sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: opencv
Issue: OpenCV 4.3.0 RELEASE build error in traits.hpp
Labels: category: build/install,category: gpu/cuda (contrib),platform: win32

##### System information (version)
- OpenCV => 4.3.0
- Operating System / Platform => Windows 10 64 Bit v 1909
- Compiler => Visual Studio 2019 community
- CUDA => v10.2.89
- GSTREAMER => v1.16.2
- NINJA => v1.10.0
- CMAKE => v3.17.2
- NVIDIA RTX2070 with Q-Max design

Please refer to the attached build config "BuildCONFIG.txt"
[BuildCONFIG.txt](https://github.com/opencv/opencv/files/4625103/BuildCONFIG.txt)

Please refer to the build file (NinjaRELEASECuDNNGStreamerNonFree.txt) here: 
[NinjaRELEASECuDNNGStreamerNonFree.txt](https://github.com/opencv/opencv/files/4625106/NinjaRELEASECuDNNGStreamerNonFree.txt)


##### Detailed description
When i build "RELEASE" version, I see the following error in building gpu_mat.cu 
And the error is:

**gpu_mat.cu**
C:/Nitin/OpenCVCode/opencv4_3_0/modules/core/include\opencv2/core/traits.hpp(374): **error C2993: 'T': illegal type for non-type template parameter '__formal'**
C:/Nitin/OpenCVCode/opencv4_3_0/modules/core/include\opencv2/core/traits.hpp(374): note: see reference to class template instantiation 'cv::traits::internal::CheckMember_fmt<T>' being compiled
C:/Nitin/OpenCVCode/opencv4_3_0/modules/core/include\opencv2/core/traits.hpp(374): **error C2065: '__T0': undeclared identifier**
C:/Nitin/OpenCVCode/opencv4_3_0/modules/core/include\opencv2/core/traits.hpp(374): **error C2923: 'std::_Select<__formal>::_Apply': '__T0' is not a valid template type argument for parameter '<unnamed-symbol>'**
C:/Nitin/OpenCVCode/opencv4_3_0/modules/core/include\opencv2/core/traits.hpp(374): e**rror C2062: type 'unknown-type' unexpected
CMake Error at cuda_compile_1_generated_gpu_mat.cu.obj.Release.cmake:280 (message):
  Error generating file**
  C:/Nitin/OpenCVCode/opencv4_3_0/build/modules/world/CMakeFiles/cuda_compile_1.dir/__/core/src/cuda/./cuda_compile_1_generated_gpu_mat.cu.obj

Whereas, DEBUG build builds just fine !
Repository: electron
Issue: I can still interact with disabled windows after a call to setEnabled(false)
Labels: platform/windows,bug :beetle:,8-x-y,10-x-y

### Preflight Checklist
* [x] I have read the [Contributing Guidelines](https://github.com/electron/electron/blob/master/CONTRIBUTING.md) for this project.
* [x] I agree to follow the [Code of Conduct](https://github.com/electron/electron/blob/master/CODE_OF_CONDUCT.md) that this project adheres to.
* [x] I have searched the issue tracker for an issue that matches the one I want to file, without success.

### Issue Details
* **Electron Version:** 8.2.0
* **Operating System:** Windows 10

### Expected Behavior
When I call `win.setEnabled(false)`, I expect that I won't be able to interact with the window.

### Actual Behavior
I can still interact if I Alt+Tab to it.

### To Reproduce
main.js:
```
const { app, BrowserWindow, ipcMain } = require('electron')

async function createWindow() {
  const mainWindow = new BrowserWindow({ webPreferences: { nodeIntegration: true } });
  await mainWindow.loadFile("./index.html");
  mainWindow.webContents.openDevTools({ mode: "detach" });

  ipcMain.on("disableWindows", (e, arg) => {
    BrowserWindow.getAllWindows().forEach((win) => {
      if (win.id != mainWindow.id) {
        win.setEnabled(false);
      }
    });
  });
}

app.on('ready', createWindow)
```

index.html:
```
<body>
	<button id="b">Cliek me</button>
	<script src="./renderer.js">
	</script>
</body>
```

renderer.js:
```
const { ipcRenderer } = require("electron");

var b = document.getElementById("b");
b.onclick = () => {
	ipcRenderer.send("disableWindows");
}
```

Launch the app. In the devtools, open a window to google. Make sure focus is in the search field.

Then click the button in the main window to disable the window. Alt+tab back to the disabled window and type something. notice that that still works and I can search for results.

Gif:
![setenabled_issue](https://user-images.githubusercontent.com/6374473/82068636-dec67e80-9697-11ea-819a-b3e2f4fd64bb.gif)
Repository: godot
Issue: Scrollcontainer which doesn't show the last element when supposed to spawn outside of Scrollbox
Labels: bug,confirmed,topic:gui

**Godot version:** v3.2.stable.official and v3.2.1.stable.official

**OS/device including version:**  Windows 64bit

**Issue description:** If your Scrollcontainer is too small, then the last element of an array wont load into the "scrolling" of the Container.

![array](https://user-images.githubusercontent.com/58604290/81880133-ebaa7b80-958c-11ea-9fd6-6362d9230bd0.png)

Like you see in this picture I do have 5 elements in my array but as you'll see in the next screenshot the 5th element isn't loaded / properly spawned.

![3](https://user-images.githubusercontent.com/58604290/81880246-3f1cc980-958d-11ea-971d-bc02ffc0a752.png)
![2](https://user-images.githubusercontent.com/58604290/81880253-4643d780-958d-11ea-856e-1fae29c92062.png)

What I did find out is that the fifth element **is** loading but it doesn't spawn it into the scrolling of the container. It spawns outside of the box so you'll never see it (That's what I saw. It could also be another problem with maybe the sizing of the Scrollcontainer or even a bug in the Vertical- and HorizontalBox).

![4](https://user-images.githubusercontent.com/58604290/81880426-c9fdc400-958d-11ea-9014-28ea03545d13.png)
![5](https://user-images.githubusercontent.com/58604290/81880428-cc601e00-958d-11ea-943c-002b7e85ca1b.png)

So I only found out one solution to this problem that is to manually spawn the last element of the array you are using.

![6](https://user-images.githubusercontent.com/58604290/81880720-7344ba00-958e-11ea-8ad8-2c09c0679900.png)

![7](https://user-images.githubusercontent.com/58604290/81881728-33cb9d00-9591-11ea-87a9-161403e10730.png)


**Steps to reproduce:** 
- make an array (a good number is 10)
- make a little scene you want to instance into the scrollingcontainer and then try to run a for loop to instance all elements

**Minimal reproduction project:**
[Scrollingcontainer Bug.zip](https://github.com/godotengine/godot/files/4625485/Scrollingcontainer.Bug.zip)

In this project you should see a difference between the size of the array and how many actually spawned. (The instances are numbered, It goes from 0 to 7 with an array of 9 elements)
Repository: go
Issue: x/tools/gopls: use RelatedInformation for diagnostics on interface implementation errors
Labels: FeatureRequest,gopls,Tools

See the example in https://play.golang.org/p/2TrSYmBsdLU.

In this case, both the compiler and go/types report error messages on L17 where the error occurs. However, in cases like these, the user is most likely interested in fixing their mistake on L9 by changing the return type of `Hello`. We should add this position in the `RelatedInformation` field of diagnostics.
Repository: terminal
Issue: Include a profile that will connect to Visual Studio Codespaces
Labels: Issue-Feature,Help Wanted,Area-Extensibility,Product-Terminal


# Description of the new feature/enhancement

When using VSCode with [Visual Studio Codespaces ](https://online.visualstudio.com/), the integrated terminal is "connected" to the codespace and all commands execute in the Codespace environment.

I would like a profile in Terminal that connects to a Codespace. I would expect it to function similar to the Azure Cloud Shell profile.
Repository: PowerToys
Issue: Nightly releases
Labels: Area-Setup/Install

Not really a feature request, more like a helpful suggestion I could do.
I have a server and maybe if you guys think I should setup a release system?
Such as: Master, Stable, Nightly builds?
Up to you! Please react with reactions if you think this is a good idea, -3 reactions and i'll close this.
(I'm not sure how I would do this but, it's up to the person running this!).

More information on how I would run this:
1) It would run jenkins.
2) Links could be in readme.md
3) I'll give the operator of this repository full access of the Jenkins website.

Thank's all!
Repository: flutter
Issue: type 'MaterialPageRoute<dynamic>' is not a subtype of type 'Route<String?>?' of ' in type cast'
Labels: framework,f: material design,f: routes,has reproducible steps,P2,found in release: 3.3,found in release: 3.7,team-design,triaged-design

### Hi, I found an uncertain problem！

#### Problem description:

> I expect to use `Navigator.of(context).pop<String>` to return a value of a certain type, but the result is always a value of dynamic type.

#### Code:

```dart
// First screen
Navigator.of(context).pushNamed<String>('login').then((String result){
                                  print('login.result runtimeType: ${result.runtimeType}');
                                });

// Second screen
Navigator.of(context).pop<String>('success');
```

#### A type error will occur in the above code:
```bash
E/flutter (16614): [ERROR:flutter/lib/ui/ui_dart_state.cc(157)] Unhandled Exception: type 'MaterialPageRoute<dynamic>' is not a subtype of type 'Route<String>' in type cast
E/flutter (16614): #0      NavigatorState._routeNamed (package:flutter/src/widgets/navigator.dart:3138:55)
E/flutter (16614): #1      NavigatorState.pushNamed (package:flutter/src/widgets/navigator.dart:3190:20)
E/flutter (16614): #2      _Transfer.build.<anonymous closure> (package:panda_exchange/views/FirstScreen.dart:157:55)
E/flutter (16614): #3      GestureRecognizer.invokeCallback (package:flutter/src/gestures/recognizer.dart:182:24)
E/flutter (16614): #4      TapGestureRecognizer.handleTapUp (package:flutter/src/gestures/tap.dart:504:11)
E/flutter (16614): #5      BaseTapGestureRecognizer._checkUp (package:flutter/src/gestures/tap.dart:282:5)
E/flutter (16614): #6      BaseTapGestureRecognizer.acceptGesture (package:flutter/src/gestures/tap.dart:254:7)
E/flutter (16614): #7      GestureArenaManager.sweep (package:flutter/src/gestures/arena.dart:156:27)
E/flutter (16614): #8      GestureBinding.handleEvent (package:flutter/src/gestures/binding.dart:222:20)
E/flutter (16614): #9      GestureBinding.dispatchEvent (package:flutter/src/gestures/binding.dart:198:22)
E/flutter (16614): #10     GestureBinding._handlePointerEvent (package:flutter/src/gestures/binding.dart:156:7)
E/flutter (16614): #11     GestureBinding._flushPointerEventQueue (package:flutter/src/gestures/binding.dart:102:7)
E/flutter (16614): #12     GestureBinding._handlePointerDataPacket (package:flutter/src/gestures/binding.dart:86:7)
E/flutter (16614): #13     _rootRunUnary (dart:async/zone.dart:1196:13)
E/flutter (16614): #14     _CustomZone.runUnary (dart:async/zone.dart:1085:19)
E/flutter (16614): #15     _CustomZone.runUnaryGuarded (dart:async/zone.dart:987:7)
E/flutter (16614): #16     _invoke1 (dart:ui/hooks.dart:275:10)
E/flutter (16614): #17     _dispatchPointerDataPacket (dart:ui/hooks.dart:184:5)
E/flutter (16614): 
```
Repository: ant-design
Issue: How could I format the week num in WeekPicker
Labels: Inactive

- [x] I have searched the [issues](https://github.com/ant-design/ant-design/issues) of this repository and believe that this is not a duplicate.

### What problem does this feature solve?
Now the week num in WeekPicker is the number of year , but for some one that is not clear, they want the number of month.   
现在WeekPicker的组件里，周数指的是一年当中的第几周，但对一些客户来说，这个不够明确，他们比较希望的表达是某个月的第几周。

### What does the proposed API look like?
I hope there is a method to format the week number, just like this.  
```
<WeekPicker
  weekNumberFormatter = {(beginDate, endDate) => ''}
/>
```


<!-- generated by ant-design-issue-helper. DO NOT REMOVE -->
Repository: vscode
Issue: Tab key when indenting with spaces does not insert correct number of spaces
Labels: feature-request,editor-commands

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- VSCode Version: 1.45.0
- OS Version: macOS Catalina 10.15.4

This is a re-filing of #80129 which was closed erroneously. This is NOT caused by an extension and reproduces when editing even a plain text document when extensions are all disabled.

Related to #2798.

If the insertion point is *anywhere* inside the indentation at the start of the line, and I press <kbd>Tab</kbd>, the indentation should be increased to the next full tab stop (multiple of the tab width).

I'll use the period `.` character instead of spaces in indentation so that it is easier to see what I'm talking about.

If I have a line of code indented by 4 spaces like this:

```python
....do_something()
```

If I place the insertion point on column 2 and press tab, I get _7_ spaces. That's really irritating, it means I have to be hyper precise placing my cursor when I want to indent a line, even when there's a very wide click target I should be able to hit anywhere.

```python
.......do_something()
```

**Xcode** does this properly, it increases the indentation to 8 spaces and moves the cursor to the end of the indentation. **TextMate** behaves the same as Xcode.


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Does this issue occur when all extensions are disabled?: Yes
Repository: pytorch
Issue: Named Tensor and Indexing
Labels: triaged,module: named tensor

First of all, thanks for all the great work on PyTorch! It's been a pleasure to use, and to watch it continue to improve. I was also excited about Named Tensor, for all the reasons described in the initial proposal: there's painful gotchas in unnamed dimensions, and opportunity to write clearer, safer code with named dimensions.

However, when we tried to use named tensors, we ran into some trouble, mostly around indexing. This post will be part feature request, and part general observation / comment.

### Indexing Not Supported - Feature Request

We make use of indexing, primarily for embedding lookups, which is not supported with named tensors (as of 1.5):
```
named_tensor = torch.tensor([100, 101, 102], names=('foo',))
named_tensor[[0,2]]  # -> RuntimeError: index is not yet supported with named tensors.
```
Similarly for `index_select`. The runtime error recommends removing the names and recreating them. Since this is rather cumbersome, it would be great if named tensor could support indexing more naturally.

### Named Dimension vs Labeled Index

One slightly unexpected observation in our exploration of named tensor is that we realized we actually had more cases where a labeled index would help with legibility and safety, than for named dimensions. Of course, both together would be better still. As a reference, consider the popular pandas dataframe API. For a concrete example, imagine we have a grocery model with a fruit embedding tensor represented as a pandas dataframe:

```
df = pd.DataFrame({'apple':[0,0],'pear':[1,1],'orange':[2,2]})
```

We can also make things even more explicit if we wish, analogous to named tensor, by assigning names to the index/columns (the pandas analogy breaks down slightly because dataframes are inherently 2-dimensional and don't fully generalize to tensors, so I'll stick with a 2 dimensional example here for clarity). But either way, we can index into this dataframe with labels rather than numeric indices:
```
df[['apple','orange']]
``` 

This is handy because it lets us standardize a label vocabulary, and avoids exposing the internal implementation detail of an arbitrary numeric index. When working with pytorch I find myself rolling my own indexing solutions, which would be simple enough in this toy example but can get quite messy as things become more complicated. Besides the potential complexity and error-prone nature of bespoke index tracking, there's also the drawback of missing out on a tighter integration of indexing with pytorch, which could be helpful for inspecting model objects.

Overall, it would simplify our model interface substantially if pytorch could provide built-in support for a labled index, possibly augmenting tensors in a similar fashion to named tensor.  Of course this is way beyond the scope of named tensor itself, but perhaps this can help motivate future exploration, or if there is existing work in this direction I'd love to hear about it!

cc @zou3519
Repository: TypeScript
Issue: templated function with multiple signatures does not have options merged for autocomplete.
Labels: Bug,Domain: Completion Lists

```ts
function regular(options: {abc: 'hello'});
function regular(options: {abc: 'world'});
function regular(options: any) {
}

regular({abc: '' });

function templated<K extends string>(options: {abc: 'hello'});
function templated<K extends string>(options: {abc: 'world'});
function templated(options: any) {
}

templated({abc: ''});
```

With the `regular` function, asking for autocomplete inside the quotes for `abc` gives `"hello"` and `"world"`. With the `templated` function, only `"hello"` is given. Type checking itself works fine.
Repository: youtube-dl
Issue: ondamedia.cl
Labels: site-support-request

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## Checklist

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- [x] I'm reporting a new site support request
- [x] I've verified that I'm running youtube-dl version **2020.05.08**
- [x] I've checked that all provided URLs are alive and playable in a browser
- [x] I've checked that none of provided URLs violate any copyrights
- [x] I've searched the bugtracker for similar site support requests including closed ones


## Example URLs

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- Single video: https://ondamedia.cl/#/player/velodromo
- Single video: https://ondamedia.cl/#/player/hoy-y-no-manana
- Playlist: https://ondamedia.cl/#/result?query=ondasinfronteras

## Description

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Collection of Chilean movies, documentaries and similar items hosted by the Chilean Ministry of Culture
Repository: pytorch
Issue: [Feature] Option to have zeros/ones/full output tensor with zero strides
Labels: triaged,enhancement,module: tensor creation,function request

## 🚀 Feature

An option to return a tensor with all strides set to 0 for `torch.zeros`, `torch.ones`, `torch.Tensor.new_ones`, `torch.Tensor.new_zeros`, etc. for smaller memory usage and better performance.

## Motivation

For now, an alternative way of doing this is by calling two methods, e.g.:
`x.new_full((1,), value).expand_as(x)`

But it is a pretty unfriendly approach, therefore, I have mostly seen a simple `torch.full_like(x, value)` being used instead, which can unnecessarily allocate a huge chunk of the memory.


## Pitch

Possible implementations:
* The most user-friendly way I can think of is to output zero-strided tensor by default and allocate additional memory only when a different value is assigned to some elements, but I can see this breaking many C++/CUDA extensions that expect a contiguous output from these methods (this could still be deprecated and changed in far future).
* Adding an additional [`torch.memory_format`](https://pytorch.org/docs/stable/tensor_attributes.html#torch.torch.memory_format) or  [`torch.layout`](https://pytorch.org/docs/stable/tensor_attributes.html#torch.torch.layout) that handles this
* Adding an additional argument for each of the functions

## Additional context

A real-life example where this would have been useful in the [NVIDIA SPADE code with a  dedicated method](https://github.com/NVlabs/SPADE/blob/0ff661e70131c9b85091d11a66e019c0f2062d4c/models/networks/loss.py#L51) for what could be potentially done as simple as `torch.zeros_like(input, expanded=False)`
Repository: pytorch
Issue: Immediate mode API (with functional flavor) for optimizers
Labels: module: optimizer,triaged,enhancement

## 🚀 Feature
_Not really formally designed. Just a seed of an idea._

Example methods:
```py
optim.apply_grad(param, **update_args)
```
Uses `param.grad`. Throws if `param` was never under `optim`
```py
optim.apply_grad(param, grad, **update_args)
```
Very vaguely feels like there might be something to salvage here. But feels like it would be quite awkward for stateful optimizers (Adam, etc.)
```py
ggraph = optim.new_gradient_graph()
ggraph = loss.backward(ggraph)
params, grads = select_params(ggraph)
modify_grad(grads)
optim.apply_grad(params, grads, **update_args)
```
And so on.

`update_args` would be per-optimizer usable variables. E.g. learning rate.

## Motivation

The current API is awkward to work around for extending gradient calculations or custom update regimes.

This would make customizing LR, gradient clipping, selective freezing, etc., doable through an explicit loop. Like decoupling evaluation, grad calculation, and optimizer step did for the overall training loop.

A more advanced scenario I haven't worked with yet is dynamically generated networks. `add_param_group` and `del .param_groups[i]` are pretty awkward and require keeping track of parameter groups externally.

## Pitch

Let's discuss this. I don't have enough of the full picture to push for it. Just felt it would be interesting.

## Alternatives

Same as today. Gradients are hidden in an associated graph, `requires_grad` loops, only in-place mutation for grad changes, etc.

## Additional context

N/A


cc @vincentqb