[WIP] Add SSD (Single Shot Multibox Detector)

I am implementing SSD (Single Shot Multibox Detector).

demo.py requires scikit-image.
result of demo:

I added test code and SSD512. I think model conversion from Caffe and training should be in examples.

@yuyu2172 To fix the APIs, could you review my codes? It is better that all detectors have same (similar) APIs.

Sure. I will be done with Faster RCNN in few days, and after that I will check your code.
The PR for FasterRCNN is extremely messy with different PRs rebased place to place.
I need to clean that up...

Just a few comments.

Following #144, I think return values should be tuple of lists.
predict  shouldn't take NMS paramters. This is because there can be Detection models that do not use NMS. These parameters should be attributes of the model.
Relating to the above comment, the default NMS parameters should be optimized for visual quality (e.g. score_thresh = 0.6) instead of mAP.
Can you stop using private classes?
I think Caffe conversion code does not need to be in repository. This is because some models may fail to reproduce performance using Caffe model because its run-time behavior is changed for consistency reasons in this framework. I think that as long as pretrained model created by ChainerCV produces almost same or better results than the originally reported results, we can forget about Caffemodel.

How about adding test_ssd.py that evaluates mAP of a pretraiend model?

Following #144, I think return values should be tuple of lists.

You are right. I wll fix it.

predict shouldn't take NMS paramters. This is because there can be Detection models that do not use NMS. These parameters should be attributes of the model.

You are right. I will move them to attributes.

Relating to the above comment, the default NMS parameters should be optimized for visual quality (e.g. score_thresh = 0.6) instead of mAP.

Why do you prefer threshold for visual quality? The reason why I chose current setting is only that I was more interested in mAP.

Can you stop using private classes?

Do you mean _Normalize or _SSDVGG16? I think no one want to use them directly because they are optimized to SSD.  Why do you want to make them public?.

I think Caffe conversion code does not need to be in the repository. This is because some models may fail to reproduce performance using Caffe model because its run-time behavior is changed for consistency reasons in this framework. I think that as long as pretrained models created by ChainerCV produce almost same or better results than the originally reported results, we can forget about Caffemodel.

For SSD, the conversion from Caffemodel works well. This is a big advantage. Why do you want to hide the model compatibility of ChainerCV's SSD? I think it is better to provide conversion code in examples.  Even in this case, we can provide the model trained on ChainerCV.
Of course, we can't provide conversion codes if we can't reproduce the performance. In this case, we can simply provide only the models trained on ChainerCV.

How about adding test_ssd.py that evaluates mAP of a pretraiend model?
Nice idea! You mean adding an example which evaluates a pre-trained model, right? (test_ssd.py already exists in tests/link_tests. But I guess you mean a different thing).

I updated SSD for new APIs #144.

Do you mean _Normalize or _SSDVGG16? I think no one want to use them directly because they are optimized to SSD. Why do you want to make them public?.

First of all, I think that it is beneficial to have _Normalize to be public, since it can be useful if someone wants to make their extension of SSD.
Second, I would encourage more reusable class design for SSDVGG16. It is only extendable to SSD300 and SSD512 in the current implementation, and not to other feature extractors.
I talked to you about this before, and I know that you have tried, but maybe we can do this. In that situation, this class should be public.
Third, I think that Chainer has loose definition of private classes. links/models/vision/resnet.py contains many public classes that have little documentation and tests. I think we can skip tests for helper classes like those since we do not have very much time.

For SSD, the conversion from Caffemodel works well. This is a big advantage.

Okay. Let's add caffemodel converter. It would be nice if you add that and a README that explains where to download caffemodel.
Eventually, I would like that README to contain a procedures to

run test without caffemodel
run test with caffemodel and how to convert caffemodel
quick demo
train

You mean adding an example which evaluates a pre-trained model,

Yes! I think this makes others to easily re-evaluate your model.

I think putting all files under chainercv.links.ssd is better because there will be multiple files relating to SSD including losses for SSD, model and possibly other feature extractors.

Adding to a note on private class, I am not familiar with the case when a public class inherits from a private class. Is this acceptable?

Second, I would encourage more reusable class design for SSDVGG16. It is only extendable to SSD300 and SSD512 in the current implementation, and not to other feature extractors.
I talked to you about this before, and I know that you have tried, but maybe we can do this. In that situation, this class should be public.

I will rethink the design of classes and APIs. Adding a base class which doesn't depend on any feature extractor looks good to me.

I think putting all files under chainercv.links.ssd is better

We can decide this after all code are implemented.

Adding to a note on private class, I am not familiar with the case when a public class inherits from a private class. Is this acceptable?

I don't feel this strange. But if this is not Python-style, I will obey it.

I don't feel this strange. But if this is not Python-style, I will obey it

In my understanding, inheritance should preserve accessibility of classes.
In some static languages, this is not compilable.

In my understanding, inheritance should preserve accessibility of classes.
In some static languages, this is not compilable.

Is it true? I don't know much about static languages. However, in C++, we can write as follows.
class Outer {
private:
  class PrivateInner {};

public:
  class PublicInner : PrivateInner {};
};

int main() {
  // this is ok
  Outer::PublicInner inner;

  // complie error
  // Outer::PrivateInner inner;

  return 0;
}

Actually, I did not know that there are languages that do not allow this in the world before this discussion.
Apparently, C# does not allow it.
http://stackoverflow.com/questions/10858107/c-sharp-private-hidden-base-class

The reason why I keep classes/methods private is that Making private things public is much easier than making public things private. If we make something public once, we have to keep it because of the backward compatibility.

Right. I am not against the concept of private something in general. Just you know.

I forgot to comment on an issue.

Why do you prefer threshold for visual quality? The reason why I chose current setting is only that I was more interested in mAP.

I think that the model should work out of the box with the default paramters.
Most casual and likely usage of this model would be not to evaluate the performance rigidly using mAP, but just visualize some outputs for fun.
In that case, it would be better to optimize for visual quality.

Most casual and likely usage of this model would be not to evaluate the performance rigidly using mAP, but just visualize some outputs for fun.
OK, I will set the default threshold to the value optimized for visual quality.

I will rethink the design of classes and APIs. Adding a base class which doesn't depend on any feature extractor looks good to me.

I re-designed classes. How about this? (docs and tests are under development and I will add trainer in another PR)

I re-designed classes. How do you think of it?

I like this more!
In the current implementation, you make SSD300 to inherit in two levels.
I personally like less inheritance.
For instance you can make SSD to take a feature extractor that outputs list of variables by __call__ as argument to __init__.
And then, make SSD300 that inherits from SSD and instantiate a feature extractor.
The feature extractor I am talking about is something like this.
In the class like below, feature extractors can be easily swapped to other conv nets like ResNet.
I am using https://arxiv.org/abs/1611.10012 as a reference on possible extensions.
class SSDVGG16Feature(chainer.Chain):

    def __init__(self):
        super(SSDVGG16Feature, self).__init__(
            conv1_1=L.Convolution2D(None, 64, 3, pad=1, **self.conv_init),
            conv1_2=L.Convolution2D(None, 64, 3, pad=1, **self.conv_init),

            conv2_1=L.Convolution2D(None, 128, 3, pad=1, **self.conv_init),
            conv2_2=L.Convolution2D(None, 128, 3, pad=1, **self.conv_init),

            conv3_1=L.Convolution2D(None, 256, 3, pad=1, **self.conv_init),
            conv3_2=L.Convolution2D(None, 256, 3, pad=1, **self.conv_init),
            conv3_3=L.Convolution2D(None, 256, 3, pad=1, **self.conv_init),

            conv4_1=L.Convolution2D(None, 512, 3, pad=1, **self.conv_init),
            conv4_2=L.Convolution2D(None, 512, 3, pad=1, **self.conv_init),
            conv4_3=L.Convolution2D(None, 512, 3, pad=1, **self.conv_init),
            norm4=Normalize(512, initial=initializers.Constant(20)),

            conv5_1=L.DilatedConvolution2D(
                None, 512, 3, pad=1, **self.conv_init),
            conv5_2=L.DilatedConvolution2D(
                None, 512, 3, pad=1, **self.conv_init),
            conv5_3=L.DilatedConvolution2D(
                None, 512, 3, pad=1, **self.conv_init),

            conv6=L.DilatedConvolution2D(
                None, 1024, 3, pad=6, dilate=6, **self.conv_init),
            conv7=L.Convolution2D(None, 1024, 1, **self.conv_init),
        )

    def __call__(self, x):
        ys = list()

        h = F.relu(self.conv1_1(x))
        h = F.relu(self.conv1_2(h))
        h = F.max_pooling_2d(h, 2)

        h = F.relu(self.conv2_1(h))
        h = F.relu(self.conv2_2(h))
        h = F.max_pooling_2d(h, 2)

        h = F.relu(self.conv3_1(h))
        h = F.relu(self.conv3_2(h))
        h = F.relu(self.conv3_3(h))
        h = F.max_pooling_2d(h, 2)

        h = F.relu(self.conv4_1(h))
        h = F.relu(self.conv4_2(h))
        h = F.relu(self.conv4_3(h))
        ys.append(self.norm4(h))
        h = F.max_pooling_2d(h, 2)

        h = F.relu(self.conv5_1(h))
        h = F.relu(self.conv5_2(h))
        h = F.relu(self.conv5_3(h))
        h = F.max_pooling_2d(h, 3, stride=1, pad=1)

        h = F.relu(self.conv6(h))
        h = F.relu(self.conv7(h))
        ys.append(h)

        return ys

class SSD300Head(chainer.Chain):

    # it would be nice if we can create a class that can generate both SSD300Head and SSD500Head

    insize = 300
    grids = (38, 19, 10, 5, 3, 1)
    aspect_ratios = ((2,), (2, 3), (2, 3), (2, 3), (2,), (2,))
    steps = [s / 300 for s in (8, 16, 32, 64, 100, 300)]
    sizes = [s / 300 for s in (30, 60, 111, 162, 213, 264, 315)]

    def __init__(self, n_class, feature_base):
        super(SSD300Head, self).__init__(
            conv8_1=L.Convolution2D(None, 256, 1, **self.conv_init),
            conv8_2=L.Convolution2D(
                None, 512, 3, stride=2, pad=1, **self.conv_init),

            conv9_1=L.Convolution2D(None, 128, 1, **self.conv_init),
            conv9_2=L.Convolution2D(
                None, 256, 3, stride=2, pad=1, **self.conv_init),

            conv10_1=L.Convolution2D(None, 128, 1, **self.conv_init),
            conv10_2=L.Convolution2D(None, 256, 3, **self.conv_init),

            conv11_1=L.Convolution2D(None, 128, 1, **self.conv_init),
            conv11_2=L.Convolution2D(None, 256, 3, **self.conv_init),
        )

    def __call__(self, x):
        for i in range(8, 11 + 1):
            h = ys[-1]
            h = F.relu(self['conv{:d}_1'.format(i)](h))
            h = F.relu(self['conv{:d}_2'.format(i)](h))
            ys.append(h)
        return ys

class SSD(chainer.Chain):

    def __init__(self, feature, head):
        super(SSD, self).__init__(
            feature=feature,
            head=head)

    def __call__(self, x):
        hs = self.feature(x)
        xs = self.head(hs)
        ys_loc = list()
        ys_conf = list()
        for i, x in enumerate(xs):
            loc = self.loc[i](x)
            loc = F.transpose(loc, (0, 2, 3, 1))
            loc = F.reshape(loc, (loc.shape[0], -1, 4))
            ys_loc.append(loc)

            conf = self.conf[i](x)
            conf = F.transpose(conf, (0, 2, 3, 1))
            conf = F.reshape(
                conf, (conf.shape[0], -1, self.n_class + 1))
            ys_conf.append(conf)

        y_loc = F.concat(ys_loc, axis=1)
        y_conf = F.concat(ys_conf, axis=1)

        return y_loc, y_conf

class SSD300(SSD):

    def __init__(self):
        feature = SSDVGG16Feature(...)
        head = SSD300Head(...)
        super(SSD300, self).__init__(
            feature, head)

Similar to Chainer's  VGG.__call__ method, it would be nice if that function returns intermediate variables by a dictionary.
I think it is not necessary to return all intermediate variables like Chainer's, but it would be nice if it can return some important features upon requests, such as outputs of the head and feature.

Here is my ongoing work on __call__ for Faster RCNN (https://github.com/yuyu2172/chainercv/blob/95909de82359dec97cdfd4f0f6096f9e34c2dd87/chainercv/links/faster_rcnn/faster_rcnn.py#L45).

I personally like less inheritance.

SSD300 and SSD512 share not only the base feature extractor but also prepare. Actually, I had tried to separate the feature detector into another class. But finally, I found this two-level inheritance is most simple.

Similar to Chainer's VGG.call method, it would be nice if that function returns intermediate variables by a dictionary.

All important features are returned by feature() method. We can access these values with an index. I don't want to assume all feature extractors have named feature maps (someone may implement feature extractor using ChainLink).

SSD300 and SSD512 share not only the base feature extractor but also prepare. Actually, I had tried to separate the feature detector into another class. But finally, I found this two-level inheritance is most simple.

Why do you think that prepare can not be implemented at SSD?

I think different feature extractors may require different preparation. For VGG-16, it consists of resizing and subtracting mean. But I don't think this is general.

All important features are returned by feature() method. We can access these values with an index. I don't want to assume all feature extractors have named feature maps (someone may implement feature extractor using ChainLink).

I think usage of ChainLink does not stop us from using dictionaries as output.
If the return outputs for ChainLink can only be a list in that case.
{'norm4': norm4_var, 'conv7': conv7_var, 'chain_link': [var_1, ..., var_n]}

I think different feature extractors may require different preparation. For VGG-16, it consists of resizing and subtracting mean. But I don't think this is general.

Well, if limit the scope to SSD, we can assume that images are resized to some fixed size.
Also, subtracting mean is quite common.
Those parameters can be passed to SSD class when instantiated.

class SSD
    def __init__(self, feature, ...):
         self.mean = feature.mean

For SSD, most important thing is the order of feature maps. feature() should return a list (or tuple) of feature maps.

For SSD, most important thing is the order of feature maps. feature() should return a list (or tuple) of feature maps.

I see. OrderedDict can work in that case.

Well, if limit the scope to SSD, we can assume that images are resized to some fixed size.
Also, subtracting mean is quite common.

Some extractor require rescale the range of value to [-1, 1]. And some others requires channel-wise rescaling. I think it is better to leave prepare unimplemented in SSD.

Some extractor require rescale the range of value to [-1, 1]. And some others require channel-wise rescaling. I think it is better to leave prepare unimplemented in SSD.

I see. I will stop for today and think again tomorrow on this.

In the current implementation, you make SSD300 to inherit in two levels.
I personally like less inheritance.

To elaborate this more, it takes more time for me to understand how links are grouped together when they are declared at multiple inheritance levels.

I see. OrderedDict can work in that case.

I don't want to introduce such a thing in APIs of SSD because this is very optional and not necessary for SSD.  How about the following solution?

features() returns a list of feature maps (defined as APIs of SSD)
Some model can have an extra method, for example extract(). (not defined as APIs of SSD. SSD doesn't care of it)

This method returns a dictionary of features.
In such models, features() calls extract() internally to get feature maps.

To elaborate this more, it takes more time for me to understand how links are grouped together when they are declared at multiple inheritance levels.

There is another group, SSD321 and SSD513. They are based on ResNet101.
In my idea, inheritance tree will be like below.

SSD

SSDVGG16

SSD300
SSD512

SSDResNet101

SSD321
SSD513

There is another group, SSD321 and SSD513. They are based on ResNet101.
In my idea, inheritance tree will be like below.
SSD
SSDVGG16
SSD300
SSD512
SSDResNet101
SSD321
SSD513
I think it looks clean.

In my taste, implementation of neural networks should make it easy to understand abstraction of layers at multiple levels.
In the case of SSD, I think that there are two levels of abstractions.

Divided the entire forward in three steps. (a) Extracting multiple features using a commonly used conv net, (b) Extract additonal features while more aggressively reducing spatial dimensions (c) Using the features to predict loc and conf.
The more lower level of abstraction is about the concrete steps taken at each module described above.

We are not quite agreed upon the higher-level abstraction as you consider the modules (a)(b) together. I can see that from features that returns aggregate of the outputs of the two modules.
I think that (a) and (b) should be separated because these two are often discussed as independent building blocks as we can see from how SSD is extended.
In order to make explicit that (a), (b) and (c) are at same level of abstractions, I preferred to separate feature extractors into different classes.
But, even if they are not separated into different classes, I would like to see a __call__ method that resonates with my conceptual image of the network. For example, it should look like below.
def __call__(self, x):
    xs = self.feature(x)
    xs += self.head(xs[-1])
    return self._multibox(xs)

Also, this is the reason why I did not like the current implementation of features being called inside the features of SSD300.

Some extractor require rescale the range of value to [-1, 1]. And some others require channel-wise rescaling. I think it is better to leave prepare unimplemented in SSD.

In my idea, we prepare a concrete class (or a function) that puts together a feature extractor, head and loc, conf. It is safe to implement predict there because it assumes the feature extractor.

In my opinion, SSD has only two concepts, feature extractor and multibox. Feature extractor reduces the spatial dimension from original to 1x1 and returns all feature maps. Multibox computes loc and conf from feature maps.
You divided feature extractor into two parts, (a) feature and (b) head. But this separation doesn't seem reasonable to me. According to your example, you defined from conv1_1 to conv7 as feature and from conv8_1 to conv11_2 as head. I guess your definition relies on whether original network (for example VGG16) contains a layer or not. But this rule will not work on a full-scratch network (designed fo SSD and there is no original network). In addition, separating feature extractor into two makes it difficult to use skip layers.

But this rule will not work on a full-scratch network (designed fo SSD and there is no original network).

You convinced me on this point.
So, from meta-architecture level, the features and (c) mentioned above are put together.
It would be easier to understand this structure if features is documented.
I still think that separating features into different classes makes it easier to understand because the features will be at least one level shorter in hierarchy than the current one.

SSD300 and SSD512 share not only the base feature extractor but also prepare. Actually, I had tried to separate the feature detector into another class. But finally, I found this two-level inheritance is most simple.

But, I understand some  difficulities (e.g. loc and conf are dependent on number of features), and I have not fully tried it by myself, so I can only give suggestions.
I will clean up my implementation of Faster RCNN in short time, so that we can consider two together.
Please wait on this.

I still think that separating features into different classes makes it easier to understand because the features will be at least one level shorter in hierarchy than the current one.

Yes, we can separate feature extractor into another class even if we don't separate it into head and feature.
However, I don't think shorter level in hierarchy is easier to understand in this case. I think current design is easy to understand the hierarchy of models.
Anyway, it is better to consider Faster-RCNN and SSD together as you said. I will leave this design as is and work on training scripts (it will be another PR).

However, I don't think shorter level in hierarchy is easier to understand in this case. I think current design is easy to understand the hierarchy of models.

Although I said current design is good, I am wondering what is the best design. I will try to separate extractor again.

I separated feature extractor into another class. In my design, an feature extractor has grid, prepare and __call__.

Can you move code from links/* to links/model/* ?

@Hakuyume
Demo seems to not work with the image downloaded from the following link (https://goo.gl/CZpHWY).

LGTM

No longer WIP?

LGTM!


ACRS 24 Setup development environment

What?
ACRS-24 Set up development environment
Why?
To allow developer have same working environment.
How?

Generated template ID for sending notification email for
- save and exit
- Submission once application is completed
- User authorization
- Notify API key
these template id were created in the Gov notify web page and reference to the ID can be found on the .env file

Setup a working environment for the entry page for a new project.

Added file to ignore on .gitignore

Added dependencies in the package.json file

Testing?
Screenshots (optional)
Anything Else? (optional)
Check list

[ x] I have reviewed my own pull request
[ x] I have written tests (if relevant)
[ x] I have created a JIRA number for my branch
[ x] I have created a JIRA number for my commit
[ x] I have followed the chris beams method for my commit https://cbea.ms/git-commit/
[ x] I will squash the commits before merging

Good initial setup, I think we should have a standard initial setup repo, with an agreed readme file format for all our project repos, maybe something to discuss in tech sessions

there's is a repo we creating for any project in HOF project  that is in review


Refreshing is causing 404

Although pages are loaded properly, refreshing them are causing 404.
Here are some attempts I did to fix it:

Including useHash worked but caused issues when the login/auth page was called by the callback from GitHub and Bitbucket app authorizing callback.
Change base-href from relative to non-relative had no effect

Issue has no significant impact and will be closed.


Morton Filters wanted

"Morton Filters: Faster, Space-Efficient Cuckoo Filters via Biasing, Compression, and Decoupled Logical Sparsity" by Alex D. Breslow and Nuwan S. Jayasena

I recently released the code for Morton filters. You can find it at this link ( https://github.com/AMDComputeLibraries/morton_filter). The main interface currently only supports inputs that are a multiple of the batch size (128 at present), but I aim to fix that limitation over the coming days.


amend maximum storage size for nvarchar(max)

amending description of maximum storage size for nvarchar(max).

Learn Build status updates of commit bc25ca4:
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For any questions, please:Try searching the learn.microsoft.com contributor guidesPost your question in the Learn support channel

@MikeRayMSFT
Can you review the proposed changes? IMPORTANT: When the changes are ready for publication, add a #sign-off comment to signal that the PR is ready for the review team to merge.
#label:"aq-pr-triaged"
@MicrosoftDocs/public-repo-pr-review-team

#sign-off


Why do I have 5 addresses under 1 stake? Cardanolands tells me to switch to Eternl

Hi,
I've never had any problems with NAMI wallet until last week, when I noticed that Cardanolands was not showing my Hexo balance. When I reached out to their team on discord, this was their response:
"Sorry for my late reply. We had conversation with our dev team and did many tests regarding Nami wallet.
So the problem is that Nami works only with 1 address (you already have 5 address under 1 stake) - https://cardanoscan.io/addresses?stakeKey=d63794fcb69012e40e01176550c017f129151333877e66c048358a2f
That's why you don't see ADA and HEXO amount on our platform, because when you connect your wallet, you connect only 1 address and all assets must be there. Also the problem is that you can't select which exact address you want to connect.
So the best and the easiest solution will be to restore your wallet in Eternl and then connect with this wallet. Eternl perfectly works with all addresses under 1 stake and it allows to read all data."
Which leaves me with the following questions:
Why would I have 4 other addresses besides my main address that all have less than 2 ADA attributed to them? Any idea how they were generated or if I can get rid of them and continue using NAMI as I did before?  It seems ludicrous that an answer to fix something that worked perfectly fine every time until last week, is to set up a new wallet... that is the last thing I need!
Thanks very much for your support.

@dreamkeeper77 Talk to Cardano Support on the Live support chat so that your issue can be looked into.


Update best-practices-retry-service-specific.md

This doc says Topaz is on Github but it is on Codeplex

Hi @hveiras, I'm your friendly neighborhood Azure Pull Request Bot (You can call me AZPRBOT). Thanks for your contribution!
You've already signed the contribution license agreement. Thanks!
We will now validate the agreement and then real humans will evaluate your PR.
TTYL, AZPRBOT;

#sign-off

Thanks for the fix!


Hide placeholder on focus

I am trying to show title text and hide placeholder on  focus of text field.
Is there any workaround on this problem?
Thanks...

Subclassing SkyFloatingLabelTextField and implementing these methods solved it for me
    override func becomeFirstResponder() -> Bool {
        if !hasText {
            placeholder = ""
        }
        setTitleVisible(true)
        return super.becomeFirstResponder()
    }

    override func resignFirstResponder() -> Bool {
        if !hasText {
            placeholder = title
        }
        setTitleVisible(hasText || hasErrorMessage)
        return super.resignFirstResponder()
    }


Display the sender's display name over a message instead of the user name.

Expected behavior
The sender's display name should be shown above the message.
Actual behavior
The sender's user name is shown above the message.
Why does this make a difference?
Other Matrix iOS clients such as FluffyChat follow the same approach as it's much more user-friendly to see the display name rather than the user name, specially if the message comes from a bridge, where the user name is something like<EMAIL_ADDRESS>

Wrong repo, sorry


'npm run build' ERROR in chunk vendor when using node 6.x

getting error when running npm run build
ERROR in chunk vendor [initial]
js/[name].[hash].js
No template for dependency: TemplateArgumentDependency
Child html-webpack-plugin for "index.html":
        + 1 hidden modules
Child extract-text-webpack-plugin:
        + 2 hidden modules

Uh, weird. I will try with a fresh build.

What node & npm are you using? Works for me.

Node 6.1 NPM 3.8.6  I will check with node 5 and 4 now.

So I just double check with a fresh project and yes there is an exact issue I described above when using node 6.1
Node 5.8 and npm 3.8.5 - OK
Node 4.4.0 and npm 3.8.2 - OK
Also FYI I am on Win 10.

I heard that node 6.x is giving issues, but I will check.

this happened for me, because I changed the nodevars.bat to load node and start in "c:/work".
If I changed that to to "C:/work" it builds fine.  Apparently node 6 is treating C:\foo and c:\foo as different places or something. so you have to be careful if you're ever explicitly using windows drive letter somewhere
https://github.com/nodejs/node/issues/6624

I had this issue with Node 6.1, but the upgrade to Node 6.2.1 solved it.
Hope this helps.

I have Node 6.4.0 and have this issue. Was anyone able to resolve it?

I'm using this proyect, but I'm getting this same issue. How do you guys solve it?

@michaeljota just do not use node 6.1 use https://github.com/creationix/nvm to switch to another verson.


[Feature}Addition of Gui interface for Smart select feature extraction

Describe the bug
Smart select feature is all about extraction of text from image ,but there are many still issues to be addressed like while extraction text from image user need to mention what language it is English or any other ,what characteristics he/she want to extract ,image selection , interactive interface where extracted text will be shown.
Technologies used would be  :-
tikinter for making gui interface

pre processing of image

Additional context

it will make more interactive
user friendly
increased performance as user can optimize with selection

Do you have a screenshot how it look like

@sanjay-kv sir I will make interface I haven't started work if assigned I will make simple interface with buttons and input bar for user inputs

Demo Sir it can be made something like this

@sanjay-kv please assign me this issue sir


Revert "Update Game Instructions"

Reverts marquisepiton/reviewing-a-pull-request#2

no need

no need


[web] run crashed on windows

Steps to Reproduce
flutter create --web  .
flutter run -d chrome

Logs

logs
Failed to build application for the web.

#0      throwToolExit (package:flutter_tools/src/base/common.dart:28:3)
#1      ResidentWebRunner.run (package:flutter_tools/src/build_runner/resident_web_runner.dart:167:7)
<asynchronous suspension>
#2      RunCommand.runCommand (package:flutter_tools/src/commands/run.dart:472:37)
<asynchronous suspension>
#3      FlutterCommand.verifyThenRunCommand (package:flutter_tools/src/runner/flutter_command.dart:490:18)
#4      _asyncThenWrapperHelper.<anonymous closure> (dart:async-patch/async_patch.dart:77:64)
#5      _rootRunUnary (dart:async/zone.dart:1132:38)
#6      _CustomZone.runUnary (dart:async/zone.dart:1029:19)
#7      _FutureListener.handleValue (dart:async/future_impl.dart:126:18)
#8      Future._propagateToListeners.handleValueCallback (dart:async/future_impl.dart:639:45)
#9      Future._propagateToListeners (dart:async/future_impl.dart:668:32)
#10     Future._complete (dart:async/future_impl.dart:473:7)
#11     _SyncCompleter.complete (dart:async/future_impl.dart:51:12)
#12     _AsyncAwaitCompleter.complete (dart:async-patch/async_patch.dart:28:18)
#13     _completeOnAsyncReturn (dart:async-patch/async_patch.dart:294:13)
#14     RunCommand.usageValues (package:flutter_tools/src/commands/run.dart)
#15     _asyncThenWrapperHelper.<anonymous closure> (dart:async-patch/async_patch.dart:77:64)
#16     _rootRunUnary (dart:async/zone.dart:1132:38)
#17     _CustomZone.runUnary (dart:async/zone.dart:1029:19)
#18     _FutureListener.handleValue (dart:async/future_impl.dart:126:18)
#19     Future._propagateToListeners.handleValueCallback (dart:async/future_impl.dart:639:45)
#20     Future._propagateToListeners (dart:async/future_impl.dart:668:32)
#21     Future._complete (dart:async/future_impl.dart:473:7)
#22     _SyncCompleter.complete (dart:async/future_impl.dart:51:12)
#23     _AsyncAwaitCompleter.complete.<anonymous closure> (dart:async-patch/async_patch.dart:33:20)
#24     _rootRun (dart:async/zone.dart:1120:38)
#25     _CustomZone.run (dart:async/zone.dart:1021:19)
#26     _CustomZone.runGuarded (dart:async/zone.dart:923:7)
#27     _CustomZone.bindCallbackGuarded.<anonymous closure> (dart:async/zone.dart:963:23)
#28     _rootRun (dart:async/zone.dart:1124:13)
#29     _CustomZone.run (dart:async/zone.dart:1021:19)
#30     _CustomZone.runGuarded (dart:async/zone.dart:923:7)
#31     _CustomZone.bindCallbackGuarded.<anonymous closure> (dart:async/zone.dart:963:23)
#32     _microtaskLoop (dart:async/schedule_microtask.dart:41:21)
#33     _startMicrotaskLoop (dart:async/schedule_microtask.dart:50:5)
#34     _runPendingImmediateCallback (dart:isolate-patch/isolate_patch.dart:116:13)
#35     _RawReceivePortImpl._handleMessage (dart:isolate-patch/isolate_patch.dart:173:5)

Flutter doctor
C:\source>flutter doctor -v
[√] Flutter (Channel master, v1.8.5-pre.117, on Microsoft Windows [Version 10.0.18362.267], locale ru-RU)
    • Flutter version 1.8.5-pre.117 at C:\libs\flutter
    • Framework revision 83a8a575ee (2 days ago), 2019-08-10 12:38:20 -0700
    • Engine revision ff49ca1c6e
    • Dart version 2.5.0 (build 2.5.0-dev.1.0 f29f41f1a5)

[√] Android toolchain - develop for Android devices (Android SDK version 29.0.2)
    • Android SDK at C:\Users\maxne\AppData\Local\Android\sdk
    • Android NDK location not configured (optional; useful for native profiling support)
    • Platform android-29, build-tools 29.0.2
    • Java binary at: C:\Program Files\Android\Android Studio\jre\bin\java
    • Java version OpenJDK Runtime Environment (build 1.8.0_152-release-1343-b01)
    • All Android licenses accepted.

[√] Chrome - develop for the web
    • Chrome at C:\Program Files (x86)\Google\Chrome\Application\chrome.exe

[√] Visual Studio - develop for Windows (Visual Studio CommunityВ 2019 16.2.1)
    • Visual Studio at C:\Program Files (x86)\Microsoft Visual Studio\2019\Community
    • Visual Studio CommunityВ 2019 version 16.2.29201.188

[√] Android Studio (version 3.4)
    • Android Studio at C:\Program Files\Android\Android Studio
    • Flutter plugin version 38.2.1
    • Dart plugin version 183.6270
    • Java version OpenJDK Runtime Environment (build 1.8.0_152-release-1343-b01)

[√] VS Code (version 1.37.0)
    • VS Code at C:\Users\maxne\AppData\Local\Programs\Microsoft VS Code
    • Flutter extension version 3.3.0

[√] Connected device (2 available)
    • Windows • Windows • windows-x64    • Microsoft Windows [Version 10.0.18362.267]
    • Chrome  • chrome  • web-javascript • Google Chrome 76.0.3809.100

• No issues found!

You'll need to rerun with -v to capture verbose logs to see what went wrong here

@jonahwilliams ,

flutter run -d chrome -v
```
[  +28 ms] executing: [C:\libs\flutter\] git log -n 1 --pretty=format:%H
[  +60 ms] Exit code 0 from: git log -n 1 --pretty=format:%H
[        ] 83a8a575eed882c49b629effedf7c95b6184515d
[        ] executing: [C:\libs\flutter\] git describe --match v*.*.* --first-parent --long --tags
[  +52 ms] Exit code 0 from: git describe --match v*.*.* --first-parent --long --tags
[        ] v1.8.4-117-g83a8a575e
[   +8 ms] executing: [C:\libs\flutter\] git rev-parse --abbrev-ref --symbolic @{u}
[  +37 ms] Exit code 0 from: git rev-parse --abbrev-ref --symbolic @{u}
[        ] origin/master
[        ] executing: [C:\libs\flutter\] git ls-remote --get-url origin
[  +34 ms] Exit code 0 from: git ls-remote --get-url origin
[        ] https://github.com/flutter/flutter.git
[  +90 ms] executing: [C:\libs\flutter\] git rev-parse --abbrev-ref HEAD
[  +36 ms] Exit code 0 from: git rev-parse --abbrev-ref HEAD
[        ] master
[ +100 ms] executing: C:\Users\maxne\AppData\Local\Android\sdk\platform-tools\adb.exe devices -l
[  +23 ms] Exit code 0 from: C:\Users\maxne\AppData\Local\Android\sdk\platform-tools\adb.exe devices -l
[        ] List of devices attached
[  +45 ms] Artifact Instance of 'MacOSEngineArtifacts' is not required, skipping update.
[   +1 ms] Artifact Instance of 'LinuxEngineArtifacts' is not required, skipping update.
[        ] Artifact Instance of 'LinuxFuchsiaSDKArtifacts' is not required, skipping update.
[        ] Artifact Instance of 'MacOSFuchsiaSDKArtifacts' is not required, skipping update.
[   +1 ms] Artifact Instance of 'FlutterRunnerSDKArtifacts' is not required, skipping update.
[ +302 ms] Building application for the web...
[+12152 ms] Starting daemon...
[ +183 ms] Initializing inputs
[ +239 ms] Bad state: Unable to start build daemon.
[   +4 ms] #0      _handleDaemonStartup (package:build_daemon/client.dart:82:5)

           #1      BuildDaemonClient.connect (package:build_daemon/client.dart:183:11)

           #2      BuildDaemonCreator._connectClient (package:flutter_tools/src/build_runner/web_fs.dart:305:30)
           #3      BuildDaemonCreator.startBuildDaemon (package:flutter_tools/src/build_runner/web_fs.dart:271:46)

           #4      WebFs.start (package:flutter_tools/src/build_runner/web_fs.dart:143:8)

           #5      ResidentWebRunner.run (package:flutter_tools/src/build_runner/resident_web_runner.dart:156:34)

           #6      RunCommand.runCommand (package:flutter_tools/src/commands/run.dart:472:37)

           #7      FlutterCommand.verifyThenRunCommand (package:flutter_tools/src/runner/flutter_command.dart:490:18)
           #8      _asyncThenWrapperHelper. (dart:async-patch/async_patch.dart:77:64)
           #9      _rootRunUnary (dart:async/zone.dart:1132:38)
           #10     _CustomZone.runUnary (dart:async/zone.dart:1029:19)
           #11     _FutureListener.handleValue (dart:async/future_impl.dart:126:18)
           #12     Future._propagateToListeners.handleValueCallback (dart:async/future_impl.dart:639:45)
           #13     Future._propagateToListeners (dart:async/future_impl.dart:668:32)
           #14     Future._complete (dart:async/future_impl.dart:473:7)
           #15     _SyncCompleter.complete (dart:async/future_impl.dart:51:12)
           #16     _AsyncAwaitCompleter.complete (dart:async-patch/async_patch.dart:28:18)
           #17     _completeOnAsyncReturn (dart:async-patch/async_patch.dart:294:13)
           #18     RunCommand.usageValues (package:flutter_tools/src/commands/run.dart)
           #19     _asyncThenWrapperHelper. (dart:async-patch/async_patch.dart:77:64)
           #20     _rootRunUnary (dart:async/zone.dart:1132:38)
           #21     _CustomZone.runUnary (dart:async/zone.dart:1029:19)
           #22     _FutureListener.handleValue (dart:async/future_impl.dart:126:18)
           #23     Future._propagateToListeners.handleValueCallback (dart:async/future_impl.dart:639:45)
           #24     Future._propagateToListeners (dart:async/future_impl.dart:668:32)
           #25     Future._complete (dart:async/future_impl.dart:473:7)
           #26     _SyncCompleter.complete (dart:async/future_impl.dart:51:12)
           #27     _AsyncAwaitCompleter.complete. (dart:async-patch/async_patch.dart:33:20)
           #28     _rootRun (dart:async/zone.dart:1120:38)
           #29     _CustomZone.run (dart:async/zone.dart:1021:19)
           #30     _CustomZone.runGuarded (dart:async/zone.dart:923:7)
           #31     _CustomZone.bindCallbackGuarded. (dart:async/zone.dart:963:23)
           #32     _rootRun (dart:async/zone.dart:1124:13)
           #33     _CustomZone.run (dart:async/zone.dart:1021:19)
           #34     _CustomZone.runGuarded (dart:async/zone.dart:923:7)
           #35     _CustomZone.bindCallbackGuarded. (dart:async/zone.dart:963:23)
           #36     _microtaskLoop (dart:async/schedule_microtask.dart:41:21)
           #37     _startMicrotaskLoop (dart:async/schedule_microtask.dart:50:5)
           #38     _runPendingImmediateCallback (dart:isolate-patch/isolate_patch.dart:116:13)
           #39     _RawReceivePortImpl._handleMessage (dart:isolate-patch/isolate_patch.dart:173:5)
[  +19 ms] Building application for the web... (completed in 12,6s)
[   +1 ms] "flutter run" took 13 120ms.
Failed to build application for the web.
#0      throwToolExit (package:flutter_tools/src/base/common.dart:28:3)
#1      ResidentWebRunner.run (package:flutter_tools/src/build_runner/resident_web_runner.dart:167:7)

#2      RunCommand.runCommand (package:flutter_tools/src/commands/run.dart:472:37)

#3      FlutterCommand.verifyThenRunCommand (package:flutter_tools/src/runner/flutter_command.dart:490:18)
#4      _asyncThenWrapperHelper. (dart:async-patch/async_patch.dart:77:64)
#5      _rootRunUnary (dart:async/zone.dart:1132:38)
#6      _CustomZone.runUnary (dart:async/zone.dart:1029:19)
#7      _FutureListener.handleValue (dart:async/future_impl.dart:126:18)
#8      Future._propagateToListeners.handleValueCallback (dart:async/future_impl.dart:639:45)
#9      Future._propagateToListeners (dart:async/future_impl.dart:668:32)
#10     Future._complete (dart:async/future_impl.dart:473:7)
#11     _SyncCompleter.complete (dart:async/future_impl.dart:51:12)
#12     _AsyncAwaitCompleter.complete (dart:async-patch/async_patch.dart:28:18)
#13     _completeOnAsyncReturn (dart:async-patch/async_patch.dart:294:13)
#14     RunCommand.usageValues (package:flutter_tools/src/commands/run.dart)
#15     _asyncThenWrapperHelper. (dart:async-patch/async_patch.dart:77:64)
#16     _rootRunUnary (dart:async/zone.dart:1132:38)
#17     _CustomZone.runUnary (dart:async/zone.dart:1029:19)
#18     _FutureListener.handleValue (dart:async/future_impl.dart:126:18)
#19     Future._propagateToListeners.handleValueCallback (dart:async/future_impl.dart:639:45)
#20     Future._propagateToListeners (dart:async/future_impl.dart:668:32)
#21     Future._complete (dart:async/future_impl.dart:473:7)
#22     _SyncCompleter.complete (dart:async/future_impl.dart:51:12)
#23     _AsyncAwaitCompleter.complete. (dart:async-patch/async_patch.dart:33:20)
#24     _rootRun (dart:async/zone.dart:1120:38)
#25     _CustomZone.run (dart:async/zone.dart:1021:19)
#26     _CustomZone.runGuarded (dart:async/zone.dart:923:7)
#27     _CustomZone.bindCallbackGuarded. (dart:async/zone.dart:963:23)
#28     _rootRun (dart:async/zone.dart:1124:13)
#29     _CustomZone.run (dart:async/zone.dart:1021:19)
#30     _CustomZone.runGuarded (dart:async/zone.dart:923:7)
#31     _CustomZone.bindCallbackGuarded. (dart:async/zone.dart:963:23)
#32     _microtaskLoop (dart:async/schedule_microtask.dart:41:21)
#33     _startMicrotaskLoop (dart:async/schedule_microtask.dart:50:5)
#34     _runPendingImmediateCallback (dart:isolate-patch/isolate_patch.dart:116:13)
#35     _RawReceivePortImpl._handleMessage (dart:isolate-patch/isolate_patch.dart:173:5)
</details>

What happens if you cycle a flutter clean in there, does it fail with the same error?

the problem remains.
problem appeared a few builds ago.
on Linux and macOS there is no problem, only windows

I have the same error on Linux :(

Current master crashes after JS exception thrown with very useful null in terminal and closes chrome window, I can't even figure out what the error is
Who on earth decided that it's a good idea?

/cc @grouma may have ideas

Error gone for me for several versions now

The  Unable to start build daemon issue should now be resolved. This issue was due to poor logic around invalidating the cached build snapshot. @jakemac53 made a fix in package:build_runner / package:build_daemon to solve this issue.

after upgrading to version 1.9.4-pre.37, i have another problem
 FileSystemException: Directory listing failed, path = 'c:\users\maxnemoy\documents\src\newweb2\.dart_tool\*'
log
[√] Flutter (Channel master, v1.9.4-pre.37, on Microsoft Windows [Version 10.0.18362.295], locale ru-RU)
    • Flutter version 1.9.4-pre.37 at C:\libs\flutter
    • Framework revision 98ef956073 (4 hours ago), 2019-08-22 16:26:36 -0400
    • Engine revision 5f03c7e35d
    • Dart version 2.5.0

[√] Android toolchain - develop for Android devices (Android SDK version 29.0.2)
    • Android SDK at C:\Users\maxnemoy\AppData\Local\Android\sdk
    • Android NDK location not configured (optional; useful for native profiling support)
    • Platform android-29, build-tools 29.0.2
    • Java binary at: C:\Program Files\Android\Android Studio\jre\bin\java
    • Java version OpenJDK Runtime Environment (build 1.8.0_152-release-1343-b01)
    • All Android licenses accepted.

[√] Chrome - develop for the web
    • Chrome at C:\Program Files (x86)\Google\Chrome\Application\chrome.exe

[√] Visual Studio - develop for Windows (Visual Studio CommunityВ 2019 16.2.2)
    • Visual Studio at C:\Program Files (x86)\Microsoft Visual Studio\2019\Community
    • Visual Studio CommunityВ 2019 version 16.2.29209.62

[√] Android Studio (version 3.4)
    • Android Studio at C:\Program Files\Android\Android Studio
    • Flutter plugin version 38.2.1
    • Dart plugin version 183.6270
    • Java version OpenJDK Runtime Environment (build 1.8.0_152-release-1343-b01)

[√] VS Code (version 1.37.1)
    • VS Code at C:\Users\maxnemoy\AppData\Local\Programs\Microsoft VS Code
    • Flutter extension version 3.3.0

[√] Connected device (2 available)
    • Windows • Windows • windows-x64    • Microsoft Windows [Version 10.0.18362.295]
    • Chrome  • chrome  • web-javascript • Google Chrome 76.0.3809.100

Workaround for now: manually create .dart_tool in the root of your flutter project. Fix will land in linked PR above

yes it is works
the thank you


Support multiple content types as input

Sample swagger:
We want 4 content types: "text/plain", "application/json", "image/jpeg", "image/png"
"post": {
  "operationId": "params_postParameters",
  "description": "POST a JSON or a JPEG",
  "consumes": ["text/plain", "application/json", "image/jpeg", "image/png"],
  "parameters": [
    {
      "name": "parameter",
      "in": "body",
      "description": "I am a body parameter with a new content type.",
      "schema": {
        "$ref": "#/definitions/PostInput"
      },
      "required": true
    }
  ],
  "responses": {
    "200": {
      "description": "Answer from service",
      "schema": {
        "type": "object"
      }
    }
  }
}

Cadl:
Example in cadl-ranch: https://github.com/Azure/cadl-ranch/pull/201
// main.cadl
@route("/serviceDriven/parameters")
@doc("POST a JSON or a JPEG")
@convenienceAPI
op postParameters(parameter: PostInput | bytes, @header contentType: "text/plain" | "application/json" | "image/jpeg" | "image/png"): object;

We expect user writes this. We could have internal mapping like M4 (how it maps needs to confirm with Tim):

bytes: "image/jpeg", "image/png", ...
PostInput: "application/json", ...
string: "text/plain", ...

Generated SDK:
// protocol method: ContentType is `Azure.Core.ContentType` containing all types of content type
public virtual Response PostParameters(RequestContent content, ContentType contentType, RequestContext context = null);

// convenience method for model
public virtual Response<BinaryData> PostParameters(PostInput parameter, ContentType contentType, CancellationToken cancellationToken = default);
// convenience method for bytes
public virtual Response<BinaryData> PostParameters(BinaryData parameter, ContentType contentType, CancellationToken cancellationToken = default);
// convenience method for string
public virtual Response<BinaryData> PostParameters(string parameter, ContentType contentType, CancellationToken cancellationToken = default);

Above examples are under the condition if there are more than 1 content types for the specific type. If there is only one content type, we omit ContentType parameter. For example, this case we will generate:
// protocol method: ContentType is `Azure.Core.ContentType` containing all types of content type
public virtual Response PostParameters(RequestContent content, ContentType contentType, RequestContext context = null);

// convenience method for "application/json"
public virtual Response<BinaryData> PostParameters(PostInput parameter, CancellationToken cancellationToken = default);
// convenience method for "image/jpeg", "image/png"
public virtual Response<BinaryData> PostParameters(BinaryData parameter, ContentType contentType, CancellationToken cancellationToken = default);
// convenience method for "text/plain"
public virtual Response<BinaryData> PostParameters(string parameter, CancellationToken cancellationToken = default);

Fine tune mapping:
// client.cadl
@overload(postParameters)
@convenienceAPI
// Here user maps "text/plain" to model type
op postParametersApplicationJson(parameter: PostInput, @header contentType: "text/plain" | "application/json" ): object;
@overload(postParameters)
@convenienceAPI
op postParametersImage(parameter: bytes, @header contentType: "image/jpeg" | "image/png"): object;

The generated SDK becomes:
// protocol method: ContentType is `Azure.Core.ContentType` containing all types of content type
public virtual Response PostParameters(RequestContent content, ContentType contentType, RequestContext context = null);

// convenience method for "text/plain", "application/json"
public virtual Response<BinaryData> PostParameters(PostInput parameter, ContentType contentType, CancellationToken cancellationToken = default);
// convenience method for "image/jpeg", "image/png"
public virtual Response<BinaryData> PostParameters(BinaryData parameter, ContentType contentType, CancellationToken cancellationToken = default);

Remaining issues:

[ ] ContentType of concenience method should be Azure.Core.ContentType? Or same as HLC to be a enum? If the answer is latter, then there are two  ContentType for two convenience methods respectively. We need to rename them. (Java uses string ContentType)
[ ] The return type is 'object': Generate as Response<BinaryData>.

All valid content types strings:
/(application|audio|font|example|image|message|model|multipart|text|video|x-(?:[0-9A-Za-z!#$%&'*+.^_`|~-]+))\/([0-9A-Za-z!#$%&'*.^_`|~-]+)\s*(?:\+([0-9A-Za-z!#$%&'*.^_`|~-]+))?\s*(?:;.\s*(\S*))?/
Decision:
ContentType of concenience method should be Azure.Core.ContentType

All the content type string with this pattern is valid:
/(application|audio|font|example|image|message|model|multipart|text|video|x-(?:[0-9A-Za-z!#$%&'*+.^_`|~-]+))\/([0-9A-Za-z!#$%&'*.^_`|~-]+)\s*(?:\+([0-9A-Za-z!#$%&'*.^_`|~-]+))?\s*(?:;.\s*(\S*))?/

And they will be categoried into one of Binary, Form, Json, Multipart, Text, Xml by above logic.
KnownMediaType.Json:
public virtual Response PostParameters(Model parameter, ContentType contentType);

KnownMediaType.Binary
public virtual Response PostParameters(BinaryData parameter, ContentType contentType)；

KnownMediaType.Text
public virtual Response PostParameters(string parameter, ContentType contentType)；

KnownMediaType.Xml (e.g. application/xml)
public virtual Response PostParameters(Model parameter, ContentType contentType);
// In CreateRequest method:
var content = new XmlWriterContent();
content.XmlWriter.WriteObjectValue(parameter, "parameter");
request.Content = content;

KnownMediaType.Form (e.g. application/x-www-form-urlencoded)
This case could contain multiple bodies. I prefer to create a new issue to track
KnownMediaType.Multipart
We just don't support.
Remaining issues:

When the content types listed in the header don't have corresponding body types. For example, "application/json" should map to a model, but the paramter type is bytes | string.

op postParameters(@body parameter: bytes | string, @header contentType: "application/json" | "image/jpeg"): void;

Same cases are "image/jpeg" is in contentType but bytes is not in the type of parameter.

When the content types contain "application/json", but more than one models are listed in parameter. We don't which model to use.

op postParameters(@body parameter: Model1 | Model2, @header contentType: "application/json"): void;

In the oveload method, more than one types of parameter are listed. In the below example, the type of parameter is Model | string. More than one types.

@overload(postParameters)
op postParametersApplicationJson(parameter: Model | string, @header contentType: "text/plain" | "application/json" ): void;

The decision of Java is:

Union body type and union header type are not allowed together
We should use @overload to define multiple content scenario. There will be linter to prevent the definition which defines both body type as union and header type as union. User should define overload if they define body type as union and header type as union.
Single body type and union header type are allowed
An operation marked as the @overload will generate corresponding convenience method with the mapping it defines.

We don't take multiple content type as a special case. Any cases with overload or shared route come up, we will just discuss overload or shared route.


Automator: update<EMAIL_ADDRESS>in<EMAIL_ADDRESS>

Generated by Automator - 2022-10-04T22:44:24+00:00

@istio-testing: The following test failed, say /retest to rerun all failed tests or /retest-required to rerun all mandatory failed tests:

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integ-security-multicluster_istio_release-1.14
fc34bc170d6a3deb956c8050a05ab2723e8e4127
link
true
/test integ-security-multicluster

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IBC Rate limiting contract

Partial work for: #2305
What is the purpose of the change
Add the contract to be used for IBC rate limiting
Brief Changelog
(for example:)

The metadata is stored in the blob store on job creation time as a persistent artifact
Deployments RPC transmits only the blob storage reference
Daemons retrieve the RPC data from the blob cache

Testing and Verifying

There are unit tests and integration tests in the contract

Documentation and Release Note

Does this pull request introduce a new feature or user-facing behavior changes? (no)
Is a relevant changelog entry added to the Unreleased section in CHANGELOG.md? (no)
How is the feature or change documented? (not applicable)

Should we have the IBC interface functions be under Cosmwasm Sudo message? https://docs.cosmwasm.com/docs/1.0/smart-contracts/sudo/

Should we have the IBC interface functions be under Cosmwasm Sudo message? https://docs.cosmwasm.com/docs/1.0/smart-contracts/sudo/
(SendPacket, RecvPacket, AddChannel, CloseChannel)

The reason to add it as regular execute messages instead of sudo is that they can be executed by someone other than the chain. Right now we define who can execute them when we instantiate the contract (https://github.com/osmosis-labs/osmosis/blob/a6cf294173fd49ec6ed7b879b941c0694475b932/x/ibc-rate-limit/contracts/rate-limiter/src/state.rs#L104-L107).
Permissions are then checked so that only the gov module is allowed to make changes and only the transfer module is allowed to send/recv packets.
My thought process is that even if these values will most likely be set to the module addresses, we could set them to something else (say, a multisig) if necessary.

That makes sense. Wdyt about send packet and recv packet being sudo though? I feel like we have an api leak if its called by something not in the state machine, right?

That makes sense. Wdyt about send packet and recv packet being sudo though? I feel like we have an api leak if its called by something not in the state machine, right?

yeah, that makes sense. I'll make the change.

Left some comments with questions (some design questions, some minor code ones)
I'm happy to merge this as long as we track these and write a spec, to unblock the other work going on for getting rate limits to happen!

Moved SendPacket and RecvPacket to sudo. There's a caveat worth noticing here though: when calling the contract via sudo, we don't specify a sender, which means that any module in the chain can call the contract. It's the responsibility of the go side to make sure this is not called in the wrong place.

Lets merge once tests pass!

@nicolaslara we've been thinking about this problem as well, something I'm curious about - why key flows on (channel, denom)? Could a malicious actor create a new client-connection-channel and bridge assets off of the chain on a channel that's not rate-limited?
This is probably less relevant for assets that have been bridged onto the chain, but might be relevant for native assets that are minted and bridged off of the source chain.

Thanks for talking through your reasoning here, it's very helpful!

If the assets get sent through a suspicious channel (and thus wrapped accordingly) they just wouldn't be recognized by the other chains.

I think the question here is how users of other chains perceive the trust properties of vouchers originating from different channels. My mental model is that the trust properties between channels are equivalent and that trust properties are derived from clients, although it's very possible that mental model is wrong. For bridged assets, the application can choose canonical channels, so while the trust properties might be the same, most of the value is locked in a few channels.
A practical case where this could matter would be a DEX that allows deposits of any IBC voucher from another chain that's one hop away, and routes the asset to the associated pool by querying the denomTrace (this might be a bad design for a DEX!) Global rate limiting is tough because creating more clients / connections / channels is permissionless, so if you add a default rate limit of 5%, you could open 20 channels to get around it.

The bigger danger (and what rate limiting is trying to prevent) is those assets flowing through "proper" channels, where they would be indistinguishable* from others of the same denom.

Agreed! I like the approach.

One other question @nicolaslara, what's the rationale for rate-limiting inflows?

The main question I have is how users of other chains perceive the trust properties of vouchers originating from different channels. My mental model is that the trust properties between channels are equivalent and that the trust properties of vouchers are derived from clients, although it's very possible that mental model is wrong.
A practical case where this could matter would be a DEX that allows deposits of any IBC voucher from another chain that's one hop away, and routes the asset to the associated pool by querying the denomTrace (this might be a bad design for a DEX!) Global rate limiting could definitely work!

I'd be interested to know if there are chains out there that do this. By default, IBC-go sets the denom to the trace hash, which effectively makes them different coins. A chain with this design would need to either override this, or have some mechanism for mixing them (a stableswap, for example).
I think this is a larger question of IBC routing/wrapping that is still unresolved. Not sure if there's an accepted design for this, but I'd expect unwrapping IBC denoms would require asking the issuing chains to validate them (haven't thought about this enough, though)

One other question @nicolaslara, what's the rationale for rate-limiting inflows?

In the case of an infinite-mint on another chain (think terra collapse) someone could bring unlimited amounts of a token and tank the price of assets pooled against it; effectively draining the pools.


Project fails to build

npm run build

><EMAIL_ADDRESS>build
> npx prisma generate && next build

Environment variables loaded from .env
Prisma schema loaded from prisma/schema.prisma

✔ Generated Prisma Client (4.8.0 | library) to ./node_modules/@prisma/client in 41ms
You can now start using Prisma Client in your code. Reference: https://pris.ly/d/client

import { PrismaClient } from '@prisma/client'
const prisma = new PrismaClient()
(node:47140) [DEP0040] DeprecationWarning: The `punycode` module is deprecated. Please use a userland alternative instead.
(Use `node --trace-deprecation ...` to show where the warning was created)
info  - Loaded env from /Users/voxel/Git/Wildberries/Temp/sentrydiscord.dev/.env
Attention: Next.js now collects completely anonymous telemetry regarding usage.
This information is used to shape Next.js' roadmap and prioritize features.
You can learn more, including how to opt-out if you'd not like to participate in this anonymous program, by visiting the following URL:
https://nextjs.org/telemetry

info  - Linting and checking validity of types .Failed to compile.

./lib/message.ts:21:7
Type error: Argument of type '{ name: string; iconURL: string; }' is not assignable to parameter of type 'EmbedFooterOptions'.
  Object literal may only specify known properties, and 'name' does not exist in type 'EmbedFooterOptions'.

  19 |     })
  20 |     .setFooter({
> 21 |       name: "Please consider sponsoring us!",
     |       ^
  22 |       iconURL: "https://sentrydiscord.dev/sponsor.png",
  23 |     })
  24 |     .setTimestamp(parser.getTime(event))

That sounds like an issue with the discord.js version - you might have to double check you've installed the right one. Closing out since this works on the main website though


snarkos: init at 2021-01-21

Motivation for this change
There was an issue with snarkos on a previous version (not compiling with cargo vendor) that was just fixed in one of the latest commits, that is why it's on unstable
Tested on both linux and darwin. Waiting the weekend to see if anyone is interested.
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[X] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
22.05 Release Notes (or backporting 21.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[ ] Fits CONTRIBUTING.md.

The tests pass on linux now. I'm going to merge this so I can experiment with the systemd service. I'm happy to take care of feedback if there is some later though.


Please add new Moes BRT-100-TRV Thermostat support.

@stas-demydiuk I've only been waiting for my Pull Request for 9 months when it will be included in the plugin, nothing is happening yet.
https://github.com/stas-demydiuk/domoticz-zigbee2mqtt-plugin/pull/663

@stas-demydiuk Please add new TuYa TV02-Zigbee Thermostat support.
https://github.com/stas-demydiuk/domoticz-zigbee2mqtt-plugin/pull/785


feat(db): batch cleanup expired rows from postgres

Summary
The PR #10405 changed cleanup to only happen on nodes that have Admin API listeners.
This PR makes deletion to happen in maximum of 50.000 row batches.
Inspired from #10331 and #10389.

Like #10405, this should also be easily backportable to previous versions.

@windmgc can you make this so that it does the loop of 50.000 rows deletion until cleanup is done. This PR can then also be backported, and future of Kong we move to trigger based approach #10389.

sure, will do

@bungle @hanshuebner  Please take a look, thanks!

@hanshuebner
Two things for different purposes:

https://github.com/Kong/kong/pull/10405 and https://github.com/Kong/kong/pull/10407 for a quick code fix that could be able to backport to an older version so that FTI production related problems could be solved.
Trigger solution for the next version to solve this problem.


How to use?

Would be nice if there are some instructions about how this lib is working, and maybe some examples...
Would this be made?

+1


Update R dockerfile

Replaces the apt install with a conda RStudio install.
closes #11
cc @cchoirat

Still with Conda, right?

@cchoirat it's the same image you've been using essentially. We can still fine tune, I just wanted to get these changes in.

@rokroskar Great.  The terminal issue might be related to the RStudio version.  Conda doesn't provide the latest R + RStudio.  I will play with an apt-only version next week.


handlr-regex: 0.11.2 -> 0.12.0

Updated handlr-regex to 0.12.0 and updated postInstall phase to address breaking changes in regards to installing man pages and shell completion scripts.
Changes: https://github.com/Anomalocaridid/handlr-regex/compare/v0.11.2...Anomalocaridid:handlr-regex:v0.12.0
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[x] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
24.11 Release Notes (or backporting 23.11 and 24.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

darwin breakage is not a regression according to hydra


[BUILDER] - Add builder pub key to Leaf

What is this task and why do we need to work on it?
For whole-block atomicity, rollups need to know the identity of the builder of a block so that they can exclude transactions which requested a different builder.
What work will need to be done to complete this task?
We need to discuss the best way to support this. Thinking about it, it seems consensus could actually be responsible for verifying the builder signature, saving the rollups that work, and honest nodes will only sign a leaf where the builder public key is correct.
Thus, perhaps we could add an optional builder signature as part of the proposal, and replicas would check it against the pub key in the proposed leaf. In the default case, the signature could be omitted and the "builder" pub key could be the same as the proposer.
Are there any other details to include?
No response
What are the acceptance criteria to close this issue?
HotShot leaves contain a builder pub key, and it is guaranteed that this key has signed the committed block hash.
Branch work will be merged to (if not the default branch)
No response

We'll prioritize this after we have a simple builder integrated into HotShot.

As discussed today, we will do this in the sequencer


Unicode character description missing in comments for codepoints above 0xFFFF

Unicode character description in the cmap table in output of ttx -l is missing in comments for codepoints above 0xFFFF, e.g.
<map code="0xffed" name="uniFFED"/><!-- HALFWIDTH BLACK SQUARE -->
<map code="0x1f4ef" name="u1F4EF"/><!-- ???? -->

The description here ???? should be POSTAL HORN, see https://unicode-table.com/en/1F4EF/

You can install unicodedata2 backport to use the latest UnicodeData 9.0.0
https://pypi.python.org/pypi/unicodedata2
fontTools will try to use that one if it finds it installed, else will fall back to the unicodedata module from the stdlib, whose version varies between python versions.
Python 3.6 has the latest UnicodeData 9.0.0, so its built-in unicodedata module is equivalent to the unicodedata2 backport module.
Yes.. that is one of those extra, implicit dependencies of fontTools, which could at least be better documented.
There has been resistance in the past to adding dependencies to fonttools, though that may change once I manage to convince the rest of us that Python Packaging Is Good Now.

Thanks. Nope, did not know that that existed. I'm using Python 3.5.1-4. I installed it with
# pip3 install unicodedata2
Collecting unicodedata2
  Downloading unicodedata2-9.0.0.post4-cp35-cp35m-manylinux1_x86_64.whl (408kB)
    100% |████████████████████████████████| 409kB 2.3MB/s
Installing collected packages: unicodedata2
Successfully installed unicodedata2-9.0.0.post4

but running ttx still resulted in ???? in the comment. Is there something else to do to get this working?

PS   I am using fonttools version 3.0-1 on updated Ubuntu 16.10.

hm.. that's weird. Do you get 'POSTAL HORN' if you do this in an interactive python shell?
>>> import unicodedata2
>>> from fontTools.misc.py23 import unichr
>>> unicodedata2.name(unichr(0x1f4ef))
'POSTAL HORN'

Ah ok! You should uninstall that old fonttools version you have, and re-install it with pip install fonttools. The latest version should be 3.7.2.

$ python3
Python 3.5.2+ (default, Sep 22 2016, 12:18:14)
[GCC 6.2.0 20160927] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import unicodedata2
>>> from fontTools.misc.py23 import unichr
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ImportError: No module named 'fontTools'

Seems like fontTools package is not installed in your python3's site-packages, so you can't import it.
How did you install it in the first place?

Yes, that fixed it, thanks
# dpkg -P fonttools
...
# pip3 install fonttools
...

Hope Ubuntu will upgrade its package soon.

No, don't use dpkg to install fonttools. We don't maintain that.
Use pip to install the latest fonttools.

Going to keep this issue open so we can discuss with the rest of the team whether to add unicodedata2 to our install_requires, or possibly to extras_require.

I try to chase Ubuntu to keep up to date with Python packages. In some organisations, one is not allowed to install outside of the official repositories because of maintenance contracts. So pip might be the fix (for you personal systems) but not everyone is allowed to that on certain (Ubuntu/Debian/Red Hat/etc) corporate servers.

Upvoting https://bugs.launchpad.net/ubuntu/+source/fonttools/+bug/1658041 (after logging in) might help a bit.

783707644bfa0d92d924faea745e34f3c0555219 already added unicodedata2 to extras_require.

Super! If you need translations of Unicode character descriptions, please see https://github.com/OpenTaal/python-unicodedata_l10n


Issue 9d4acb17ddb18dba04990af308e0ba0e - Error with Slack messaging and Unusual Character?

New Issue Checklist

[ x ] Updated fastlane to the latest version
[ x ] I have read the Contribution Guidelines

Issue Description
Had an error when sending Slack message (I think?). All steps completed successfully and then I had an error / crash when sending the Slack command.
I see ":beta:Symbol" mentioned in the crash reporter. This app's bundle display name includes the β symbol in it; I wonder if this is related? Not sure if this is a problem in Fastlane's tools or Swift's messaging API?
Complete output when running fastlane, including the stack trace and command used
[14:27:08]: -------------------
[14:27:08]: --- Step: slack ---
[14:27:08]: -------------------
[14:27:08]: Successfully sent Slack notification
[14:27:08]: Variable Dump:
[14:27:08]: {:DEFAULT_PLATFORM=>:ios, :PLATFORM_NAME=>:ios, :LANE_NAME=>"ios beta", :GIT_REPO_WAS_CLEAN_ON_START=>true, :BUILD_NUMBER=>"148", :VERSION_NUMBER=>"1.5.0", :IPA_OUTPUT_PATH=>"[MY_PATH]", :DSYM_OUTPUT_PATH=>"[MY_PATH]", :XCODEBUILD_ARCHIVE=>"[MY_PATH]"}
[14:27:08]: undefined method `+' for :beta:Symbol

+------+-------------------------+-------------+
|               fastlane summary               |
+------+-------------------------+-------------+
| Step | Action                  | Time (in s) |
+------+-------------------------+-------------+
| 1    | default_platform        | 0           |
| 2    | cocoapods               | 21          |
| 3    | ensure_git_status_clean | 0           |
| 4    | increment_build_number  | 1           |
| 5    | get_version_number      | 0           |
| 6    | get_build_number        | 0           |
| 7    | gym                     | 364         |
| 8    | pilot                   | 1790        |
| 9    | clean_build_artifacts   | 0           |
| 10   | commit_version_bump     | 0           |
| 11   | slack                   | 0           |
+------+-------------------------+-------------+

[14:27:08]: fastlane finished with errors
Successfully submitted a crash report. If this is a problem with one of the tools specifically,
please submit an issue on GitHub and attach the following number to it: '9d4acb17ddb18dba04990af308e0ba0e'
The crash report has been stored locally '/tmp/sentry_9d4acb17ddb18dba04990af308e0ba0e.json'
Fastfile:42:in `block (2 levels) in parsing_binding': [!] undefined method `+' for :beta:Symbol (NoMethodError)
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/fastlane-1.83.0/lib/fastlane/runner.rb:56:in `call'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/fastlane-1.83.0/lib/fastlane/runner.rb:56:in `block in execute'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/fastlane-1.83.0/lib/fastlane/runner.rb:46:in `chdir'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/fastlane-1.83.0/lib/fastlane/runner.rb:46:in `execute'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/fastlane-1.83.0/lib/fastlane/lane_manager.rb:46:in `cruise_lane'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/fastlane-1.83.0/lib/fastlane/command_line_handler.rb:30:in `handle'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/fastlane-1.83.0/bin/fastlane:38:in `block (2 levels) in run'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/commander-4.3.5/lib/commander/command.rb:178:in `call'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/commander-4.3.5/lib/commander/command.rb:178:in `call'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/commander-4.3.5/lib/commander/command.rb:153:in `run'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/commander-4.3.5/lib/commander/runner.rb:428:in `run_active_command'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/fastlane_core-0.43.0/lib/fastlane_core/ui/fastlane_runner.rb:23:in `run!'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/commander-4.3.5/lib/commander/delegates.rb:15:in `run!'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/fastlane-1.83.0/bin/fastlane:168:in `run'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/lib/ruby/gems/2.0.0/gems/fastlane-1.83.0/bin/fastlane:174:in `<top (required)>'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/bin/fastlane:23:in `load'
	from /Users/timcamber/.rbenv/versions/2.0.0-p247/bin/fastlane:23:in `<main>'

Configuration Files
Please copy the complete content of your Fastfile and any other configuration files you use below:
Fastfile:
default_platform :ios

platform :ios do
  version = nil
  build_number = nil
  tag_string = nil

  before_all do
    ENV["SLACK_URL"] = SLACK_URL

    cocoapods

    ensure_git_status_clean # Make sure Git working directory is clean
    increment_build_number  # Increment Build Number

    version = get_version_number(xcodeproj: MY_PROJECT_FILE)
    build_number = get_build_number(xcodeproj: MY_PROJECT_FILE)

  end

  desc "Submit a new Alpha Build to Apple TestFlight"
  lane :alpha do
    gym(scheme: "[MY APP NAME] α")
    pilot
  end

  desc "Submit a new Beta Build to Apple TestFlight"
  lane :beta do
    gym(scheme: "[MY APP NAME] β")
    pilot
  end

  desc "Deploy a new version to the App Store"
  lane :appstore do
    gym(scheme: "[MY APP NAME] App Store") # Build your app - more options available
    deliver(force: true)
  end

  after_all do |lane|
    clean_build_artifacts
    commit_version_bump
    tag_string = lane + "/" + version + "(" + build_number + ")"
    add_git_tag(tag: tag_string)

    push_to_git_remote
    clean_build_artifacts
    reset_git_repo

    slack(
      message: "Successfully deployed update to [MY APP NAME]"
    )
  end

  error do |lane, exception|
    slack(
      message: exception.message,
      success: false
    )
  end
end

Environment
fastlane version (run fastlane -v):
fastlane 1.83.0
Do you use bundler to execute fastlane (i.e. bundle exec fastlane)?
No
Do you use a Ruby environment manager (e.g. chruby, rbenv, rvm)?
rbenv

Hi @timcamber! Hope you are doing well. I wanted to know if you've tested without this symbol? That'll help us track down the cause of this. Thanks!


Add new example with workloads

Create a new example with vulnerable workloads that trigger events / security threats so that they can be used to see Sysdig+EKS in action

New example added https://github.com/sysdiglabs/terraform-eksblueprints-sysdig-addon/tree/main/blueprints/lab-security


qiskit_algorithms namespace is not supported.

Environment

Qiskit Optimization version: 0.5.0
Python version: 3.11
Operating system: Linux

What is happening?
MinimumEigenOptimizer doesn't support algorithms from qiskit-algorithms.
The qiskit.algorithms namespace is deprecated since qiskit-terra v0.25.0. The qiskit_algorithms namespace from qiskit-algorithms should be a drop-in replacement (for the transition period).
How can we reproduce the issue?
For example:
from qiskit_algorithms.minimum_eigensolvers import QAOA
from qiskit_optimization.algorithms import MinimumEigenOptimizer

_ = MinimumEigenOptimizer(min_eigen_solver=QAOA(...))

fails with:
TypeError: MinimumEigenOptimizer supports qiskit.algorithms.minimum_eigensolvers.SamplingMinimumEigensolver, qiskit.algorithms.minimum_eigensolvers.NumPyMinimumEigensolver, and qiskit.algorithms.minimum_eigen_solvers.MinimumEigensolver. But <class 'qiskit_algorithms.minimum_eigensolvers.qaoa.QAOA'> is given.

raised at https://github.com/qiskit-community/qiskit-optimization/blob/5e8bc0fe22f9f28569eca95ceed20db8c8990f61/qiskit_optimization/algorithms/minimum_eigen_optimizer.py#L164
What should happen?
It should be possible to use legacy qiskit.algorithms and qiskit_algorithms namespaces interchangeably (until the latter diverges).
Any suggestions?
To ease up the transition and keep the type annotations correct, one could prefer qiskit_algorithms if it is present:
try:
    from qiskit_algorithms.minimum_eigensolvers import ...
except ImportError:
    from qiskit.algorithms.minimum_eigensolvers import ...
)

The TypeError message should already now be informative enough to figure out what is happening.

It has been resolved by #537

Awesome, thanks!


Remove non-image based CI action files

PR Type

[ ] Breaking change
[ ] Feature
[X] Patch

Brief Description
Remove non-docker-image based CI actions with dependencies.

Not In Scope

PR Checklist

[ ] Is documented
[ ] Is tested
[ ] Adheres to applicable organization standards

TODOs

[X] Removed test_docs.yaml, deploy_docs.yaml and c-cpp.yaml.

🚀 [bumpr] Bumped! New version:v0.1.8 Changes:v0.1.7...v0.1.8


Add swift version badge

I want to learn from you project.
Think add some badges to the repository will be cool.
Hope I can make some help. :)

Thank you :)


micro-benchmarks

using bracketObserverIO run a micro-benchmark
describe the process for developers.

https://github.com/input-output-hk/ouroboros-network/commit/bb03901e6e4f87f5f9a8c242869dcdb1f1350f51


YouTube will withdraw the views caused by this script

It seems that YouTube will withdraw the views caused by this script. Now sure how to fix it.

did that happen to you, if yes we can try to do some update


Observed one core full load when writing to custom fifo through script

I'm not sure of what's going on. I have been wrangling FIFOs a while today but this one leaves me ?_?. I'd have to walk through pigpio to understand what's going on but for the time being I'd just like to know if you can observe this as well.
Reproduction
HW: Rpi 2B+
OS: Raspbian Stretch
Pigpio version: I forgot to pull this.

Have a console, let it be called 'conout'
working dir is /home/pi
mkfifo target_pipe
sudo echo /home/pi/target_pipe w >/opt/pigpio/access
sudo pigpiod
cat target_pipe
Leave this alone.
Have a console, let it be 'concommand'
pigs fo /home/pi/target_pipe 2 (result is '0' for me)
pigs fw 0 115 116 97 114 116 58
conout shows "start:", as expected
pigs proc fw 0 115 116 97 114 116 58 (result is '0' for me)
pigs procr 0

Outcome
Expected: conout should be updated with another start:.
Observed: nothing appears in conout; CPU load 25% not observed to terminate. Concommand is ready for other commands right away.
Notes
I looked at fileWrite and I cannot figure out why this behaviour should ever happen. Parsing isn't quite crystal-clear to me. Given my understanding of file handles in pigpiod (looks like they're all shared) I am without a clue on why this happens. Is this even supposed to work?

I can't see that working from a script.  If I remember correctly commands with more than three parameters will not work within a script.

Could not reproduce this issue.  Observed start:start: in conout.  Never observed high cpu utilization.
Note.  4. sudo sh 'echo /home/pi/target_pipe w >/opt/pigpio/access'


Fix spelling and grammar in README.md

I made some changes but there are still other parts of README that could use clarification.

Let me know if it's ok so far. I put a post up on Reddit looking for input so maybe you'll hear from some others :)


Google Nest Hub window doesn't scroll anymore after using bubble-card

Describe the bug
I have a verticale stack card with some buttons and bubble-card as first card. I use a tile card to navigate to the bubble-card. Everything works fine and I can use the pop-up as designed. But after I close the pop-up card I can not swipe my window on my Google Nest Hub anymore.  Everything stills works on the screen but I have some buttons more below and not visible below of the screen. After closing the pop-up swipe the screen more up is not possible anymore.
To Reproduce
Steps to reproduce the behavior:

Open the more buttons tile card
Click one of my buttons to switch a light on
Close the button and also the pop-up
Now I can not scroll my window anymore

Expected behavior
I expected everything works as before I used the bubble pop-up card.
Screenshots
Not really fit in a screenshot
YAML
not-applicable
Informations (please complete the following information):

OS: Google Nest HUb
Browser/App: Google Nest Hub
Bubble Card version: 2.3.0-beta.4
Home Assistant version: [e.g. 2024.11.1

Additional context
Add any other context about the problem here.
Thank you! 🍻

Hi! I've fixed something related to this issue, I'm not sure that this will fix this case, but wait for the next beta then tell me if it works after that 🤞

Hi, I have downloaded v2.3.0-beta 5. unfortunately the problem in my situation still excists. Now is the dashboard I stream complex but I don't know if that has any impact. On my MacBook the same Dashboard works fine, also after the use of Bubblecard pop-up.

Thank you for the feedback, can you tell me if your cards still works when you are unable to scroll? Just to be sure that this is not some kind of freeze.

I just tested. Every button or menu item works as designed. No freeze. Only no scrollable anymore directly after use of Bubblecard pop-up

Can you tell me if it was working before the v2.3.0 beta?

I was using it for the first time so I can't tell you. sorry. Must I try an earlier version?

You can do that if you want to help me understand what is happening here, the issue is that I don't have a Nest Hub to try it.

I am having same issue.
It also forces a vertical stack even though I selected masonry. Or is that expected?


Fix double scrollbar issue

https://twitter.com/steveklabnik/status/617031020429373440

r? @huonw
(rust_highfive has picked a reviewer for you, use r? to override)

r? @alexcrichton

@bors: r+

:pushpin: Commit cab644a has been approved by alexcrichton

:hourglass: Testing commit cab644a with merge a48fe5f...

:sunny: Test successful - cargo-linux-32, cargo-linux-64, cargo-mac-32, cargo-mac-64, cargo-win-gnu-32, cargo-win-gnu-64, cargo-win-msvc-64

hooray!!!


Add webdav client utils to relevant pipelines

retiling, data processing, and geotiff extraction pipelines need to be able to pull and push data from and to webdav. Implement a client for this purpose to replace clone mount.

addressed with PR #16


fix(deps): Upgrade node from 16.13.1 to 19.8.1

:tada: This PR is included in version 3.24.5 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


[TA] unskip aad samples/tests

API change check
API changes are not detected in this pull request.


Keyboard navigation updates

Fixes #164

@emeaguiar The "Search" button is using the Primary colors, but the top nav bar could have a different color, could you update the search button color to always use the --mdc-theme-on-header color ?


Dedup paths for attack path graphs

right now attack path graphs can have same pathway twice. We should dedup in backend if this is the case

done w/ adj list representation


Blender 2.8x compatibility

When will this plugin receive an update for Blender 2.8x?

https://github.com/Azure/azure-batch-rendering/pull/42 hopefully this helps as an initial step.

https://b3d.interplanety.org/en/using-microsoft-visual-studio-code-as-external-ide-for-writing-blender-scripts-add-ons/ The VS Code extension made it really easy to troubleshoot too.


Added ability to reuse a context of another window

When using multiple windows with OpenGL, there is some options:

create the windows with different independent GL contexts
create the windows with different GL contexts sharing resources
create the windows with the same GL context

At current time the third option is not supported by GLFW, however sometimes it's useful. This can be achieved with a new window hint: the target name can be GLFW_REUSE_CONTEXT. When this is set to true and a non-null share parameter is added to glfwCreateWindow, then the context of the share window is used for the created window instead of creating a new one with sharing resources by GL contexts.
Implementation is only provided for Win32 now.

You don't reference count the context so it'll get destroyed along with the first window that shares it, or depending on hints, by context recreation. You also look up a new pixel format and risk incompatibility. This design requires you to ignore all framebuffer and context related hints, which is confusing to the user and not currently done.
This is better solved by #25.

I agree that the implementation is highly incomplete now (it only answers my own purpose in practice). Maybe the idea should be added to the issues instead.
The problem may be solved better with https://github.com/glfw/glfw/issues/25, however  (if I haven't missed something) this involves creating a native window, which is uncomfortable (at least in my point of view: then why use glfw).
Yes, this solution requires to ignore all framebuffer and context related hints. I don't feel this is very confusing when one wants to do reusing a context of another window.
Then what could be a better design? Another window creation function? Any other idea, directions?

Exactly what different options will be provided by #25 is influenced by exactly these kinds of questions. Please add your $0.02 to the thread.


on dominiks request, the /#/ is needed to trick github pages

looks good! small change, so good to go


tabs in file explorer

Description of the new feature / enhancement
tabs in file explorer
Scenario when this would be used?
multiple tabs helps in quickly searching through content.
also mac like tree search would be great
Supporting information
multiple tabs helps in quickly searching through content.
also mac like tree search would be great

/dup #10


Allow config files to contain a root element named 'gpg'.

Before this change if the config file had a 'gpg' root element it would
override the figgypy gpg object. I'm unsure if this really broke
anything but it was a bit awkward that an internal only object existed
in the config object (as conf.gpg) when the file didn't have a gpg
element. I was also awkward that a config file could change the internal
workings of the config object.

Oh cool. I'll take the PR now. I'll build a release in the morning. Thank you for catching this.

Released 0.2.0


is there any wey to transform .flr to .riv

hi, Im first use Rive.
I try to run a demo in js and I find Rive1 file is .flr but Rive2 file is .riv
Is there any way to transform them or the engine can run in Compatibility mode？

At present this runtime only supports Rive 2 files. We are in the process of updating the Rive 2 editor to be able to import Rive 1 files to convert them to Rive 2.

Hum,ok. I will waiting for it and thank you.
I will close this issue.

Give this a shot @KuuBee. Note that some features are not supported yet, please refer to the details in the link! https://help.rive.app/getting-started/faq-1/importing-rive-1-files

Hey, I have a wired problem, I am only getting the .riv file, not the .flr file. I am not getting the option to export its only showing the option to download which downloads as a .riv file. Any idea what am I doing wrong

Hi, the new Rive exports .riv files not .flr (that was the old version, formerly Flare).
What documentation are you looking at? You’re probably looking at something that’s out of date!
Check out our guides and resources for the new Rive at https://rive.app/resources

Hey,  I have a .flr file and I need to convert it to .riv. As per the link given by @neurowave, I tried to go to https://flare.rive.app/ but there it shows that registrations will not be done and I cannot import the file in the new editor by drag and drop. So, I shall be glad if I could get some help.
[https://github.com/FilledStacks/flutter-tutorials/blob/master/002-flutter-flare-pt1/01-start/assets/button-animation.flr] is the file I am trying to convert.

Hey @iamaryanshandilya not a silly question! You need to contact the creator (FilledStacks) of that file and ask them to give you the source for that file (should be a .flr2d file). Then you can try to import it into the new editor, though keep in mind that not all the old features are supported yet. https://help.rive.app/getting-started/faq-1/importing-rive-1-files

I follow this:https://help.rive.app/getting-started/faq-1/importing-rive-1-files ,but it can't success

Well we are in 2022 and still no Rive support for there original format.. What a cluster fudge...

Well we are in 2022 and still no Rive support for there original format.. What a cluster fudge...

There has been support for converting the source file (.fl2rd) to the new editor since 2020, as my message from Dec 2, 2020 above states. The original issue is about converting the exported format (.flr) to the new exported format (.riv) which was never planned to be supported. You need the original source to import it into the new editor. The old export format (.flr) was purely intended for runtime and has no editor data associated to it. It cannot be imported into the new editor.

Hummm. It's cannot import from .fl2rd file. I tried and It's throw error cannot upload file.

Hummm. It's cannot import from .fl2rd file. I tried and It's throw error cannot upload file.

@sinhpn92 could you share the the Flare file that's failing for you?
Either here or at<EMAIL_ADDRESS>


Create liceocavour.txt

@LIUKRAST First stage of verification passed, official domain is liceocavour.edu.it as far as I verified. This is just an informational note. Pull request is still in the review. I appreciate your patience while waiting for the final decision.

@LIUKRAST Thank you for your patience while waiting for a review and processing your request. Pull request merged.

I'm sorry for opening again this pull req. I tried to add my email address but it says it's not valid

Hello!Please wait an hour and try again.Changes take time to propagate. Thank you!On 16. Jan 2024, at 21.38, LIUKRAST @.***> wrote:
I'm sorry for opening again this pull req. I tried to add my email address but it says it's not valid
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—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you modified the open/close state.Message ID: @.***>