kind of "dummy-experiment" we could use for testing this?

There is no "example" experiment. Even if there was, it wouldn't change semantics, so it would be impossible to test whether it was enabled or not.
I guess we'll just have to rewrite a new test each time we introduce a new flag. Maybe auto-generate the test from experimental_options.yaml.

Hmm -I see no other choice than removing the tests for now then.
I think auto-generating will be hard when we don't know what semantics to look for.

Maybe we can keep the test as a comment (but document that it's a template to use for later tests, because we don't keep code as comments!)

Keeping a TODO/template sounds good for now.

I think auto-generating will be hard when we don't know what semantics to look for.

I retract that somewhat. If one was willing to put the effort we could include the source of an example program with each experiment in the experimental_features.yaml.
That program should have some fixed semantics (output "feature enabled" on stdout if the feature is enabled, fail static checking or output "feature not enabled" if the feature is not enabled).
That would make autogenerating these tests workable, and indeed do so for every active flag.
(I guess that was also what you had in mind - I just did not think that far.)
Now might however not be the time to implement that, since there would be no flags to test the autogenerated flags on.

We're working on two active experiments right now, completion of the "triple-shift" feature and a new "generic-metadata" experiment.
Yes, I was thinking of including some example in the YAML file, one which should throw if the experiment is not enabled. It probably needs to be a complete program, to ensure we can cover all local features, and it still won't be able to test import based features easily.

We're working on two active experiments right now,

Nice - then we could surely do it!
I think you are right - a single file program would be good enough for most features. We can always make something more advanced if we later.

This should be fixed by: https://dart-review.googlesource.com/c/sdk/+/184790


Hubot does not respond (installed using docker-compose)

I installed rocket.chat and hubot on a digital ocean droplet  using docker-compose.
Right now Rocket.chat is up, hubot is connected (bot user is green in rocket.chat) but it does not respond.
Here is my docker-compose.yml:
https://gist.github.com/lukaszwos/980d1e0b8f791362e28c4eb5a731d9ef
This is my first deployment using docker and while it is fast and easy to do, I don't even know where are those apps (hubot and rocket) installed, so troubleshooting is hard for me in this case.
Thanks in advance for any help

OK. hubot is up. I had to change:
image: rocketchat/hubot-rocketchat:v0.1.4
to:
image: rocketchat/hubot-rocketchat:latest in hubot part of .yml
s a problem when rocketchat imagee _rocketchat image_and hubot image are different (DUH...)
But still how do I service hubot started with docker-compose? For instance. Where (folder location), should I run npm install [script name] to add it to hubot? The same folder in which .yml file is located?
How can I customise scripts? Where are they located?

The issue here is you were pointing at v0.1.4 and latest needed is v1.0.4 at least.  Where did you find this docker-compose file?

Yeah. That's exactly what I wrote above.  I didn't find this yml file anywhere.  I wrote it myself basing on info I gathered.
Anyway. Thanks for taking interest in this issue.
Hubot is awesome.


Feature: New tehcnique to compute the gaze vector

Discussed in https://github.com/vladmandic/human/discussions/465

Originally posted by saeidn95 May 16, 2024
Here is what I propose as an alternative to compute the gaze vector. The results are much better than the current technique. The current technique actually does not produces the right results (by a wide margin in the opposite direction for some samples.)
a. Select one of the eyes that is closer to the camera (same as the current technique)
b. Pick four points around the each eye
leftEyePoints  = [33,  133, 159, 145];  //left, right, up, down, (we can replace 159, 145 with 27 and 23)
rightEyePoints = [362, 263, 374, 386];   //left, right, up, down, (we can replace 374, 386 with 257 and 253 )
compute the x and y coordinates of the centers of the eye by taking the averages of x and y coordinates of these four sets of points.
c. With the x, y, z coordinates of these four points build a linear system of equations as  f = Ac, and solve for c (the center of the eyeball and the radius of the eyeball). The procedure is explained in  (https://jekel.me/2015/Least-Squares-Sphere-Fit/)
d. Use the  opencv linear solver or something similar to solve for c cv::solve(A, f, c, cv::DECOMP_SVD);
e. With x, y, z coordinates of center of the eyeball, the radius of the center of the eyeball, and x, y coordinates of c enter of the eye, compute the z component of the center of the eye. Change coordinates so that everything is with reference with the eyeball center (simple subtraction).
repeat the same procedure for iris. Note that for iris we might have to choose an offset. The offset I have chosen is (-5.0f, -10.0f) for the left eye, and (5.0f, -10.0f) for the right eye.
Note that we do sqrt to compute the z component of eye and iris center, we need to choose a right sign. For  leftEyeCenter.z and  leftIrisCenter.z, the sign is +ve and for the right eye righEyeCenter.z and  rightrisCenter.z the sign is -ve.
f. convert from x, y, z for the eye center and the iris center to polar coordinate using the equation
leftEyeCenterHor  = atan2(leftEyeCenter.x,  - leftEyeCenter.z);
leftIrisCenterVer = asin(leftIrisCenter.y / leftEyeSphereRadious);
Finally
verAngle =  leftEyeCenterVer  - leftIrisCenterVer;
horAngle =  leftIrisCenterHor - leftEyeCenterHor;
That is all!

Big shot, it's too powerful.

can you provide actual examples - image and results before/after?

d. Use the opencv linear solver or something similar to solve for c cv::solve(A, f, c, cv::DECOMP_SVD);

"or something similar" - to make human portable, whatever is used must be a pure js solution.
do you know of any such solution?

I also really want to participate, but I don't have the ability and knowledge to participate in such projects, it's really uncomfortable.😶

closing as no information provided by author for the past 3 months.


NCCL support

We need to add NCCL support as backend/implementation of Communicator abstraction, which will provide all required functionality for synchronous distributed SameDiff training

is this functionality available in dl4j at this time?

Nope.


added command to update departments

Pre-Flight checklist

[x] Testing

[x] Changes have been manually tested

What are the relevant tickets?
Closes #1247
What's this PR do?
Adds a management command to update departments for courses having prefix  21w and CMS
How should this be manually tested?

Run the management command
Verify the courses with name and shortcode prefix "21w" and "cms" departments contains "CMS-W"

Codecov Report

Merging #1256 (23ec90b) into master (4162f9b) will not change coverage.
The diff coverage is n/a.

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  Coverage   89.50%   89.50%
=======================================
  Files         219      219
  Lines        9153     9153
  Branches     1704     1704
=======================================
  Hits         8192     8192
  Misses        849      849
  Partials      112      112

Continue to review full report at Codecov.

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@mbertrand I have updated the code but I do have a question, department_numbers written in the metadata for sitemetadata websitecontent and not metadata for the website

WebsiteContent of type sitemetadata is the correct place, the Website.metadata field was just used initially for importing old ocw courses


How to use this tool ?

I want to get shell or meterpreter access

Maybe we can try to upload a payload and execute it~

Maybe we can try to upload a payload and execute it~

Yes, of course, you can execute after uploading the file

I want to get shell or meterpreter access

You can read the readme file


[Issue] Azure Functions deployment does not work well in the case of a monorepo

[x] Make sure you've installed the latest version using instructions in the wiki

Output from azd version
azd version 1.8.0 (commit 8246323c2472148288be4b3cbc3c424bd046b985)
Describe the bug
When working on JS monorepo, using NPM workspaces for example it's common to have tool dependencies installed at the root level, so you have a single version of each of the packages inside the repo.
In such repos, the lockfile is also located at the root of the project, with dependencies version for all packages.
When deploying an Azure Functions project that's configured as a sub-package inside the repo, the root dependencies are omitted and the lockfile is not used at all, causing potential security and behavior issues.
To Reproduce
You can use this sample repo as an example for this behavior: https://github.com/Azure-Samples/serverless-chat-langchainjs/tree/main/packages/api

The typescript package is installed at the root, but we had to duplicate it in the packages/api/package.json file otherwise the Azure Functions API would not deploy.

The package-lock.json file. is located at the root, but when deploying the Azure Functions API it's not used, so we don't control the versions.

Expected behavior
AZD should support NPM workspaces when deploying Azure Functions deployment.
Compatibility with NPM workspaces should be supported, especially as application monorepos are used a lot with projects using AZD.
Potential solutions
From what I understand, the app source code is zipped and built remotely using Oryx.
Based on that assumption, here are a few ideas to solve this issue:

Add an option use_npm_workspace: true in Functions deployment options. This flag would include the root package*.json files and the functions project files respecting their initial structure (keep it inside their subfolders) in the zip file sent to Oryx.

Add an option include_dependencies: true in Functions deployment options. This flag would copy the the root package*.json files and the functions project files respecting their initial structure (keep it inside their subfolders) into a temporary folder, run npm install or npm ci from there, build the app and zip the resulting package and zip the result including the node_modules/ folders.

Both these solutions have a flaw though: it's the root package.json file that will be used to start the function app, so it has to contain the file paths and script for it. If you have multiple Functions project, that would not work, unless maybe it's possible to use a custom startup script like in App Service, that AZD would generate.
As an example on how we currently handle such cases when using containers, here's a Dockerfile when you can see the build process inside such a monorepo: https://github.com/Azure-Samples/azure-openai-rag-workshop/blob/main/src/backend-node-qdrant/Dockerfile
Environment
Information on your environment:
* Language name and version: JavaScript/TypeScript
* IDE and version : VS Code

We ran into this again, and this caused a tricky deployment error.
You can reproduce it from this commit here: https://github.com/Azure-Samples/serverless-chat-langchainjs/tree/a1403aa5785985468c6d28b8549adc59f7a3a53e
If you clone the repo from this commit and run npm install, you can build the function app with no error as it respects the lockfile.
However, if you try to deploy it if will report a successful deployment (see https://github.com/Azure/azure-dev/issues/3698) though nothing gets deployed: because the root lockfile of the workspace wasn't included in the zip file, the remote build doesn't work because a type changed in an updated dependency.
This an important feature for JS users, as monorepo are common for enterprise projects, and we use it for all our JS code samples.


Minister does not spawn in raids

Mod Loader
1.20.1　1.44
Mod version
2.5.1.５
Issue description
I gathered enough soul energy to challenge the raid, but the minister did not appear.
Link or Post Log Files
No response
Steps to reproduce
No response
Additional information
No response

They only appear during or after wave 7 of Raids on hard difficulty.

I see.


Prepare for re-enabled opcodes

Prepare for re-enabled opcodes for the May 2018 protocol upgrade - https://reviews.bitcoinabc.org/D1141
Add a flag to gate opcodes activation for the new HF - https://reviews.bitcoinabc.org/D1208
Add helper function for disabled opcodes - https://reviews.bitcoinabc.org/D1209

Fixed issue found by @dgenr8


chore: Remove accidental addition.

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.06%) to 90.538%

Totals

Change from base Build<PHONE_NUMBER>:
0.06%

Covered Lines:
3073

Relevant Lines:
3353

💛  - Coveralls


Various Elasticsearch improvements

This pull request enhances some aspects of the Elasticsearch binding:

explain embedded vs. remote mode
change test runner to JUnit
require path.home when running in embedded mode
version bump to 2.3.4

+1

The build failure here is an on-going issue unrelated to this PR so I'm going to proceed with merging. 😇


Camera roll sync: Queried photos are deleted on app re-start

I saw an instance where there was a error processing some camera roll photos. They never completed the process of being added to the Textile node. They should continue to exist in a pending or error state for retry. Later on, after the app was re-started, the image files that were included in the camera roll query results no longer existed on the filesystem. I'm guessing they are being written to a tmp location. We'll need to move them to a permanent location (permanent until we explicitly delete them), either in the camer roll library or in the Photos app.

Ok I looked into this more and yes, the image files we get in iOS (both for camera roll sync and for photo sharing) are written in a temporary location that is cleared out whenever the app restarts. On Android, we get paths to the original files.
This has the effect of creating the bug in iOS originally described in this issue and also caused us to add that canDelete property to our image query results and subsequent handling during cleanup.
I think a nice update that will fix the bug about temporary files disappearing and allow us to get rid of canDelete handling, is to always copy files queried from the phone's camera roll to our own directory. The files won't be deleted until we want to delete them and we know we always need to delete the files when we're done with them.


⚠ GitHub has degraded performance

In c757d3b, GitHub (https://www.githubstatus.com/api/v2/status.json) experienced degraded performance:

HTTP code: 200
Response time: 363 ms

Resolved: GitHub performance has improved in 87b25b3.


node-gyp error.

when i tried to install canvas package
node-gyp errors
`PS C:\Users\siyah\Desktop\Botlar\TakoBot> npm install canvas

<EMAIL_ADDRESS>install C:\Users\siyah\Desktop\Botlar\TakoBot\node_modules\canvas
node-gyp rebuild

C:\Users\siyah\Desktop\Botlar\TakoBot\node_modules\canvas>if not defined npm_config_node_gyp (node "C:\Users\siyah\AppData\Roaming\npm\node_modules\npm\node_modules\npm-lifecycle\node-gyp-bin\....\node_modules\node-gyp\bin\node-gyp.js" rebuild )  else (node "C:\Users\siyah\AppData\Roaming\npm\node_modules\npm\node_modules\node-gyp\bin\node-gyp.js" rebuild )
Terminate batch job (Y/N)? N
PS C:\Users\siyah\Desktop\Botlar\TakoBot> npm i canvas

<EMAIL_ADDRESS>install C:\Users\siyah\Desktop\Botlar\TakoBot\node_modules\canvas
node-gyp rebuild

C:\Users\siyah\Desktop\Botlar\TakoBot\node_modules\canvas>if not defined npm_config_node_gyp (node "C:\Users\siyah\AppData\Roaming\npm\node_modules\npm\node_modules\npm-lifecycle\node-gyp-bin\....\node_modules\node-gyp\bin\node-gyp.js" rebuild )  else (node "C:\Users\siyah\AppData\Roaming\npm\node_modules\npm\node_modules\node-gyp\bin\node-gyp.js" rebuild )
Warning: Missing input files:
C:\GTK\bin\libexpat-1.dll
C:\GTK\bin\libpng14-14.dll
gyp ERR! UNCAUGHT EXCEPTION
gyp ERR! stack Error: spawn C:\Program Files (x86)\Microsoft Visual Studio\2017\Professional\MSBuild\15.0\Bin\MSBuild.exe ENOENT
gyp ERR! stack     at Process.ChildProcess._handle.onexit (internal/child_process.js:229:19)
gyp ERR! stack     at onErrorNT (internal/child_process.js:406:16)
gyp ERR! stack     at process._tickCallback (internal/process/next_tick.js:63:19)
gyp ERR! System Windows_NT 10.0.17134
gyp ERR! command "C:\Program Files\nodejs\node.exe" "C:\Users\siyah\AppData\Roaming\npm\node_modules\npm\node_modules\node-gyp\bin\node-gyp.js" "rebuild"
gyp ERR! cwd C:\Users\siyah\Desktop\Botlar\TakoBot\node_modules\canvas
gyp ERR! node -v v10.3.0
gyp ERR! node-gyp -v v3.6.2
gyp ERR! This is a bug in node-gyp.
gyp ERR! Try to update node-gyp and file an Issue if it does not help:
gyp ERR!     https://github.com/nodejs/node-gyp/issues
npm WARN<EMAIL_ADDRESS>requires a peer of<EMAIL_ADDRESS>but none is installed. You must install peer dependencies yourself.
npm WARN<EMAIL_ADDRESS>requires a peer of<EMAIL_ADDRESS>but none is installed. You must install peer dependencies yourself.
npm WARN<EMAIL_ADDRESS>requires a peer of erlpack@discordapp/erlpack but none is installed. You must install peer dependencies yourself.
npm WARN<EMAIL_ADDRESS>requires a peer of<EMAIL_ADDRESS>but none is installed. You must install peer dependencies yourself.
npm WARN<EMAIL_ADDRESS>requires a peer of<EMAIL_ADDRESS>but none is installed. You must install peer dependencies yourself.
npm WARN<EMAIL_ADDRESS>requires a peer of<EMAIL_ADDRESS>but none is installed. You must install peer dependencies yourself.
npm WARN<EMAIL_ADDRESS>requires a peer of<EMAIL_ADDRESS>but none is installed. You must install peer dependencies yourself.
npm WARN<EMAIL_ADDRESS>requires a peer of<EMAIL_ADDRESS>but none is installed. You must install peer dependencies yourself.
npm WARN<EMAIL_ADDRESS>requires a peer of<EMAIL_ADDRESS>but none is installed. You must install peer dependencies yourself.
npm WARN<EMAIL_ADDRESS>No description
npm WARN<EMAIL_ADDRESS>No repository field.
npm ERR! code ELIFECYCLE
npm ERR! errno 7
npm ERR<EMAIL_ADDRESS>install: node-gyp rebuild
npm ERR! Exit status 7
npm ERR!
npm ERR! Failed at the<EMAIL_ADDRESS>install script.
npm ERR! This is probably not a problem with npm. There is likely additional logging output above.
npm ERR!      C:\Users\siyah\AppData\Roaming\npm-cache_logs\2018-05-31T16_06_13_893Z-debug.log`

Please report that over at node-canvas, the "missing input files" thing is not a node-gyp issue.


Auto-formatting TSX removes signifigant whitespace

When VSCode formats a TSX document it can remove significant white-space, altering the output of the program.
VSCode Version:

Version: 1.6.0
Commit: e52fb0bc87e6f5c8f144e172639891d8d8c9aa55
Date: 2016-10-10T18:37:40.189Z
Shell: 1.3.7
Renderer: 52.0.2743.82
Node: 6.5.0

OS Version

OS Name: Microsoft Windows 10 Pro
Version: 10.0.14393 Build 14393

Example code
File: https://gist.github.com/marcomorain/9b84f35ada35e0eceb030ff27fba2e1f
import * as React from 'react'

var restaurantName = 'My Restaurant'
var closedAlert: JSX.Element = (
  <h4>{restaurantName} is Closed</h4>
)

Steps to Reproduce:

Open a .tsx file in vscode with some significant whitespace in a JSX element.
Format the document (via command palette or format on save).

Expected:
The space between } and is Closed is preserved, ultimately producing the string My Restaurant is Closed
Actual
The space between } and is Closed is removed, ultimately producing the string My Restaurantis Closed

@marcomorain thank you for opening this issue and for the clear bug report. I have confirmed this with the latest bits. Moving to the language service repo.

This issue was moved to Microsoft/TypeScript#11619

Thanks Wes.

Auto-correct fail.
Thanks Wade!


Various SPfx webparts styling incorrect - grid not working - borders around webparts

Category

[x] Bug

Describe the bug
Various spfx webparts have begun to show styling errors. one webpart no longer adhering to ms-grid. Other web parts are showing extra borders around them where they didn't previously.
Steps to reproduce
Modern Webpage loads with webparts.
Webparts are not adhering to style
Expected behavior
Webpart styling should not be changed. No changes have been made to source code.
Environment details (development & target environment)

Windows 10

Sharepoint Online

Node JS v 8

Chrome v88.0.4324.190 , Edge v88.0.705.74 , IE v1909

Tooling: SPfx v1.4

Additional details: The more context you can provide, the easier it is (and therefore quicker) to help.

Additional context
Possible relate to or recurrence of https://github.com/SharePoint/sp-dev-docs/issues/5763

We are seeing this issue as well.

Bump. Same on a couple of our tenants. Having to apply "display: flex" on some elements to temporarily fix them.

Yup this is occurring in multiple tenants. We have solutions built on 1.6 experiencing this.
ms-SPLegacyFabricBlock is no longer being loaded it appears.

Bump. Happening on SPFx 1.7.1 also

We are absolutely tracking this internally. If anyone has premier support option, please do report using that channel as well as helps on increasing internal awareness.

@VesaJuvonen any updates? because I'm seeing the correct DOM structure now.

@VesaJuvonen any updates? because I'm seeing the correct DOM structure now. It looks like they added the ms-SPLegacyFabricBlock class to the sp-feature-tag div.

@DonKirkham  - i reverted my code in my dev environment and it all seemed back to normal.

@rmba74 Thanks Ray. I saw the same thing late yesterday and a Microsoft SP engineer confirmed that the bug fix was being rolled out. I fixed it earlier in our webpart that was having issues. It only took 2 minutes, but several hours later I realize the original dev didn't check in his latest changes amd I was "fixing" code that was out of date. (facepalm) By the time I had access to the correct code, Microsoft had rolled out the fix to me tenant. #wastedday

@andrewconnell @VesaJuvonen  I don't know who closes these, but it can probably be closed now.

Closing as based on the comments here, situation was sorted out. We should be good, which is great.


Stability Issue

the Quilt mod loader is current in beta and it is an unwise choice to force this as a default upon users. I recommend switching to Forge or Fabric until Quilt advances further in the future.

force this as a default

This is an example pack, not a template, as detailed in the README. This isn't being forced upon anyone.


Idea: detect next SemVer automatically by categories

Context
I'm now well accustomed to categorizing PRs into Features, Bugfixes or documentation when authoring them. For example:
PRs labelled as "bugfix" or "dependency" always get a Patch release version increment (e.g. v1.2.3 to v1.2.4).
PRs labelled as "feature" always get a Minor release version increment (e.g. v1.2.3 to v1.3.0).
PRs labelled as "breaking" get a Major release version increment (v1.2.3 to v2.0.0).
Problem
After merging a bunch of them, when creating a new release, I have to manually go over the merged PRs to figure out the next version according to SemVer and make an accordingly git tag. The category with the "highest increment policy" wins if even 1 PR is in there. For example, there could be 100 bugfixes since the last release version and it would be just a new Patch release, but if even 1 feature PR is in the list, then SemVer dictates a Minor release.
Solution idea
What if this action can actually figure out the next release version by itself? All the information is there.

Each category gets an additional property in the configuration, I call it "incrementPolicy", which takes values as "patch", "minor", "major" (maybe "prerelease" but let's keep simple for this discussion)
If toTag is empty (or some other property saying "figure it out by PR labels"), then the action determines the next release version after categorizing the PRs.
Save the next version increment in the action output, so it can be used later on in the GH workflow. For example, a subsequent step would make a git tag and push it, and then others would continue with building & releasing artifacts, docker images etc. Such a workflow would then rather be triggered by on: workflow_dispatch, e.g. through GitHub browser or through other means than pushing a git tag.

Alternative
I have started to create my own action (https://github.com/ccremer/auto-detect-semver-action/tree/initial) inspired by yours, even sharing the same configuration.json with the added increment policy. But when I realized I could almost use the same code (get the PRs, categorize them, etc) as this action, I started to import that in the package.json.
Eventually I thought to discuss it here, whether it would make sense to add this functionality to this action. Technically this would avoid fetching and categorizing PRs twice in the same workflow. I would be willing to fork and contribute such a feature if you'd accept it.
Footnotes

I'm aware this action also supports categorization by commits, I guess all the problem description applies here as well.
We should also somehow support prereleases, e.g. if incrementPrelease is true then the action would, if fromTag contains a prerelease like v1.2.0-rc1, increment to v1.2.0-rc2
In case there is no initial version, choose 0.1.0.

Good day @ccremer
Thank you very much for the very detailed description on this proposal.
You are absolutely right that the action practically already has all the information to make such a decisions.

Right now the action was kept very specifically on the task of creating changelogs, excluding functionality like creating a release for example. These decisions were made to keep the action easier maintainable and there are already a ton of great actions out there doing these things.
Looking briefly into your source it looks that most of it seems to be handled by the SemVer plugin, but I am not sure how well that will hold up for more complex situations like pre-releases as you described?

So I was thinking on alternative ideas, but they also have downsides. For example this action could return the categories it collected and a step afterwards could parse this information to detect the next release version.
The major downside is that the TO_TAG placeholder would not be replaceable by the action itself.
This could allow to create the action deciding on the next version very precisely for that usecase (so it could even be used beyond that in other usecases) - while still keeping the changelog-builder focused on building the changelog.

Hi.
I agree that releasing things should be out of scope of this action.
Determine the next semver is maybe not directly involved in this, but borderline already.
The alternative idea to put the categories into the output sounds okay to me. Technically, at least for the figuring out the next SemVer, it should be sufficient to have only a count of PRs for each category, But maybe it's better to put more meta information into it.
It probably makes sense to output this as JSON.

The major downside is that the TO_TAG placeholder would not be replaceable by the action itself.

Hm, yes. Not sure about dealing with that.
A very wild idea would be to introduce an optional 2-step process of changelog building:

First, fetch the PRs and categorize them, put them into the output.
Then, another step in the workflow would figure out the tag.
Invoke changelog builder again, with the output from first step as the input for the 2nd invocation to actually build the changelog (so the 2nd invocation doesn't need to fetch PRs again).
But maybe this is as broken as it sounds :see_no_evil:

It's probably enough to put a special placeholder into the TO_TAG placeholder, so it can be replaced in the changelog by another step (sed or similar) before actually using the changelog in a releasing step.

@ccremer having this orchestration acts like an add-on, which I think is from a maintenance perspective I believe the cleanest solution.
It would actually be interesting to invoke an action as part of an action, like plugins but I fear that this would be too risky from a security perspective and very hard to control.

Returning as a json sounds more clever than "just" a comma separated list of which categories have been found.
There may be some limitations on the data to be returned by an action but I think we are not yet at this limitation.
For the placeholder, I think it's possibly edge-case enough whereas a sed or other string replacement should handle it. executing the changelog builder multiple times is not really advised as you may run into API quota limitations, also it just costs time :D

Yes I agree with the add-on bit.
But a plugin system is surely also quite a bit to maintain and probably should also be out of scope of this action.

There may be some limitations on the data to be returned by an action but I think we are not yet at this limitation.

I think we don't need to put in PRs with the full metadata, maybe just selected properties like ID, PR number. Maybe labels and author, but that's about it. It's enough so that a follow-up action /add-on can invoke the API again if needed. For figuring out the next semver as an add-on though, they're not required.
If we consider the next-semver-detecting as an add-on as "agreed upon", how should we continue here?
The add-on would somewhat depend on the changelog-builder since the JSON output is its input.
Is this something that you'd be willing to maintain in your GH space on your own, or should I start with an initial implementation and transfer/sponsor the action to you? Or should I completely maintain this under my name? Other ideas?
(I might not be as fast as I'd like, since I'm still just learning TypeScript atm.)

We are kind of doing this already with the help of couple simple actions:
`

name: Determine the release type
id: release-type
uses<EMAIL_ADDRESS>with:
cond: ${{ contains(steps.release-notes.outputs.changelog, '## 🚀 Features') }}
if_true: minor
if_false: patch

name: Generate the release version
id: release-version
uses<EMAIL_ADDRESS>with:
level: ${{ steps.release-type.outputs.value }}
current_version: ${{ steps.current-version.outputs.value }}
`

I believe with: https://github.com/mikepenz/release-changelog-builder-action/pull/1132 landing, we can close this as complete?

Available in v4 (v4.0.0-b01)


Adapt pipeline examples and scheduler's to huggingface diffusers interface

This PR aims at generalizing the three pipeline examples to make them work with the schedulers that need to scale the denoising model input depending on the current timestep and that have a initial noise standard deviation that depends on the timesteps.
This is done making all of them implementing the following methods

init_noise_sigma
scale_model_input

The pipeline examples are modified as follows:

the initial latents are rescaled by the scheduler's init_noise_sigma
the latents are first passed to the scheduler's scale_model_input method before being fed to the unet forward pass.

Looks good both for the scheduler itself and for the enhanced api, thanks!


Remove labels from name/URL in lockfile JSON

[Hopefully] addresses https://github.com/chainguard-dev/apko/issues/1052.
Seems like a fairly straightforward fix -- this PR removes the @label portion of the URI string so that the lock file doesn't causes the errors noted in the aforementioned issue.
Comparison:
Before:
{
    "version": "v1",
    "config": {
      "name": "examples/label.yaml",
      "checksum": "sha256-MlNjWrkMHwpre/9kkrDCXU2+y/pzyD4DMZgdc97ymk4="
    },
    "contents": {
      "keyring": [
        {
          "name": "packages.wolfi.dev/os/wolfi-signing.rsa.pub",
          "url": "https://packages.wolfi.dev/os/wolfi-signing.rsa.pub"
        }
      ],
      "repositories": [
        {
          "name": "@wolfi https://packages.wolfi.dev/os/x86_64",
          "url": "@wolfi https://packages.wolfi.dev/os/x86_64/APKINDEX.tar.gz",
          "architecture": "x86_64"
        },
        {
          "name": "@wolfi https://packages.wolfi.dev/os/aarch64",
          "url": "@wolfi https://packages.wolfi.dev/os/aarch64/APKINDEX.tar.gz",
          "architecture": "aarch64"
        }
      ],
      "packages": []
    }
  }

After:
{
  "version": "v1",
  "config": {
    "name": "examples/label.yaml",
    "checksum": "sha256-MlNjWrkMHwpre/9kkrDCXU2+y/pzyD4DMZgdc97ymk4="
  },
  "contents": {
    "keyring": [
      {
        "name": "packages.wolfi.dev/os/wolfi-signing.rsa.pub",
        "url": "https://packages.wolfi.dev/os/wolfi-signing.rsa.pub"
      }
    ],
    "repositories": [
      {
        "name": "https://packages.wolfi.dev/os/x86_64",
        "url": "https://packages.wolfi.dev/os/x86_64/APKINDEX.tar.gz",
        "architecture": "x86_64"
      },
      {
        "name": "https://packages.wolfi.dev/os/aarch64",
        "url": "https://packages.wolfi.dev/os/aarch64/APKINDEX.tar.gz",
        "architecture": "aarch64"
      }
    ],
    "packages": []
  }
}

make test and make lint pass with these changes.

@jonjohnsonjr -- mind giving this a review when you get the chance? Thanks!


If vcsSidecar is not set in project, no default sidecar is set.

I think this is a regression...
In 0.16, no vcsSidecar is set by default. The expectation was that the server would use the default. However, the controller does not apply a default. Instead, it skips the VCS mount.
The correct behavior is for brig project create to apply a default value of deis/git-sidecar:latest. (That is, the controller rightly allows an empty sidecar)

This was closed by #591


Fix #147: Added custom logo for the website

Description

I have added a custom logo to match with the website's UI. @itsmohit097 please review it and merge it with main.
Related Issues*

Fixes #147

Screenshots! (Optional)
Before changes:

After changes:

Checklist
Replace "[ ]" with "[x]" to mark them as completed.

[X] I have forked the repo and pushed the changes according to contribution guidelines.
[X] I have tested these changes locally.
[X] I have tried to maintain the consistency of the code.
[X] I have tested these changes locally.
[x] I have updated the documentation accordingly.

@itsmohit097 please review it and merge it to main.


Private field "#et" must be declared in an enclosing class

fuels-ts SDK Version
<EMAIL_ADDRESS>Toolchain Versions
Don't have this
Node.js Version
v20.12.2 but also observed with other nodejs versions
Browser
Chrome but also observed with others
Operating System
macOs
Describe the Problem
The enum coder class in @fuel-ts/abi-coder is incorrectly being transpiled during next build. Even if NODE_ENV is set to development, it still produces the error.
Running next dev works.
The private method decodeNativeEnum somehow is not accessible leading to syntax errors in the produced js code.
Not sure at all why this is happening.
Code Snippet
No response
Contract ABI
No response
Errors
Private field "#et" must be declared in an enclosing class

-> where #et is the minified version of #decodeNativeEnum

Hey @fl0ydj 👋
Thanks for reporting this issue. I've just tried to replicate this my side and everything seems to work correctly. Could you provide us  with a repository or Gist with a reproduction of this error please?


consider decoupling GetIdentityServerUser APIs from cookie middleware

and design an interface for it instead

Should wait for preview-2 or beyond.

Might also involve reworking session id and/or client session list features.


Paste doesn't work

VSCode Version: 1.12.1
OS Version: macOS Sierra 10.12.4

Paste doesn't work.
Check the video here

Seems to be related to issue #13366?
Does Command + V work for you?

@Kas1894 Looks like it happens randomly. I think it's duplicate with https://github.com/Microsoft/vscode/issues/24112.


datree: 1.8.1 -> 1.8.8

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://repology.org/metapackage/datree/versions.
meta.description for datree is: "CLI tool to ensure K8s manifests and Helm charts follow best practices"
meta.homepage for datree is: "https://datree.io/"
meta.changelog for datree is: ""
Updates performed

Version update

To inspect upstream changes

Release on GitHub

Compare changes on GitHub

Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
found 1.8.8 with grep in /nix/store/sr010y63dhng78937kv29a97cqqj46qv-datree-1.8.8
found 1.8.8 in filename of file in /nix/store/sr010y63dhng78937kv29a97cqqj46qv-datree-1.8.8

Rebuild report (if merged into master) (click to expand)

1 total rebuild path(s)

1 package rebuild(s)

First fifty rebuilds by attrpath
datree

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/sr010y63dhng78937kv29a97cqqj46qv-datree-1.8.8 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A datree https://github.com/r-ryantm/nixpkgs/archive/2d811a3709aef8b3aca8a75627685099484d6d39.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/sr010y63dhng78937kv29a97cqqj46qv-datree-1.8.8
ls -la /nix/store/sr010y63dhng78937kv29a97cqqj46qv-datree-1.8.8/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review run on x86_64-linux 1

1 package built:

datree

Maintainer pings
cc @azahi @jceb for testing.

Result of nixpkgs-review pr 204065 run on x86_64-linux 1

1 package built:

datree


PnP Script Sample: Get inactive sites based on days and export it to CSV.

This sample demonstrates the process of exporting sites that have been inactive for a specified number of days (in this script, we've set it to the last 30 days) to a CSV file. The exported report encompasses all columns, such as URL, Title, Template, and more.

Hey @chandaniprajapati, really nice sample, thank you and highly appreciated of your submissions, this should be live shortly 😍✨🎉


Clarification in license file is needed

Main license  file should probably warn that it doesn't cover whole project and some parts are now proprietary.

I believe it's planned to be MIT again once 11.0 is out.

Whether it is temporary or not the main licensing should certainly be clarified since even on NuGet the license is just MIT and even I noticed that hidden proprietary code accidentally only after spending considerable time on doing research on the source.
Especially since this part of the proprietary license could be interpreted as "Only official Avalonia binary packages"

This code may be used free of charge by any application that consumes Avalonia binary packages as a direct or indirect dependency.

which certainly limits my usage for example if I have to build my own version of Avalonia.Base which could be or could be not against the terms.

You can build your own version as long as the code lives in Avalonia.Something.dll

I believe it's planned to be MIT again once 11.0 is out.

Is making this code MIT again still planed for 11.0?

With #11992 the proprietary license was withdrawn and Avalonia is entirely MIT.


New error unknown light model

I just installed the latest version .02.4. I was running .02.2.
Now i get this error:
[2/18/2017, 3:42:05 PM] [Philips Hue 1] Kitchen Top RGB: warning: dresden elektronik: unknown FLS-PP3 light model
[2/18/2017, 3:42:05 PM] [Philips Hue 1] Kitchen Bottom RGB: warning: dresden elektronik: unknown FLS-PP3 light model
[2/18/2017, 3:42:05 PM] [Philips Hue 1] Philips hue: 15 accessories
[2/18/2017, 3:42:05 PM] [Philips Hue 1] Initializing platform accessory 'Philips hue'...
[2/18/2017, 3:42:05 PM] [Philips Hue 1] Philips hue: 2 services
[2/18/2017, 3:42:05 PM] [Philips Hue 1] Initializing platform accessory 'Kitchen Top RGB'...
[2/18/2017, 3:42:05 PM] [Philips Hue 1] Initializing platform accessory 'Kitchen Top White LED'...
[2/18/2017, 3:42:05 PM] [Philips Hue 1] Cannot add a bridged Accessory with the same UUID as another bridged Accessory: f6267034-4a18-40db-b89f-8ae52b2338a5
Any idea why it's happening? never got this error before.

I have two runs of LED's that connect to the Hue bridge via this device: dresden elektronik FLS-PP
They are RGBW LED's. I run then in a configuration where the White LED's on each strip are controlled independently from the RGB Led's on each strip. So each of my led runs actually shows up as two lights each for a total of 4 lights that i can control.
My setup with these lights used to work perfectly on 0.2.2.

My bad.  I'll see if I can put out a new version with a fix later today.
Yes, it is related to the way the way the wireless ballasts appear on the Hue bridge, see issue #14.

@pponce v0.2.5 should support the wireless ballasts like before.

thanks!
I just installed 0.3.0
I am seeing this error "[2/19/2017, 7:47:32 AM] [Philips Hue 1] Cannot read property 'push' of undefined".
But also only one of the 4 "lights" appear now.
When loading homebridge It pauses for a few seconds at
"[2/19/2017, 7:55:13 AM] [Philips Hue 1] Initializing platform accessory 'Kitchen Top RGB'...
then continues without loading the other three lights.

Thanks for testing, @pponce.
You're seeing only /lights/8 "Kitchen Top RGB", because homebridge-hue sort of crashes while configuring /lights/9 "Kitchen Top White LED".  It recovers from the crash, but the other lights are never processed.  I expect the Daylight and Hue dimmer switches are also missing?
Could you please see of v0.3.1. fixes this issue?  Thanks.

just updated to 0.3.1:
Here's the message i'm getting
[2/19/2017, 1:26:08 PM] [Philips Hue 1] Initializing platform accessory 'Kitchen Top RGB'...
[2/19/2017, 1:26:08 PM] [Philips Hue 1] Cannot add a Service with the same UUID '00000043-0000-1000-8000-0026BB765291' as another Service in this Accessory without also defining a unique 'subtype' property.

Just tried out 0.3.2....
Happened to just catch the commit.
No errors. things look good!

Ah, that's good to hear.  However, v0.3.2 causes HomeKit to lose the room, group, scene, and rule assignments of all lights.  I've deprecated that version in favour of v0.3.3.

v0.3.3 Works for me as well.


How tf.contrib.seq2seq.AttentionWrapper . working ?

I am trying to understand tf.contrib.seq2seq.AttentionWrapper  working , I have created simple program to understand the working of AttentionWrapper :
num_units=32

batch_size = 12
max_time = 10
num_dim = 11

input_data = np.random.randn(batch_size,max_time,num_dim).astype(np.float32)

# atch_size = np.random.randn(batch_size,num_dim).astype(np.float32)

sequence_length =[len(i) for i in input_data]

lstm_cell = tf.contrib.rnn.LSTMCell(num_units=num_units)

output,last_state = tf.nn.dynamic_rnn(lstm_cell,input_data,sequence_length=sequence_length,dtype=tf.float32)

print(output,last_state)

#now let's use attention

#rnn_no_units , encoder output , sequence_length , dtype , name

attention_Bahdanau = tf.contrib.seq2seq.BahdanauAttention(num_units=num_units,memory=output,memory_sequence_length=sequence_length,dtype=tf.float32,name='BahdanauAttention')

batch_size = attention_Bahdanau.batch_size
memory_layer = attention_Bahdanau.memory_layer
keys=attention_Bahdanau.keys
values=attention_Bahdanau.values
alignment_size= attention_Bahdanau.alignments_size
state_size = attention_Bahdanau.state_size

query_ = tf.get_variable(name='query_dta_1',
                         shape=[batch_size,num_units],
                         dtype=tf.float32,initializer=tf.random_uniform_initializer(-0.01,0.01))

state_ = tf.get_variable(name='state__dta_l',
                         shape=[batch_size,alignment_size],
                         dtype=tf.float32,initializer=tf.random_uniform_initializer(-0.01,0.01))

initial_alignments = attention_Bahdanau.initial_alignments(batch_size,dtype=tf.float32)

initial_state   =    attention_Bahdanau.initial_state(batch_size,dtype=tf.float32)

fg=attention_Bahdanau.__call__(query_,state_)

#(12, 10)
#(12, 10)

#lstm_cell , attention_mech , rnn_num_units

attention_wrapper = tf.contrib.seq2seq.AttentionWrapper(lstm_cell,attention_Bahdanau,num_units)

zero_s= attention_wrapper.zero_state(batch_size=batch_size,dtype=tf.float32)
print(zero_s)

print(attention_wrapper.__call__(query_,zero_s))

Then i am getting this error:
AttentionWrapperState(cell_state=LSTMStateTuple(c=<tf.Tensor 'AttentionWrapperZeroState/checked_cell_state:0' shape=(12, 32) dtype=float32>, h=<tf.Tensor 'AttentionWrapperZeroState/checked_cell_state_1:0' shape=(12, 32) dtype=float32>), attention=<tf.Tensor 'AttentionWrapperZeroState/zeros_2:0' shape=(12, 32) dtype=float32>, time=<tf.Tensor 'AttentionWrapperZeroState/zeros_1:0' shape=() dtype=int32>, alignments=<tf.Tensor 'AttentionWrapperZeroState/zeros:0' shape=(12, 10) dtype=float32>, alignment_history=(), attention_state=<tf.Tensor 'AttentionWrapperZeroState/zeros_3:0' shape=(12, 10) dtype=float32>)
---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
   1588   try:
-> 1589     c_op = c_api.TF_FinishOperation(op_desc)
   1590   except errors.InvalidArgumentError as e:

InvalidArgumentError: Dimensions must be equal, but are 96 and 43 for 'rnn/while/lstm_cell/MatMul_1' (op: 'MatMul') with input shapes: [12,96], [43,128].

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-80-0926d476036c> in <module>()
      5 print(zero_s)
      6
----> 7 print(attention_wrapper.__call__(query_,zero_s))

/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/rnn_cell_impl.py in __call__(self, inputs, state, scope)
    230         setattr(self, scope_attrname, scope)
    231       with scope:
--> 232         return super(RNNCell, self).__call__(inputs, state)
    233
    234   def _rnn_get_variable(self, getter, *args, **kwargs):

/usr/local/lib/python3.6/dist-packages/tensorflow/python/layers/base.py in __call__(self, inputs, *args, **kwargs)
    327
    328       # Actually call layer
--> 329       outputs = super(Layer, self).__call__(inputs, *args, **kwargs)
    330
    331     if not context.executing_eagerly():

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, inputs, *args, **kwargs)
    701
    702       if not in_deferred_mode:
--> 703         outputs = self.call(inputs, *args, **kwargs)
    704         if outputs is None:
    705           raise ValueError('A layer\'s `call` method should return a Tensor '

/usr/local/lib/python3.6/dist-packages/tensorflow/contrib/seq2seq/python/ops/attention_wrapper.py in call(self, inputs, state)
   1410     cell_inputs = self._cell_input_fn(inputs, state.attention)
   1411     cell_state = state.cell_state
-> 1412     cell_output, next_cell_state = self._cell(cell_inputs, cell_state)
   1413
   1414     cell_batch_size = (

/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/rnn_cell_impl.py in __call__(self, inputs, state, scope, *args, **kwargs)
    337     # method.  See the class docstring for more details.
    338     return base_layer.Layer.__call__(self, inputs, state, scope=scope,
--> 339                                      *args, **kwargs)
    340
    341

/usr/local/lib/python3.6/dist-packages/tensorflow/python/layers/base.py in __call__(self, inputs, *args, **kwargs)
    327
    328       # Actually call layer
--> 329       outputs = super(Layer, self).__call__(inputs, *args, **kwargs)
    330
    331     if not context.executing_eagerly():

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, inputs, *args, **kwargs)
    701
    702       if not in_deferred_mode:
--> 703         outputs = self.call(inputs, *args, **kwargs)
    704         if outputs is None:
    705           raise ValueError('A layer\'s `call` method should return a Tensor '

/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/rnn_cell_impl.py in call(self, inputs, state)
    855     # i = input_gate, j = new_input, f = forget_gate, o = output_gate
    856     lstm_matrix = math_ops.matmul(
--> 857         array_ops.concat([inputs, m_prev], 1), self._kernel)
    858     lstm_matrix = nn_ops.bias_add(lstm_matrix, self._bias)
    859

/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_ops.py in matmul(a, b, transpose_a, transpose_b, adjoint_a, adjoint_b, a_is_sparse, b_is_sparse, name)
   2012     else:
   2013       return gen_math_ops.mat_mul(
-> 2014           a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
   2015
   2016

/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/gen_math_ops.py in mat_mul(a, b, transpose_a, transpose_b, name)
   4277     _, _, _op = _op_def_lib._apply_op_helper(
   4278         "MatMul", a=a, b=b, transpose_a=transpose_a, transpose_b=transpose_b,
-> 4279         name=name)
   4280     _result = _op.outputs[:]
   4281     _inputs_flat = _op.inputs

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py in _apply_op_helper(self, op_type_name, name, **keywords)
    785         op = g.create_op(op_type_name, inputs, output_types, name=scope,
    786                          input_types=input_types, attrs=attr_protos,
--> 787                          op_def=op_def)
    788       return output_structure, op_def.is_stateful, op
    789

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in create_op(self, op_type, inputs, dtypes, input_types, name, attrs, op_def, compute_shapes, compute_device)
   3412           input_types=input_types,
   3413           original_op=self._default_original_op,
-> 3414           op_def=op_def)
   3415
   3416       # Note: shapes are lazily computed with the C API enabled.

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in __init__(self, node_def, g, inputs, output_types, control_inputs, input_types, original_op, op_def)
   1754           op_def, inputs, node_def.attr)
   1755       self._c_op = _create_c_op(self._graph, node_def, grouped_inputs,
-> 1756                                 control_input_ops)
   1757     else:
   1758       self._c_op = None

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
   1590   except errors.InvalidArgumentError as e:
   1591     # Convert to ValueError for backwards compatibility.
-> 1592     raise ValueError(str(e))
   1593
   1594   return c_op

ValueError: Dimensions must be equal, but are 96 and 43 for 'rnn/while/lstm_cell/MatMul_1' (op: 'MatMul') with input shapes: [12,96], [43,128].

I am not getting from where this [43,128] coming from and how to compute_attention successfully using this wrapper ?
For live experiment i have created google colab notebook , You can run and check code there :
https://colab.research.google.com/drive/1oR039KJgtpNsJFGh8VtQt-NRcAtXi4NR

After some research i found how it is working
if hyperparameters are
num_units =6 (lstm hidden_units )
batch_size = 4
max_time = 90
num_dim = 12  (input_size or embedding dim )
Now  input will be
input_size = . Batch_size x max_time x num_dim   #4x90x12
it will pass through dynamic_rnn  :
lstm_output =dynamic_rnn_function ( input_size )
which will return  [Batch_size x  max_time x rnn_dim ] and last state [Batch_size x rnn_dim ]
#4x90x6 and 4x 6
Now what attention is doing , it's creating two matrix
rnn_output is 4x6
In first matrix it is adding rnn_dim three times  so  matrix will be . [4,(6x3) ]
second matrix it is adding num_dim + num_units and then reduce_max across rnn_dim
num_dim + num_units ==>6+12 = 18
reduce_max across rnn_dim ==> (num_units x batch_size ) ==> (6x4) . ==> [18,24]
now matmul ( [4,18] , [18,24] ) . ==> [4,24]
My confusion is why it is adding rnn_dim three times every time ?

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This question is better asked on StackOverflow since it is not a bug or feature request. There is also a larger community that reads questions there.
If you think we've misinterpreted a bug, please comment again with a clear explanation, as well as all of the information requested in the issue template. Thanks!


AVRO-2069: Use primitive fields in generated getters & setters in Java code

Currently, for primitive types (such as int, long, etc) generated getters and setters return and accept java.lang.* boxed (while fields actually holds primitive values). This is inefeccient and produces code boilerplate.
The only issue with this approach that it breaks source compatibility with previously generated code.

This can be an option at generation time for those that don't want to break compatibility (defaulting to the old way prior to 1.9).

This can be an option at generation time for those that don't want to break compatibility (defaulting to the old way prior to 1.9).

Was this option ever implemented? This change causes a lot of compatibility issues when upgrading from 1.8.2. Thanks!


[Data] Update frontend to accommodate any changes from migrating to new subgraphs

Is your feature request related to a problem? Please describe.
The old polygon-bridged-carbon subgraph is outdated and we need to migrate to the new polygon-digital-carbon subgraph
The data.klimadao frontend will need to be updated to accommodate any changes, though the API should mask most, but for instance data field names may have changed.
Describe the solution you'd like
Once the pipeline and API changes are live in staging, test out the frontend against them:
https://github.com/KlimaDAO/data-pipelines/issues/38
https://github.com/KlimaDAO/dash-apps/issues/181
Describe alternatives you've considered
This is a necessary migration for ongoing maintenance of data feeds moving forward

Blocked until pipeline changes and API have been staged

Migration appears to be complete


Fixed #8 " is already defined in the registry" error on autoreload

Current coverage is 88.23%

Merging #19 into master will not affect coverage as of a828b93

@@            master     #19   diff @@
======================================
  Files            8       8
  Stmts          170     170
  Branches         0       0
  Methods          0       0
======================================
  Hit            150     150
  Partial          0       0
  Missed          20      20

Review entire Coverage Diff as of a828b93

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pull request for e2e test at 01/09/2017 14:45:11

:white_check_mark: Validation status: passed
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.


fido2-mds: Update dependencies

Fixes: https://github.com/Nitrokey/nitrokey-3-firmware/security/dependabot/9

No significant changes.

Insignifcant changes

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value

change

binary-size-nk3am
1422910
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binary-size-nk3am-test
2021274
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+0 (+0.00%)

binary-size-nk3xn
510096
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+0 (+0.00%)

binary-size-nk3xn-test
547132
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binary-size-nkpk
736119
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[Rancher2] Tracking issue to remove scale-down verbiage once issue is fixed

Completed new docs for this scale down issue.
Per @thedadams, this issue will be fixed in an upcoming release. Created this issue to track and will remove from docs at that time.

Moving milestone as referenced issue is still open.


The Hungry Variable

If wtfjs.com's syntax highlighter highlights the code correctly, could you change the triple grave accents double grave accents around the relevant blocks to not spoil the surprise, please?

merged your post! :) I have not deployed yet, but will soon, and I'll @mention you. Cheers!

No problem.
D
On Mar 23, 2015 3:48 PM, "Zemnmez"<EMAIL_ADDRESS>wrote:

No problem. Happy you're keeping the wtfjs dream alive ;)
—
Reply to this email directly or view it on GitHub
https://github.com/brianleroux/wtfjs/pull/83#issuecomment-85236630.