Unable to Archive due to Bitcode

I have been getting this error over the last week and am unable to resolve it. Apologies if this is incorrect usage of the "issues" tab.
Auto-Linking bitcode bundle could not be generated because '/Users/allenwixted/Desktop/iOS : OS X/NoPlaceLike/Frameworks/ARVideoKit.framework/ARVideoKit' was built without full bitcode. All frameworks and dylibs for bitcode must be generated from Xcode Archive or Install build
I've tried this article and it worked for a day or so. Then I realised I was working on Xcode beta and needed to build it for iOS 11.3 and am unable to resolve the issue this time around. Any help is much appreciated.

@allenwixted, are you using the .framework binary file?
If so, I'd recommend to follow those steps:

https://github.com/AFathi/ARVideoKit#publishing-to-the-app-store

Hi @AFathi I couldnt get it to work so I just removed the framework and went with importing the code folder itself. Thanks for responding though. Side Q regarding licencing, my app doesn't have a licence page yet (it's just a basic table view with ARViews spanning from those). Is it okay to mention/link ARVideoKit in the AppStore page or is there a specific requirement in what way to give you the credit deserved for the framework?


Hello I am trying to use the start method but I get an error that is not defined when I reload the page using nextjs

Hello I am trying to use the start method but I get an error that is not defined when I reload the page using nextJS
I only want to execute the start method if a condition is met.
 import userflow from 'userflow.js'

 userflow.init(TOKEN)
 userflow.identify(...) //Return a Promise
 userflow.start(CODE_START) //Return a Promise

Error: TypeError: userflow_js__WEBPACK_IMPORTED_MODULE_1__.default.start is not a function

Hi @willydavid1 :)

Which version of userflow.js is in your node_modules?
Could you try to console.log(userflow) before the userflow.start() line (or run with a debugger) to figure out what the userflow object actually is. It seems strange that init and identify are there but not start.

"userflow.js": "^2.1.1" in my package.json
Here the object

 import userflow from 'userflow.js'

 userflow.init(TOKEN)
 userflow.identify(...)
 console.log('userflow', userflow)
 userflow.start(CODE_START)

Am I importing userflow wrong? or do I have to wait for the identity?
something like that using async/await
 import userflow from 'userflow.js'

 userflow.init(TOKEN)
 (async () => {
   await userflow.identify(...)
   await userflow.start(CODE_START)
 })()

When I do this if it shows successfully but imagine that I have separated the start
I have another question I have to call init first and then start right?

As you can see on my previus response the start function appears but when I tried using debbuger as you suggest, the start funtion did not appear.
 import userflow from 'userflow.js'

 userflow.init(TOKEN)
 userflow.identify(...)
 console.log('userflow', userflow)
 debugger
 userflow.start(CODE_START)

I found the error, the start method does not appear until the identify method is called and its execution ends with the await

Ah, my memory is slow today. This issue was fixed in v2.1.2. Please upgrade to that version :)

...and you don’t have to await anything before you call userflow.start()


iframe based embedding

So far you could embed asciinema.org hosted recordings in your HTML pages by copy-pasting the

The existing embed script automatically inserts an  into a document, and resizes the iframe after the player inside initializes.
This PR adds direct iframe embedding support. Example:

This allows for embedding in places where


Is v3 Animatediff supported

Loading models from: models/AnimateDiff\v3_sd15_mm.ckpt
We cannot detect the model type. No models are loaded.

Sorry, this model is not supported.


Fix Attendee element

The Attendee element was missing potential ProposedStart and
ProposedEnd child elements. Those were missing from Microsoft
documentation. They are used when an attendee proposes a different
date and time for the meeting.
I already created a pull request for Microsofts docs. But the types
schema shows that ProposedStart and ProposedEnd are possible
child elements.
BTW: The Mailbox child element is now mandatory. I'm pretty sure
this is correct. But the type schema doesn't sepecify this element with
'required'.

😢
I made a mistake...
I'm trying to fix it...

I will never try to amend a commit that is already in a remote which is in the process of a PR.
But I think I fixed it.

Looks good! Thanks!


easyRefresh 3.4.0 firstRefresh: true .app crash.

easyRefresh 3.4.0 firstRefresh: true 每次都会导致 assert.
════════ Exception caught by foundation library ════════════════════════════════
The following assertion was thrown while dispatching notifications for ValueNotifier:
setState() or markNeedsBuild() called during build.
This EasyRefresh widget cannot be marked as needing to build because the framework is already in the process of building widgets. A widget can be marked as needing to be built during the build phase only if one of its ancestors is currently building. This exception is allowed because the framework builds parent widgets before children, which means a dirty descendant will always be built. Otherwise, the framework might not visit this widget during this build phase.
The widget on which setState() or markNeedsBuild() was called was: EasyRefresh
state: _EasyRefreshState#550ef
The widget which was currently being built when the offending call was made was: LayoutBuilder
renderObject: _RenderLayoutBuilder#24c1d relayoutBoundary=up2
查了下代码. 在 easyRefesh 的 init 里有 setState()这时候 onRefresh 正在刷新.
// 监听首次刷新是否结束
if (_enableFirstRefresh && !_taskNotifier.value.refreshing) {
_scrollerController?.jumpTo(0.0);
setState(() {
_enableFirstRefresh = false;
});
}


Enable hyperlinks in in-tool Help field #3579

I allowed rendering HTML in the expression-preview-dialog.js file and added an anchor tag for all the URLs
I also changed any tag symbol '<' to '<' in the translations files in order not to be rendered as an HTML tag and appear as '<' as it was before

@sarahelshabrawy thank you very much for that! It looks very good to me. Unfortunately this conflicts with another change, could you solve the merge conflicts? Thank you!

@wetneb Done


Deobfuscation fixes

Fixes the following issues with deobfuscation:

Name generation on variables of deobfuscated objects were sometimes based off of the original class name, and not the alias.
Renamed classes/methods referenced in a different dex file would not be renamed properly.
Deobfuscator.postProcess may overwrite Deobfuscated method names for overriden methods.

Also fixes one issue not related to the  deobfuscation:

Inner classes residing in an empty package name were not being linked to their parent class due to an issue with ClassInfo.splitNames

Thanks for this project!

Good job!


document contribution and release processes

Since a bunch of folks seem to be using otel-cli in their work, it's probably time we get serious about consistent release process and actually doing PR approvals.
I've been merging PRs to move things along towards a 0.1.0 release, but that shouldn't continue if others are relying on this. I'd also like to add some maintainers, starting with @ahayworth and see who else volunteers.
Sortof unrelated but we (Equinix Metal) might migrate this repo over to one of our dedicated OSS GitHub organizations soon. That will hopefully make the provenance and status of otel-cli a little clearer, and give it a long-term home.

@cyrille-leclerc @ahayworth I'd love to hear your thoughts. I'm leaning towards a pretty typical GitHub/OSS workflow, especially as we get more contributors in here.

@tobert I'd be delighted to help! Although, I'm not really using it day-to-day at the moment. But if I can share the load, I'd be glad to!

https://github.com/equinix-labs/otel-cli/releases/tag/v0.0.5 released with more packages and adjustments to goreleaser.
Gotta figure out how to make those changelogs nicer.

I added some docs to the README a while ago. Gonna open a new issue about automating releases.


Composer cleanup and update

Unless there's a reason for using tilde instead, we should use google/apiclient:^2.0, as this is more strict to semantic versioning.

The e2e tests are also passing on our jenkins!

LGTM!


Allow sorting

It would be good to have a "sort alphabetically: ascending/descending" type toggle.
The use case is I want a Visa card, it's at the bottom of the list - I either have to scroll or type into the filter box (so much work! 😛)
Ideally, with a single click on the "sort" button, I could flip Visa to the top of the list

@sponglord Users can now pin favourite cards (#11) to quickly access the cards they use more often. Sorting is a good feature but not ideal when looking for cards that are in the middle.


Create replace_a_faulty_device

Context
Changes proposed in this pull request
Guidance to review

Combined with #972 nto a new PR #984


Android App with dApp Connector and in-app dApp Browser

Created a Nami Wallet Android App with dApp Connector based on Android Intents using Capacitor JS

Oh wow, didn't expect such a PR hahaha. I'm gonna check that out!

@vineeth2941 was able to successfully build. How does the communication between the app and the browser work exactly? I see it works with Intents somehow, but how do I call that from the website?

@alessandrokonrad Intents work only for App to App communication, We need to build a dApp browser if it has to be between a website and the wallet app. For testing, you can use this Android-based sample dApp: https://github.com/vineeth2941/nami-client-android

@alessandrokonrad Intents work only for App to App communication, We need to build a dApp browser if it has to be between a website and the wallet app. For testing, you can use this Android-based sample dApp: https://github.com/vineeth2941/nami-client-android

Does the browser need to be built from scratch or is it possible to embed the exisiting chrome browser?

Most probably we can embed the existing one as webview but some configuration might be needed to wrap the CIP-30 JS API to the Android Intent API

Most probably we can embed the existing one as webview but some configuration might be needed to wrap the CIP-30 JS API to the Android Intent API

Reference Link: https://developer.android.com/guide/webapps/webview#BindingJavaScript

Android App with Capacitor JS
Android dApp Connector using Intents
Android sample dApp & dApp Browser using dApp Connector (https://github.com/vineeth2941/nami-client-android)
Android in-app dApp Browser (dApp client connector: https://github.com/vineeth2941/nami-dapp-browser-connector)
Extension in-app dApp Browser

https://user-images.githubusercontent.com/47296387/170102385-bdb1f87a-555c-4c1b-a7d2-44b0052d1f76.mp4
https://user-images.githubusercontent.com/47296387/170102485-cf50ac55-6e6f-46bf-b5b1-d176f8985d55.mp4

What? This is nice haha


LSTM/RNN input and output

Hi,
This is a general question regarding using LSTM/RNN. What does the input and output look like? Are there any concrete examples? Kindly let me know
Say I have 5 dimension features per frame and want to use them for binary classification. Normally, for a feed forward network, the data and label would be as below
[1,2,3,4,5] [0]
[2,3,4,5,6] [0]
[3,4,5,6,7] [0]
[4,5,6,7,8] [1] -> different class
[5,6,7,8,9] [1] -> different class
If I want to use RNN/LSTM, then how would my output and inputs be?
For a timeStep = 2, batch_size = 3, Will I have one label for each time step?
Any pointers will be appreciated
Thanks

For a feed-forward network, your input has the shape (number of samples, number of features). With an LSTM/RNN, you add a time dimension, and your input shape becomes (number of samples, number of timesteps, number of features). This is in the documentation.
So if your feature dimension is 5, and you have 2 timesteps, your input could look like
[ [[1,2,3,4,5], [2,3,4,5,6]], [[2,4,6,8,0], [9,8,7,6,5]] ]
Your output shape depends on how you configure the net. If your LSTM/RNN has return_sequences=False, you'll have one label per sequence; if you set return_sequences=True, you'll have one label per timestep.

Thanks for the reply. Really appreciate it
So in the example, [ [[1,2,3,4,5], [2,3,4,5,6]], [[2,4,6,8,0], [9,8,7,6,5]] ]
input_shape is (2, 2, 5). Is that correct?
And a 'sequence' is '[[1,2,3,4,5], [2,3,4,5,6]]' I assume. Is that correct?
and has 2 timesteps

That should be correct, yes.

Hi,
I am working on a similar thing, my feature vector is a 2-d matrix(say, mxm) for each frame with time steps = 4. Can you please help me out with the input shape for lstm.
Also, how can i use CNN + LSTM for the same.
Thanks

Hi,
I am trying to work with CNN+LSTM and facing problem in using LSTM after CNN. From the last ConvLayer of the network i am getting the shape 32x8x26, how can i use LSTM after this?

Hi,
I am trying to work with CNN+LSTM and facing problem in using LSTM after CNN. From the last ConvLayer of the network i am getting the shape 32x8x26, how can i use LSTM after this?
Thanks.

@anirudhgupta22
Hi, firstly I have to say that I am also new to CNN+LSTM, but my feeling is that you probably need to reshape your data after CNN using the Flatten layer. In your case, if you have an output from CNN with shape, 32x8x26 at each time step, then you use Flatten layer to make it 32x8x26=6656, so you will then have a 6656 dimensional feature at each time step. But how to then connect it to the LSTM, I also not sure either, and also currently studying it. Hopes this helps.
Cheers

Hi all,
A similar question: given that I have a time series dataset, I want to use an (14 x 1) input data vector consists of data from 14 days ago until now i.e [t-13, t-12, t-11 ... t-1, t] to predict an (3 x 1)output data vector 10,11 and 12 days later i.e [t+10, t+11, t+12].
The final input data will therefore have shape of (34536, 14, 1).
The final output data will therefore have shape of (34536, 3, 1).
Now I want to build a very simple model : LSTM -> TimeDistributed. Is it correct if I built my model as followed:

xshape = (34536, 14, 1)
model = Sequential()
model.add(LSTM(units = 3, input_shape=(xshape[1], 1), return_sequences = True ))
model.add(TimeDistributed(Dense(3)))

Thanks in advance for any advice!

@wengchen1993 You can use from keras.utils.layer_utils import print_summary; print_summary(model) to check the shapes of your layers. From there, you can see that the output shape is (None, 14, 3), so your code does not do what you want.
First of all, the number 3 in your code, both in LSTM(units=3) and in Dense(3), has nothing to do with the number of timesteps, but specifies the dimensionality of the output space. LSTM(3) would therefore produce an LSTM that outputs 3-dimensional vectors (which is tiny for an LSTM, really). Similarly, Dense(3) also outputs 3-dimensional vectors, which would be useful if you wanted to predict one of three classes, for example.
What you could do - but note, I have no idea if that is actually a good choice for your particular problem domain - is have an LSTM that outputs an n-dimensional vector, then split up that vector into three parts (the three timesteps you want in your output).  For example:
n = 300
model = Sequential()
model.add(LSTM(n, input_shape=(xshape[1], 1)))
model.add(Reshape((3, -1)))
model.add(TimeDistributed(Dense(1)))

Hi thanks @mbollmann! The format you suggested seems to be correct as I observe from the model summary:

Layer (type)                 Output Shape              Param #
lstm_1 (LSTM)                (None, 14, 3)             60

reshape_1 (Reshape)          (None, 3, 14)             0

time_distributed_1 (TimeDist (None, 3, 1)              15
Total params: 75
Trainable params: 75
Non-trainable params: 0

However, I notice the outputs I get are all the same :

[[[ 19.89518166]
[ 17.22050476]
[ 20.95066833]]
[[ 19.89518166]
[ 17.22050476]
[ 20.95066833]]
[[ 19.89518166]
[ 17.22050476]
[ 20.95066833]]
...,
[[ 19.89518166]
[ 17.22050476]
[ 20.95066833]]
[[ 19.89518166]
[ 17.22050476]
[ 20.95066833]]
[[ 19.89518166]
[ 17.22050476]
[ 20.95066833]]]
(8628, 3, 1)

Are there any reasons you can think of why this happens? I have inspected the inputs and they are quite different.

For the model summary, I guess you're still using return_sequences=True and units=3 with your LSTM. You should have return_sequences=False and a much higher number for the units to start with.
Apart from that, it's really hard to say anything else without knowing what you're trying to do, how you're trying to train the model, etc.

@mbollmann Sorry if I have not been able to make it clear, but let me try to explain again:
What I have done (Many-to-one)
I have a single time series data, for example [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15] and I split it into a (mx1) input vector to predict a scalar value, t timesteps ahead.
If m is 5 and t is 4, I will have [1,2,3,4,5] -> 9, [2,3,4,5,6] -> 10, [3,4,5,6,7] -> 11 ...... [6,7,8,9,10] -> 14 and [7,8,9,10,11] -> 15. This is done by using LSTMs and a Dense(1) at the end because this is a regression problem.
What I want now (Many-to-many)
I want to do basically the same thing but instead of predicting a scalar value, I predict a n vector. If m is 5, t is 4 and n is 3, I will have:  [1,2,3,4,5] -> [9,10,11], [2,3,4,5,6] -> [10,11,12], [3,4,5,6,7] -> [11,12,13], [4,5,6,7,8] -> [12,13,14], [5,6,7,8,9] -> [13,14,15].
The parameters used above are just for example and I used much larger values in the actual code. Is TimeDistributed layer suitable to be used in a regression problem as above?

I've never worked with predicting scalars, and I don't know if my sample code is the best model for this problem, but it should roughly be able to do what you want.
The LSTM would encode all of the input timesteps into a single vector (so return_sequences=False) which is then split up into three parts, to produce the three separate output timesteps you want. (Alternatively, you could probably skip the Reshape and TimeDistributed parts and just predict a 3-dimensional vector via Dense(3), where each dimension is one of the values you want to predict... that might also work. With neural networks, there is rarely a single correct answer. :))

@mbollmann
Going off the example you gave: [ [[1,2,3,4,5], [2,3,4,5,6]], [[2,4,6,8,0], [9,8,7,6,5]] ]
If input_shape=(2, 2, 5) then,
Would the keras line be:
model.add(LSTM(hidden_units, input_shape=(2, 2, 5)))?
And if that's true, how come in this example tutorial it's using:
model.add(LSTM(256, input_shape=(X.shape[1], X.shape[2]))), translated to:
model.add(LSTM(256, input_shape=(n_patterns, sequence_length))), translated to:
model.add(LSTM(256, input_shape=(147574, 100)))
Instead of:
model.add(LSTM(256, input_shape=(147574, 100, 1)))
Which results to:
ValueError: Input 0 is incompatible with layer lstm_1: expected ndim=3, found ndim=4

@naisanza
The input shape is (2, 2, 5), yes, but the batch dimension (= number of samples) is never specified when giving an input_shape argument to Keras. See this part of the documentation.
So the Keras line would have input_shape=(2, 5).

@mbollmann oh I didn't know batch dimension meant samples, I thought it was referring to batch_size
So many words

Hello friends
I could not the term 'None' in output shape like

Layer (type)
Output Shape
Param #

embedding_2 (Embedding)
(None, 28, 128)
256000

spatial_dropout1d_2 (Spatial)
(None, 28, 128)
0

Please let me know that why None is given in output layer

waiting for your response

Hi,
I have a question for the RNN output dimension.
I use (I simply the model here)
model.add(SimpleRNN(2,input_shape=(None, 1),return_sequences=True,name="1"))
model.add(SimpleRNN(4,return_sequences=False, name="2"))
Each of my input sequence length is 9 so I got the layer"1" output shape as (2297, 9, 2), 2297 is my total samples, 2 is my output dimension.
The model works well. But I'm wondering why the RNN output dimension is related to hidden units?
Refer to S_t=(UX_t+WS_t), O_t=Softmax(V*St)
For layer 1:
U(hiddeninput_dim) is 21 matrix, X_t is 11 matrix, W(hiddenhidden) is 22 matrix, V(input_dimhidden)=12.
Then the O_t should be a 11 here. Why my output dimension is 2?
Below is my input example:
[[4.00298875]
[4.00298875]
[4.00298875]
[4.00298875]
[4.00298875]
[4.00298875]
[4.00298875]
[4.00298875]
[4.00298875]]
Can anyone help this?

If I have the only sample, do I need to reshape it into three dimensions? For example, if I have the input data of shape [m,n] and output also has [m,n] shape. Do I need to change the input into [m,1,n] shape? Also, can I keep the output shape [m,n] if I am using return_sequences=False?  I am dealing with time series data.  Thank you.

@mazharaliabro 'None' mostly refers to the batch size. In the standard way of defining the input size of the model, the first dimension is the batch size, but it is not yet fixed at the time the model is created. This is why it is unknown and thus is 'None'. If you want it fixed, then you need to use the parameter batch_input_shape(batch_size, time_steps, no_features) instead of input_shape(time_steps, no_features).

Hello, a quick question, please could someone help, it would be greatly appreciated! I'm struggling with understanding the LSTM input and I hope someone here could help me and confirm if what I am doing is right or wrong. To be clear, I do not get any errors, I just want to know if my reasoning is correct :) I am using Keras, the code is below.

I have 200 patients and for each patient I have a signal of 5 minutes that I split into 30 fragments of 10 seconds.
I extract 15 features from each 10 sec fragment. So each patient has a feature matrix of [30 time steps x 15 features].
My X data is thus the size of [200 patients x 30 timesteps x 15 features].
Every patient is binary classified as healthy "1" or sick "0".
My Y data is thus the size of [200 x 1].

As the input to an LSTM should be (batch_size, time_steps, no_features), I thought the input_shape would just be input_shape=(30, 15), corresponding to my number of timesteps per patient and features per timesteps.
When I use model.fit, I use my X (200,30,15) and Y (200,).
My question here is, am I doing this right? Is my model actually connecting per patient the [30 timesteps x 15 features] to the the binary classification of Y? I also do not really get if I need to specify a batch size at model.fit?
CODE
Build model
model = Sequential()
model.add(LSTM(128, input_shape=(30,15), activation='relu', return_sequences=True))
model.add(Dropout(0.2))
model.add(LSTM(128, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(1))
model.add(Activation('sigmoid'))
Compile model
opt = tf.keras.optimizers.Adam(lr=0.001, decay=1e-6)
model.compile(
loss='binary_crossentropy',
optimizer=opt,
metrics=['accuracy'])
Fit model
history = model.fit(x,
y,
epochs=20,
validation_split=0.1)

@Imvanpoppel
It seems like you're doing this right. As the shapes do not throw an error, this is what the model processes. If you are not sure, you can use the model.summary function to check if the network structure is actually the way you want it.
https://keras.io/api/models/model/#summary-method
You do not need to specify a batch_size. The API states:
"If unspecified, batch_size will default to 32."
https://keras.io/api/models/model_training_apis/
I'm not sure if you want the dropout within the LSTM layer or outside of it. In my understanding, you would rater like to have it inside. Especially since the training of LSTM units is very long, this outer dropout might slow down the training of the second layer.
Binary classification can be done that way. An alternative would use a Dense layer with softmax activation as last layer and a recoding of your classes to use a one-hot encoding instead of the one you use now.
I'm not sure about the validation_split, I've always done the splitting manually. To see if it worked as expected, you can plot the training history. I guess that you are - with only 20 epochs - underfitting the model.

@Chrisinger
Thanks you so much for the fast reply! Would you be willing to give me some of your knowledge on the following (I'm sorry its a lot, I really hope you can help me, thanks so much in advance). Again, it would be greatly appreciated, I need to do this for my thesis but I do not know anyone who could help me (it outside the scope of my studies).
I chose the structure a bit random,  I don't have a really good idea of what that should be yet and after reading/watching many tutorials, it's all still a bit difficult for me.
I'm not sure if I will need 1 or 2 layers, and how many units a layer should have. I get that I should try different architectures  and check the performance but do you have any idea what should be a good range or starting point is for the number of units? I read multiple "rules" that should give me an idea:
E.g. the neurons should be below this value:
𝑁ℎ=𝑁𝑠/(𝛼∗(𝑁𝑖+𝑁𝑜))
𝑁𝑖 = number of input neurons
𝑁𝑜 = number of output neurons
𝑁𝑠= number of samples in training data set
𝛼 = an arbitrary scaling factor usually 2-10
But for me this would result in this right?  200/(alpha*(30+2), which would give a really low amount.
Other rules of thumb on that forum are as follows:

The number of hidden neurons should be between the size of the input layer and the size of the output layer.
The number of hidden neurons should be 2/3 the size of the input layer, plus the size of the output layer.
The number of hidden neurons should be less than twice the size of the input layer.
Which would also give me below 30 neurons in the LSTM layer, which (looking at all the tutorials that use like 64 or 128) seems a bit small to me.

As for the dropout, could you explain what you mean with inside or outside (is inside like this: model.add(LSTM(128, dropout=0.5) ?) Also I'm not exactly sure what you suggest, should I move the dropouts inside, or do I need to remove the 2nd dropout? And if I end up using only 1 layers LSTM, should it then include a dropout? (Sorry, I just read it was useful for overfitting but I lack the knowledge to judge whether I need it and where)
As for the classification, I tried to use softmax, but I'm not sure how. I thought that it would be like this, with 2 neurons where the output is the probability for each of the classes:
model.add(Dense(2,activation='softmax'))
But then I get this error:
ValueError: A target array with shape (200, 1) was passed for an output of shape (None, 2) while using as loss binary_crossentropy. This loss expects targets to have the same shape as the output.
If I understand correctly, I'm asking for 2 outputs (the probabilities) but I only provide 1 output (1 or 0) per patient, which is why this doesn't work? You say I should use "recoding of your classes to use a one-hot encoding" but I lack the knowledge to understand that.
As for the number of epochs, if I use the model architecture I previously send, and use 20 and 100 epochs, I get this:
20:

100:

I'm sorry, again a question, I do get an error even though the model runs, but I read online on some forum that I could ignore it but maybe you know if its important:
WARNING:tensorflow:Entity <function Function._initialize_uninitialized_variables..initialize_variables at 0x7fb92ce738c0> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, export AUTOGRAPH_VERBOSITY=10) and attach the full output. Cause:
WARNING: Entity <function Function._initialize_uninitialized_variables..initialize_variables at 0x7fb92ce738c0> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, export AUTOGRAPH_VERBOSITY=10) and attach the full output.

@imvanpoppel
The bad new about the structure of neural networks: Noone knows in advance which network structure should be used. This depends on the nature of your data. So in your case: What are the 15 features that you create for your EEG recordings?
It maybe that a different network structure may be better suited - you are the only one who can find it out.
My first recommendation is to start with very simple models, they train very fast and you can get used to how the training works and check the results. Have you tried other simpler machine learning models? If not, I recommend decision trees for a start. They are much faster than neural networks and easy to interpret, and you do not need to decide numbers of neurons, activation functions, optimizers, etc.
Once they work, you can try to improve your performance by using more complex models, like random forests, support vector machines or neural networks. Again, when starting with neural networks, start with very small models like with 5 or 10 neurons just to get an intuition on the results. You can increase these parameters and play with them afterwards.
Second, I strongly recommend to use a cross-validation: In your figures, it seems to me that the outcomes differ significantly for 20 and 100 epochs. I guess this is caused by the fact that keras has used different splits. And with the current source code you cannot influence this split. Normally, one is interested in an accuracy, that serves as an estimate for new, unknown data. Therefore, you make several runs, with different random splits and look at the average outcome afterwards. This should be a better indicator that just one or two random runs.
Dropout: The computations within an LSTM are not trivial, they are explained nicely in colah's blog
https://colah.github.io/posts/2015-08-Understanding-LSTMs/
Again, I would start simple, without dropout, look at diagrams and the overall result. Then try a version with one dropout layer, see how it performs and so on. Yes, in the last message I meant to use dropout within the LSTM as you wrote it: LSTM(128, dropout=0.5). You can see in the diagrams if you should do something against overfitting: Normally at the beginning of the training, the loss on the training data and on the test data is reduced, as the model is being trained. But at some point the test
loss starts to increase again. This is the point where your model does not generalize properly - so although it keeps improving on the training data, it is getting worse on the test data. And this is what you want to prevent. This is why I recommend first to make some experiments, and add dropout later.
There are two ways to make models for a 2-class classification. One is what you applied, and the other one uses:
model.add(Dense(2,activation='softmax'))
But this then needs 2 output neurons and class 0 is not represented by a single number "0" anymore, but by a binary vector [1, 0]. The second class "1", would then be [0,1]. This is why there was an error, when gave the numbers, when keras expected binary vectors.
Aboput your warning in tensorflow: I have no idea, sorry. However, I hope that I could help. There may be some courses on coursera.com on basics of machine learning that might help you. Good luck!


Addition request - Loodse/Kubermatic

Please only report on one project or product per issue
Guidelines for getting added to the CNCF Cloud Native Landscape:

We generally will only list a company in one box, to represent its major or best known offering. We occasionally make exceptions for large companies.
Projects with at least 250 GitHub stars that clearly fit in an existing category are generally included.
We are unlikely to create a new category for products/projects as we'd rather find the best home with the current options.
We are generally not including commercial versions of open source software, when that version just includes minor tweaks.
Closed source products need to link to a clear description of your product; no stealth mode companies.
Your project or company needs a logo.

Project or Product name: Kubermatic
Is it open source? (if you are tempted to say partially, please answer no): No
What are the best URL(s) for it? Repo and homepage (if different) for open source, product homepage for closed source?: https://cloud.kubermatic.io/; https://loodse.com/en/
What one category does it best belong in?
Platform
What's the URL for the best logo (and it needs to include the name)?
https://we.tl/sJgEdim5uf
Anything else we need to know?:
New website providing more detail on Kubermatic to be launched early November

Hi @KrissiWi, we are including Kubermatic in the upcoming version, releasing soon! Thanks

Closing as this update was included in the most recent version https://github.com/cncf/landscape#current-version


Add NSubstitute.Analyzers.CSharp

Also need to validate whether projects that consume this package will also get the analyzer package.

This cannot be done because not all consumers of the Neovolve.Streamline.NSubstitute package will be using CSharp and the analyser packages are language specific.


segmentation fault when window size is bigger than buffer

crashes when using this code
use minifb::{Key, WindowOptions, Window};

const WIDTH: usize = 640;
const HEIGHT: usize = 360;

fn main() {
    let mut buffer: Vec<u32> = vec![0; 1];

    let mut window = Window::new("Test - ESC to exit",
                                 WIDTH,
                                 HEIGHT,
                                 WindowOptions::default()).unwrap_or_else(|e| {
        panic!("{}", e);
    });

    while window.is_open() && !window.is_key_down(Key::Escape) {

        // We unwrap here as we want this code to exit if it fails. Real applications may want to handle this in a different way
        window.update_with_buffer(&buffer).unwrap();
    }
}

rustc version
rustc 1.36.0 (a53f9df32 2019-07-03)
binary: rustc
commit-hash: a53f9df32fbb0b5f4382caaad8f1a46f36ea887c
commit-date: 2019-07-03
host: x86_64-unknown-linux-gnu
release: 1.36.0
LLVM version: 8.0

nevermind, didn't use the git version

Using 0.12 version (just released) should be fine also


Inconsistencies between the PR when it's viewed as checked out and not checked out

Hi guys, Can anyone shed some light on this for me? Great tool by the way 👍 I can't wait to see how it evolves over the coming months 😄
TL;DR
The Problem: I have a branch which is outdated against master. In Github and Github Pull Requests, the branch seems to be being compared the version of master that the branch was cut from. But when I checkout the branch using Github Pull Requests, the branch seems to be being compared to the latest version of master. See below for a more in depth explanation and some screenshots.
Detailed explanation:
When I view a PR through the extension without checking it out, the PR behaves the exact same as the PR does through Github.
I have pictures for this not checked out scenario:

You can see it's not checked out
I'm viewing the PR using the Github Pull Requests extension
Indicates the PR I'm looking at
Is verification that I don't have the PR checked out.

So here is the outdated code in the branch when viewed through Github Pull Requests:

I'm viewing the PR using the Github Pull Requests extension
Indicates I'm looking at the layouts/default.tsx file in the PR
Is verification that I don't have the PR checked out.
Verifies the outdated code isn't showing up as change in the PR

And this image verifies that the PR on Github behaves the very same:

So far, so good
But when I check out the code:

You can see it is checked out
I'm viewing the PR as checked out using the Github Pull Requests extension
Is verification that I have the PR checked out.

Then the outdated coded shows up as changes in the PR but I cannot comment on it:

I'm viewing the PR as checked out using the Github Pull Requests extension
Indicates I'm looking at the layouts/default.tsx file in the PR
Is verification that I don't have the PR checked out
Displays the outdated code in the branch
Illustrates the white line which indicates where I can comment

I hope this has been useful/helpful. If you need any more information please let me know.

Extension version:
VSCode Version: 1.27.1 (1.27.1)
OS: macOS High Sierra - 10.13.6 (17G65)

Steps to Reproduce:

Open a PR on a branch which is outdated against master

@woppers Sorry, I missed this earlier!
There are two different code paths for how file changes are displayed before and after checkout, but they should show the same diff, so I think this is actually a bug.
Before check out, there is some chance that the changes don't exist locally - if you haven't fetched recently, you may not have the commits on disk to compare. So to handle this the git extension relies more heavily on GitHub, it fetches the change patches and attempts to reconstruct the files.
During the checkout, we switch to the PR branch and run fetch, so we assume we have the commit locally. We use git show with the file path and the head sha and base sha for the PR to get the file content for each of those commits and diff that content.
Just to clarify, by "outdated against master", you just mean some commits behind it?

This should be fixed as part of https://github.com/Microsoft/vscode-pull-request-github/commit/6d11839cbca6e35f1f2b6827122bbabc0e10a573, we were using a different commit for the base file in the "Changes in Pull Request" tree


Make throttling nmagent fetches for nodesubnet more dynamic

Reason for Change:
We previously added fetch of secondary IPs to the NMAgent client in CNS. This PR makes the fetch asynchronous, with the ability to adjust the frequency dynamically. Specifically,

Min and max interval between fetches can be configured
Frequency is cut in half (interval doubled) if no diff is seen, up to the max interval.
Min interval is used as soon as a diff is seen

This is implemented using a time Ticker, but we wrap it with a wrapper so as to mock it for tests. This PR also includes some additional checks for empty responses from the nmagent (this was raised in this comment). Also have UTs.


Is not loading element inside body

Hi,
I added the plugin to my site with a container of fixed height and overflow scroll; and binding it with $('.homeSlider').panelSnap({ strictContainerSelection: false });
I am missing something to make it work?
Thanks,
Alberto

Well, if you read the documentation, your selection is not set up properly. This should fix your implementation:
$('.homeSlider').panelSnap({ panelSelector: '> li' });

It worked, thanks!


Details regarding IKEv2 support of Basic SKU out of date?

The answer to this question states the following:

Note that the Basic SKU does not support RADIUS or IKEv2.

From reading much of the other documentation, it sounds like the Basic SKU has recently been updated to support IKEv2 (in fact, it sounds as though it's now only IKEv2). The statement regarding this is here where it states:

Traditionally we allowed IKEv1 connections for Basic SKUs only and allowed IKEv2 connections for all VPN gateway SKUs other than Basic SKUs. The Basic SKUs allow only 1 connection and along with other limitations such as performance, customers using legacy devices that support only IKEv1 protocols were having limited experience. In order to enhance the experience of customers using IKEv1 protocols, we are now allowing IKEv1 connections for all of the VPN gateway SKUs, except Basic SKU.

My understanding may be incorrect as I haven't actually deployed a Basic gateway recently to test, but wanted to raise this as a potential inconsistency.

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

ID: 98d7fd30-80a8-f690-6191-d97ae4cac174
Version Independent ID: 3e15f99b-2f2d-7adc-a2d9-0b2184989db7
Content: Azure VPN Gateway FAQ
Content Source: articles/vpn-gateway/vpn-gateway-vpn-faq.md
Service: vpn-gateway
GitHub Login: @yushwang
Microsoft Alias: yushwang

@theonlycoder , thank you for the feedback. We'll review this and get back to you shortly!

@theonlycoder , below is the correct information regarding Basic SKU VPN gateway:
IKEv1 connections can be created on all RouteBased VPN type SKUs, except the Basic SKU, Standard SKU, and other legacy SKUs.
Refer : https://docs.microsoft.com/en-us/azure/vpn-gateway/vpn-gateway-about-compliance-crypto#how-do-i-create-connections-with-ikev1-or-ikev2-protocol-type
And the below table shows the IKE version support for Basic SKU:

Refer : https://docs.microsoft.com/en-us/azure/vpn-gateway/vpn-gateway-connect-multiple-policybased-rm-ps#azure-support-for-policy-based-vpn
But the statement in this doc seems incorrect and we will work on it in your other issue # https://github.com/MicrosoftDocs/azure-docs/issues/77353
We are closing this issue for now. If there are further questions regarding this matter, please reply and we will gladly continue the discussion.

Hi @GitaraniSharma-MSFT, thanks for taking a look.
From the information you provided it sounds as though my issue is valid. The Basic SKU does support IKEv2, but the answer to the FAQ question says it does not. Please let me know if I have misunderstood.
Thanks again


Change the severity of the linting issues.

Currently, the severity of the SQLfluff linting issues are at the severity level Error this seems to be hardcoded here. However, these linting issues are very unlikely to actually be an error. Instead, this should probably be hint or warning. It would be great if you were able to select this in the settings.

@Luttik In v0.1.5 I have added the option sqlfluff.linter.diagnosticSeverity and sqlfluff.linter.diagnosticSeverityByRule that allows you to set the default diagnostic severity and the severity for each rule.


Fixed #696

I still need to visit the microsite which may require some updating of the example function signatures etc, some renaming.

@Cereopsis Is this ready for final review / merge?

@jdegoes Apologies, I couldn't get to it at the weekend, hope o do so in the next couple of days.

@Cereopsis No worries, just let me know when you're ready!

@jdegoes I have no idea where the last 8 days went! Hopefully all good now. I have to say I spent a bit of time understanding the subtleties of the various resource management approaches.

@Cereopsis Love this pull request! Hopefully more people will use reserve now. 😄


chore: upgrade typescript

Overview

Updates Typescript to 5.1.3

PR Checklist

[ ] Related to designs:
[x] Related to JIRA ticket: [web-2378]
[x] I have run this code to verify it works
[x] This PR includes unit tests for the code change
[x] This PR includes testing instructions tests for the code change
[x] The alpha package of this PR is passing end-to-end tests in all relevant Codecademy repositories

Testing Instructions

Check out the PR locally
Confirm all the checks pass and there are no errors
Click around storybook + confirm everything looks fab
Rinse + repeat for the monorepo + monolith PRS
...Profit!

PR Links and Envs

Repository
PR Link
PR Env

Monolith
Monolith PR
Monolith Env

Monoreop
Portal PR
Head to the monorepo PR!

📬Published Alpha Packages:@codecademy/gamut-kit@0.6.330-alpha.dbf1bc.0@codecademy/gamut-labs@35.15.3-alpha.dbf1bc.0@codecademy/gamut@55.1.8-alpha.dbf1bc.0@codecademy/monaco@0.7.34-alpha.dbf1bc.0<EMAIL_ADDRESS>
🚀 Styleguide deploy preview ready!https://6495f05a9a87657658f9bc6e--gamut-preview.netlify.appDeploy Logs

📬Published Alpha Packages:@codecademy/gamut-kit@0.6.334-alpha.85a5a8.0@codecademy/gamut-labs@35.15.7-alpha.85a5a8.0@codecademy/gamut@55.1.12-alpha.85a5a8.0@codecademy/monaco@0.7.38-alpha.85a5a8.0<EMAIL_ADDRESS>
📬Published Alpha Packages:@codecademy/gamut-kit@0.6.334-alpha.2bd4e6.0@codecademy/gamut-labs@35.15.7-alpha.2bd4e6.0@codecademy/gamut@55.1.12-alpha.2bd4e6.0@codecademy/monaco@0.7.38-alpha.2bd4e6.0<EMAIL_ADDRESS>
🚀 Styleguide deploy preview ready!https://64b95339d271a8151ef616ac--gamut-preview.netlify.appDeploy Logs

📬Published Alpha Packages:@codecademy/gamut-kit@0.6.334-alpha.e0f0d3.0@codecademy/gamut-labs@35.15.7-alpha.e0f0d3.0@codecademy/gamut@55.1.12-alpha.e0f0d3.0@codecademy/monaco@0.7.38-alpha.e0f0d3.0<EMAIL_ADDRESS>
🚀 Styleguide deploy preview ready!https://64b96e172a45852e22ac9ac3--gamut-preview.netlify.appDeploy Logs

📬Published Alpha Packages:@codecademy/gamut-illustrations@0.39.0-alpha.23e645.0@codecademy/gamut-kit@0.6.334-alpha.23e645.0@codecademy/gamut-labs@35.15.7-alpha.23e645.0@codecademy/gamut@55.1.12-alpha.23e645.0@codecademy/monaco@0.7.38-alpha.23e645.0<EMAIL_ADDRESS>
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lgtm w/ the yarn.lock removal 👍 @jakemhiller

the version of storybook we're using won't build with just the newer TS version - i'm gonna see if there's a version of SB that fixes it w/o a full SB upgrade

📬Published Alpha Packages:@codecademy/gamut-kit@0.6.335-alpha.8442f0.0@codecademy/gamut-labs@35.15.8-alpha.8442f0.0@codecademy/gamut@55.1.13-alpha.8442f0.0<EMAIL_ADDRESS>

lgtm w/ the yarn.lock removal 👍

@jakemhiller tried the fix detailed here + it seems like its working now, lmk if it seems alright!


Doubts About Training Time

Hi @JeditPro.
To train from scratch, you need colab pro or pro+, because you need a machine to work with long time (24 hours max). To see how is going the model from scratch, you can see through tensorBoard.
Fine-tunning depends on the dataset but can take 4-6 hours to get good results. You can see tensorBoard in this case too.
Continue training is available if version 0 exists.


Add old classes and methods to trick JsonClientCaller

.. which still uses the login(user, pwd) methods

Is there a list of services that need to have those calls available?

All core java services, pretty much

Enough that need it to compile, so we need to maintain it, even though it's a dead-end function. Annoying, but I get it.


Plotting script: Plot DDG

Plot the DDG per system and the DDG for all systems combined.

Also plot the repeat runs against each other to look for differences.


Update age_load to make property value conversion optional

This is an addition to a previous patch that introduced loading
property values from CSV files as agtype. This behavior is
made optional in this patch with a boolean function parameter
load_as_agtype. When this parameter is false, values are
loaded as string.

@jrgemignani @muhammadshoaib This patch makes the age_load test finish in ~same time as before.


Add dask.bag.zip

Towards https://github.com/dask/dask/issues/1023
r @mrocklin

Things considered along the way and punted on to limit scope / keep it simple:

I considered adding more general zip(*bags, zipfunc=zip) and zip_longest(*bags, fillvalue=None) however:

combining *arg and specific key=value args isn't supported in py2; we'd have to take a fully general **kwargs, and manually (or not) validate it
the use case for zip_longest in this case is tenuous, since if your partition lengths don't match, it's most likely due to something like a filter (or something even weirder); in this case you really need indexed data alignment like pandas provides, and probably don't want to zip your data together

db.range really should act more like real range and take start/step; it would simply at least the example and test code for zip

I feel like there's room to add a convenience layer after this PR, something that lets you do:
records = dask.bag.from_something(...)
stuff = records.pluck('A')
stuff = stuff.zip(records.pluck('B'))
...

Essentially:

Bag.zip :: func(bag) Zip
Zip.zip :: func(bag) Zip // but this one appends on to the end of the growing zip, rather than creating a stair case of (((a, b), c), d) result tuples

Overall this looks good, thanks for the PR! One caveat about this approach is that it will silently drop data if the number of partitions in each bag is equivalent, but the length of each partition is different.
>>> x = db.from_sequence(range(20), npartitions=3)
>>> y = db.from_sequence(range(30), npartitions=3)
>>> z = db.zip(x, y)
>>> z.compute()
[(0, 0),
 (1, 1),
 (2, 2),
 (3, 3),
 (4, 4),
 (5, 5),
 (6, 6),
 (7, 10),
 (8, 11),
 (9, 12),
 (10, 13),
 (11, 14),
 (12, 15),
 (13, 16),
 (14, 20),
 (15, 21),
 (16, 22),
 (17, 23),
 (18, 24),
 (19, 25)]

There's not an easy way around this limitation though, but it might be good to but a disclaimer in the docstring.

Disclaimer in docstring sounds good.  We could also make a special zip function that raised an error at runtime.

In general I agree that this looks really nice.  Thank you especially for the docstring, simple code, and tests!

Updated with a disclaimer and an example of why zip_longest probably isn't what's wanted in this context

This looks good to me. If you want, add yourself to AUTHORS.md, and I'll merge. Thanks!

Added

+1


Intagram Reels Clone

Description
Instagram Reels Clone

Code of Conduct

[X] I follow Contributing Guidelines of this project.

/assign


[cleanup][broker]: Refactor PulsarAuthorizationProvider.

Motivation
PulsarAuthorizationProvider has many duplicate codes and some logic is un-readable.
Modifications

canConsumeAsync : remove permissionFuture
allowConsumeOrProduceOpsAsync: Using Set to avoid duplicate codes.
grantPermissionAsync: make fully async.
checkPermission: make fully async.
path : remove this unsed method.

Documentation

[x] no-need-doc

@Technoboy-  I notice that no tests to cover the PulsarAuthorizationProvider, could you add some tests for this?

@Technoboy- I notice that no tests to cover the PulsarAuthorizationProvider, could you add some tests for this?

Integration test has coverage this.


Ruby/ImageMagick issue: checks hang with no output

Describe the bug
From this community question: https://github.community/t5/GitHub-Actions/Checks-hang-with-no-output/td-p/46658
There seems to be an intermittent issue that below 2 combinations will hang at commend 'bundle exec rake' sometimes: "ruby 2.6 + IM6.7/6.8".
However it passed consistently on CircleCI and local server.
Area for Triage:

Question, Bug, or Feature?:
Bug
Virtual environments affected

[ ] macOS 10.15
[ ] Ubuntu 16.04 LTS
[x] Ubuntu 18.04 LTS
[ ] Windows Server 2016 R2
[x] Windows Server 2019

Expected behavior
Checks should pass or fail, but not hang.
Actual behavior
Checks hang with no output.
cc @weide-zhou

Hello @gimenete , Could you please double check if the issue is still actual?

Hi @weide-zhou! Few images were rolled out since your original issue, could you please check if the issue still appears for you?

Closing this issue since we didn't get any confirmation the issue is still actual.
If it continue happening, please, feel free to file a new issue.
Thanks!


Error when releasing end user access licenses

What version of Butler are you using?
13.1.0
What version of Node.js are you using? Not applicable if you use the standalone version of Butler.

What command did you use to start Butler?

What operating system are you using?

What CPU architecture are you using?

What Qlik Sense versions are you using?

Describe the Bug
Dry run enabled.
Not clear where "u" is used, most likely in some imported module.
2024-10-24T08:50:35.294Z info: QLIKSENSE LICENSE RELEASE PROFESSIONAL: Dry-run enabled. No licenses will be released
2024-10-24T08:50:35.320Z info: [QSEOW] INFLUXDB QLIK SENSE LICENSE STATUS: Sent aggregated Qlik Sense license status to InfluxDB
2024-10-24T08:50:35.371Z error: [QSEOW] QLIKSENSE LICENSE RELEASE: TypeError: u is not iterable
2024-10-24T08:50:35.372Z error: [QSEOW] QLIKSENSE LICENSE RELEASE: TypeError: u is not iterable

Expected Behavior
No response
To Reproduce
No response

Caused by missing check if neverReleaseUsers indeed contains any data.
In qliksense_license.js around line 620
            // Check do-not-release user names
            for (const user of neverReleaseUsers) {
                if (license.user.userDirectory === user.userDir && license.user.userId === user.userId) {
                    doNotRelease = true;
                    doNotReleaseReason = 'User is in the neverRelease.user list';
                    break;
                }
            }

Should be
            // Check do-not-release user names if there are any
            if (neverReleaseUsers?.length > 0) {
              for (const user of neverReleaseUsers) {
                  if (license.user.userDirectory === user.userDir && license.user.userId === user.userId) {
                      doNotRelease = true;
                      doNotReleaseReason = 'User is in the neverRelease.user list';
                      break;
                  }
              }
            }

Also do similar change before accessing neverReleaseTags, neverReleaseCustomProperties and neverReleaseUserDirectories arrays.


add Microsoft unobtrusive validation

fix regex for names so it can be used both in .Net & JS.
Add aspnet unobtrusive validation to dynamically use .Net DataAnnotations in JS client (with custom adapter for custom password validation).

@VadymLevkovskyi untested code is only JS code, we don't have JS tests setup yet so can't do 80% coverage :(


Code block comments ('#', '//') are not transferred through

Hey bud, found out about this library yesterday and I love it!
One thing I noticed is that comments in code blocks are not being transferred to the downloaded md file.
For example, this code block:
// import socket class
import Socket from '../socket';

Will give this output:

import Socket from '../socket';

Another thing that I noticed is that the language type is also not transferred (e.g: js, yaml, etc..). I don't know if it's something that is easy to implement but it will definitely be a neat addition
Thanks!

So, here's a thing. If I try and use markdownload to get the text from your post there, I do get the comments, but I don't actually get it as a code block. Not sure why 🤔
In the meantime, could you provide me with a link to a different page to test with where you are getting code blocks but are losing comments?

@deathau Interesting, I'll play around with the code block extraction feature more today to see if I can zero in on the issue.
This is the link I used: https://snassr.io/post/0002_goreactsockets/

Hi, just wanted to say this is still an issue. Comments or any lines in code blocks starting with # are still not coming through. If there are multiple, the first comes through but not the subsequent one or the rest of the line.
I was trying on this page: https://www.nicholas-ollberding.com/post/wrench-normalization-for-sparse-microbiome-data/

I think I might've fixed this by adding better support for pre as code blocks in this commit: https://github.com/deathau/markdownload/commit/5fb11ae8cf2afff94bb710f19c47268ad56ce646


Add design doc for the network router feature

More details and running code in #981

The diagrams are via https://excalidraw.com. If exported as described below you can simply drag the PNG into excalidraw to edit it. The embedding is simply JSON. Worth a consideration since its much easier to draw detailed docs than other tools and its shareable via the process below.
export the Excalidraw drawing as a PNG and select the Embed Scene option. Excalidraw will embed the JSON inside the PNG file and the PNG file can be edited by simply dragging it onto the Excalidraw website. The PNG is completely compatible with browsers and other applications though.

Honestly, I felt confused after reading this because now I'm not sure I understand what --child-prefix is for by itself. What does it do specifying that option by itself?

We had a live discussion about this and I understand better now. --child-prefix by itself does not set up any routing for the prefix. It works for either:

An IP range that's local to the nexd device, like containers running on that host.
An IP range that a user has set up routing for manually.

TODO

Add a future enhancement idea of a flag that allows routing traffic into a Nexodus network with SNAT but without specifying any prefixes to advertise


Support BIGTIFF

Pretty self exaplantory, aiocogeo doesn't currently support BIGTIFF. https://github.com/geospatial-jeff/aiocogeo/blob/950ea55e3a885bbd3b9123ebc51c398403e13d44/aiocogeo/cog.py#L88

@geospatial-jeff I would be interested in working on this. We're hoping to productionize COGs at DroneDeploy in a few months and BIGTIFF support would be very nice to have. I'm not an expert with the TIFF specification though...is this just a matter of doubling the number of bytes read for each offset or is there more complexity lurking in the shadows? I suppose I can look at the GDAL/libtiff implementation?

@geospatial-jeff I would be interested in working on this. We're hoping to productionize COGs at DroneDeploy in a few months and BIGTIFF support would be very nice to have. I'm not an expert with the TIFF specification though...is this just a matter of doubling the number of bytes read for each offset or is there more complexity lurking in the shadows? I suppose I can look at the GDAL/libtiff implementation?

is this just a matter of doubling the number of bytes read for each offset

AFAIK this is correct, but I am also not an expert in BIGTIFF
Here are some other implementations to look at in addition to GDAL/libtiff.  I would start with COGDumper since the initial aiocogeo code was based on that project.

COGDumper - https://github.com/mapbox/COGDumper
geotiff.js - https://github.com/geotiffjs/geotiff.js

is this just a matter of doubling the number of bytes read for each offset

AFAIK this is correct, but I am also not an expert in BIGTIFF
Here are some other implementations to look at in addition to GDAL/libtiff.  I would start with COGDumper since the initial aiocogeo code was based on that project.

COGDumper - https://github.com/mapbox/COGDumper
geotiff.js - https://github.com/geotiffjs/geotiff.js

Not sure if anybody still needs this or not, but I needed something like this for some images I was accessing. I had trouble understanding how it all worked, so was reluctant to make pull request. Instead, to allow me to understand it, I wrote my own package, available at https://gitlab.com/jrsrp/sys/asyncog. It's pretty much a crappier and more limited version of  this package, but I learned a lot about COGs on the way. But maybe it would be useful to others, even if just to encourage someone to do this the right way, and add BigTiff support to aiocogeo.


adds style section to CONTRIBUTING

This is a starting point for the Python 3 CONTRIBUTING changes we discussed while reviewing #328. I couldn't think of any changes other than string formatting off the top of my head, but that list should probably get longer at some point.
I've taken the liberty of also mentioning PEP8 and import sorting. isort is the tool I used here and I think it's nice.
Feel free to propose things to add/remove. I tried to describe how we already do things and not to impose anything new.

+1

Thanks Jim for that addition. +1


Added some German road signs that don't fit into europe.cson

danger_level_crossing
information_bus_stop
priority_priority_road_end
prohibitory_end_of_limits
prohibitory_low_emission_zone
prohibitory_low_emission_zone_end

Amazing as always, thanks! :+1:


unrelated question

I'm sorry, this is the only way i could think to contact you.
i was wondering if you ever found a solution to this issue you had?
https://github.com/pterodactyl/panel/issues/3885

I'm sorry, this is the only way i could think to contact you.
i was wondering if you ever found a solution to this issue you had?
pterodactyl/panel#3885

Hello there the solution is to make an VM of Debian (or have an server with debian aside of unRAID(os) then put wings on it, and then Garry's mod, In fact some game like GMOD cannot be run docker in docker, like if Wings are aleadry on Docker some game on Steam won't work like gmod for dark reason, I didn't searched a lot why and how, but I guess it's from steam Download ect.


Make the Contact Us! form actually send the message to your mail ID. #166

Last pull request (#166) was closed automatically due to inactivity of owner, kindly accept, merge  this PR and assign GSSoC lvl.
Thank you!

when navigating to the offers web page from the service page showing "Page Not Found"
Could you solve this Error in your PR to safely merge your contribution into main?

Task Accepted, issue created in repository.
Issue found and resolved in services.html. Kindly visit issue #906 and
accept my PR with gssoc labels.
Thank you.
On Tue, Jun 4, 2024 at 12:12 AM Sukhbir Singh @.***>
wrote:

when navigating to the offers web page from the service page showing "Page
Not Found"
Could you solve this Error in your PR to safely merge your contribution
into main?
—
Reply to this email directly, view it on GitHub
https://github.com/khushi-joshi-05/Food-ordering-website/pull/848#issuecomment-2145884340,
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You are receiving this because you were assigned.Message ID:
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Problem with compile openwrt with luci package

Without Luci - it compile without problem.
If i chose in menuconfig luci - i have main error at stage of compiling the openwrt:
(compile without the root rights)
install -d -m0755 /bin
install -m0755 src/po2lmo /bin/po2lmo
install: cannot create regular file '/bin/po2lmo': Permission denied
...
and Error

If i compile with root rights - I have NO this error...
64-bit /Ubuntu / 2 Core

Your OpenWrt source it too old for this version of LuCI. Either update your OpenWrt or use an older LuCI release.

In partcular you need commit https://github.com/openwrt/openwrt/commit/7d7858f6f1b95f1f11e02bb0e6e386f4fa93bcf5


SqlServerDsc: Updated the handling of multiple AppVeyor jobs

Pull Request (PR) description

Updated the appveyor.yml to have the correct build step, and also
correct run the build step only in one of the jobs.
Improved the handling of different AppVeyor jobs per the same way as was done in xPSDesiredStateConfiguration. *Already and change log entry for this.

This Pull Request (PR) fixes the following issues
No issue for this
Task list

[x] Added an entry under the Unreleased section of the change log in the CHANGELOG.md.
Entry should say what was changed, and how that affects users (if applicable).
[ ] Resource documentation added/updated in README.md.
[ ] Resource parameter descriptions added/updated in README.md, schema.mof
and comment-based help.
[ ] Comment-based help added/updated.
[ ] Localization strings added/updated in all localization files as appropriate.
[ ] Examples appropriately added/updated.
[x] Unit tests added/updated. See DSC Resource Testing Guidelines.
[x] Integration tests added/updated (where possible). See DSC Resource Testing Guidelines.
[x] New/changed code adheres to DSC Resource Style Guidelines and Best Practices.

This change is

Codecov Report

Merging #1277 into dev will decrease coverage by 3%.
The diff coverage is n/a.

@@          Coverage Diff          @@
##            dev   #1277    +/-   ##
=====================================
- Coverage    97%     93%    -4%
=====================================
  Files        35      35
  Lines      4311    4311
=====================================
- Hits       4208    4040   -168
- Misses      103     271   +168


Wiggler source size calculation

Hello,
I have a problem when tracing a wiggler source using shadowoui. The sizes of source it gives are different from that of Spectra with the same parameters. It gives 118 micron x 35 micron with two distinct spots as shown below while the Spectra gives 1940 micron x 160 micron.

Is there a problem here in my settings?
Thank you for any help,
Zimeng Wang

Dear Zimeng,
everything depends on what you call source size. Your settings look correct.
What you get in the plot is the cartesian projection of the rays on the (x,z) plane. But this is not the size, as the effect of the depth is ignored.
In order to get into account the depth you can propagate the source to a screen in the far field, and then backpropagate to the source plane again. Or, similarly the use of a sort of "ideal lens" or ideal mirror to make a 1 to 1 image.
I prefer to "propagate" all the rays to the (x,z) plane (not project!) just by adding a PlotXY widget and retracing to a distance zero. This will calculate the intersection of every ray in the (x,z) plane and gives a better idea of the source size:

You see that the image has a Lorentzian shape typical of a source with depth. Pay attention to the dimensions: FWHM is 934 x 83 um but the sigmas are: 1890 x 130 um. The vertical size depends much on the energy range.  For a Gaussian distribution FWHM=2.35 sigma, and here sigmas are higher than FWHM because of the long tails of the Lorentzian.
I hope this helps!.
Regards, Manuel

Dear  Manuel ，
Thank you very much! This really helps!
Best,
Zimeng

You're welcomed!


Define/Find lat/lon of alp border

For #1 the location of all points in the alps is needed. First of all the border of the alps has to be defined. For that research needs to be done.
After the border is definded a grid of points can be inserted into it. The grid resolution can be calculated via the scale of the model and the nozzle size of the 3D printer.

Done, even more than required actually.
There is a hexgrid of the alps existing right now as a geojson. Next steps from here:

extract centroids of the hexagons
querry height of centroids and add as property to each centroid
there are 3 dimensions for all points in the alps now (with given resolution)
use 3D point cloud to make stl


moving some GE tests to stable and fixing some timing issues

Critical Changes
Changes
Issues Closed
Community Ideas Delivered
New Metadata
Deleted Metadata

closing as not needed anymore


Option to hide the JSON/Table/Help pane via URL Parameter

Would be great to have an additional URL param that will change body class="fullscreen" for hiding the JSON/Table/Help panel.

I would also love to see this option.

So GeoJson.io is no longer being developed? I ask because this was closed with a "wontfix", sounds kind of final.

See the readme.


Add Spartan to the themes page

Thanks Francesco! http://jsonresume.org/themes/

That's great. Thank you! People likes more this, check it out https://github.com/francescoes/jsonresume-theme-stackoverflow

Added!
I should have done this  a long time ago =D
In the future, if I am slow again, just pull request this file -> https://github.com/jsonresume/resume-website/blob/gh-pages/_data/themes.yaml


doc: Do not fail when manually authored doc file is not tracked by git

This fixes a bug where a newly created documentation file not yet tracked by git would cause the documentation generation to fail.

@simhein this should fix your problem, please give it a try!

@simhein this should fix your problem, please give it a try!

Works great thank you!


Djangonaut.Space Logo and Motto

"Helping django professionals lift off!" < work in progress

use the "dj" of django inside the rocket

@dawnwages  i think this is done?

Where contributors launch!


COVID-19 Updates

Update the COVID-19 notebook with information on cases per day and vaccinations
Update data-set
Added script to pull Synthea CSV output and replace the data-set

@babraham33 On Point 1 (Cell 17) - I think this is a case where better documentation would be helpful. We were building tables to replicate one of the early COVID-19 studies. What "percent survivors" means is the number of people who had COVID-19 and Sepsis (in the first row) during an inpatient admission and survived divided by the number of people who had COVID-19 during an inpatient admission and survived. "percent non survivors" is the number of people who had COVID-19 and Sepsis (in the first row) during an inpatient admission and died divided by the number of people who had COVID-19 during an inpatient admission and died.
So it's really saying, out of all of the survivors, how many had sepsis? Out of all of the non-survivors, how many had sepsis? (almost all)
I'll update the documentation to better explain that.

@babraham33 I've made changes in response to your comments. The only thing I didn't address was 3, because it looks like the description was copied and pasted from 2.


[tcat] implementation of TCAT general class commands.

Commit introduces implementation of missing general class commands:

PresentPskdHash
PresentPskcHash
PresentInstallCodeHash
RequestRandomNumChallenge
RequestPskdHash

Also include minor fixes in Tcat python client and refactoring of expect tests for tcat.

@arnulfrupp @EskoDijk FYI

@jwhui @abtink  the CI fails on establishing TLS connection due to missing backend argument in load_der_x509_certificate
This was removed in version 36: https://cryptography.io/en/latest/changelog/#v36-0-0
Where can I bump it since the only place I can see it's set is https://github.com/openthread/openthread/blob/main/third_party/mbedtls/repo/scripts/ci.requirements.txt#L20 ?

@EskoDijk Thanks for review.

@EskoDijk looks like all your comments were addressed. Can I count on +1 from you?

@EskoDijk looks like all your comments were addressed. Can I count on +1 from you?

Yes, ok. I did see Arnulf's comments on the fact that proof-of-possession (of PSKc/PSKd) is not yet used in making the Commissioner authorization decisions. Not sure if this was already planned for a next PR (I think it was?) but I just wanted to mention that. So the command class implementation is effectively incomplete with this PR only.

@arnulfrupp
Please check the newest version of the code it should address Your comments.

Thank you for this contribution. Approved from my side.

@EskoDijk looks like all your comments were addressed. Can I count on +1 from you?

Yes, ok. I did see Arnulf's comments on the fact that proof-of-possession (of PSKc/PSKd) is not yet used in making the Commissioner authorization decisions. Not sure if this was already planned for a next PR (I think it was?) but I just wanted to mention that. So the command class implementation is effectively incomplete with this PR only.
So +1 for me (I can't enter an official review for this item).

@jwhui it looks that everyone accepted the PR. Can we merge it?


Replace AsSliceU8 trait with zerocopy::AsBytes

Padding is uninitialized: Glossary - Unsafe Code Guidelines Reference
We do not check for padding, neither is AsSliceU8 unsafe.
zerocopy::AsBytes performs these checks.

Hi @mkroening! @scotran and I are part of a Virtualization course at UT Austin, and as part of a project we have to contribute to open source repositories. Can we take up this issue?

Sure, do you want to do all three issues?
PS: To assign @scotran, he has to be a participant of this issue. Just write anything, then I can add him as well.

Hi @mkroening! I was able to switch the VirtioNetHdr from implementing AsSliceU8 to deriving AsBytes, but I ran into an issue when trying to change from AsSliceU8 to AsBytes for the Cmd and Rsp structs (https://github.com/hermitcore/libhermit-rs/blob/master/src/fs/fuse.rs#L293): #[derive(AsBytes)] is not supported on types with type parameters. Digging around, there seems to be a workaround (https://github.com/google/zerocopy/issues/10), but this would require using repr(transparent), which then cannot be used alongside repr(C) or repr(packed), which would strip padding and possibly cause alignment issue.
I just wanted to touch base first as to whether this would be the desired approach, and if so, I can continue looking into how to derive AsBytes for structs with type parameters.

Just as an aside, there is a proposal for DynSized, with a very similar purpose to our AsSliceU8: https://github.com/rust-lang/rfcs/pull/3536

AsSliceU8 was removed with #1316. I think we can close this issue.

Superseded by https://github.com/hermit-os/kernel/pull/1316


Query for tx audit reporting

Transaction id
Commerce id
Item type
Description
Time stamp

Reference:
https://forums.counterparty.io/discussion/703/sec-rule-613-consolidated-audit-trail#latest

Want to back this issue? Post a bounty on it! We accept bounties via Bountysource.

The URL changed due to domain change: https://counterpartytalk.org/t/sec-rule-613-consolidated-audit-trail/472
This can be closed, it's an old feature request.


feat: use packaging to parse requirements

PR Checklist

[x] A description of the changes is added to the description of this PR.
[ ] If there is a related issue, make sure it is linked to this PR.
[x] If you've fixed a bug or added code that should be tested, add tests!
[ ] If you've added or modified a feature, documentation in docs is updated

Description of changes
This is something that has been on my mind for quite some time now.
We currently rely on several regexes to parse dependencies in requirements files. Although this allows parsing formats that pip handles, there are many formats that PEP 508 does not cover, as both remote dependencies and local dependencies need to follow <package> @ <path> format. Even pip documentation suggests to use PEP 508 format.
The usage of regexes itself definitely makes the parsing best-effort, but it could also creates some false positives, as for instance for what looks like git URLs, we try to guess where the package name is, based on the git project name in the URL, which could depend on the git server used, or, worse, the git project name could be different than the real Python package name.
This PR suggests using packaging, maintained by PyPA, to parse dependencies where we expect PEP 508 format to be used (requirements files, PEP 621 metadata). This would remove support for URLs that do not follow PEP 508 dependencies, so this is a breaking change we would have to mention in the changelog, if we effectively want to go this way.

I do like the idea of using packaging to extract the dependencies, instead of using our own regexes, I think that is an improvement. As I understand; the only breaking change that we are aware of is for parsing requirements in requirements.txt in one of the following forms, right?
https://github.com/urllib3/urllib3/archive/refs/tags/1.26.8.zip
git+https://github.com/baz/foo-bar.git@asd#egg=foo-bar

In the link you share to the pip documentation, they suggest use PEP 508 format for installing installing from a package index. But they also show that they support other formats for packages that do not come from a package index.
Can we maybe do both for requirements.txt files? First try to extract the dependency with packaging, and if that fails, use a regex to extract the URL? Or maybe we can use something different completely?  e.g. https://pypi.org/project/requirements-parser/

Can we maybe do both for requirements.txt files? First try to extract the dependency with packaging, and if that fails, use a regex to extract the URL? Or maybe we can use something different completely? e.g. https://pypi.org/project/requirements-parser/

Between the 2 options, I'd personally prefer the first one, as packaging will not only be used to parse dependencies in requirements.txt files, but also in other formats that support PEP 508 (for instance [project.dependencies] in pyproject.toml.
I still think though that trying to guess the package name from a random URL on which we have no real control on feels quite hacky, even if most of the time this should give the user the expected result.
I'll put back the PR as a draft for now until I find the time to get back to this.


Missing downloads

https://getoutline.org has no downlink for the Android client. Only to the playstore - not everybody has access to that, specially in countries you really need it.
Solution:
Add link to APK
On Github I found a page with planty of Android daily releases - but the latest stable is missing.
https://github.com/Jigsaw-Code/outline-client/releases
Solution:
Add or mark latest stable release.
Current workaround for the brave:
Get whatever is claimed 'latest' from some sort of APK warez sites.

Hi @4044ever, thanks for the feedback. We tag the latest stable releases with their version (i.e. Android v1.1.1). Additionally, you can find the Android and Windows clients at outline-releases. The Apple clients must be distributed through the App Store due to the entitlements they require so we do not offer downloads for these.


Add Color settings

Include Colorized gem dependency and colorized log option

Nice! Merged and published as 0.2.14. Thanks!


[flutter_tools] _CastError in flutter_adapter_args.dart

In Flutter beta/3.1.0
Command flutter debug_adapter --test
_CastError: type '_InternalLinkedHashMap<String, dynamic>' is not a subtype of type 'Map<String, String>?' in type cast
at new DartCommonLaunchAttachRequestArguments.fromMap(dart.dart:220)
at new FlutterLaunchRequestArguments.fromMap(flutter_adapter_args.dart:109)
at FlutterLaunchRequestArguments.fromJson(flutter_adapter_args.dart:154)
at BaseDebugAdapter.handle(base_debug_adapter.dart:112)
at BaseDebugAdapter._handleIncomingRequest(base_debug_adapter.dart:286)
at BaseDebugAdapter._handleIncomingMessage(base_debug_adapter.dart:273)
at ByteStreamServerChannel._readMessage(protocol_stream.dart:82)
at ByteStreamServerChannel.listen.<anonymous closure>(protocol_stream.dart:53)
at _rootRunUnary(zone.dart:1434)
at _CustomZone.runUnary(zone.dart:1335)
at _CustomZone.runUnaryGuarded(zone.dart:1244)
at _BufferingStreamSubscription._sendData(stream_impl.dart:341)
at _DelayedData.perform(stream_impl.dart:591)
at _StreamImplEvents.handleNext(stream_impl.dart:706)
at _PendingEvents.schedule.<anonymous closure>(stream_impl.dart:663)
at _rootRun(zone.dart:1418)
at _CustomZone.run(zone.dart:1328)
at _CustomZone.runGuarded(zone.dart:1236)
at _CustomZone.bindCallbackGuarded.<anonymous closure>(zone.dart:1276)
at _rootRun(zone.dart:1426)
at _CustomZone.run(zone.dart:1328)
at _CustomZone.runGuarded(zone.dart:1236)
at _CustomZone.bindCallbackGuarded.<anonymous closure>(zone.dart:1276)
at _microtaskLoop(schedule_microtask.dart:40)
at _startMicrotaskLoop(schedule_microtask.dart:49)
at _runPendingImmediateCallback(isolate_patch.dart:122)
at _RawReceivePortImpl._handleMessage(isolate_patch.dart:193)

Fixed upstream in https://dart-review.googlesource.com/c/sdk/+/239309

Optimistically closing this per https://dart-review.googlesource.com/c/sdk/+/239309


wozmon fails

I have to reset the terminal after this error message
$ ./ntvao wozmon.hex
\
R
mos6502 unsupported comparison instruction 33

Thanks for reporting this. Yes, the terminal session isn't restored on hard failures. R without an address argument runs whatever random values are in RAM. When the emulator exits it should restore the console to its original state.


General improvements

Fix Polygon shape on all-shapes example
Clean all-shapes example
Add onHover and onEndHover functionality to Feature component
Pass map object to every events on the map component

@alex3165 not ready for merge 😛 I'll simplify the layer code


 If you have some logic around it, use a navigation guard instead

Oh also, you need to change the syntax you are using

https://github.com/vuejs/core/issues/3652#issuecomment-1188959103
https://vuejs.org/guide/built-ins/suspense.html#combining-with-other-components

Makes sense. Thanks :)


Fix shader attribute constants and transitions

Decided to consolidate these:

Fix shader attribute constant updates
Fix shader attribute transitions
Move shader attribute logic into Attribute class.

Coverage increased (+0.1%) to 62.412% when pulling cd76b28299e859dfb1617fb913772178ee1156f8 on transition-shader-attrib into 033546b69a5f97865d85a4f03a2e1dac0b3f522b on master.

Coverage increased (+0.1%) to 62.412% when pulling cd76b28299e859dfb1617fb913772178ee1156f8 on transition-shader-attrib into 033546b69a5f97865d85a4f03a2e1dac0b3f522b on master.


deprecated and move hystrix-dashboard to Netflix-skunkworks

Why is Hystrix Dashboard deprecated? Is there any alternative?

Netflix hasn't used it for a long while. They use Atlas


Use Python 3 style OSError handling

In Python 3 there is no need to check errno any more for most use-cases, as there are specific exception subclasses.
IOError and EnvironmentError are now aliases of OSError, so those are changed here too.
I've left versioneer alone since that's vendored code.

@eric-wieser thanks for submitting this, I've queued it for review.


Infinite Loop of Hopping in Place

I've noticed that sometimes a hostile mob will fail at chasing me, and instead of continuing the pursuit, it will jump in place without stopping. It keeps doing this even if I switch to creative mode and there are no other players around.

I'll check it out - if I can find and fix it, it will probably be in the 1.16.2 update.


(doc) Point to right getShortClassName flavor in Javadoc for relevant notes

I was reading the Javadoc online and was confused by the reference, until I noticed that instead of pointing to itself, the idea is to point to getShortClassName(String).

Codecov Report

Merging #1097 (a64e545) into master (09bc83b) will not change coverage.
Report is 1 commits behind head on master.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master    #1097   +/-   ##
=========================================
  Coverage     92.21%   92.21%
  Complexity     7551     7551
=========================================
  Files           197      197
  Lines         15801    15801
  Branches       2923     2923
=========================================
  Hits          14571    14571
  Misses          660      660
  Partials        570      570

Files Changed
Coverage Δ

...main/java/org/apache/commons/lang3/ClassUtils.java
93.23% <ø> (ø)

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


Why generator loss in vae model not plus the ae's cost

Hi, it's a nice work and thanks for sharing the code.
I have a puzzle, in arga_vae model, when you define the OptimizerVAE in optimizer.py, the generator_loss doesn't plus the auto-encoder cost
self.generator_loss = tf.reduce_mean(             tf.nn.sigmoid_cross_entropy_with_logits(labels=tf.ones_like(d_fake), logits=d_fake))
rather than
self.generator_loss = tf.reduce_mean(             tf.nn.sigmoid_cross_entropy_with_logits(labels=tf.ones_like(d_fake), logits=d_fake))+self.cost.
Can you please tell me the reason to do this?
Thanks a lot.

Hello, what is the generator_loss?


[wip] OpenOrganelle demo

@tpietzsch I'm getting stuck on the OpenOrganelle demo because the N5 data is UnsignedByteType, but clearly it needs to get rendered as an UnsignedShortType.
However, the N5 is being opened as Volatile:
https://github.com/scenerygraphics/sciview/blob/5a3d0ea2a8e424187074b214917aa02d54f4219d/src/main/java/sc/iview/commands/demo/advanced/OpenOrganelleDemo.java#L246
scenery will need some corresponding updates for proper detection of multiscale images that are opened with N5 (currently it is focused on detecting normal BDV images with XML metadata).

@kephale
First, note that N5Utils.openVolatile will still open the image as a (non-volatile) UnsignedByteType image. (But with underlying VolatileByteAccess that provides the capability to turn it into a volatile image.)
At some point you need to use VolatileViews.wrapAsVolatile(...) to make it volatile.
I wish I could tell you that you can convert it to UnsignedShortType and it will just work. Unfortunately it wont, yet, because VolatileViews can't deal with the Converter.
You could try to first VolatileViews.wrapAsVolatile(...) to turn it into RandomAccessibleInterval<UnsignedByteType>. And then convert from VolatileUnsignedByteType to VolatileUnsignedShortType. I fear that it will still not work because BVV assumes that it will get some kind of AbstractCellImg, and the converted RAI will not be that.
So, unfortunately you'll have to make a (lazy) copy... :-(
I'm pretty sure this will work:
import bdv.util.volatiles.VolatileViews;
import net.imglib2.RandomAccessibleInterval;
import net.imglib2.algorithm.blocks.BlockAlgoUtils;
import net.imglib2.algorithm.blocks.convert.Convert;
import net.imglib2.blocks.PrimitiveBlocks;
import net.imglib2.cache.img.CachedCellImg;
import net.imglib2.type.numeric.integer.UnsignedByteType;
import net.imglib2.type.numeric.integer.UnsignedShortType;
import net.imglib2.type.volatiles.VolatileUnsignedShortType;

static RandomAccessibleInterval< VolatileUnsignedShortType > convert(
		RandomAccessibleInterval< UnsignedByteType > rai )
{
	final int[] cellDimensions = { 64, 64, 64 };
	final PrimitiveBlocks< UnsignedByteType > blocks = PrimitiveBlocks.of( rai );
	final CachedCellImg< UnsignedShortType, ? > img = BlockAlgoUtils.cellImg(
			blocks,
			Convert.convert( new UnsignedByteType(), new UnsignedShortType() ),
			new UnsignedShortType(),
			rai.dimensionsAsLongArray(),
			cellDimensions
	);
	return VolatileViews.wrapAsVolatile( img );
}

It requires recently released versions
<net.imglib2.imglib2.version>6.2.0</net.imglib2.imglib2.version>
<net.imglib2.imglib2-algorithm.version>0.14.0</net.imglib2.imglib2-algorithm.version>

Of course, the better solution would be to make BVV just handle these datatypes, but I don't have a timeline for that.

Thank you very much @tpietzsch ! You've unblocked the demo work 🍪 !

This is getting stuck here https://github.com/scenerygraphics/scenery/blob/be284d2488c8635952d0a62f5ca3e5bed15742d1/src/main/kotlin/graphics/scenery/volumes/VolumeManager.kt#L396. it seems like it is trying to create a ton of FillTasks (129705 blocks?), the next thing i would check is how the BVV volume is being initialized w.r.t. the camera

That sounds like it doesn't use multi-resolution

migrated to https://github.com/scenerygraphics/sciview/pull/537


Multiple usage of same enum constant in dict derived class

I have a special use case which has worked until version 1.5.2.
I'm using a class derived from dict and store enum constants as variables.
If some of the enum constants are the same the decode process does not work correctly.
Attached example:
from enum import IntEnum

import jsonpickle as json

class MyEnum(IntEnum):
    ONE = (1,)
    TWO = (2,)

class MyDict(dict):
    def __init__(self, _enum1, _enum2):
        self._enum1 = _enum1
        self._enum2 = _enum2

    def __repr__(self):
        return repr(self.__dict__)

def _test(_enum1, _enum2):
    obj1 = MyDict(_enum1, _enum2)
    obj2 = json.decode(json.dumps(obj1))
    print(f"obj1: {obj1}")
    print(f"obj2: {obj2}")
    return (obj1._enum1 == obj2._enum1) and (obj1._enum2 == obj2._enum2)

def test_1():
    assert _test(MyEnum.ONE, MyEnum.ONE)

def test_2():
    assert _test(MyEnum.ONE, MyEnum.TWO)

======================================================= FAILURES =======================================================
________________________________________________________ test_1 ________________________________________________________

    def test_1():
>       assert _test(MyEnum.ONE, MyEnum.ONE)
E       assert False
E        +  where False = _test(<MyEnum.ONE: 1>, <MyEnum.ONE: 1>)
E        +    where <MyEnum.ONE: 1> = MyEnum.ONE
E        +    and   <MyEnum.ONE: 1> = MyEnum.ONE

test_jsonpickle.py:29: AssertionError
------------------------------------------------- Captured stdout call -------------------------------------------------
obj1: {'_enum1': <MyEnum.ONE: 1>, '_enum2': <MyEnum.ONE: 1>}
obj2: {'_enum1': <MyEnum.ONE: 1>, '_enum2': {...}}
=============================================== short test summary info ================================================
FAILED test_jsonpickle.py::test_1 - assert False
============================================= 1 failed, 1 passed in 0.08s ==============================================```

I apologize for the delay in getting back to you, I forgot to check jsonpickle's repo for a few months. Looking at the code, I have no idea what the issue is. Have you narrowed down the issue to a specific commit (with git bisect or something) between 1.5.1 and 1.5.2, or should I do that? Once I can identify the issue, I can probably get a fix in for 2.0.1

Oh, I just tried reproducing this, and it worked fine on jsonpickle 1.5.2:
theel@theel:~/Coding$  py.test sch_alex_jsonpickle_1_5_2.py
============================= test session starts ==============================
platform linux -- Python 3.9.5, pytest-6.2.4, py-1.10.0, pluggy-0.13.1
benchmark: 3.4.1 (defaults: timer=time.perf_counter disable_gc=False min_rounds=5 min_time=0.000005 max_time=1.0 calibration_precision=10 warmup=False warmup_iterations=100000)
rootdir: /home/theel/Coding
plugins: benchmark-3.4.1, hypothesis-6.21.6, black-0.3.12, asyncio-0.15.1, black-multipy-1.0.1, cov-2.12.1, flake8-1.0.7, xdist-2.3.0, forked-1.3.0, anyio-3.3.0
collected 2 items

sch_alex_jsonpickle_1_5_2.py ..                                          [100%]

============================== 2 passed in 0.06s ===============================

(you'll notice it has my benchmarking plugins enabled, that's just a default setting. it's still testing the code you wrote though)
jsonpickle version:
theel@theel:~/Coding$ pip show jsonpickle
Name: jsonpickle
Version: 1.5.2
Summary: Python library for serializing any arbitrary object graph into JSON
Home-page: https://github.com/jsonpickle/jsonpickle
Author: David Aguilar
Author-email<EMAIL_ADDRESS>License: UNKNOWN
Location: /home/theel/.pyenv/versions/3.9.5/lib/python3.9/site-packages
Requires:
Required-by:


How to detect request for page render path?

Hello there!
In my app I want to intercept server requests which target is to render next.js page, to perform some API call before the page actually renders. Is there any way to do this both in dev and prod enviroments?
Thanks

do you mean getInitialProps ?
this should help
https://learnnextjs.com/basics/fetching-data-for-pages

Do you mean something like this?
static getInitialProps ({ res }) {
  const name = res ? res.locals.name : 'My name';
  return {name};
}

where you set the res.locals.name from the server and you get the value on the Client side.... you can check this example that I made to handle the cookies from the server Example

I mean I want to intercept request BEFORE getInitialProps is fired. Is there any way to do this?

This actually won't work cause it'd only be called the first render. Subsequent routing happens client side and getInitialProps will be fired client side. getInitialProps is fired before rendering and it's the correct place to implement api call logic.


(PUP-6225) Add new function to object type

This PR adds the ability to create new instances of an Object type from the Puppet Language. It also adds the ability to call members (attributes and functions) on the object since it's difficult to test instantiations of an object if it is possible to examine the result.

This PR supersedes PR-4915 due to an issue number confusion in the branch name. Same commits except for some added comments in the #new_function method in response to comment from @hlindberg.

CLA signed by all contributors.

What should happen when instantiating an object type that requires implementation (i.e. it has derived attributes and declares functions) ? By default I think that should raise an error. It is however of value to be able to instantiate such objects when you are aware of this  - the question then is how to signal this as the new call passes on all arguments to the object. The other alternative is to ignore this completely and simply error when trying to use the features that require an implementation (i.e. calling a_person.age() when age is a derived attribute). Third option - default implementation adds methods that accepts the arguments as specified and always returns undef after possibly logging a warning.
I think I prefer it to just error when requiring impl and not having one.

The act of binding implementation to interface (object type) requires a proper specifcation. And the error suggested (previous comment) will ensure that only the sensical case of object not requiring an impl, and not having an impl binding gets a workable dynamic impl. Then we can work on the next phase without breaking people's code).

So, I would like to see tests that provoke those errors.

PR rebased and the member call logic moved.

Regarding when to error out if an implementation is required. Consider the case when you want to do a model to model transformation. Requiring an implementation of derived attributes or functions is then not necessary unless the transformation requires access to them (which often isn't the case). Hence the current design where the Ruby generator emits code that will yield an "no method is implemented for ...". My preference would be to keep it that way so that models can be instantiated dynamically even when no implementation exists.

Regarding spec for binding implementation to interface. IMO, that should be part of the Object type spec.

Regarding errors when there is no impl: While there should be a way to get a default (dynamic) implementation, having that as the default is problematic. When you are doing transformations and similar things you know you are not going to be using implementations and you can take action to state this is ok. In general users just loading stuff unknowingly will end up with errors like "no method implemented" errors which is going to mean nothing to them. It is far better to error at the earliest possible point.
The difference in when an error (and what the error is) is less of a concern than the possible API changes this implies.

I am merging this as the basis for further work. There are several things missing that we are just coming to consensus on.
There will be tickets...


CollapsePrefixesOnLoad not acted upon

While working on #162 I noticed prefixes are also not collapsed when Yasgui.Yasqe.defaults.collapsePrefixesOnLoad is set to true.
To reproduce:

Only when also uncommenting the per-tab function call, the prefixes are collapsed.
I post this as an issue since I'm not sure where this default should be read.

Thanks for the report, this is now fixed :+1: