sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: neovim
Issue: API: `VisualChanged` autocmd
Labels: enhancement,ui,complexity:low,has:workaround,events

## Feature description

For there to be a `VisualChanged` autocommand that fires whenever the visual selection changes. For `v:event` to be populated with visual mode and visual boundaries (row and col).

Alternatively, for there to be a `visual_change` ui event with the same information.

The information (mode and boundaries) is not strictly required, as it can be obtained by `mode()`, `getpos('v')`, and `getpos('.')`. However, getting it directly would be better. The most important thing is to be notified when the selection changes.

### Background
I am the current maintainer of https://github.com/vscode-neovim/vscode-neovim.

Currently, visual selection is not properly managed. Instead of telling vscode exactly where the visual selection is (so that vscode can render it, use it for commands, show it in minimap, etc), we render it ourselves using the `Visual` highlight. This is suboptimal.

To properly sync visual selection to vscode, we need to know when the visual selection changes in neovim. We can't use the `Visual` highlight, because it only gives updates for ranges inside the viewport. We can't use `CursorMoved`, because the visual selection can change without the cursor moving (`viw`).

This is a duplicate of https://github.com/neovim/neovim/issues/11590.
Repository: angular
Issue: HTML element attribute interpolation is not handle correctly
Labels: feature,area: core,core: binding & interpolation,P3,feature: insufficient votes

### Which @angular/* package(s) are the source of the bug?

Don't known / other

### Is this a regression?

No

### Description

HTML element attribute interpolation is not handle correctly.

For the below code, attribute interpolation doesn't work.
```html
<img aria-label="image of {{image.desc}}" [src]="image.src">
```

While for this code, the attribute interpolation with `attr.` prefix does work.
```html
<img attr.aria-label="image of {{image.desc}}" [src]="image.src">
```

The usage of `attr.` prefix is not documented. Please either update the documentation or change the attribute interpolation handler.

Thanks.


### Please provide a link to a minimal reproduction of the bug

_No response_

### Please provide the exception or error you saw

_No response_

### Please provide the environment you discovered this bug in (run `ng version`)

_No response_

### Anything else?

_No response_
Repository: pytorch
Issue: torch.nn.PixelShuffle error message wrong
Labels: module: nn,triaged

### 🐛 Describe the bug

There is something wrong in torch.nn.PixelShuffle's error message. It seems that the result is overflow.

```
import torch
results={}
arg_class = torch.nn.PixelShuffle(10000000000)
arg_2 = torch.rand([16, 256, 72, 72], dtype=torch.float32)
results['res'] = arg_class(arg_2)
```
Above code outputs: RuntimeError: pixel_shuffle expects its input's 'channel' dimension to be divisible by the square of upscale_factor, but input.size(-3)=256 is not divisible by 7766279631452241920.

But actually the error message should be RuntimeError: pixel_shuffle expects its input's 'channel' dimension to be divisible by the square of upscale_factor, but input.size(-3)=256 is not divisible by 100000000000000000000.

### Versions

pytorch: 1.8.1
python: 3.8.3
os: win11

cc @albanD @mruberry @jbschlosser @walterddr @kshitij12345 @saketh-are
Repository: ant-design
Issue: Better type inference for Select.onChange
Labels: TypeScript,Inactive

### Reproduction link

[https://stackblitz.com/edit/react-ts-8uzkys?file=App.tsx](https://stackblitz.com/edit/react-ts-8uzkys?file=App.tsx)

### Steps to reproduce

Seemed typescript failed to infer property of Option

### What is expected?

`option.label` do not trigger error 

### What is actually happening?

`option.label` is triggering error

| Environment | Info |
| --- | --- |
| antd | undefined |
| React | latest |
| System | any |
| Browser | any |

<!-- generated by ant-design-issue-helper. DO NOT REMOVE -->
Repository: pytorch
Issue: torch.nn.ReplicationPad{1|2}d supports more input dimension than are written on documentation
Labels: module: docs,module: nn,triaged

### 📚 The doc issue

torch.nn.ReplicationPad1d supports (C,W) or (N, C, W) input, and needs a int or 2-tuple padding on the documentation. That is to say, torch.nn.ReplicationPad1d only supports 2D or 3D tensor.

torch.nn.ReplicationPad2d supports (C,H,W) or (N, C, H,W) input, and needs a int or 4-tuple padding on the documentation. That is to say, torch.nn.ReplicationPad2d only supports 3D or 4D tensor.

After running code, I find that torch.nn.ReplicationPad1d also supports 4D tensor with 4-tuple padding, and torch.nn.ReplicationPad2d also supports 5D tensor with 6-tuple padding.

```
import torch
results={}
arg_1 = [3,0,2,1]
arg_class = torch.nn.ReplicationPad1d(arg_1,)
arg_2 = torch.rand([25, 2, 46, 1], dtype=torch.float32)
results['res'] = arg_class(arg_2)
```

```
import torch
results={}
arg_1 = [2,2,2,2,2,2]
arg_class = torch.nn.ReplicationPad2d(arg_1,)
arg_2 = torch.rand([4, 1, 1, 3, 3], dtype=torch.float32)
results['res'] = arg_class(arg_2)
```
Above code runs well.

### Suggest a potential alternative/fix

_No response_

cc @svekars @holly1238 @albanD @mruberry @jbschlosser @walterddr @kshitij12345 @saketh-are
Repository: pytorch
Issue: The type of parameter 'p' in torch.nn.TripletMarginLoss wrong
Labels: module: nn,triaged

### 📚 The doc issue

Parameter 'p' of torch.nn.TripletMarginLoss is int value on the documentation parameter part. However, in source code, p's type is float. By running code, it can be proved that parameter 'p' supports float value.

```
import torch
results={}
arg_class = torch.nn.TripletMarginLoss(margin=1.0,p=24.5)
arg_3_0 = torch.rand([100, 128], dtype=torch.float32)
arg_3_1 = torch.rand([100, 128], dtype=torch.float32)
arg_3_2 = torch.rand([100, 128], dtype=torch.float32)
arg_3 = [arg_3_0,arg_3_1,arg_3_2,]
results['res'] = arg_class(*arg_3)
```
Above code works.

### Suggest a potential alternative/fix

_No response_

cc @albanD @mruberry @jbschlosser @walterddr @kshitij12345 @saketh-are
Repository: godot
Issue: Bug with the refresh of the resource type data shown in the editor
Labels: topic:editor,needs testing

### Godot version

v3.5.stable.official [991bb6ac7]

### System information

win10 64

### Issue description

Problem:
The editor does not show the last generated values ​​and keeps showing the first ones that were shown.
The editor does not refresh the displayed data when the generated data changes.
To solve this, reload the project and the editor will show the last assigned value in the generated file.

To show this bug a ".res" file is created.
Two scripts make up the generated data.
"ScriptDatosInicial"
It has a method to initialize the data, it creates a "ScriptDatosSecundario" object and assigns a value to the variable of this object.

"ScriptDatosSecundario"
It simply has an export variable

https://youtu.be/rEQ6rzu1uVo

In the video you can see that initially some data is created by assigning 1 to the value of the variable.
Then the editor displays the value 1 of the generated ".res" data.
So far OK.
Now the value assigned to the variable is changed and assigned the number 2.
The data is generated again.
The editor still displays the value 1 even though the generated data has changed.
The project is reloaded and the data is displayed again.
Now the editor shows the correct value which is number 2.

**_This error occurs when the data is composed of a second script ("ScriptDatosSecondario")._**
The data is displayed refreshed if the data generated is only composed of a script.

The scripts:

![Captura](https://user-images.githubusercontent.com/19652075/184094261-c7f1a7b1-bcc5-4fdb-a9ec-2f09d318e80b.PNG)

![Captura0](https://user-images.githubusercontent.com/19652075/184093530-166d8839-b00b-4894-8c88-9bbd8122f28b.PNG)

![Captura1](https://user-images.githubusercontent.com/19652075/184093557-b4389b45-00a6-4cce-aef0-82cb9d810d19.PNG)


### Steps to reproduce

See the video.

### Minimal reproduction project

[testsVarios.zip](https://github.com/godotengine/godot/files/9307222/testsVarios.zip)
Repository: rust
Issue: PGO profile invalidation in `-Cprofile-use`
Labels: T-compiler,A-incr-comp,C-bug

Hi! While working on https://github.com/Kobzol/cargo-pgo, I noticed a peculiar thing about the invalidation of the PGO profile path.
When PGO is used for compiling, we specify the path to the PGO profile using `-Cprofile-use=<path>`. When `<path>` changes, it invalidates the compilation session, so the code is recompiled again (as it should be, if the profile changes).

However, if the path stays the same, but the contents of the profile file change, the code will not be recompiled. That can be a footgun, since users might try to gather profiles incrementally and then try to compile/benchmark using the new profiles, but if the profile path stays the same (if it's just overwritten each time), they might not notice that the code is not recompiled and they thus might get stale results.

Would it be feasible to check the hash/modification time of the profile file instead of just the file path, w.r.t. invalidating recompilation? Is there any prior art to this in some other Rust flags?

I think that hashing the file wouldn't be such a bottleneck (I think that it was done for `sccache` [here](https://github.com/mozilla/sccache/pull/952)), unless it would have to be done by every `rustc` invocation instead of just once per Cargo run? :thinking: I don't think that `-Cprofile-use` is that common that this would cause perf. problems, but it could resolve a potential footgun.

CC @michaelwoerister
Repository: flutter
Issue: [video_player] Support video that's downloaded using XHR/fetch on Web
Labels: c: new feature,platform-web,p: video_player,package,c: proposal,P3,team-web,triaged-web


The `VideoPlayerController.network` constructor seems to be ignoring `httpHeaders` value when set.
Looking at the request on server side the header `myHeader` (in the following code example) is missing.

```dart
VideoPlayerController videoController = VideoPlayerController.network(
        "http://localhost:8000/path/to/myFile.mp4",
        httpHeaders: {
          "myHeader": "headerValue",
        },
      );
```
Repository: pytorch
Issue: torch.nn.Upsample's error message is inconsistent with the documentation
Labels: module: docs,module: nn,triaged,actionable

### 🐛 Describe the bug

Problem 1:
Parameter 'scale_factor' shoule be float or tuple[float] on documentation. However, when I set list to 'scale_factor', the error message shows that 'scale_factor' must be a string or a number which cannot match the documentation.
```
import torch
results={}
arg_1 = [1]
arg_2 = "nearest"
arg_class = torch.nn.Upsample(scale_factor=arg_1,mode=arg_2,)
arg_3 = torch.rand([1, 1, 2, 2], dtype=torch.float32)
results['res'] = arg_class(*arg_3)
#TypeError: float() argument must be a string or a number, not 'list'
```

Problem 2:
It's written on documentation that if 'scale_factor' is tuple, it has to match input size. That is to say, if input is a 2D tensor, then 'scale_factor' should be a float number or a tuple of length 2. I find that if input is a 2D tensor, 'scale_factor' can be a tuple of length 1. It's inconsistent with the documentation.
```
import torch
results={}
arg_1 = (33)
arg_2 = "nearest"
arg_class = torch.nn.Upsample(scale_factor=arg_1,mode=arg_2,)
arg_3 = torch.rand([1, 1, 2, 2], dtype=torch.float32)
results['res'] = arg_class(*arg_3)
```

### Versions

pytorch: 1.8.1
python: 3.8.3
os: win11

cc @svekars @holly1238 @albanD @mruberry @jbschlosser @walterddr @kshitij12345 @saketh-are
Repository: pytorch
Issue: During DDP training timm densenet121, mobilenetv2(v3) models do not save state_dict correctly.
Labels: oncall: distributed,triaged,module: ddp

### 🐛 Describe the bug

During DDP training timm densenet121, mobilenetv2(v3) models do not save state_dict correctly.
 After load the stat dicts, the model do not act well.  However, when using torch.save save the model, it works well.


### Versions

both 1.11, 1.12 and 1.12.1

cc @pietern @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @SciPioneer @H-Huang @kwen2501 @ezyang
Repository: flutter
Issue: [camera] Provide a way to record a video in landscape when device orientation is locked to portrait
Labels: c: new feature,p: camera,package,c: proposal,team-ecosystem,P3,triaged-ecosystem

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## Use case

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i want to have more use case rotation in camera flutter. 
## Proposal

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For example:  Initially, device is in portrait mode . Then i rotate screen to horizontal (remember that the device rotation is set to locked) and record video.  My expectation is the output video is in landscape mode but the actual result is that the video is still in portrait mode. For more detail you can see in the [CameraX usecase rotation How to determine the target rotation example 1](https://developer.android.com/training/camerax/orientation-rotation)

Procedure: 
- When rotate camera with locked portrait mode: 
<img width="300" src="https://user-images.githubusercontent.com/102939631/184106524-1cedf148-3823-4179-8542-32fdf90a2488.png">

(the status bar show that device is still in portrait mode)
- Expectation output:
<img width="300" src="https://user-images.githubusercontent.com/102939631/184105912-8ba2e242-4a7f-42c6-9671-53b025269362.png">
(The picture or video which is recorded should be in portrait mode).

In android, they have some function like `Display.getRotation()` to get this device, we can use it to change `recordingRotation` before record video.
Repository: godot
Issue: Icons on the very top of the inspector look blurry
Labels: bug,topic:editor,confirmed,topic:gui

### Godot version

4.0.alpha13

### System information

Ubuntu 20.04.3 LTS

### Issue description

![image](https://user-images.githubusercontent.com/85438892/184107467-1642cf62-d651-4cca-bae6-9b99699370ac.png)

Compare the rightmost one to the other two.

### Steps to reproduce

N/A

### Minimal reproduction project

N/A
Repository: rust
Issue: Solaris target m32
Labels: I-ICE,T-compiler,O-solaris,C-bug

<!--
Thank you for finding an Internal Compiler Error! 🧊  If possible, try to provide
a minimal verifiable example. You can read "Rust Bug Minimization Patterns" for
how to create smaller examples.

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-->

### Code

```Rust
Cargo build --target=sparcv9-sun-solaris-m32
```


### Meta
<!--
If you're using the stable version of the compiler, you should also check if the
bug also exists in the beta or nightly versions.
-->

`rustc --version --verbose`: 
```
1.53.0-dev
```

`OS version`: 
```
Oracle Solaris 11.4
```

### Error output

```
ELFCLASS64
```

<!--
Include a backtrace in the code block by setting `RUST_BACKTRACE=1` in your
environment. E.g. `RUST_BACKTRACE=1 cargo build`.
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<details><summary><strong>Backtrace</strong></summary>
<p>

```

We support old software.
The project is written in C and we want to connect it with Rust in order to implement new modules.
Makefile self-written.
The main problem is that the OS is 64-bits and the software is 32-bits.
We decided to rewrite target sparcv9-sun-solaris but it doesn't work.
Due to certain problems, the current version of rustc is the maximum possible.
Rustup is not available.

{

  "dynamic-linking": true,

  "executables": true,

  "data-layout": "E-m:e-i64:64-n32:64-S128",

  "has-rpath": true,

  "is-like-solaris": true,

  "limit-rdylib-exports": false,

  "linker_is_gnu": false,

  "eh_frame_header": false,

  "llvm-target": "base-solaris-m32",

  "os": "solaris",

  "pre-link-args": {

    "gcc": [

      "-m32"

    ]

  },

  "target-endian": "big",

  "target-family": "unix",

  "target-pointer-width": "32",

  "vendor": "sun"

}
```

</p>
</details>
Repository: pytorch
Issue: Using Pytorch and Mapbox in the same project
Labels: oncall: mobile

Hello,

I'm trying to use Mapbox and Pytorch together in the same Android project but I receive this compilation error:
2 files found with path 'lib/arm64-v8a/libc++_shared.so' from inputs:
 - /Users/eyalamir/.gradle/caches/transforms-3/39574a221961eb18fa9deadbee69fea4/transformed/common-22.1.0/jni/arm64-v8a/libc++_shared.so
 - /Users/eyalamir/.gradle/caches/transforms-3/c73fb4c1d8f48b7cbb206e310613488d/transformed/pytorch_android_lite-1.10.0/jni/arm64-v8a/libc++_shared.so
If you are using jniLibs and CMake IMPORTED targets, see
https://developer.android.com/r/tools/jniLibs-vs-imported-targets

If I only use one of the libraries, the project compiles correctly.
I also reproduced this issue with a new Android Project.

I'm using these versions:
Mapbox - com.mapbox.maps:android:10.7.0
Pytorch - org.pytorch:pytorch_android_lite:1.10.0

The issue is also reproduced with the full PyTorch library instead of the lite version.

Can you please instruct me on how to solve this issue?
Repository: go
Issue: proposal: reflect: add generic type arg info to reflect.Type
Labels: Proposal

I'm not sure if this has been discussed already (I couldn't find a prior issue),  but currently `reflect.Type` has no direct methods to retrieve the type arguments of generic types.

The only way to retrieve these type arguments is by parsing the string returned by `Type.Name()` which includes fully qualified package names and could look something like this in a complex case: `MyGenericType[some/package.Foo, map[string]other/package.Bar]`. This string is not easy to parse because of the possibility of nested type arguments, maps, slices, etc.

I propose adding methods to `reflect.Type` to retrieve these type arguments programmatically:
```go
NumTypeArg() int
TypeArg(i int) Type
```
Repository: rust
Issue: Compilation error E0207 for `impl` for another const generic trait
Labels: A-diagnostics,T-compiler

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along with any information you feel relevant to replicating the bug.

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Given the following code: <!-- Please provide a link to play.rust-lang.org -->

```rust
pub trait ExtraFieldHeader {
    fn header_id(&self) -> u16;
}

pub trait FixedIDZIPExtraField<const ID: u16> {
    const HEADER_ID: u16 = ID;
    /// Gets header ID (Unique for each type of extra fields)
    fn header_id(&self) -> u16 {
        Self::HEADER_ID
    }
}

impl<T, const ID: u16> ExtraFieldHeader for T where T: FixedIDZIPExtraField<ID> {}
```

The current output is:

```
error[E0207]: the const parameter `ID` is not constrained by the impl trait, self type, or predicates
  --> src\zip_extra_field.rs:27:9
   |
27 | impl<T, const ID: u16> ExtraFieldHeader for T where T: FixedIDZIPExtraField<ID> {}
   |         ^^^^^^^^^^^^^ unconstrained const parameter
   |
   = note: expressions using a const parameter must map each value to a distinct output value
   = note: proving the result of expressions other than the parameter are unique is not supported
```

<!-- The following is not always necessary. -->
Ideally the output should look like:

```
(no errors)
```

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I believe `ID` is constrained for `FiexedIDZIPExtraField<ID>` and this error must not be raised. Could someone provide a solution?

```
rustc --version
rustc 1.62.1 (e092d0b6b 2022-07-16)
```
Repository: node
Issue: HTTP/2 secure upload is slower than HTTP/1.1 over TLS
Labels: http,performance,http2

Thank you so much for the wonderful project!

### Version

16.16.0

### Platform

macOS Big Sur

### What steps will reproduce the bug?

I create simple HTTPS servers over HTTP/1.1 and HTTP/2 which handle client-to-server upload.


## Result

- HTTP1.1: about 600MB/sec
- HTTP/2: about 280MB/sec

The result of HTTP/1.1 is as follows.

https://user-images.githubusercontent.com/10933561/184122262-e70c2e34-efe0-452f-bba2-8e9d46d6b492.mp4

The result of HTTP/2 is as follows.

https://user-images.githubusercontent.com/10933561/184122531-81168462-10d8-4a42-b142-1f9decaf1709.mp4


## Code

Here are codes.

```js
// http1.1-server.js
const fs = require("fs");
const https = require("https");

const server = https.createServer({
  key: fs.readFileSync("./server.key"),
  cert: fs.readFileSync("./server.crt"),
}, (req, res) => {
  console.log("request accepted");
  res.writeHead(200);
  req.pipe(fs.createWriteStream("/dev/null"));
});

server.listen(8443, () => {
  console.log("HTTPS (HTTP/1.1) listening on 8443 port");
});
```

```js
// http2-server.js
const fs = require("fs");
const http2 = require("http2");

const server = http2.createSecureServer({
  key: fs.readFileSync("./server.key"),
  cert: fs.readFileSync("./server.crt"),
});

server.on("stream", (stream, headers) => {
  console.log("on stream");
  stream.respond({
    ":status": 200,
  });
  stream.pipe(fs.createWriteStream("/dev/null"));
})

server.listen(8443, () => {
  console.log("HTTPS (HTTP/2) listening on 8443 port");
});
```

```bash
cat /dev/zero | pv | curl -kT- https://localhost:8443
```

full code: https://github.com/nwtgck/public-code/tree/f2002382e1fae26d7821f37a7c50ad93ea83ce1e/node-http2-is-slower-than-http1.1

### How often does it reproduce? Is there a required condition?

always

### What is the expected behavior?

The expected behavior is the same transfer speed.

### What do you see instead?

written in "What steps will reproduce the bug?"